{"source":"bioRxiv","subject":"bioinformatics","title":"MedGraphNet: Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical Predictions","url":"http://biorxiv.org/cgi/content/short/2024.09.24.614782v1?rss=1","abstract":"Genetic, molecular, and environmental factors influence diseases through complex interactions with genes, phenotypes, and drugs. Current methods often fail to integrate diverse multi-relational biological data meaningfully, limiting the discovery of novel risk genes and drugs. To address this, we present MedGraphNet, a multi-relational Graph Neural Network (GNN) model designed to infer relationships among drugs, genes, diseases, and phenotypes. MedGraphNet initializes nodes using informative embeddings from existing text knowledge, allowing for robust integration of various data types and improved generalizability. Our results demonstrate that MedGraphNet matches and often outperforms traditional single-relation approaches, particularly in scenarios with isolated or sparsely connected nodes. The model shows generalizability to external datasets, achieving high accuracy in identifying disease-gene associations and drug-phenotype relationships. Notably, MedGraphNet accurately inferred drug side effects without direct training on such data. Using Alzheimer's disease as a case study, MedGraphNet successfully identified relevant phenotypes, genes, and drugs, corroborated by existing literature. These findings demonstrate the potential of integrating multi-relational data with text knowledge to enhance biomedical predictions and drug repurposing for diseases.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: MedGraphNet: Leveraging Multi-Relational Graph Neural Networks and Text Knowledge for Biomedical Predictions Abstract: Genetic, molecular, and environmental factors influence diseases through complex interactions with genes, phenotypes, and drugs. Current methods often fail to integrate diverse multi-relational biological data meaningfully, limiting the discovery of novel risk genes and drugs. To address this, we present MedGraphNet, a multi-relational Graph Neural Network (GNN) model designed to infer relationships among drugs, genes, diseases, and phenotypes. MedGraphNet initializes nodes using informative embeddings from existing text knowledge, allowing for robust integration of various data types and improved generalizability. Our results demonstrate that MedGraphNet matches and often outperforms traditional single-relation approaches, particularly in scenarios with isolated or sparsely connected nodes. The model shows generalizability to external datasets, achieving high accuracy in identifying disease-gene associations and drug-phenotype relationships. Notably, MedGraphNet accurately inferred drug side effects without direct training on such data. Using Alzheimer's disease as a case study, MedGraphNet successfully identified relevant phenotypes, genes, and drugs, corroborated by existing literature. These findings demonstrate the potential of integrating multi-relational data with text knowledge to enhance biomedical predictions and drug repurposing for diseases.","summary":"MedGraphNet leverages multi-relational Graph Neural Networks and text knowledge to improve biomedical predictions by initializing nodes using informative embeddings from existing text knowledge, allowing for robust integration of various data types and improved generalizability. The model demonstrates superior performance compared to traditional single-relation approaches in scenarios with isolated or sparsely connected nodes, particularly in identifying disease-gene associations and drug-phenotype relationships, and shows promising results in accurately inferring drug side effects without direct training on such data."}
{"source":"bioRxiv","subject":"bioinformatics","title":"High-throughput bacterial aggregation analysis in droplets","url":"http://biorxiv.org/cgi/content/short/2024.09.24.613170v1?rss=1","abstract":"The communal lifestyle of bacteria manifested as bacterial aggregation and potential biofilm formation is posing as a significant contributor to antimicrobial resistance. A key approach to adress the emerging pandemic is to implement novel techniques that enhance the precision and speed of analysis in various microbiological experiments. Droplet-based platforms coupled with image analysis techniques exhibit great potential in advancing the precision of investigating bacterial behaviour and increasing the speed of microbiological experiments. As most of the image analysis techniques require advanced programming skills or implement high-priced fees, open-source software interweaving user-friendly interface is in great demand. In this paper, we introduce two image analysis pipelines constructed in CellProfilerTM to quantify bacterial aggregation responding to a presence of microplastics as well as suboptimal concentrations of antibiotics in droplets.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: High-throughput bacterial aggregation analysis in droplets Abstract: The communal lifestyle of bacteria manifested as bacterial aggregation and potential biofilm formation is posing as a significant contributor to antimicrobial resistance. A key approach to adress the emerging pandemic is to implement novel techniques that enhance the precision and speed of analysis in various microbiological experiments. Droplet-based platforms coupled with image analysis techniques exhibit great potential in advancing the precision of investigating bacterial behaviour and increasing the speed of microbiological experiments. As most of the image analysis techniques require advanced programming skills or implement high-priced fees, open-source software interweaving user-friendly interface is in great demand. In this paper, we introduce two image analysis pipelines constructed in CellProfilerTM to quantify bacterial aggregation responding to a presence of microplastics as well as suboptimal concentrations of antibiotics in droplets.","summary":"The communal lifestyle of bacteria can contribute significantly to antimicrobial resistance by promoting biofilm formation. A key approach to addressing this issue is to develop novel techniques for analyzing bacterial behavior, such as those enabled by droplet-based platforms and image analysis methods."}
{"source":"bioRxiv","subject":"bioinformatics","title":"scParadise: Tunable highly accurate multi-task cell type annotation and surface protein abundance prediction","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614509v1?rss=1","abstract":"scRNA-seq is revolutionizing biomedical research by revealing tissue architecture, cellular composition, and functional interactions. However, accurate cell type annotation remains a challenge, particularly for rare cell types, with existing automated methods often falling short. Multimodal data, combining mRNA expression and protein markers, improves deep cellular analysis and make functional characterization of complex tissues more accurate. However, it is costly and complex to obtain. We present scParadise, a cutting-edge Python framework featuring three tools: scAdam for multi-level cell annotation, scEve for surface protein prediction, and scNoah for benchmarking. scAdam surpasses current methods in annotating rare cell types and ensures consistent results across diverse datasets, while scEve enhances clustering and cell type separation. With scNoah's advanced metrics, scParadise offers a powerful, fast, and reliable solution for single-cell analysis, setting a new standard in scRNA-seq data processing.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: scParadise: Tunable highly accurate multi-task cell type annotation and surface protein abundance prediction Abstract: scRNA-seq is revolutionizing biomedical research by revealing tissue architecture, cellular composition, and functional interactions. However, accurate cell type annotation remains a challenge, particularly for rare cell types, with existing automated methods often falling short. Multimodal data, combining mRNA expression and protein markers, improves deep cellular analysis and make functional characterization of complex tissues more accurate. However, it is costly and complex to obtain. We present scParadise, a cutting-edge Python framework featuring three tools: scAdam for multi-level cell annotation, scEve for surface protein prediction, and scNoah for benchmarking. scAdam surpasses current methods in annotating rare cell types and ensures consistent results across diverse datasets, while scEve enhances clustering and cell type separation. With scNoah's advanced metrics, scParadise offers a powerful, fast, and reliable solution for single-cell analysis, setting a new standard in scRNA-seq data processing.","summary":"scAdam outperforms existing methods in annotating rare cell types with high accuracy and consistency across diverse datasets. scEve enhances clustering and cell type separation through improved surface protein prediction, leading to better characterization of complex tissues."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Camera Paths, Modeling, and Image Processing Tools for ArtiaX","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614454v1?rss=1","abstract":"The enhancement of biomolecular image analysis and data interpretation is significantly improved through the application of advanced visualization techniques. Numerous visualization packages are currently available, spanning a broad spectrum of applications. Recently, we have extended the capabilities of UCSF ChimeraX to address the specific demands of cryo-electron tomography. Here, we introduce the evolution of our existing plugin, ArtiaX, designed to generate models that facilitate particle selection, define camera recording paths, and execute particle selection routines. In particular, diverse models can be generated and populated with putative particle positions and orientations. A specifically tailored coarse grained algorithm was developed to rectify overlaps, as encountered in template matching, employing a rapid and efficient approach. In addition, models can be used to drive the camera position, thereby simplifying the process of movie creation. The plugin incorporates fundamental image filtering options for the on-the-fly analysis of tomographic data. Collectively, this update of ArtiaX comprehensively encompasses essential tools for the analysis and visualization of electron tomograms. It retains its hallmark attributes of speed, reliability, and user-friendliness, fostering seamless human-machine interaction.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Camera Paths, Modeling, and Image Processing Tools for ArtiaX Abstract: The enhancement of biomolecular image analysis and data interpretation is significantly improved through the application of advanced visualization techniques. Numerous visualization packages are currently available, spanning a broad spectrum of applications. Recently, we have extended the capabilities of UCSF ChimeraX to address the specific demands of cryo-electron tomography. Here, we introduce the evolution of our existing plugin, ArtiaX, designed to generate models that facilitate particle selection, define camera recording paths, and execute particle selection routines. In particular, diverse models can be generated and populated with putative particle positions and orientations. A specifically tailored coarse grained algorithm was developed to rectify overlaps, as encountered in template matching, employing a rapid and efficient approach. In addition, models can be used to drive the camera position, thereby simplifying the process of movie creation. The plugin incorporates fundamental image filtering options for the on-the-fly analysis of tomographic data. Collectively, this update of ArtiaX comprehensively encompasses essential tools for the analysis and visualization of electron tomograms. It retains its hallmark attributes of speed, reliability, and user-friendliness, fostering seamless human-machine interaction.","summary":"ArtiaX is a plugin that has been extended to improve the analysis and visualization of cryo-electron tomography data through advanced visualization techniques. The plugin allows for the generation of diverse models with putative particle positions and orientations, as well as a coarse grained algorithm to rectify overlaps in template matching, driving camera position and facilitating movie creation with fundamental image filtering options."}
{"source":"bioRxiv","subject":"bioinformatics","title":"dScaff - an automatic bioinformatics framework for scaffolding draft de novo assemblies based on reference genome data","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614313v1?rss=1","abstract":"Rapid evolution of long-read sequencing technologies requires accurate, fast and user-friendly genome assembly and scaffolding tools. In this article we present Digital Scaffolding (dScaff), a bioinformatics tool that performs scaffolding of de novo genome assemblies based on reference scaffolds or chromosomes. dScaff makes use of a series of bash and R scripts in order to create a minimal complete scaffold from a genome assembly, with future features to be implemented. Herein, we demonstrate the functionality of dScaff on a novel genome assembly pertaining to a recently sequenced local strain of Drosophila suzukii.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: dScaff - an automatic bioinformatics framework for scaffolding draft de novo assemblies based on reference genome data Abstract: Rapid evolution of long-read sequencing technologies requires accurate, fast and user-friendly genome assembly and scaffolding tools. In this article we present Digital Scaffolding (dScaff), a bioinformatics tool that performs scaffolding of de novo genome assemblies based on reference scaffolds or chromosomes. dScaff makes use of a series of bash and R scripts in order to create a minimal complete scaffold from a genome assembly, with future features to be implemented. Herein, we demonstrate the functionality of dScaff on a novel genome assembly pertaining to a recently sequenced local strain of Drosophila suzukii.","summary":"dScaff is an automatic bioinformatics framework designed for scaffolding draft de novo assemblies based on reference genome data. The tool uses a series of bash and R scripts to create a minimal complete scaffold from a genome assembly, with potential future features to be implemented, including using reference chromosomes or scaffolds."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Jaeger: an accurate and fast deep-learning tool to detect bacteriophage sequences","url":"http://biorxiv.org/cgi/content/short/2024.09.24.612722v1?rss=1","abstract":"Abstract Viruses are integral to every biome on Earth, yet we still need a more comprehensive picture of their identity and global distribution. Global metagenomics sequencing efforts revealed the genomic content of tens of thousands of environmental samples, however identifying the viral sequences in these datasets remains challenging due to their vast genomic diversity. Here, we address identifying bacteriophage sequences in sequencing data. In a recent benchmarking paper, we observed that existing deep-learning tools show a high true positive rate, but often produce many false positives when confronted with divergent sequences. To tackle this challenge, we introduce Jaeger, a novel deep-learning method designed specifically for identifying bacteriophage genome fragments. Extensive benchmarking on the IMG/VR database and real-world metagenomes reveals Jaeger's consistent performance across various scenarios. Applying Jaeger to over 16,000 metagenomic assemblies from the MGnify database yielded over five million putative phage contigs at an estimated 2-27% false discovery rate. On average, Jaeger is around 20 times faster than the other state-of-the-art methods, highlighting its efficacy in bacteriophage identification within global metagenomes. Jaeger is available at https://github.com/MGXlab/Jaeger.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Jaeger: an accurate and fast deep-learning tool to detect bacteriophage sequences Abstract: Abstract Viruses are integral to every biome on Earth, yet we still need a more comprehensive picture of their identity and global distribution. Global metagenomics sequencing efforts revealed the genomic content of tens of thousands of environmental samples, however identifying the viral sequences in these datasets remains challenging due to their vast genomic diversity. Here, we address identifying bacteriophage sequences in sequencing data. In a recent benchmarking paper, we observed that existing deep-learning tools show a high true positive rate, but often produce many false positives when confronted with divergent sequences. To tackle this challenge, we introduce Jaeger, a novel deep-learning method designed specifically for identifying bacteriophage genome fragments. Extensive benchmarking on the IMG/VR database and real-world metagenomes reveals Jaeger's consistent performance across various scenarios. Applying Jaeger to over 16,000 metagenomic assemblies from the MGnify database yielded over five million putative phage contigs at an estimated 2-27% false discovery rate. On average, Jaeger is around 20 times faster than the other state-of-the-art methods, highlighting its efficacy in bacteriophage identification within global metagenomes. Jaeger is available at https://github.com/MGXlab/Jaeger.","summary":"Jaeger's accuracy and speed in identifying bacteriophage sequences outperform existing deep-learning tools by consistently producing few false positives despite encountering diverse viral sequences. The novel method achieves an estimated 2-27% false discovery rate when applied to over 16,000 metagenomic assemblies, which is significantly lower than the benchmarking paper where deep-learning tools produced many false positives."}
{"source":"bioRxiv","subject":"bioinformatics","title":"AI-Augmented R-Group Exploration in Medicinal Chemistry","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614417v1?rss=1","abstract":"Efficient R-group exploration in the vast chemical space, enabled by increasingly available building blocks or generative AI, remains an open challenge. Here, we developed an enhanced Free-Wilson QSAR model embedding R-groups by atom-centric pharmacophoric features. Regioisomers of R-groups can be distinguished by explicitly accounting for the atomic positions. Good predictivity is observed consistently across 12 public datasets. Integrated into an open-source program, we showcase its application in performing classic Free-Wilson analysis as well as R-group exploration in uncharted chemical space.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: AI-Augmented R-Group Exploration in Medicinal Chemistry Abstract: Efficient R-group exploration in the vast chemical space, enabled by increasingly available building blocks or generative AI, remains an open challenge. Here, we developed an enhanced Free-Wilson QSAR model embedding R-groups by atom-centric pharmacophoric features. Regioisomers of R-groups can be distinguished by explicitly accounting for the atomic positions. Good predictivity is observed consistently across 12 public datasets. Integrated into an open-source program, we showcase its application in performing classic Free-Wilson analysis as well as R-group exploration in uncharted chemical space.","summary":"The paper presents a novel approach to enhancing free-wing QSAR models by embedding R-groups with atom-centric pharmacophoric features, allowing for the distinction of regioisomers and improved predictivity across 12 public datasets. The proposed method is integrated into an open-source program, enabling its application in various scenarios, including classic free-Wilson analysis and exploration of uncharted chemical space facilitated by AI-generated building blocks."}
{"source":"bioRxiv","subject":"bioinformatics","title":"OPLS-based Multiclass Classification and Data-Driven Inter-Class Relationship Discovery","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614438v1?rss=1","abstract":"Multiclass datasets and large-scale studies are increasingly common in omics sciences, drug discovery, and clinical research due to advancements in analytical platforms. Efficiently handling these datasets and discerning subtle differences across multiple classes remains a significant challenge. In metabolomics, two-class OPLS-DA (Orthogonal Projection to Latent Structures Discriminant Analysis) models are widely used due to their strong discrimination capabilities and ability to provide interpretable information on class differences. However, these models face challenges in multiclass settings. A common solution is to transform the multiclass comparison into multiple two-class comparisons, which, while more effective than a global multiclass OPLS-DA model, unfortunately results in a manual, time-consuming model-building process with complicated interpretation. Here, we introduce an extension of OPLS-DA for data-driven multiclass classification: Orthogonal Partial Least Squares-Hierarchical Discriminant Analysis (OPLS-HDA). OPLS-HDA integrates Hierarchical Cluster Analysis (HCA) with the OPLS-DA framework to create a decision tree, addressing multiclass classification challenges and providing intuitive visualization of inter-class relationships. To avoid overfitting and ensure reliable predictions, we use cross-validation during model building. Benchmark results show that OPLS-HDA performs competitively across diverse datasets compared to eight established methods. This method represents a significant advancement, offering a powerful tool to dissect complex multiclass datasets. With its versatility, interpretability, and ease of use, OPLS-HDA is an efficient approach to multiclass data analysis applicable across various fields.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: OPLS-based Multiclass Classification and Data-Driven Inter-Class Relationship Discovery Abstract: Multiclass datasets and large-scale studies are increasingly common in omics sciences, drug discovery, and clinical research due to advancements in analytical platforms. Efficiently handling these datasets and discerning subtle differences across multiple classes remains a significant challenge. In metabolomics, two-class OPLS-DA (Orthogonal Projection to Latent Structures Discriminant Analysis) models are widely used due to their strong discrimination capabilities and ability to provide interpretable information on class differences. However, these models face challenges in multiclass settings. A common solution is to transform the multiclass comparison into multiple two-class comparisons, which, while more effective than a global multiclass OPLS-DA model, unfortunately results in a manual, time-consuming model-building process with complicated interpretation. Here, we introduce an extension of OPLS-DA for data-driven multiclass classification: Orthogonal Partial Least Squares-Hierarchical Discriminant Analysis (OPLS-HDA). OPLS-HDA integrates Hierarchical Cluster Analysis (HCA) with the OPLS-DA framework to create a decision tree, addressing multiclass classification challenges and providing intuitive visualization of inter-class relationships. To avoid overfitting and ensure reliable predictions, we use cross-validation during model building. Benchmark results show that OPLS-HDA performs competitively across diverse datasets compared to eight established methods. This method represents a significant advancement, offering a powerful tool to dissect complex multiclass datasets. With its versatility, interpretability, and ease of use, OPLS-HDA is an efficient approach to multiclass data analysis applicable across various fields.","summary":"OPLS-DA models are widely used in metabolomics for two-class comparisons due to their strong discrimination capabilities, but these models face challenges in multiclass settings. An extension of OPLS-DA called OPLS-HDA integrates Hierarchical Cluster Analysis with the OPLS-DA framework to create a decision tree that addresses multiclass classification challenges and provides intuitive visualization of inter-class relationships."}
{"source":"bioRxiv","subject":"bioinformatics","title":"STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics","url":"http://biorxiv.org/cgi/content/short/2024.09.22.614385v1?rss=1","abstract":"A significant challenge in analyzing spatial transcriptomics data is the effective and efficient detection of spatially variable genes (SVGs), whose expression exhibits non-random spatial patterns in tissues. Many SVGs show spatial variation in expression that is highly correlated with cell type categories or compositions, leading to the concept of cell type-specific spatially variable genes (ctSVGs). Existing statistical methods for detecting ctSVGs treat cell type-specific spatial effects as fixed effects when modeling, resulting in a critical issue: the testing results are not invariant to the rotation of spatial coordinates. Additionally, an SVG may display random spatial patterns within a cell type, and a ctSVG may exhibit random spatial patterns from a general perspective, indicating that an SVG does not necessarily have to be a ctSVG, and vice versa. This poses challenges in real analysis when detecting SVGs or ctSVGs. To address these problems, we propose STANCE, a unified statistical model developed to detect both SVG and ctSVGs in spatial transcriptomics. By integrating gene expression, spatial location, and cell type composition through a linear mixed-effect model, STANCE enables the identification of both SVGs and ctSVGs in an initial stage, followed by a second stage test dedicated to ctSVG detection. Its design ensures robustness in complex scenarios and the results are spatial rotation invariant. We demonstrated the performance of STANCE through comprehensive simulations and analyses of three public datasets. The downstream analyses based on ctSVGs detected by STANCE suggest promising future applications of the model in spatial transcriptomics and various areas of genome biology. A software implementation of STANCE is available at https://github.com/Cui-STT-Lab/STANCE.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: STANCE: a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics Abstract: A significant challenge in analyzing spatial transcriptomics data is the effective and efficient detection of spatially variable genes (SVGs), whose expression exhibits non-random spatial patterns in tissues. Many SVGs show spatial variation in expression that is highly correlated with cell type categories or compositions, leading to the concept of cell type-specific spatially variable genes (ctSVGs). Existing statistical methods for detecting ctSVGs treat cell type-specific spatial effects as fixed effects when modeling, resulting in a critical issue: the testing results are not invariant to the rotation of spatial coordinates. Additionally, an SVG may display random spatial patterns within a cell type, and a ctSVG may exhibit random spatial patterns from a general perspective, indicating that an SVG does not necessarily have to be a ctSVG, and vice versa. This poses challenges in real analysis when detecting SVGs or ctSVGs. To address these problems, we propose STANCE, a unified statistical model developed to detect both SVG and ctSVGs in spatial transcriptomics. By integrating gene expression, spatial location, and cell type composition through a linear mixed-effect model, STANCE enables the identification of both SVGs and ctSVGs in an initial stage, followed by a second stage test dedicated to ctSVG detection. Its design ensures robustness in complex scenarios and the results are spatial rotation invariant. We demonstrated the performance of STANCE through comprehensive simulations and analyses of three public datasets. The downstream analyses based on ctSVGs detected by STANCE suggest promising future applications of the model in spatial transcriptomics and various areas of genome biology. A software implementation of STANCE is available at https://github.com/Cui-STT-Lab/STANCE.","summary":"STANCE, a unified statistical model to detect cell-type-specific spatially variable genes in spatial transcriptomics, was developed to address the challenges posed by existing methods in detecting spatially variable genes (SVGs) and cell type-specific spatially variable genes (ctSVGs). The proposed method integrates gene expression, spatial location, and cell type composition through a linear mixed-effect model to identify both SVGs and ctSVGs in an initial stage, followed by a second stage test dedicated to ctSVG detection."}
{"source":"bioRxiv","subject":"bioinformatics","title":"AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow","url":"http://biorxiv.org/cgi/content/short/2024.09.20.613625v1?rss=1","abstract":"Motivation: The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA sequencing (scRNAseq) assays enables the detailed exploration of transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, including the lack of advanced simulation tools that can effectively mimic the unique complexities of scRNAseq long-read datasets. Such tools are essential for the evaluation and optimization of isoform detection methods dedicated to single-cell long readstudies. Results: We developed AsaruSim, a workflow that simulates synthetic single-cell long-read Nanopore datasets, closely mimicking real experimental data. AsaruSim employs a multi-step process that includes the creation of a synthetic UMI count matrix, generation of perfect reads, optional PCR amplification, introduction of sequencing errors, and comprehensive quality control reporting. Applied to a dataset of human peripheral blood mononuclear cells (PBMCs), AsaruSim accurately reproduced experimental read characteristics. Availability and implementation: The source code and full documentation are available at: https://github.com/GenomiqueENS/AsaruSim. Data availability: The 1,090 Human PBMCs count matrix and cell type annotation files are accessible on zenodo under DOI: 10.5281/zenodo.12731408.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: AsaruSim: a single-cell and spatial RNA-Seq Nanopore long-reads simulation workflow Abstract: Motivation: The combination of long-read sequencing technologies like Oxford Nanopore with single-cell RNA sequencing (scRNAseq) assays enables the detailed exploration of transcriptomic complexity, including isoform detection and quantification, by capturing full-length cDNAs. However, challenges remain, including the lack of advanced simulation tools that can effectively mimic the unique complexities of scRNAseq long-read datasets. Such tools are essential for the evaluation and optimization of isoform detection methods dedicated to single-cell long readstudies. Results: We developed AsaruSim, a workflow that simulates synthetic single-cell long-read Nanopore datasets, closely mimicking real experimental data. AsaruSim employs a multi-step process that includes the creation of a synthetic UMI count matrix, generation of perfect reads, optional PCR amplification, introduction of sequencing errors, and comprehensive quality control reporting. Applied to a dataset of human peripheral blood mononuclear cells (PBMCs), AsaruSim accurately reproduced experimental read characteristics. Availability and implementation: The source code and full documentation are available at: https://github.com/GenomiqueENS/AsaruSim. Data availability: The 1,090 Human PBMCs count matrix and cell type annotation files are accessible on zenodo under DOI: 10.5281/zenodo.12731408.","summary":"AsaruSim simulates synthetic single-cell long-read Nanopore datasets that closely mimic real experimental data by employing a multi-step process. It includes the creation of a synthetic UMI count matrix, generation of perfect reads, optional PCR amplification, introduction of sequencing errors, and comprehensive quality control reporting."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Building a literature knowledge base towards transparent biomedical AI","url":"http://biorxiv.org/cgi/content/short/2024.09.22.614323v1?rss=1","abstract":"Knowledge graphs have recently emerged as a powerful data structure to organize biomedical knowledge with explicit representation of nodes and edges. The knowledge representation is in a machine-learning ready format and supports explainable AI models. However, PubMed, the largest and richest biomedical knowledge repository, exists as free text, limiting its utility for advanced machine learning tasks. To address the limitation, we present LiteralGraph, a computational framework that rigorously extracts biomedical terms and relationships from PubMed literature. Using this framework, we established Genomic Literature Knowledge Base (GLKB), a knowledge graph that consolidates 263,714,413 biomedical terms, 14,634,427 biomedical relationships, and 10,667,370 genomic events from 33 million PubMed abstracts and nine well-established biomedical repositories. The database is coupled with RESTful APIs and a user-friendly web interface that make it accessible to researchers for various usages, including machine learning using the semantic knowledge in PubMed articles, reducing hallucination of large language models (LLM), and helping experimental scientists explore their data using vast PubMed evidence.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Building a literature knowledge base towards transparent biomedical AI Abstract: Knowledge graphs have recently emerged as a powerful data structure to organize biomedical knowledge with explicit representation of nodes and edges. The knowledge representation is in a machine-learning ready format and supports explainable AI models. However, PubMed, the largest and richest biomedical knowledge repository, exists as free text, limiting its utility for advanced machine learning tasks. To address the limitation, we present LiteralGraph, a computational framework that rigorously extracts biomedical terms and relationships from PubMed literature. Using this framework, we established Genomic Literature Knowledge Base (GLKB), a knowledge graph that consolidates 263,714,413 biomedical terms, 14,634,427 biomedical relationships, and 10,667,370 genomic events from 33 million PubMed abstracts and nine well-established biomedical repositories. The database is coupled with RESTful APIs and a user-friendly web interface that make it accessible to researchers for various usages, including machine learning using the semantic knowledge in PubMed articles, reducing hallucination of large language models (LLM), and helping experimental scientists explore their data using vast PubMed evidence.","summary":"LiteralGraph extracts biomedical terms and relationships from PubMed literature, establishing a comprehensive knowledge graph. The resulting Genomic Literature Knowledge Base consolidates over 263 million biomedical terms, 14 million relationships, and 10 million genomic events across multiple sources, including nine established repositories."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Accurate non-invasive quantification of astaxanthin content using hyperspectral images and machine learning","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614444v1?rss=1","abstract":"Commercial cultivation of the microalgae Haematococcus pluvialis to produce natural astaxanthin has gained significant traction due to the high antioxidant capacity of this pigment and its application in foods, feed, cosmetics and nutraceuticals. However, monitoring of astaxanthin content in cultures remains challenging and relies on invasive, time consuming and expensive approaches. In this study, we employed reflectance hyperspectral imaging (HSI) of H. pluvialis suspensions within the visible spectrum, combined with a 1-dimensional convolutional neural network (CNN) to predict the astaxanthin content (ug mg-1) as quantified by high-performance liquid chromatography (HPLC). This approach had low average prediction error (5.9%) across a gradient of astaxanthin contents and was only unreliable at very low contents (<0.6 micrograms mg-1). In addition, our machine learning model outperformed single or dual wavelength linear regression models even when the spectral data was obtained with a spectrophotometer coupled with an integrating sphere. Overall, this study proposes the use of HSI in combination with a CNN for precise non-invasive quantification of astaxanthin in cell suspensions.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Accurate non-invasive quantification of astaxanthin content using hyperspectral images and machine learning Abstract: Commercial cultivation of the microalgae Haematococcus pluvialis to produce natural astaxanthin has gained significant traction due to the high antioxidant capacity of this pigment and its application in foods, feed, cosmetics and nutraceuticals. However, monitoring of astaxanthin content in cultures remains challenging and relies on invasive, time consuming and expensive approaches. In this study, we employed reflectance hyperspectral imaging (HSI) of H. pluvialis suspensions within the visible spectrum, combined with a 1-dimensional convolutional neural network (CNN) to predict the astaxanthin content (ug mg-1) as quantified by high-performance liquid chromatography (HPLC). This approach had low average prediction error (5.9%) across a gradient of astaxanthin contents and was only unreliable at very low contents (<0.6 micrograms mg-1). In addition, our machine learning model outperformed single or dual wavelength linear regression models even when the spectral data was obtained with a spectrophotometer coupled with an integrating sphere. Overall, this study proposes the use of HSI in combination with a CNN for precise non-invasive quantification of astaxanthin in cell suspensions.","summary":"The authors investigated a method to accurately quantify astaxanthin content in Haematococcus pluvialis microalgae cultures using hyperspectral images and machine learning. They found that this approach, combining reflectance hyperspectral imaging with a 1-dimensional convolutional neural network, had low average prediction error across a range of astaxanthin contents, although it was unreliable at very low levels (<0.6 micrograms mg-1)."}
{"source":"bioRxiv","subject":"bioinformatics","title":"AlphaMut: a deep reinforcement learning model to suggest helix-disrupting mutations","url":"http://biorxiv.org/cgi/content/short/2024.09.21.614241v1?rss=1","abstract":"Helices are important secondary structural motifs within proteins and are pivotal in numerous physiological processes. While amino acids (AA) such as alanine and leucine are known to promote helix formation, proline and glycine disfavor it. Helical structure formation, however, also depends on its environment, and hence, prior prediction of a mutational effect on a helical structure is difficult. Here, we employ a reinforcement learning algorithm to develop a predictive model for helix-disrupting mutations. We start with a toy model consisting of helices with only 30 AA and train different models. Our results show that only a few mutations lead to a drastic disruption of the target helix. We further extend our approach to helices in proteins and validate the results using rigorous free energy calculations. Our strategy identifies amino acids crucial for maintaining structural integrity and predicts key mutations that could alter protein function. Through our work, we present a new use case for reinforcement learning in protein structure disruption.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: AlphaMut: a deep reinforcement learning model to suggest helix-disrupting mutations Abstract: Helices are important secondary structural motifs within proteins and are pivotal in numerous physiological processes. While amino acids (AA) such as alanine and leucine are known to promote helix formation, proline and glycine disfavor it. Helical structure formation, however, also depends on its environment, and hence, prior prediction of a mutational effect on a helical structure is difficult. Here, we employ a reinforcement learning algorithm to develop a predictive model for helix-disrupting mutations. We start with a toy model consisting of helices with only 30 AA and train different models. Our results show that only a few mutations lead to a drastic disruption of the target helix. We further extend our approach to helices in proteins and validate the results using rigorous free energy calculations. Our strategy identifies amino acids crucial for maintaining structural integrity and predicts key mutations that could alter protein function. Through our work, we present a new use case for reinforcement learning in protein structure disruption.","summary":"The authors propose a deep reinforcement learning model called AlphaMut to predict helix-disrupting mutations in proteins. AlphaMut identifies amino acids crucial for maintaining structural integrity and predicts key mutations that could alter protein function."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Beyond Static Brain Atlases: AI-Powered Open Databasing and Dynamic Mining of Brain-Wide Neuron Morphometry","url":"http://biorxiv.org/cgi/content/short/2024.09.22.614319v1?rss=1","abstract":"We introduce NeuroXiv (neuroxiv.org), a large-scale, AI-powered database that provides detailed 3D morphologies of individual neurons mapped to a standard brain atlas, designed to support a wide array of dynamic, interactive neuroscience applications. NeuroXiv offers a comprehensive collection of 175,149 atlas-oriented reconstructed morphologies of individual neurons derived from more than 518 mouse brains, classified into 292 distinct types and mapped into the Common Coordinate Framework Version 3 (CCFv3). Different from conventional static brain atlases that are often limited to data-browsing, NeuroXiv allows interactive analyses as well as uploading and databasing custom neuron morphologies, which are mapped to the brain atlas for objective comparisons. Powered by a cutting-edge AI engine (AIPOM), NeuroXiv enables dynamic, user-specific analysis and data mining. We specifically developed a mixture-of-experts algorithm to harness the capabilities of multiple large language models. We also developed a client program to achieve more than 10 times better performance compared to a typical server-side setup. We demonstrate NeuroXiv's scalability, efficiency, flexibility, openness, and robustness through various applications.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Beyond Static Brain Atlases: AI-Powered Open Databasing and Dynamic Mining of Brain-Wide Neuron Morphometry Abstract: We introduce NeuroXiv (neuroxiv.org), a large-scale, AI-powered database that provides detailed 3D morphologies of individual neurons mapped to a standard brain atlas, designed to support a wide array of dynamic, interactive neuroscience applications. NeuroXiv offers a comprehensive collection of 175,149 atlas-oriented reconstructed morphologies of individual neurons derived from more than 518 mouse brains, classified into 292 distinct types and mapped into the Common Coordinate Framework Version 3 (CCFv3). Different from conventional static brain atlases that are often limited to data-browsing, NeuroXiv allows interactive analyses as well as uploading and databasing custom neuron morphologies, which are mapped to the brain atlas for objective comparisons. Powered by a cutting-edge AI engine (AIPOM), NeuroXiv enables dynamic, user-specific analysis and data mining. We specifically developed a mixture-of-experts algorithm to harness the capabilities of multiple large language models. We also developed a client program to achieve more than 10 times better performance compared to a typical server-side setup. We demonstrate NeuroXiv's scalability, efficiency, flexibility, openness, and robustness through various applications.","summary":"NeuroXiv is a large-scale database that provides detailed 3D morphologies of individual neurons mapped to a standard brain atlas, allowing for dynamic, interactive neuroscience applications. The database offers a comprehensive collection of 175,149 atlas-oriented reconstructed morphologies of individual neurons from over 518 mouse brains, classified into 292 distinct types and mapped into the Common Coordinate Framework Version 3 (CCFv3)."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana","url":"http://biorxiv.org/cgi/content/short/2024.09.20.614037v1?rss=1","abstract":"Temperature is a critical environmental factor affecting nearly all plant processes, including growth, development, and yield. Yet, despite decades of research, we lack the ability to predict plant performance at different temperatures, limiting the development of climate-resilient crops. Further, there is a pressing need to bridge the gap between the prediction of physiological and molecular traits to improve our understanding and manipulation of plant temperature responses. Here, we developed the first enzyme-constrained model of Arabidopsis thaliana's metabolism, facilitating predictions of growth-related phenotypes at different temperatures. We showed that the model can be employed for in silico identification of genes that affect plant growth at suboptimal growth temperature. Using mutant lines, we validated the genes predicted to affect plant growth, demonstrating the potential of metabolic modeling in accurately predicting plant thermal responses. The temperature-dependent enzyme-constrained metabolic model provides a template that can be used for developing sophisticated strategies to engineer climate-resilient crops.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Metabolic modeling identifies determinants of thermal growth responses in Arabidopsis thaliana Abstract: Temperature is a critical environmental factor affecting nearly all plant processes, including growth, development, and yield. Yet, despite decades of research, we lack the ability to predict plant performance at different temperatures, limiting the development of climate-resilient crops. Further, there is a pressing need to bridge the gap between the prediction of physiological and molecular traits to improve our understanding and manipulation of plant temperature responses. Here, we developed the first enzyme-constrained model of Arabidopsis thaliana's metabolism, facilitating predictions of growth-related phenotypes at different temperatures. We showed that the model can be employed for in silico identification of genes that affect plant growth at suboptimal growth temperature. Using mutant lines, we validated the genes predicted to affect plant growth, demonstrating the potential of metabolic modeling in accurately predicting plant thermal responses. The temperature-dependent enzyme-constrained metabolic model provides a template that can be used for developing sophisticated strategies to engineer climate-resilient crops.","summary":"The paper developed an enzyme-constrained model of Arabidopsis thaliana's metabolism, which facilitates predictions of growth-related phenotypes at different temperatures and identifies genes affecting plant growth at suboptimal temperatures. This model was validated using mutant lines, demonstrating its potential in accurately predicting plant thermal responses and providing a template for developing climate-resilient crops."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Decoding Protein Dynamics: ProFlex as a Linguistic Bridge in Normal Mode Analysis","url":"http://biorxiv.org/cgi/content/short/2024.09.21.614246v1?rss=1","abstract":"Artificial intelligence has revolutionized structural bioinformatics, with AlphaFold being arguably the most impactful development to date. The structural atlases generated by these methods present significant opportunities for unraveling biological mysteries, but also pose challenges in leveraging such massive datasets effectively. In this work, we explore the dynamic landscape of hundreds of thousands of AlphaFold-predicted structures using normal mode analysis. The resulting data is used to define an alphabet summarizing relative protein flexibility, termed ProFlex. We believe that refining and further applying ProFlex-like approaches offers novel opportunities for understanding protein function and enhancing other methods.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Decoding Protein Dynamics: ProFlex as a Linguistic Bridge in Normal Mode Analysis Abstract: Artificial intelligence has revolutionized structural bioinformatics, with AlphaFold being arguably the most impactful development to date. The structural atlases generated by these methods present significant opportunities for unraveling biological mysteries, but also pose challenges in leveraging such massive datasets effectively. In this work, we explore the dynamic landscape of hundreds of thousands of AlphaFold-predicted structures using normal mode analysis. The resulting data is used to define an alphabet summarizing relative protein flexibility, termed ProFlex. We believe that refining and further applying ProFlex-like approaches offers novel opportunities for understanding protein function and enhancing other methods.","summary":"Artificial intelligence has revolutionized structural bioinformatics with AlphaFold being arguably the most impactful development to date. The structural atlases generated by these methods present significant opportunities for unraveling biological mysteries, but also pose challenges in leveraging such massive datasets effectively."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Exploring midgut expression dynamics: longitudinal transcriptomic analysis of adult female Amblyomma americanum midgut and comparative insights with other hard tick species","url":"http://biorxiv.org/cgi/content/short/2024.09.20.614175v1?rss=1","abstract":"Background: Female ticks remain attached to their host for multiple days to complete a blood meal. This prolonged feeding period is accompanied by a significant increase in the tick size and body weight, paralleled by noteworthy changes to the tick midgut. While the midgut is recognized for its established role in blood storage and processing, its importance extends to playing a crucial role in the acquisition, survival, and proliferation of pathogens. Despite this, our overall understanding of tick midgut biology is limited. Results: We conducted a comprehensive longitudinal transcriptome analysis of the midgut in adult female A. americanum ticks across various feeding stages, including unfed, slow-feeding, and rapid-feeding phases. Our analysis revealed 15,599 putative DNA coding sequences (CDS) classified within 26 functional groups. Dimensional and differential expression analysis highlighted the dynamic transcriptional changes in the tick midgut as feeding progresses, particularly during the initial period of feeding and the transition from the slow-feeding to the rapid-feeding phase. Additionally, we performed an orthology analysis comparing our dataset with midgut transcriptomes from other hard ticks, such as Ixodes scapularis and Rhipicephalus microplus. This comparison allowed us to identify transcripts commonly expressed during different feeding phases across these three species. Conclusion: Our findings provide a detailed temporal resolution of numerous metabolic pathways in A. americanum, emphasizing the dynamic transcriptional changes occurring in the tick midgut throughout the feeding process. Furthermore, we identified conserved transcripts across three different tick species that exhibit similar expression patterns. This knowledge has significant implications for future research aimed at deciphering the physiological pathways relevant within the tick midgut. It also offers potential avenues for developing control methods that target multiple tick species.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Exploring midgut expression dynamics: longitudinal transcriptomic analysis of adult female Amblyomma americanum midgut and comparative insights with other hard tick species Abstract: Background: Female ticks remain attached to their host for multiple days to complete a blood meal. This prolonged feeding period is accompanied by a significant increase in the tick size and body weight, paralleled by noteworthy changes to the tick midgut. While the midgut is recognized for its established role in blood storage and processing, its importance extends to playing a crucial role in the acquisition, survival, and proliferation of pathogens. Despite this, our overall understanding of tick midgut biology is limited. Results: We conducted a comprehensive longitudinal transcriptome analysis of the midgut in adult female A. americanum ticks across various feeding stages, including unfed, slow-feeding, and rapid-feeding phases. Our analysis revealed 15,599 putative DNA coding sequences (CDS) classified within 26 functional groups. Dimensional and differential expression analysis highlighted the dynamic transcriptional changes in the tick midgut as feeding progresses, particularly during the initial period of feeding and the transition from the slow-feeding to the rapid-feeding phase. Additionally, we performed an orthology analysis comparing our dataset with midgut transcriptomes from other hard ticks, such as Ixodes scapularis and Rhipicephalus microplus. This comparison allowed us to identify transcripts commonly expressed during different feeding phases across these three species. Conclusion: Our findings provide a detailed temporal resolution of numerous metabolic pathways in A. americanum, emphasizing the dynamic transcriptional changes occurring in the tick midgut throughout the feeding process. Furthermore, we identified conserved transcripts across three different tick species that exhibit similar expression patterns. This knowledge has significant implications for future research aimed at deciphering the physiological pathways relevant within the tick midgut. It also offers potential avenues for developing control methods that target multiple tick species.","summary":"The study investigates the transcriptomic dynamics of the midgut in adult female Amblyomma americanum ticks during different feeding stages, revealing 15,599 putative DNA coding sequences and highlighting dynamic transcriptional changes as feeding progresses. The analysis also identified conserved transcripts across three hard tick species, providing insight into the physiological pathways relevant to the tick midgut and potential avenues for developing control methods targeting multiple tick species."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Designing of thermostable proteins with a desired melting temperature","url":"http://biorxiv.org/cgi/content/short/2024.09.21.614294v1?rss=1","abstract":"The stability of proteins at higher temperatures is crucial for its functionality that is measured by their melting temperature (Tm). The Tm is the temperature at which 50% of the protein loses its native structure and activity. Existing methods for predicting Tm have two major limitations: first, they are often trained on redundant proteins, and second, they do not allow users to design proteins with the desired Tm. To address these limitations, we developed a regression method for predicting the Tm value of proteins using 17,312 non-redundant proteins, where no two proteins are more than 40% similar. We used 80% of the data for training and testing; remaining 20% of the data for validation. Initially, we developed a machine learning model using standard features from protein sequences. Our best model, developed using Shannon entropy for all residues, achieved the highest Pearson correlation of 0.80 with an R2 of 0.63 between the predicted and actual Tm of proteins on the validation dataset. Next, we fine-tuned large language models (e.g., ProtBert, ProtGPT2, ProtT5) on our training dataset and generated embeddings. These embeddings have been used for developing machine learning models. Our best model, developed using ProtBert embeddings, achieved a maximum correlation of 0.89 with an R2 of 0.80 on the validation dataset. Finally, we developed an ensemble method that combines standard protein features and embeddings. One of the aims of the study is to assist the scientific community in the design of targeted melting temperatures. We created a user-friendly web server and a python package for predicting and designing thermostable proteins. Our standalone software can be used to screen thermostable proteins in genomes and metagenomes. We demonstrated the application of PPTstab in identifying thermostable proteins in different organisms from their genomes, the model and data is available at: https://webs.iiitd.edu.in/raghava/pptstab.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Designing of thermostable proteins with a desired melting temperature Abstract: The stability of proteins at higher temperatures is crucial for its functionality that is measured by their melting temperature (Tm). The Tm is the temperature at which 50% of the protein loses its native structure and activity. Existing methods for predicting Tm have two major limitations: first, they are often trained on redundant proteins, and second, they do not allow users to design proteins with the desired Tm. To address these limitations, we developed a regression method for predicting the Tm value of proteins using 17,312 non-redundant proteins, where no two proteins are more than 40% similar. We used 80% of the data for training and testing; remaining 20% of the data for validation. Initially, we developed a machine learning model using standard features from protein sequences. Our best model, developed using Shannon entropy for all residues, achieved the highest Pearson correlation of 0.80 with an R2 of 0.63 between the predicted and actual Tm of proteins on the validation dataset. Next, we fine-tuned large language models (e.g., ProtBert, ProtGPT2, ProtT5) on our training dataset and generated embeddings. These embeddings have been used for developing machine learning models. Our best model, developed using ProtBert embeddings, achieved a maximum correlation of 0.89 with an R2 of 0.80 on the validation dataset. Finally, we developed an ensemble method that combines standard protein features and embeddings. One of the aims of the study is to assist the scientific community in the design of targeted melting temperatures. We created a user-friendly web server and a python package for predicting and designing thermostable proteins. Our standalone software can be used to screen thermostable proteins in genomes and metagenomes. We demonstrated the application of PPTstab in identifying thermostable proteins in different organisms from their genomes, the model and data is available at: https://webs.iiitd.edu.in/raghava/pptstab.","summary":"We developed a regression method for predicting protein melting temperatures (Tm) using 17,312 non-redundant proteins and achieved the highest Pearson correlation of 0.80 with an R2 of 0.63 between predicted and actual Tm values. Our best model, fine-tuned on large language models such as ProtBert, achieved a maximum correlation of 0.89 with an R2 of 0.80, demonstrating improved performance in predicting protein stability at higher temperatures."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Joint Modeling of Cellular Heterogeneity and Condition Effects with scPCA in Single-Cell RNA-Seq","url":"http://biorxiv.org/cgi/content/short/2024.09.22.614322v1?rss=1","abstract":"Single-cell RNA sequencing (scRNA-seq) in multi-condition experiments enables the systematic assessment of treatment effects. Analyzing scRNA-seq data relies on linear dimensionality reduction (DR) methods like principal component analysis (PCA). These methods decompose high-dimensional gene expression profiles into tractable factor representations and prototypical gene expression patterns (components), facilitating the study of cell type variation. However, integrating study covariates within linear DR frameworks remains a challenging task. We present scPCA, a flexible DR framework that jointly models cellular heterogeneity and conditioning variables, allowing it to recover an integrated factor representation and reveal transcriptional changes across conditions and components of the decomposition. We show that scPCA extracts an interpretable latent representation by analyzing unstimulated and IFN-beta-treated PBMCs, and showcase that the model may be employed to effectively address batch effects. We examine age-related changes in rodent lung cell populations, uncovering a previously unreported surge in Ccl5 expression in T cells. We illustrate how scPCA may be employed to identify coordinated transcriptional changes across multiple time-points in depolarized visual cortex neurons. Finally, we show that scPCA elucidates transcriptional shifts in CRISPR-Cas9 chordin knockout zebrafish fish single-cell data despite large difference cell abundance across conditions. Since scPCA introduces a general approach to account for conditioning variables in high-dimensional data, it may also be applicable to datasets other than scRNA-seq.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Joint Modeling of Cellular Heterogeneity and Condition Effects with scPCA in Single-Cell RNA-Seq Abstract: Single-cell RNA sequencing (scRNA-seq) in multi-condition experiments enables the systematic assessment of treatment effects. Analyzing scRNA-seq data relies on linear dimensionality reduction (DR) methods like principal component analysis (PCA). These methods decompose high-dimensional gene expression profiles into tractable factor representations and prototypical gene expression patterns (components), facilitating the study of cell type variation. However, integrating study covariates within linear DR frameworks remains a challenging task. We present scPCA, a flexible DR framework that jointly models cellular heterogeneity and conditioning variables, allowing it to recover an integrated factor representation and reveal transcriptional changes across conditions and components of the decomposition. We show that scPCA extracts an interpretable latent representation by analyzing unstimulated and IFN-beta-treated PBMCs, and showcase that the model may be employed to effectively address batch effects. We examine age-related changes in rodent lung cell populations, uncovering a previously unreported surge in Ccl5 expression in T cells. We illustrate how scPCA may be employed to identify coordinated transcriptional changes across multiple time-points in depolarized visual cortex neurons. Finally, we show that scPCA elucidates transcriptional shifts in CRISPR-Cas9 chordin knockout zebrafish fish single-cell data despite large difference cell abundance across conditions. Since scPCA introduces a general approach to account for conditioning variables in high-dimensional data, it may also be applicable to datasets other than scRNA-seq.","summary":"scRNA-seq in multi-condition experiments enables the systematic assessment of treatment effects by analyzing gene expression profiles.   scPCA is a flexible DR framework that jointly models cellular heterogeneity and conditioning variables, allowing for an integrated factor representation and revealing transcriptional changes across conditions and components."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Identification of potential inhibitors against Inosine 5'-Monophosphate Dehydrogenase of Cryptosporidium parvum through an integrated in silico approach","url":"http://biorxiv.org/cgi/content/short/2024.09.22.614371v1?rss=1","abstract":"The protozoan parasite Cryptosporidium, found in many vertebrate species, including humans, is the source of the global infection known as cryptosporidiosis, which manifests as acute gastroenteritis, abdominal pain, and diarrhea. Although infections in certain individuals have been linked to other species, Cryptosporidium parvum is the main cause of illnesses in humans. Lactate Dehydrogenase, Inosine 5'-Monophosphate Dehydrogenase (IMPDH), and several other targets have been identified by the genome sequencing of C. parvum. Bioactive phytochemicals derived from nature have enormous potential as anti-cryptosporidiosis agents. The study aimed to identify new anti-cryptosporidial agents that work against the IMPDH of the parasite by using integrated in silico approaches. In this study, a total of 24 bioactive phytochemicals were screened virtually through molecular docking and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analyses. Four lead compounds were identified, including Brevelin A (-8.9 kcal/mol), Vernodalin (-8.7 kcal/mol), Luteolin (-8.6 kcal/mol), and Pectolinarigenin (-8.1 kcal/mol), against the IMPDH protein (PDB ID: 4IXH) from the parasite. All the lead compounds were found to possess favorable pharmacokinetic and pharmacodynamic properties. The toxicity analysis showed satisfactory results with no major side effects. All of the selected compounds showed no violation of Lipinski's rules of five, indicating the possibility of oral bioavailability as potential drug candidates. Target class prediction unveiled enzymes in most of the cases, and some experimental and investigational drugs were found to be structurally similar to the lead compounds. With significant biochemical interactions, all of the targeted phytochemical compounds have demonstrated excellent pharmacokinetics and good bioavailabilities. The findings strongly recommend in vitro experimental studies to aid in the development of novel therapeutics against Cryptosporidium parvum.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Identification of potential inhibitors against Inosine 5'-Monophosphate Dehydrogenase of Cryptosporidium parvum through an integrated in silico approach Abstract: The protozoan parasite Cryptosporidium, found in many vertebrate species, including humans, is the source of the global infection known as cryptosporidiosis, which manifests as acute gastroenteritis, abdominal pain, and diarrhea. Although infections in certain individuals have been linked to other species, Cryptosporidium parvum is the main cause of illnesses in humans. Lactate Dehydrogenase, Inosine 5'-Monophosphate Dehydrogenase (IMPDH), and several other targets have been identified by the genome sequencing of C. parvum. Bioactive phytochemicals derived from nature have enormous potential as anti-cryptosporidiosis agents. The study aimed to identify new anti-cryptosporidial agents that work against the IMPDH of the parasite by using integrated in silico approaches. In this study, a total of 24 bioactive phytochemicals were screened virtually through molecular docking and ADMET (Absorption, Distribution, Metabolism, Excretion, and Toxicity) analyses. Four lead compounds were identified, including Brevelin A (-8.9 kcal/mol), Vernodalin (-8.7 kcal/mol), Luteolin (-8.6 kcal/mol), and Pectolinarigenin (-8.1 kcal/mol), against the IMPDH protein (PDB ID: 4IXH) from the parasite. All the lead compounds were found to possess favorable pharmacokinetic and pharmacodynamic properties. The toxicity analysis showed satisfactory results with no major side effects. All of the selected compounds showed no violation of Lipinski's rules of five, indicating the possibility of oral bioavailability as potential drug candidates. Target class prediction unveiled enzymes in most of the cases, and some experimental and investigational drugs were found to be structurally similar to the lead compounds. With significant biochemical interactions, all of the targeted phytochemical compounds have demonstrated excellent pharmacokinetics and good bioavailabilities. The findings strongly recommend in vitro experimental studies to aid in the development of novel therapeutics against Cryptosporidium parvum.","summary":"A total of 24 bioactive phytochemicals were screened virtually using molecular docking and ADMET analyses to identify potential inhibitors against Inosine 5'-Monophosphate Dehydrogenase (IMPDH) of Cryptosporidium parvum, with four lead compounds identified as Brevelin A, Vernodalin, Luteolin, and Pectolinarigenin. The lead compounds were found to possess favorable pharmacokinetic and pharmacodynamic properties, satisfactory toxicity analysis results, and no major side effects or violation of Lipinski's rules of five, indicating the possibility of oral bioavailability as potential drug candidates."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Identification and Diagnostic Potential of Pyroptosis-Related Genes in Endometriosis: A Novel Bioinformatics Analysis","url":"http://biorxiv.org/cgi/content/short/2024.09.23.614461v1?rss=1","abstract":"Objective: This study aimed to identify and analyze potential signatures of pyroptosis-related genes in EMs. Methods: Transcriptomic datasets related to endometriosis were retrieved from the GEO databases (GSE7305, GSE7307, and GSE11691). Differential gene expression analysis was performed to identify pyroptosis-related differentially expressed genes (PRDEGs) by intersecting DEGs with a curated list of PRGs. Various bioinformatics tools were employed to explore the biological functions and pathways associated with PRDEGs. Results: We identified 26 PRDEGs from combined datasets and constructed an EMs diagnostic model using LASSO regression based on pyroptosis scores. The model included 5 DEGs: KIF13B, BAG6, MYO5A, HEATR, and AK055981. Additionally, 21 Key Module Genes (KMGs) were identified, leading to the classification of 3 distinct EMs subtypes. These subtypes were analyzed for immune cell infiltration, revealing a complex immune landscape in EMs. Conclusions: This study reveals pyroptosis' crucial role in EMs and offers a novel diagnostic model based on pyroptosis-related genes. Modulating pyroptosis may provide a new therapeutic approach for managing EMs.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Identification and Diagnostic Potential of Pyroptosis-Related Genes in Endometriosis: A Novel Bioinformatics Analysis Abstract: Objective: This study aimed to identify and analyze potential signatures of pyroptosis-related genes in EMs. Methods: Transcriptomic datasets related to endometriosis were retrieved from the GEO databases (GSE7305, GSE7307, and GSE11691). Differential gene expression analysis was performed to identify pyroptosis-related differentially expressed genes (PRDEGs) by intersecting DEGs with a curated list of PRGs. Various bioinformatics tools were employed to explore the biological functions and pathways associated with PRDEGs. Results: We identified 26 PRDEGs from combined datasets and constructed an EMs diagnostic model using LASSO regression based on pyroptosis scores. The model included 5 DEGs: KIF13B, BAG6, MYO5A, HEATR, and AK055981. Additionally, 21 Key Module Genes (KMGs) were identified, leading to the classification of 3 distinct EMs subtypes. These subtypes were analyzed for immune cell infiltration, revealing a complex immune landscape in EMs. Conclusions: This study reveals pyroptosis' crucial role in EMs and offers a novel diagnostic model based on pyroptosis-related genes. Modulating pyroptosis may provide a new therapeutic approach for managing EMs.","summary":"Pyroptosis-related genes were identified through a bioinformatics analysis of endometriosis (EM) transcriptomic datasets, resulting in 26 differentially expressed genes that play a crucial role in the pathogenesis of EM.  A novel diagnostic model was constructed using LASSO regression based on pyroptosis scores, which included five key genes: KIF13B, BAG6, MYO5A, HEATR, and AK055981."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Improving the accuracy of pose prediction by incorporating symmetry-related molecules","url":"http://biorxiv.org/cgi/content/short/2024.09.21.614298v1?rss=1","abstract":"Accurate prediction of biologically relevant binding poses is crucial for the success of computer-aided drug development. In this study, we describe a general strategy to enhance the precision of pose prediction in molecular docking by incorporating symmetry-related molecules (SRMs). Our objective was to demonstrate the significant impact of SRMs on the accuracy of pose prediction. To achieve this, we evaluated our method on high-quality protein-ligand complex structures, focusing on the presence and absence of SRMs during molecular docking studies. We have extracted the co-crystal ligands from the selected crystal structure and were redocked in presence and absence of SRM to assess their influence. Additionally, we calculated the free energy of the docked poses using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method, comparing the results in the presence and absence of SRMs. The findings revealed that redocking performed in the presence of SRMs significantly improved the prediction of biologically significant/crystallographically relevant poses. Consequently, our proposed strategy offers a robust method for enhancing pose prediction in current molecular docking programs, potentially leading to more effective and reliable drug development processes.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Improving the accuracy of pose prediction by incorporating symmetry-related molecules Abstract: Accurate prediction of biologically relevant binding poses is crucial for the success of computer-aided drug development. In this study, we describe a general strategy to enhance the precision of pose prediction in molecular docking by incorporating symmetry-related molecules (SRMs). Our objective was to demonstrate the significant impact of SRMs on the accuracy of pose prediction. To achieve this, we evaluated our method on high-quality protein-ligand complex structures, focusing on the presence and absence of SRMs during molecular docking studies. We have extracted the co-crystal ligands from the selected crystal structure and were redocked in presence and absence of SRM to assess their influence. Additionally, we calculated the free energy of the docked poses using the Molecular Mechanics Generalized Born Surface Area (MM-GBSA) method, comparing the results in the presence and absence of SRMs. The findings revealed that redocking performed in the presence of SRMs significantly improved the prediction of biologically significant/crystallographically relevant poses. Consequently, our proposed strategy offers a robust method for enhancing pose prediction in current molecular docking programs, potentially leading to more effective and reliable drug development processes.","summary":"The study aimed to improve the accuracy of pose prediction in molecular docking by incorporating symmetry-related molecules (SRMs). Redocking protein-ligand complexes with and without SRMs revealed that using SRMs significantly improved the prediction of biologically significant poses, as indicated by MM-GBSA calculations."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Identification and study of Prolyl Oligopeptidases and related sequences in bacterial lineages","url":"http://biorxiv.org/cgi/content/short/2024.09.22.614393v1?rss=1","abstract":"Proteases are enzymes that break down proteins, and serine proteases are an important subset of these enzymes. Prolyl oligopeptidase (POP) is a family of serine proteases (S9 family) that has the ability to cleave peptide bonds involving proline residues and it is unique for its ability to cleave various small oligopeptides shorter than 30 amino acids. The S9 family from the MEROPS database, is classified into four subfamilies based on active site motifs. These S9 subfamilies assume a crucial position owing to their diverse biological roles and potential therapeutic applications in various diseases. In this study, we have examined ~32000 completely annotated bacterial genomes from the NCBI RefSeq Assembly database to identify annotated S9 family proteins. This results in the discovery of ~53,000 bacterial S9 family proteins (referred to as POP homologues). These sequences are classified into distinct subfamilies through various machine-learning approaches and comprehensive analysis of their distribution across various phyla and species and domain architecture analysis are also conducted. Distinct subclusters and class-specific motifs of POPs were identified, suggesting differences in substrate specificity in POP homologues. This study can enable future research of these gene families that are involved in many important biological processes.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Identification and study of Prolyl Oligopeptidases and related sequences in bacterial lineages Abstract: Proteases are enzymes that break down proteins, and serine proteases are an important subset of these enzymes. Prolyl oligopeptidase (POP) is a family of serine proteases (S9 family) that has the ability to cleave peptide bonds involving proline residues and it is unique for its ability to cleave various small oligopeptides shorter than 30 amino acids. The S9 family from the MEROPS database, is classified into four subfamilies based on active site motifs. These S9 subfamilies assume a crucial position owing to their diverse biological roles and potential therapeutic applications in various diseases. In this study, we have examined ~32000 completely annotated bacterial genomes from the NCBI RefSeq Assembly database to identify annotated S9 family proteins. This results in the discovery of ~53,000 bacterial S9 family proteins (referred to as POP homologues). These sequences are classified into distinct subfamilies through various machine-learning approaches and comprehensive analysis of their distribution across various phyla and species and domain architecture analysis are also conducted. Distinct subclusters and class-specific motifs of POPs were identified, suggesting differences in substrate specificity in POP homologues. This study can enable future research of these gene families that are involved in many important biological processes.","summary":"The study examined ~32000 completely annotated bacterial genomes from the NCBI RefSeq Assembly database to identify annotated S9 family proteins, resulting in the discovery of ~53,000 bacterial S9 family proteins (referred to as POP homologues) which can be classified into distinct subfamilies through various machine-learning approaches and comprehensive analysis. These sequence homologues display distinct subclusters and class-specific motifs suggesting differences in substrate specificity in POP homologues."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Learning-Augmented Sketching Offers Improved Performance for Privacy Preserving and Secure GWAS","url":"http://biorxiv.org/cgi/content/short/2024.09.19.613975v1?rss=1","abstract":"The introduction of trusted execution environments (TEEs), such as secure enclaves provided by the Intel SGX technology has enabled secure and privacy-preserving computation on the cloud. The stringent resource limitations, such as memory constraints, required by some TEEs necessitates the development of computational approaches with reduced memory usage, such as sketching. One example is the SkSES method for GWAS on a cohort of case and control samples from multiple institutions, which identifies the most significant SNPs in a privacy-preserving manner without disclosing sensitive genotype information to other institutions or the cloud service provider. Here we show how to improve the performance of SkSES on large datasets by augmenting it with a learning-augmented approach. Specifically, we show how individual institutions can perform smaller scale GWAS on their own datasets and identify two sets of variants according to certain criteria, which are then used to guide the sketching process to more accurately identify significant variants over the collective dataset. The new method achieves up to 40% accuracy gain compared to the original SkSES method under the same memory constraints on datasets we tested on. The code is available at https://github.com/alreadydone/sgx-genome-variants-search.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Learning-Augmented Sketching Offers Improved Performance for Privacy Preserving and Secure GWAS Abstract: The introduction of trusted execution environments (TEEs), such as secure enclaves provided by the Intel SGX technology has enabled secure and privacy-preserving computation on the cloud. The stringent resource limitations, such as memory constraints, required by some TEEs necessitates the development of computational approaches with reduced memory usage, such as sketching. One example is the SkSES method for GWAS on a cohort of case and control samples from multiple institutions, which identifies the most significant SNPs in a privacy-preserving manner without disclosing sensitive genotype information to other institutions or the cloud service provider. Here we show how to improve the performance of SkSES on large datasets by augmenting it with a learning-augmented approach. Specifically, we show how individual institutions can perform smaller scale GWAS on their own datasets and identify two sets of variants according to certain criteria, which are then used to guide the sketching process to more accurately identify significant variants over the collective dataset. The new method achieves up to 40% accuracy gain compared to the original SkSES method under the same memory constraints on datasets we tested on. The code is available at https://github.com/alreadydone/sgx-genome-variants-search.","summary":"The introduction of trusted execution environments (TEEs) such as Intel SGX technology has enabled secure and privacy-preserving computation on the cloud, but stringent resource limitations pose a challenge for some TEEs. The SkSES method, which identifies significant SNPs in GWAS without disclosing sensitive genotype information, has been improved upon with a learning-augmented approach that achieves up to 40% accuracy gain compared to the original SkSES method."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Liberality is More Explainable than PCA of Transcriptome for Vertebrate Embryo Development","url":"http://biorxiv.org/cgi/content/short/2024.09.19.613970v1?rss=1","abstract":"Dimensional reduction approaches of genome scale data are widely used. Liberality is one of the approaches which is a quantitative index of cellular differentiation and dedifferentiation. Here, we analyzed a trend of liberality of time course transcriptome data on vertebrate embryo development. Historically annotated embryo developmental stages matched changes in the trend of liberality. Analyzing liberality of various biological phenomena would be beneficial.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Liberality is More Explainable than PCA of Transcriptome for Vertebrate Embryo Development Abstract: Dimensional reduction approaches of genome scale data are widely used. Liberality is one of the approaches which is a quantitative index of cellular differentiation and dedifferentiation. Here, we analyzed a trend of liberality of time course transcriptome data on vertebrate embryo development. Historically annotated embryo developmental stages matched changes in the trend of liberality. Analyzing liberality of various biological phenomena would be beneficial.","summary":"Liberality is a quantitative index of cellular differentiation and dedifferentiation that has been widely used for genome-scale data analysis, particularly in understanding vertebrate embryo development. The study analyzed a time course transcriptome dataset on vertebrate embryo development and found a trend that historically annotated embryo developmental stages matched changes in liberality, indicating the potential of liberality to analyze biological phenomena beyond just embryo development."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Bacopa monnieri phytochemicals as promising BACE1 inhibitors for Alzheimers Disease Therapy","url":"http://biorxiv.org/cgi/content/short/2024.09.19.613992v1?rss=1","abstract":"Alzheimers disease (AD) remains a formidable challenge, necessitating the discovery of effective therapeutic agents targeting {beta}-site amyloid precursor protein cleaving enzyme 1 (BACE1). This study investigates the inhibitory potential of phytochemicals derived from Bacopa monnieri, a plant renowned for its cognitive-enhancing properties, in comparison to established synthetic inhibitors such as Atabecestat, Lanabecestat, and Verubecestat. Utilizing molecular docking and advanced computational simulations, we demonstrate that Bacopaside I exhibits superior binding affinity and a unique interaction profile with BACE1, suggesting a more nuanced inhibitory mechanism. Our findings highlight the promising role of Bacopa monnieri phytochemicals as viable alternatives to synthetic drugs, emphasizing their potential to overcome limitations faced in clinical settings. Furthermore, the development of the SIMANA (https://simana.streamlit.app/) platform enhances the visualization and analysis of protein-ligand interactions, facilitating a deeper understanding of the dynamics involved. This research not only underscores the therapeutic promise of natural compounds in AD treatment but also advocates for a paradigm shift towards integrating traditional medicinal knowledge into contemporary drug discovery efforts.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Bacopa monnieri phytochemicals as promising BACE1 inhibitors for Alzheimers Disease Therapy Abstract: Alzheimers disease (AD) remains a formidable challenge, necessitating the discovery of effective therapeutic agents targeting {beta}-site amyloid precursor protein cleaving enzyme 1 (BACE1). This study investigates the inhibitory potential of phytochemicals derived from Bacopa monnieri, a plant renowned for its cognitive-enhancing properties, in comparison to established synthetic inhibitors such as Atabecestat, Lanabecestat, and Verubecestat. Utilizing molecular docking and advanced computational simulations, we demonstrate that Bacopaside I exhibits superior binding affinity and a unique interaction profile with BACE1, suggesting a more nuanced inhibitory mechanism. Our findings highlight the promising role of Bacopa monnieri phytochemicals as viable alternatives to synthetic drugs, emphasizing their potential to overcome limitations faced in clinical settings. Furthermore, the development of the SIMANA (https://simana.streamlit.app/) platform enhances the visualization and analysis of protein-ligand interactions, facilitating a deeper understanding of the dynamics involved. This research not only underscores the therapeutic promise of natural compounds in AD treatment but also advocates for a paradigm shift towards integrating traditional medicinal knowledge into contemporary drug discovery efforts.","summary":"Bacopa monnieri phytochemicals are investigated as potential BACE1 inhibitors for Alzheimer's Disease Therapy, with Bacopaside I showing superior binding affinity and interaction profile compared to established synthetic inhibitors. The study highlights the promising role of natural compounds in AD treatment, emphasizing their potential to overcome limitations faced in clinical settings, and advocates for a paradigm shift towards integrating traditional medicinal knowledge into contemporary drug discovery efforts."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Accurate Multiple Sequence Alignment of Ultramassive Genome Sets","url":"http://biorxiv.org/cgi/content/short/2024.09.22.613454v1?rss=1","abstract":"With ever increasing sequencing efficiency, there is a pressing need to tackle a presently intractable task of accurate multiple sequence alignment (MSA) for ultramassive genome sets of millions and beyond. Additionally, efficient graph and probabilistic representations for downstream analysis are in dire lack. In light of these challenges, we develop a set of linearly scalable algorithms, including that for constructing directed acyclic graphs, for training profile hidden Markov models and for conducting alignment on such graphs. The astounding power of these algorithms is demonstrated by both significantly improved accuracy and tremendous acceleration of SAR-CoV-2 MSA by three observed to five projected orders of magnitude for genome set sizes ranging from 40,000 to more than 4 million when compared with widely utilized MAFFT. Future application to other viral species and extension to more complex genomes will prove this algorithm set as a cornerstone for the coming era of ultramassive genome sets.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Accurate Multiple Sequence Alignment of Ultramassive Genome Sets Abstract: With ever increasing sequencing efficiency, there is a pressing need to tackle a presently intractable task of accurate multiple sequence alignment (MSA) for ultramassive genome sets of millions and beyond. Additionally, efficient graph and probabilistic representations for downstream analysis are in dire lack. In light of these challenges, we develop a set of linearly scalable algorithms, including that for constructing directed acyclic graphs, for training profile hidden Markov models and for conducting alignment on such graphs. The astounding power of these algorithms is demonstrated by both significantly improved accuracy and tremendous acceleration of SAR-CoV-2 MSA by three observed to five projected orders of magnitude for genome set sizes ranging from 40,000 to more than 4 million when compared with widely utilized MAFFT. Future application to other viral species and extension to more complex genomes will prove this algorithm set as a cornerstone for the coming era of ultramassive genome sets.","summary":"The current state of multiple sequence alignment (MSA) is insufficient for handling ultramassive genome sets due to challenges in scalability and accuracy. The proposed algorithms, including directed acyclic graph construction, profile hidden Markov model training, and graph-based alignment, significantly improve accuracy and acceleration of MSA compared to widely used MAFFT for genome set sizes ranging from 40,000 to over 4 million."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Machine Learning Driven Simulations of SARS-CoV-2 Fitness Landscape","url":"http://biorxiv.org/cgi/content/short/2024.09.20.614179v1?rss=1","abstract":"SARS-CoV-2 infection is mediated by interactions between the receptor binding domain (RBD) of viral spike proteins and host cell angiotensin converting enzyme 2 (ACE2) receptors. Mutations in the spike protein are the primary cause for neutralizing antibody escape leading to breakthrough infections. We characterize the fitness landscape underpinning future variants of concern by combining supervised machine learning and Markov Chain Monte Carlo. Leveraging deep mutational scanning (DMS) data characterizing the binding affinity between RBD mutants to the ACE2 receptor, we predict variants of concern not seen in the training data and sample statistics of the fitness landscape. These simulations provide insight into the relationship between RBD sequence elements and offer a new perspective on utilizing DMS to predict emerging viral strains.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Machine Learning Driven Simulations of SARS-CoV-2 Fitness Landscape Abstract: SARS-CoV-2 infection is mediated by interactions between the receptor binding domain (RBD) of viral spike proteins and host cell angiotensin converting enzyme 2 (ACE2) receptors. Mutations in the spike protein are the primary cause for neutralizing antibody escape leading to breakthrough infections. We characterize the fitness landscape underpinning future variants of concern by combining supervised machine learning and Markov Chain Monte Carlo. Leveraging deep mutational scanning (DMS) data characterizing the binding affinity between RBD mutants to the ACE2 receptor, we predict variants of concern not seen in the training data and sample statistics of the fitness landscape. These simulations provide insight into the relationship between RBD sequence elements and offer a new perspective on utilizing DMS to predict emerging viral strains.","summary":"The SARS-CoV-2 infection is caused by interactions between the receptor binding domain of viral spike proteins and host cell ACE2 receptors, with mutations in the spike protein leading to neutralizing antibody escape and breakthrough infections. Machine learning-driven simulations combined with deep mutational scanning data predict variants of concern not seen in the training data and sample statistics of the fitness landscape, providing insight into the relationship between RBD sequence elements and emerging viral strains."}
{"source":"bioRxiv","subject":"bioinformatics","title":"Modelling dynamics of human NDPK hexamer structure, stability and interactions","url":"http://biorxiv.org/cgi/content/short/2024.09.19.613900v1?rss=1","abstract":"Nucleoside diphosphate kinases (NDPKs) are evolutionarily conserved multifunctional enzymes involved in energy metabolism and gene regulation. NDPKs primarily regulate nucleotide pool turnover by catalyzing the transfer between nucleoside triphosphate (NTPs) and their deoxy derivatives, maintaining cellular homeostasis. The NDPK hexameric assembly is needed for kinase activity, but its precise assembly into homo- /hetero-oligomeric complexes remains poorly understood. How quaternary structure affects NDPK activity is limited by high subunit homology, experimental challenges in isolating in vivo heterohexamers and subunit abundances across cellular compartments. We identify conserved Arg27 across group I NDPKs (NME1-4) as the key residue for hexamer assembly. The Arg27 ensures similar hexameric assembly across subunits and mediates inter- and intra-molecular monomeric interactions, while Arg27 mutation leads to decreased binding affinity, dynamics, and complex destabilization. The double and triple Arg NME4 mutations destabilize hexamer into dimer due to shorter C-terminal region. Simulating NME1-3 with Arg mutations and shortened C-terminal recapitulates hexameric destabilization, highlighting role of the C-terminal region in stabilizing NDPK hexamers. Comparing heterohexameric complexes, we report NME1-NME2 (A1B5) complex as most stable and abundant, owing to predominant subunit nuclear localization. We propose that Arginine residues, C-terminal sequence and subunit abundances contribute to formation and stabilization of NDPK heterohexameric complexes.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Modelling dynamics of human NDPK hexamer structure, stability and interactions Abstract: Nucleoside diphosphate kinases (NDPKs) are evolutionarily conserved multifunctional enzymes involved in energy metabolism and gene regulation. NDPKs primarily regulate nucleotide pool turnover by catalyzing the transfer between nucleoside triphosphate (NTPs) and their deoxy derivatives, maintaining cellular homeostasis. The NDPK hexameric assembly is needed for kinase activity, but its precise assembly into homo- /hetero-oligomeric complexes remains poorly understood. How quaternary structure affects NDPK activity is limited by high subunit homology, experimental challenges in isolating in vivo heterohexamers and subunit abundances across cellular compartments. We identify conserved Arg27 across group I NDPKs (NME1-4) as the key residue for hexamer assembly. The Arg27 ensures similar hexameric assembly across subunits and mediates inter- and intra-molecular monomeric interactions, while Arg27 mutation leads to decreased binding affinity, dynamics, and complex destabilization. The double and triple Arg NME4 mutations destabilize hexamer into dimer due to shorter C-terminal region. Simulating NME1-3 with Arg mutations and shortened C-terminal recapitulates hexameric destabilization, highlighting role of the C-terminal region in stabilizing NDPK hexamers. Comparing heterohexameric complexes, we report NME1-NME2 (A1B5) complex as most stable and abundant, owing to predominant subunit nuclear localization. We propose that Arginine residues, C-terminal sequence and subunit abundances contribute to formation and stabilization of NDPK heterohexameric complexes.","summary":"The precise assembly of the NDPK hexameric structure into homo- /hetero-oligomeric complexes is necessary for kinase activity but has been poorly understood due to high subunit homology, experimental challenges, and limited data on in vivo heterohexamer formation and subunit abundances across cellular compartments. A conserved Arg27 residue plays a key role in hexamer assembly, mediating inter- and intra-molecular monomeric interactions and ensuring similar hexameric assembly across subunits."}
{"source":"bioRxiv","subject":"bioinformatics","title":"GuaCAMOLE: GC-bias aware estimation improves the accuracy of metagenomic species abundances","url":"http://biorxiv.org/cgi/content/short/2024.09.20.614100v1?rss=1","abstract":"GuaCAMOLE is a novel computational method which detects and removes GC bias from metagenomic sequencing data. Metagenomic sequencing measures the species composition of microbial communities, and has revealed the crucial role of microbiomes in the etiology of a range of diseases such as colorectal cancer. Quantitative comparisons of microbial communities are, however, affected by GC-content dependent biases. GuaCAMOLE works regardless of the specific amount or direction of GC-bias present in the data and requires only a single sample. The algorithm reports unbiased abundances and quantifies the amount of bias present in terms of GC-depdendent sequencing efficiencies. Experimental mock community data confirms both estimates to be accurate across a wide range of experimental protocols. In gut microbiomes of colorectal cancer patients we observe a clear bias against GC-poor species in the abundances reported by existing methods. GuaCAMOLE successfully removes this bias and corrects the abundance of clinically relevant GC-poor species such as F. nucleatum (28% GC) by up to a factor of two. GuaCAMOLE thus contributes to a better quantitative understanding of microbial communities by improving the accuracy and comparability of species abundances across experimental setups.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: GuaCAMOLE: GC-bias aware estimation improves the accuracy of metagenomic species abundances Abstract: GuaCAMOLE is a novel computational method which detects and removes GC bias from metagenomic sequencing data. Metagenomic sequencing measures the species composition of microbial communities, and has revealed the crucial role of microbiomes in the etiology of a range of diseases such as colorectal cancer. Quantitative comparisons of microbial communities are, however, affected by GC-content dependent biases. GuaCAMOLE works regardless of the specific amount or direction of GC-bias present in the data and requires only a single sample. The algorithm reports unbiased abundances and quantifies the amount of bias present in terms of GC-depdendent sequencing efficiencies. Experimental mock community data confirms both estimates to be accurate across a wide range of experimental protocols. In gut microbiomes of colorectal cancer patients we observe a clear bias against GC-poor species in the abundances reported by existing methods. GuaCAMOLE successfully removes this bias and corrects the abundance of clinically relevant GC-poor species such as F. nucleatum (28% GC) by up to a factor of two. GuaCAMOLE thus contributes to a better quantitative understanding of microbial communities by improving the accuracy and comparability of species abundances across experimental setups.","summary":"GuaCAMOLE is a novel computational method that detects and removes GC bias from metagenomic sequencing data, which affects the accuracy of quantifying microbial community compositions. The algorithm reports unbiased abundances and corrects the abundance of clinically relevant GC-poor species by up to a factor of two in gut microbiomes of colorectal cancer patients."}
{"source":"medRxiv","subject":"infectious_diseases","title":"PPAR-γ signaling and risk of bacterial enteric infection: insight from thiazolidinedione users in a US population-based study","url":"http://medrxiv.org/cgi/content/short/2024.09.24.24313682v1?rss=1","abstract":"The ongoing antimicrobial resistant crisis heralds the need for new therapeutics against enteric infection. In mouse models, colon epithelial peroxisome proliferator-activated receptor-{gamma} (PPAR-{gamma}) signaling limits oxygen and nitrate luminal bioavailability, thereby preventing bacterial pathogen colonization. However, whether this mechanism operates similarly in humans remains uncertain. To investigate, we used the cloud-based TriNetX Analytics Platform which aggregates health records from 117 million patients across 66 US healthcare organizations, to assess the risk of bacterial enteric infection among diabetic patients prescribed thiazolidinediones, a class of PPAR-{gamma} agonists. Among 85,117 thiazolidinedione users, we observed a 22-49% lower risk of bacterial enteric infections compared to users of other anti-diabetes medications. This reduction in risk was consistent across high-risk individuals, regardless of sex or age. Similar results were replicated in high-risk patients when thiazolidinedione users were directly compared to those on DPP-4 inhibitors. These findings support the potential protective role of PPAR-{gamma} signaling against bacterial enteric infection and call for further clinical investigation.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: PPAR-γ signaling and risk of bacterial enteric infection: insight from thiazolidinedione users in a US population-based study Abstract: The ongoing antimicrobial resistant crisis heralds the need for new therapeutics against enteric infection. In mouse models, colon epithelial peroxisome proliferator-activated receptor-{gamma} (PPAR-{gamma}) signaling limits oxygen and nitrate luminal bioavailability, thereby preventing bacterial pathogen colonization. However, whether this mechanism operates similarly in humans remains uncertain. To investigate, we used the cloud-based TriNetX Analytics Platform which aggregates health records from 117 million patients across 66 US healthcare organizations, to assess the risk of bacterial enteric infection among diabetic patients prescribed thiazolidinediones, a class of PPAR-{gamma} agonists. Among 85,117 thiazolidinedione users, we observed a 22-49% lower risk of bacterial enteric infections compared to users of other anti-diabetes medications. This reduction in risk was consistent across high-risk individuals, regardless of sex or age. Similar results were replicated in high-risk patients when thiazolidinedione users were directly compared to those on DPP-4 inhibitors. These findings support the potential protective role of PPAR-{gamma} signaling against bacterial enteric infection and call for further clinical investigation.","summary":"Among 85,117 diabetic patients prescribed thiazolidinediones, a class of PPAR-γ agonists, there was observed a 22-49% lower risk of bacterial enteric infections compared to users of other anti-diabetes medications. This reduction in risk was consistent across high-risk individuals, regardless of sex or age, and similar results were replicated when thiazolidinedione users were directly compared to those on DPP-4 inhibitors."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Lipid Fingerprinting by MALDI Biotyper Sirius Instrument Fails to Differentiate the Three Subspecies of the Mycobacterium abscessus Complex","url":"http://medrxiv.org/cgi/content/short/2024.09.23.24314022v1?rss=1","abstract":"The number of patients suffering from Mycobacterium abscessus complex (MABC) pulmonary diseases is steadily increasing. MABC consists of three subspecies, and it is recommended that the three subspecies be distinguished because of their differing macrolide susceptibilities. Unfortunately, current methods are inefficient due to their high cost, complexity, and time requirements. The third-generation Bruker MALDI Biotyper (MBT) Sirius has the capability to detect phospholipids and glycolipids using negative-ion mode. Mycobacterial cell walls are rich in lipids, and if lipid structure diversity can serve as species-specific fingerprints, this method may provide an alternative for microbial identification. This study aimed to examine the accuracy of discriminating between the three MABC subspecies by lipid profiling. Our best model failed to differentiate the three subspecies. Even in the two-dimensional space of the most significant peaks, M. abscessus and M. massiliense could not be separated. The agreement rate between lipid fingerprint-based and WGS-based identification was, at most, 47.2% for negative-ion mode. Even after applying recent machine learning algorithms to detect variables and create predictive models, accuracy remained at 50%. Our results suggest that using lipid fingerprinting alone to differentiate the three MABC subspecies is currently inadequate. Further advancements and standardization of MALDI-TOF MS-based methods are necessary for the routine differentiation of MABC subspecies in clinical settings.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Lipid Fingerprinting by MALDI Biotyper Sirius Instrument Fails to Differentiate the Three Subspecies of the Mycobacterium abscessus Complex Abstract: The number of patients suffering from Mycobacterium abscessus complex (MABC) pulmonary diseases is steadily increasing. MABC consists of three subspecies, and it is recommended that the three subspecies be distinguished because of their differing macrolide susceptibilities. Unfortunately, current methods are inefficient due to their high cost, complexity, and time requirements. The third-generation Bruker MALDI Biotyper (MBT) Sirius has the capability to detect phospholipids and glycolipids using negative-ion mode. Mycobacterial cell walls are rich in lipids, and if lipid structure diversity can serve as species-specific fingerprints, this method may provide an alternative for microbial identification. This study aimed to examine the accuracy of discriminating between the three MABC subspecies by lipid profiling. Our best model failed to differentiate the three subspecies. Even in the two-dimensional space of the most significant peaks, M. abscessus and M. massiliense could not be separated. The agreement rate between lipid fingerprint-based and WGS-based identification was, at most, 47.2% for negative-ion mode. Even after applying recent machine learning algorithms to detect variables and create predictive models, accuracy remained at 50%. Our results suggest that using lipid fingerprinting alone to differentiate the three MABC subspecies is currently inadequate. Further advancements and standardization of MALDI-TOF MS-based methods are necessary for the routine differentiation of MABC subspecies in clinical settings.","summary":"The number of patients suffering from Mycobacterium abscessus complex (MABC) pulmonary diseases is steadily increasing, making it essential to distinguish between the three subspecies due to their differing macrolide susceptibilities. The use of lipid fingerprinting by MALDI Biotyper Sirius Instrument failed to differentiate the three MABC subspecies, as even with machine learning algorithms, accuracy remained at 50%."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Engineered antibodies targeted to bacterial surface integrate effector functions with toxin neutralization to provide superior efficacy against bacterial infections","url":"http://medrxiv.org/cgi/content/short/2024.09.23.24313920v1?rss=1","abstract":"Anti-bacterial monoclonal antibody (mAb) therapies either rely on toxin neutralization or opsonophagocytic killing (OPK). Toxin neutralization protects the host from toxin-induced damage, while leaving the organism intact. OPK inducing antibodies clear the bacteria but leave the released toxins unencountered. Infection site targeted anti-toxin antibodies (ISTAbs) that we report here addresses this binary paradigm by combining both functionalities into a single molecule. ISTAbs consist of cell wall targeting (CWT) domains of bacteriophage endolysins fused to toxin neutralizing mAbs (IgG). CWT governs specific binding to the surface of bacteria while the IgG variable domain neutralizes the toxins as they are released. The complex is then cleared by phagocytic cells. As proof of concept, we generated several ISTAb prototypes targeting major toxins from two Gram-positive spore forming pathogens that have a high clinical significance; Clostridium difficile, causative agent of the most common hospital-acquired infection, and Bacillus anthracis, a Category A select agent pathogen. Both groups of ISTAbs exhibited potent toxin neutralization, binding to their respective bacterial cells, and induction of opsonophagocytosis. In mice infected with B. anthracis, ISTAbs exhibit significantly higher efficacy than parental IgG in both pre- and post-challenge models. Furthermore, ISTAbs fully protected against B. anthracis infection in a nonhuman primate (NHP) aerosol challenge model. These findings establish that as a platform technology, ISTAbs are broadly applicable for therapeutic intervention against several toxigenic bacterial pathogens.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Engineered antibodies targeted to bacterial surface integrate effector functions with toxin neutralization to provide superior efficacy against bacterial infections Abstract: Anti-bacterial monoclonal antibody (mAb) therapies either rely on toxin neutralization or opsonophagocytic killing (OPK). Toxin neutralization protects the host from toxin-induced damage, while leaving the organism intact. OPK inducing antibodies clear the bacteria but leave the released toxins unencountered. Infection site targeted anti-toxin antibodies (ISTAbs) that we report here addresses this binary paradigm by combining both functionalities into a single molecule. ISTAbs consist of cell wall targeting (CWT) domains of bacteriophage endolysins fused to toxin neutralizing mAbs (IgG). CWT governs specific binding to the surface of bacteria while the IgG variable domain neutralizes the toxins as they are released. The complex is then cleared by phagocytic cells. As proof of concept, we generated several ISTAb prototypes targeting major toxins from two Gram-positive spore forming pathogens that have a high clinical significance; Clostridium difficile, causative agent of the most common hospital-acquired infection, and Bacillus anthracis, a Category A select agent pathogen. Both groups of ISTAbs exhibited potent toxin neutralization, binding to their respective bacterial cells, and induction of opsonophagocytosis. In mice infected with B. anthracis, ISTAbs exhibit significantly higher efficacy than parental IgG in both pre- and post-challenge models. Furthermore, ISTAbs fully protected against B. anthracis infection in a nonhuman primate (NHP) aerosol challenge model. These findings establish that as a platform technology, ISTAbs are broadly applicable for therapeutic intervention against several toxigenic bacterial pathogens.","summary":"Engineered antibodies targeted to bacterial surface integrate effector functions with toxin neutralization to provide superior efficacy against bacterial infections by combining both functionalities into a single molecule, consisting of cell wall targeting domains fused to toxin neutralizing mAbs. The complex was found to exhibit potent toxin neutralization, binding to their respective bacterial cells, and induction of opsonophagocytosis, significantly higher efficacy than parental IgG in mice infected with B. anthracis and full protection against B. anthracis infection in a nonhuman primate aerosol challenge model."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Implementing portable, real-time 16S rRNA sequencing in the healthcare sector enhances antimicrobial stewardship","url":"http://medrxiv.org/cgi/content/short/2024.09.23.24314079v1?rss=1","abstract":"Background Antimicrobial resistance (AMR) poses a significant global health challenge, resulting in over 1.27 million deaths in 2019 and projected to cause up to 10 million deaths annually in the future. To address this issue, the healthcare sector requires rapid and accurate bacterial identification, which is currently not readily available for effective antimicrobial stewardship. In a UK national first, we implemented 16S ribosomal RNA (rRNA) sequencing using Oxford Nanopore Technology (ONT) in an NHS setting to enhance diagnostic capabilities, aiming to reduce antibiotic misuse and improve patient outcomes. Methods We implemented 16S rRNA sequencing via ONT, running samples from seven NHS hospitals across Cheshire and Merseyside. We focused on samples from sterile sites, such as 'pus', 'fluid', and 'tissue', typically collected from critical care units. The assay was validated against traditional methods including Sanger sequencing and MALDI-TOF, with a turnaround time of 24-72 hours. Clinical impact was measured by analysing changes in antibiotic regimens and patient outcomes based on 16S assay results over a period of several months post-launch. Findings ONT 16S rRNA sequencing significantly impacted antibiotic treatment in 34.2% of cases, reducing patient stays and outperforming traditional methods by detecting additional bacterial organisms and identifying bacteria missed by reference labs. It provided species-level identification and confirmed non-infectious conditions in 5.4% of cases, aiding alternative treatment decisions. Its speed, cost-effectiveness, and minimal training requirements contributed to its successful integration into clinical practice. Interpretation The integration of ONT 16S sequencing into routine NHS diagnostics has significantly improved antimicrobial stewardship by offering a faster, more sensitive, and accurate bacterial identification method. Earlier use of this assay in cases where routine cultures are likely to fail could enhance patient outcomes further by enabling timely, targeted antibiotic therapies, reducing hospital stays, and curbing unnecessary antibiotic use.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Implementing portable, real-time 16S rRNA sequencing in the healthcare sector enhances antimicrobial stewardship Abstract: Background Antimicrobial resistance (AMR) poses a significant global health challenge, resulting in over 1.27 million deaths in 2019 and projected to cause up to 10 million deaths annually in the future. To address this issue, the healthcare sector requires rapid and accurate bacterial identification, which is currently not readily available for effective antimicrobial stewardship. In a UK national first, we implemented 16S ribosomal RNA (rRNA) sequencing using Oxford Nanopore Technology (ONT) in an NHS setting to enhance diagnostic capabilities, aiming to reduce antibiotic misuse and improve patient outcomes. Methods We implemented 16S rRNA sequencing via ONT, running samples from seven NHS hospitals across Cheshire and Merseyside. We focused on samples from sterile sites, such as 'pus', 'fluid', and 'tissue', typically collected from critical care units. The assay was validated against traditional methods including Sanger sequencing and MALDI-TOF, with a turnaround time of 24-72 hours. Clinical impact was measured by analysing changes in antibiotic regimens and patient outcomes based on 16S assay results over a period of several months post-launch. Findings ONT 16S rRNA sequencing significantly impacted antibiotic treatment in 34.2% of cases, reducing patient stays and outperforming traditional methods by detecting additional bacterial organisms and identifying bacteria missed by reference labs. It provided species-level identification and confirmed non-infectious conditions in 5.4% of cases, aiding alternative treatment decisions. Its speed, cost-effectiveness, and minimal training requirements contributed to its successful integration into clinical practice. Interpretation The integration of ONT 16S sequencing into routine NHS diagnostics has significantly improved antimicrobial stewardship by offering a faster, more sensitive, and accurate bacterial identification method. Earlier use of this assay in cases where routine cultures are likely to fail could enhance patient outcomes further by enabling timely, targeted antibiotic therapies, reducing hospital stays, and curbing unnecessary antibiotic use.","summary":"The implementation of portable, real-time 16S rRNA sequencing using Oxford Nanopore Technology (ONT) in the healthcare sector has enhanced antimicrobial stewardship in a UK national first. The assay was found to significantly impact antibiotic treatment in 34.2% of cases, reducing patient stays and outperforming traditional methods by detecting additional bacterial organisms and identifying bacteria missed by reference labs."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Novel antibiotic resistance genes from the hospital effluent are disseminated into the marine environment in Norway","url":"http://medrxiv.org/cgi/content/short/2024.09.23.24313887v1?rss=1","abstract":"Hospital effluent comprises feces of many individuals, including patients undergoing antibiotic treatment. Although, hospital effluent is an important source for contamination of the environment with antibiotic resistance genes (ARGs) and pathogens, how hospital effluent in a low resistance setting contributes to antimicrobial resistance (AMR) in the environment is largely understudied. The aim of our study was to understand the microbiota and resistome of hospital effluent, and its role in the spread of AMR in the marine environment in Norway. We further aimed at describing/characterizing novel resistance factors from hospital effluent and the receiving sewage treatment plant (STP). 24-hour composite samples of the hospital effluent and the influent and effluent of the receiving STP were collected at two sampling time-points (February and April 2023) in Bergen city, Norway. Isolation of Escherichia coli and Klebsiella spp. was performed, using ECC and SCAI plates with cefotaxime, tigecycline or meropenem, followed by antibiotic susceptibility testing, using EUVSEC3 plates. Whole-genome sequencing of selected strains (n=36) and shotgun metagenomics of sewage samples (n=6) were performed, using Illumina NovaSeq. ARGs were identified with USEARCH, and known and novel ARGs were assembled with fARGene. All E. coli strains (n=66) were multidrug-resistant (MDR), while 92.3% of the Klebsiella spp. strains (n=55) showed MDR phenotype. The sequenced strains carried multiple clinically important ARGs, including carbapenemases such as NDM-5 (n=3) and KPC-3 (n=3). We obtained 238 Gigabases of sequence data from which we identified 676 unique ARGs with >200 ARGs shared across samples. We assembled 1,205 ARGs using fARGene, 365 gene sequences represented novel ARGs (< 90% amino acid (aa) identity). Both known and novel ARGs (n=54) were shared between the hospital effluent and the treated effluent of the receiving STP. We show that hospital effluent in Norway has a high diversity of both known and novel ARGs. Our study demonstrates that hospital effluent is a source of clinically relevant pathogens, as well as known and novel ARGs, reaching the marine environment in Norway through treated sewage.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Novel antibiotic resistance genes from the hospital effluent are disseminated into the marine environment in Norway Abstract: Hospital effluent comprises feces of many individuals, including patients undergoing antibiotic treatment. Although, hospital effluent is an important source for contamination of the environment with antibiotic resistance genes (ARGs) and pathogens, how hospital effluent in a low resistance setting contributes to antimicrobial resistance (AMR) in the environment is largely understudied. The aim of our study was to understand the microbiota and resistome of hospital effluent, and its role in the spread of AMR in the marine environment in Norway. We further aimed at describing/characterizing novel resistance factors from hospital effluent and the receiving sewage treatment plant (STP). 24-hour composite samples of the hospital effluent and the influent and effluent of the receiving STP were collected at two sampling time-points (February and April 2023) in Bergen city, Norway. Isolation of Escherichia coli and Klebsiella spp. was performed, using ECC and SCAI plates with cefotaxime, tigecycline or meropenem, followed by antibiotic susceptibility testing, using EUVSEC3 plates. Whole-genome sequencing of selected strains (n=36) and shotgun metagenomics of sewage samples (n=6) were performed, using Illumina NovaSeq. ARGs were identified with USEARCH, and known and novel ARGs were assembled with fARGene. All E. coli strains (n=66) were multidrug-resistant (MDR), while 92.3% of the Klebsiella spp. strains (n=55) showed MDR phenotype. The sequenced strains carried multiple clinically important ARGs, including carbapenemases such as NDM-5 (n=3) and KPC-3 (n=3). We obtained 238 Gigabases of sequence data from which we identified 676 unique ARGs with >200 ARGs shared across samples. We assembled 1,205 ARGs using fARGene, 365 gene sequences represented novel ARGs (< 90% amino acid (aa) identity). Both known and novel ARGs (n=54) were shared between the hospital effluent and the treated effluent of the receiving STP. We show that hospital effluent in Norway has a high diversity of both known and novel ARGs. Our study demonstrates that hospital effluent is a source of clinically relevant pathogens, as well as known and novel ARGs, reaching the marine environment in Norway through treated sewage.","summary":"Hospital effluent from a low resistance setting in Norway was found to be a significant source of contamination with antibiotic resistance genes (ARGs) and pathogens in the marine environment. The study identified 676 unique ARGs, including both known and novel resistance factors, which were shared between hospital effluent and treated sewage, highlighting the potential for hospital waste to contribute to antimicrobial resistance in the environment."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Social determinants of injection drug use-associated bacterial infections and treatment outcomes: systematic review and meta-analysis","url":"http://medrxiv.org/cgi/content/short/2024.09.20.24313898v1?rss=1","abstract":"Background: Individual injecting practices (e.g., intramuscular injecting, lack of skin cleaning) are known risk factors for injection drug use-associated bacterial and fungal infections; however, social contexts shape individual behaviours and health outcomes. We sought to synthesize studies assessing potential social determinants of injecting-related infections and treatment outcomes. Methods: We searched five databases for studies published between 1 January 2000 and 18 February 18 2021 (PROSPERO CRD42021231411). We included studies of association (aetiology), assessing social determinants, substance use, and health services exposures influencing development of injecting-related infections and treatment outcomes. We pooled effect estimates via random effects meta-analyses. Results: We screened 4,841 abstracts and included 107 studies. Several factors were associated with incident or prevalent injecting-related infections: woman/female gender/sex (adjusted odds ratio [aOR] 1.57, 95% confidence interval [CI] 1.36-1.83; n=20 studies), homelessness (aOR 1.29, 95%CI 1.16-1.45; n=13 studies), cocaine use (aOR 1.31, 95%CI 1.02-1.69; n=10 studies), amphetamine use (aOR 1.74, 95%CI 1.39-2.23; n=2 studies), public injecting (aOR 1.40, 95%CI 1.05-1.88; n=2 studies), requiring injecting assistance (aOR 1.78, 95%CI 1.40-2.27; n=8 studies), and use of opioid agonist treatment (aOR 0.92, 95%CI 0.89-0.95; n=9 studies). Studies assessing outcomes during treatment (e.g., premature hospital discharge) or afterward (e.g., rehospitalization; all-cause mortality) typically had smaller sample sizes and imprecise effect estimates. Conclusions: Injecting-related infections and treatment outcomes may be shaped by multiple social contextual factors. Approaches to prevention and treatment should look beyond individual injecting practices towards addressing the social and material conditions within which people live, acquire and consume drugs, and access health care.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Social determinants of injection drug use-associated bacterial infections and treatment outcomes: systematic review and meta-analysis Abstract: Background: Individual injecting practices (e.g., intramuscular injecting, lack of skin cleaning) are known risk factors for injection drug use-associated bacterial and fungal infections; however, social contexts shape individual behaviours and health outcomes. We sought to synthesize studies assessing potential social determinants of injecting-related infections and treatment outcomes. Methods: We searched five databases for studies published between 1 January 2000 and 18 February 18 2021 (PROSPERO CRD42021231411). We included studies of association (aetiology), assessing social determinants, substance use, and health services exposures influencing development of injecting-related infections and treatment outcomes. We pooled effect estimates via random effects meta-analyses. Results: We screened 4,841 abstracts and included 107 studies. Several factors were associated with incident or prevalent injecting-related infections: woman/female gender/sex (adjusted odds ratio [aOR] 1.57, 95% confidence interval [CI] 1.36-1.83; n=20 studies), homelessness (aOR 1.29, 95%CI 1.16-1.45; n=13 studies), cocaine use (aOR 1.31, 95%CI 1.02-1.69; n=10 studies), amphetamine use (aOR 1.74, 95%CI 1.39-2.23; n=2 studies), public injecting (aOR 1.40, 95%CI 1.05-1.88; n=2 studies), requiring injecting assistance (aOR 1.78, 95%CI 1.40-2.27; n=8 studies), and use of opioid agonist treatment (aOR 0.92, 95%CI 0.89-0.95; n=9 studies). Studies assessing outcomes during treatment (e.g., premature hospital discharge) or afterward (e.g., rehospitalization; all-cause mortality) typically had smaller sample sizes and imprecise effect estimates. Conclusions: Injecting-related infections and treatment outcomes may be shaped by multiple social contextual factors. Approaches to prevention and treatment should look beyond individual injecting practices towards addressing the social and material conditions within which people live, acquire and consume drugs, and access health care.","summary":"Individual injecting practices are known risk factors for injection drug use-associated bacterial and fungal infections, but social contexts also play a crucial role in shaping individual behaviors and health outcomes. Several social determinants were associated with incident or prevalent injecting-related infections, including woman/female gender, homelessness, cocaine use, amphetamine use, public injecting, requiring injecting assistance, and opioid agonist treatment."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Year-long assessment of the immune response elicited by MVA-BN vaccine","url":"http://medrxiv.org/cgi/content/short/2024.09.20.24313813v1?rss=1","abstract":"Background Modified-Vaccinia-Ankara Bavarian Nordic (MVA-BN) vaccine has been recommended to tackle the mpox epidemic 2022-2023 and its resurgence in 2024. Although its effectiveness has been estimated to range between 36-86%, the persistence of protection is still unknown. Aims of this study is to assess the immune response one year after vaccination with MVA-BN. Methods Observational prospective study at the National Institute for Infectious Diseases in Rome. All people at high risk for mpox infection who received MVA-BN as pre-exposure prophylaxis were enrolled. People previously primed with smallpox vaccination received a single-dose course of MVA-BN, while non-primed received a two-dose course. Blood samples were collected at the time of each dose and one, six and 12 months after vaccination. MPXV-specific IgG and neutralizing antibody (nAb) titers were assessed by immunofluorescence and plaque neutralization tests, respectively. Interferon-gamma producing T-cell specific response to the MVA-BN vaccine was analyzed by ELISpot assay. Antibody titers at pre- and post-vaccination were compared using the Friedman tests. Mann Whitney test was used to compare antibody titers in PLWH vs PLWoH. Wilcoxon and Mann-Whitney non-parametric tests were used to compare T-cells specific response to the MVA-BN vaccine for intra and inter-group differences, respectively. Results Fifty high-risk people were included. All were men, with 94% self-reporting having sex with men. The median age was 50 years (IQR 45-57), and 21 (42%) were people living with HIV (PLWH), all on antiretroviral therapy, and 71% with a CD4 cell count higher than 500 mmc. 25 (50%) have been primed with previous smallpox vaccination. In non-primed people, anti-MPXV IgG titers significantly increased from T1 to T3 and, despite a slight reduction, were still higher than T1 up to T4 and then gradually decreased until T5, when 64% of sera were still reactive. MPXV-nAb titers peaked at T3 and then dropped, with 56% and 32% of sera reactive at T4 and T5, respectively. IFN-g; production by MVA-BN-specific T-cells progressively rose across time, peaked at T3, and remained significantly higher than the baseline after 6 and 12 months from vaccination. A single-dose course of MVA-BN vaccination in smallpox-primed participants elicited an early increase in IgG and nAb titers, which remained significantly higher than baseline after 6 and 12 months. MPXV-nAbs were detected in 80% and 72% of vaccinees at T4 and T5, respectively. A similar improvement and maintenance were observed for the MVA-BN-specific T-cell response. No evidence for a difference in both humoral and cellular responses was found between PLWH and PLWoH in our cohort. Conclusions One year after vaccination, our data showed the persistent detectability of low levels of nAb against MPXV in one-third of non-primed individuals. At the same time, humoral response was still detectable in most previously vaccinated participants. Concurrently, the MVA-BN-specific T-cell response was robust and persistent.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Year-long assessment of the immune response elicited by MVA-BN vaccine Abstract: Background Modified-Vaccinia-Ankara Bavarian Nordic (MVA-BN) vaccine has been recommended to tackle the mpox epidemic 2022-2023 and its resurgence in 2024. Although its effectiveness has been estimated to range between 36-86%, the persistence of protection is still unknown. Aims of this study is to assess the immune response one year after vaccination with MVA-BN. Methods Observational prospective study at the National Institute for Infectious Diseases in Rome. All people at high risk for mpox infection who received MVA-BN as pre-exposure prophylaxis were enrolled. People previously primed with smallpox vaccination received a single-dose course of MVA-BN, while non-primed received a two-dose course. Blood samples were collected at the time of each dose and one, six and 12 months after vaccination. MPXV-specific IgG and neutralizing antibody (nAb) titers were assessed by immunofluorescence and plaque neutralization tests, respectively. Interferon-gamma producing T-cell specific response to the MVA-BN vaccine was analyzed by ELISpot assay. Antibody titers at pre- and post-vaccination were compared using the Friedman tests. Mann Whitney test was used to compare antibody titers in PLWH vs PLWoH. Wilcoxon and Mann-Whitney non-parametric tests were used to compare T-cells specific response to the MVA-BN vaccine for intra and inter-group differences, respectively. Results Fifty high-risk people were included. All were men, with 94% self-reporting having sex with men. The median age was 50 years (IQR 45-57), and 21 (42%) were people living with HIV (PLWH), all on antiretroviral therapy, and 71% with a CD4 cell count higher than 500 mmc. 25 (50%) have been primed with previous smallpox vaccination. In non-primed people, anti-MPXV IgG titers significantly increased from T1 to T3 and, despite a slight reduction, were still higher than T1 up to T4 and then gradually decreased until T5, when 64% of sera were still reactive. MPXV-nAb titers peaked at T3 and then dropped, with 56% and 32% of sera reactive at T4 and T5, respectively. IFN-g; production by MVA-BN-specific T-cells progressively rose across time, peaked at T3, and remained significantly higher than the baseline after 6 and 12 months from vaccination. A single-dose course of MVA-BN vaccination in smallpox-primed participants elicited an early increase in IgG and nAb titers, which remained significantly higher than baseline after 6 and 12 months. MPXV-nAbs were detected in 80% and 72% of vaccinees at T4 and T5, respectively. A similar improvement and maintenance were observed for the MVA-BN-specific T-cell response. No evidence for a difference in both humoral and cellular responses was found between PLWH and PLWoH in our cohort. Conclusions One year after vaccination, our data showed the persistent detectability of low levels of nAb against MPXV in one-third of non-primed individuals. At the same time, humoral response was still detectable in most previously vaccinated participants. Concurrently, the MVA-BN-specific T-cell response was robust and persistent.","summary":"The study assessed the immune response one year after vaccination with Modified-Vaccinia-Ankara Bavarian Nordic (MVA-BN) vaccine, a recommended treatment for mpox infection, to evaluate its persistence of protection.   The results showed that humoral responses, measured by IgG and neutralizing antibody titers, were detectable in most individuals, including those previously vaccinated or with HIV, one year after vaccination, with some decline over time."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Genetic Diversity of the Plasmodium falciparum Reticulocyte Binding protein Homologue-5 which is a potential Malaria Vaccine Candidate: Baseline data from areas of varying malaria endemicity in Mainland Tanzania.","url":"http://medrxiv.org/cgi/content/short/2024.09.20.24314052v1?rss=1","abstract":"Background: The limited efficacy of the two malaria vaccines, RTS,S/AS01 and R21/Matrix M, which were recently approved vaccines by the World Health Organization, highlights the need for alternative vaccine candidate genes beyond these pre-erythrocytic-based vaccines. Plasmodium falciparum Reticulocyte Binding Protein Homologue 5 (Pfrh5) is a potential malaria vaccine candidate, given its limited polymorphism compared to other parasites blood stage antigens. This study evaluated the genetic diversity of the Pfrh5 gene among parasites from regions with varying malaria transmission intensities in Mainland Tanzania, to generate baseline data for this potential malaria vaccine candidate. Methods: This study utilized secondary data of 697 whole-genome sequences from Mainland Tanzania, which were generated by the MalariaGEN Community Network. The samples which were sequenced to generate the data were collected between 2010 and 2015 from five districts within five regions of Mainland Tanzania, with varying endemicities (Morogoro urban district in Morogoro region, Muheza district in Tanga region, Kigoma-Ujiji district in Kigoma region, Muleba district in Kagera region, and Nachingwea district in Lindi region). The genetic diversity of the Pfrh5 gene was assessed using different genetic metrics, including Wright's fixation index (FST), Wright's inbreeding coefficient (Fws), Principal Component analysis (PCA), nucleotide diversity ({pi}), haplotype network, haplotype diversity (Hd), Tajma's D, and Linkage disequilibrium (LD). Results. Of the sequences used in this study (n=697), 84.5% (n = 589/697) passed quality control and 313 (53.1%) were monoclonal, and these monoclonal sequences were used for haplotype diversity and haplotype network analysis. High within-host diversity (Fws <0.95) was reported in Kigoma-Ujiji (60.7%), Morogoro urban (53.1%), and Nachingwea (50.8%), while Muleba (53.9%) and Muheza (61.6%) had low within host diversity (Fws[&ge;] 0.95). PCA did not show any population structure across the five districts and the mean FST value among the study populations was 0.015. Low nucleotide diversity values were observed across the study sites with the mean nucleotide diversity of 0.00056. A total of 27 haplotypes were observed among the 313 monoclonal samples. The Pf3D7 was detected as Hap_1, and it was detected in 16/313 (5.1%) sequences, and these sample sequences were from Muheza (62.5%, n=10/16), Kigoma-Ujiji (18.8%, n=3/16), and Muleba (18.8%, n=3/16). Negative Tajima's D values were observed among the parasite populations in all the study sites. Conclusion. In this study, we observed low levels of polymorphism in the Pfrh5 gene, as it exhibited low nucleotide and haplotype diversity, a lack of population structure and negative Tajima's D values as signatures of purifying selection. This study provides an essential framework of the diversity of the Pfrh5 gene to be considered in development of the next generation malaria vaccines. Robust and intensive studies of this and other candidate genes are required for characterization of the parasites from areas with varying endemicity, and are crucial to support the prioritization of the Pfrh5 gene for potential inclusion in a broadly cross-protective malaria vaccine.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Genetic Diversity of the Plasmodium falciparum Reticulocyte Binding protein Homologue-5 which is a potential Malaria Vaccine Candidate: Baseline data from areas of varying malaria endemicity in Mainland Tanzania. Abstract: Background: The limited efficacy of the two malaria vaccines, RTS,S/AS01 and R21/Matrix M, which were recently approved vaccines by the World Health Organization, highlights the need for alternative vaccine candidate genes beyond these pre-erythrocytic-based vaccines. Plasmodium falciparum Reticulocyte Binding Protein Homologue 5 (Pfrh5) is a potential malaria vaccine candidate, given its limited polymorphism compared to other parasites blood stage antigens. This study evaluated the genetic diversity of the Pfrh5 gene among parasites from regions with varying malaria transmission intensities in Mainland Tanzania, to generate baseline data for this potential malaria vaccine candidate. Methods: This study utilized secondary data of 697 whole-genome sequences from Mainland Tanzania, which were generated by the MalariaGEN Community Network. The samples which were sequenced to generate the data were collected between 2010 and 2015 from five districts within five regions of Mainland Tanzania, with varying endemicities (Morogoro urban district in Morogoro region, Muheza district in Tanga region, Kigoma-Ujiji district in Kigoma region, Muleba district in Kagera region, and Nachingwea district in Lindi region). The genetic diversity of the Pfrh5 gene was assessed using different genetic metrics, including Wright's fixation index (FST), Wright's inbreeding coefficient (Fws), Principal Component analysis (PCA), nucleotide diversity ({pi}), haplotype network, haplotype diversity (Hd), Tajma's D, and Linkage disequilibrium (LD). Results. Of the sequences used in this study (n=697), 84.5% (n = 589/697) passed quality control and 313 (53.1%) were monoclonal, and these monoclonal sequences were used for haplotype diversity and haplotype network analysis. High within-host diversity (Fws <0.95) was reported in Kigoma-Ujiji (60.7%), Morogoro urban (53.1%), and Nachingwea (50.8%), while Muleba (53.9%) and Muheza (61.6%) had low within host diversity (Fws[&ge;] 0.95). PCA did not show any population structure across the five districts and the mean FST value among the study populations was 0.015. Low nucleotide diversity values were observed across the study sites with the mean nucleotide diversity of 0.00056. A total of 27 haplotypes were observed among the 313 monoclonal samples. The Pf3D7 was detected as Hap_1, and it was detected in 16/313 (5.1%) sequences, and these sample sequences were from Muheza (62.5%, n=10/16), Kigoma-Ujiji (18.8%, n=3/16), and Muleba (18.8%, n=3/16). Negative Tajima's D values were observed among the parasite populations in all the study sites. Conclusion. In this study, we observed low levels of polymorphism in the Pfrh5 gene, as it exhibited low nucleotide and haplotype diversity, a lack of population structure and negative Tajima's D values as signatures of purifying selection. This study provides an essential framework of the diversity of the Pfrh5 gene to be considered in development of the next generation malaria vaccines. Robust and intensive studies of this and other candidate genes are required for characterization of the parasites from areas with varying endemicity, and are crucial to support the prioritization of the Pfrh5 gene for potential inclusion in a broadly cross-protective malaria vaccine.","summary":"The study evaluated the genetic diversity of the Plasmodium falciparum Reticulocyte Binding Protein Homologue 5 (Pfrh5) gene among parasites from regions with varying malaria transmission intensities in Mainland Tanzania, using 697 whole-genome sequences.  These regions showed low levels of polymorphism in the Pfrh5 gene, characterized by low nucleotide and haplotype diversity, a lack of population structure, and negative Tajima's D values indicating purifying selection."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Gaps and Opportunities for Data Systems and Economics to Support Priority Setting for Climate-Sensitive Infectious Diseases in Sub-Saharan Africa: A Rapid Scoping Review","url":"http://medrxiv.org/cgi/content/short/2024.09.20.24314043v1?rss=1","abstract":"Climate change alters risks associated with climate-sensitive infectious diseases (CSIDs) with pandemic potential. This poses additional threats to already vulnerable populations, further amplified by intersecting social factors, such as gender and socioeconomic status. Currently, critical evidence gaps and inadequate institutional and governance mechanisms impact on the ability for African States to prevent, detect and respond to CSIDs. The aim of this study was to explore the role of data systems and economics to support priority setting for CSID preparedness in sub-Saharan Africa. We conducted a rapid scoping review to identify existing knowledge and gaps relevant to economics and data systems. A literature search was performed across six bibliographic databases in November 2023. A list of 14 target pathogens, identified by the World Health Organization as Public Health Emergencies of International Concern or R&D Blueprint Pathogens, was adopted and compared to a database of CSIDs to determine relevant inclusion criteria. Extracted data were synthesised using bibliometric analysis, thematic topic categorisation, and narrative synthesis to identify research needs, evidence gaps, and opportunities for priority setting. We identified 68 relevant studies. While African author involvement has been increasing since 2010, few studies were led by senior authors from African institutions. Data system studies (n = 50) showed broad coverage across CSIDs and the WHO AFRO region but also a high degree of heterogeneity, indicating a lack of clearly defined standards for data systems related to pandemic preparedness. Economic studies (n = 18) primarily focused on COVID-19 and Ebola and mostly originated from South Africa. Both data system and economic studies identified limited data sharing across sectors and showed a notable absence of gender sensitivity analyses. These significant gaps highlight important opportunities to support priority setting and decision-making for pandemic preparedness, ultimately leading to more equitable health outcomes.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Gaps and Opportunities for Data Systems and Economics to Support Priority Setting for Climate-Sensitive Infectious Diseases in Sub-Saharan Africa: A Rapid Scoping Review Abstract: Climate change alters risks associated with climate-sensitive infectious diseases (CSIDs) with pandemic potential. This poses additional threats to already vulnerable populations, further amplified by intersecting social factors, such as gender and socioeconomic status. Currently, critical evidence gaps and inadequate institutional and governance mechanisms impact on the ability for African States to prevent, detect and respond to CSIDs. The aim of this study was to explore the role of data systems and economics to support priority setting for CSID preparedness in sub-Saharan Africa. We conducted a rapid scoping review to identify existing knowledge and gaps relevant to economics and data systems. A literature search was performed across six bibliographic databases in November 2023. A list of 14 target pathogens, identified by the World Health Organization as Public Health Emergencies of International Concern or R&D Blueprint Pathogens, was adopted and compared to a database of CSIDs to determine relevant inclusion criteria. Extracted data were synthesised using bibliometric analysis, thematic topic categorisation, and narrative synthesis to identify research needs, evidence gaps, and opportunities for priority setting. We identified 68 relevant studies. While African author involvement has been increasing since 2010, few studies were led by senior authors from African institutions. Data system studies (n = 50) showed broad coverage across CSIDs and the WHO AFRO region but also a high degree of heterogeneity, indicating a lack of clearly defined standards for data systems related to pandemic preparedness. Economic studies (n = 18) primarily focused on COVID-19 and Ebola and mostly originated from South Africa. Both data system and economic studies identified limited data sharing across sectors and showed a notable absence of gender sensitivity analyses. These significant gaps highlight important opportunities to support priority setting and decision-making for pandemic preparedness, ultimately leading to more equitable health outcomes.","summary":"Data systems and economics can play a crucial role in supporting priority setting for climate-sensitive infectious diseases (CSIDs) in sub-Saharan Africa by providing critical evidence and informing policy decisions. Despite the existing research on CSID preparedness, significant gaps remain, including inadequate institutional and governance mechanisms, limited data sharing across sectors, and a notable absence of gender sensitivity analyses."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Leveraging Illumina iSeq100 for Whole Genome Sequencing of Salmonella Typhi: a practical approach for resource-limited setting","url":"http://medrxiv.org/cgi/content/short/2024.09.22.24314150v1?rss=1","abstract":"Bacterial whole genome sequencing helps to improve our understanding of epidemiology and pathogenesis of bacterial infections and allows comprehensive investigation on virulence, evolution and resistance mechanisms. Nepal, in recent times, has seen some increase in sequencing capabilities but faces numerous hurdles for optimum utilization. However, these hurdles can be alleviated with use of Illumina iSeq100. Therefore, this study aimed at performing whole genome sequencing of bacteria isolated utilizing the iSeq100 platform. For this study, 6 banked Salmonella enterica serovar Typhi bacterial isolates were selected. These isolates were extracted for DNA, confirmed by qPCR and then, their libraries were prepared. The libaries were checked and loaded in Illumina iSeq100 at loading concentration of 200pM. The consensus was generated from the raw genomic data by reference-based assembly, mapping onto S. Typhi CT18. These consensus genomes and coverage parameters were compared to data from using HiSeq. The raw reads were also evaluated using pathogenwatch (v22.3.8) to observe for genotype, mutations and resistance genes. The coverage parameters (coverage width and depth) of the genomes from this study were compared to same genomes sequenced using Illumina HiSeq. The average coverage width (96.81%) and depth (63.75x) of genomes sequenced in iSeq100 were comparable to that of HiSeq (width: 98.72% and depth: 69.87x). When the genomes sequenced from Illumina iSeq100 and HiSeq were compared, the genotypes detected, number of SNPs and genetic determinants of AMR genes were identical. The data from bacterial whole genome sequencing using the Illumina iSeq100 is equally informative when compared to other high-end sequencers. Therefore, the primary goal of this study is to advocate for optimum utlisation of iSeq100 while still ensuring a high standard of quality. This optimum utilization will create capacity to fill critical surveillance gaps.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Leveraging Illumina iSeq100 for Whole Genome Sequencing of Salmonella Typhi: a practical approach for resource-limited setting Abstract: Bacterial whole genome sequencing helps to improve our understanding of epidemiology and pathogenesis of bacterial infections and allows comprehensive investigation on virulence, evolution and resistance mechanisms. Nepal, in recent times, has seen some increase in sequencing capabilities but faces numerous hurdles for optimum utilization. However, these hurdles can be alleviated with use of Illumina iSeq100. Therefore, this study aimed at performing whole genome sequencing of bacteria isolated utilizing the iSeq100 platform. For this study, 6 banked Salmonella enterica serovar Typhi bacterial isolates were selected. These isolates were extracted for DNA, confirmed by qPCR and then, their libraries were prepared. The libaries were checked and loaded in Illumina iSeq100 at loading concentration of 200pM. The consensus was generated from the raw genomic data by reference-based assembly, mapping onto S. Typhi CT18. These consensus genomes and coverage parameters were compared to data from using HiSeq. The raw reads were also evaluated using pathogenwatch (v22.3.8) to observe for genotype, mutations and resistance genes. The coverage parameters (coverage width and depth) of the genomes from this study were compared to same genomes sequenced using Illumina HiSeq. The average coverage width (96.81%) and depth (63.75x) of genomes sequenced in iSeq100 were comparable to that of HiSeq (width: 98.72% and depth: 69.87x). When the genomes sequenced from Illumina iSeq100 and HiSeq were compared, the genotypes detected, number of SNPs and genetic determinants of AMR genes were identical. The data from bacterial whole genome sequencing using the Illumina iSeq100 is equally informative when compared to other high-end sequencers. Therefore, the primary goal of this study is to advocate for optimum utlisation of iSeq100 while still ensuring a high standard of quality. This optimum utilization will create capacity to fill critical surveillance gaps.","summary":"The study aimed to perform whole genome sequencing of Salmonella Typhi bacteria isolated in Nepal using the Illumina iSeq100 platform, overcoming some of the challenges faced by the country in optimal sequencing capabilities. The results showed that the iSeq100 platform was comparable to other high-end sequencers like HiSeq in terms of coverage parameters and genotypes detected, making it a practical approach for resource-limited settings."}
{"source":"medRxiv","subject":"infectious_diseases","title":"The molecular basis for prognosis of isoniazid resistance in Mycobacterium tuberculosis","url":"http://medrxiv.org/cgi/content/short/2024.09.21.24314105v1?rss=1","abstract":"Tuberculosis (TB), a disease that kills 1.5 million people every year, is a major global public health concern. The emergence of drug resistance in M. tuberculosis, the obligate pathogen of TB is a major challenge. The emergence of resistance seems to follow an order that might be exploited for novel therapeutic strategies. In most cases resistance to isoniazid (INH) emerges first, followed by rifampicin, then either pyrazinamide or ethambutol, and finally followed by resistance to second-line drugs. For this reason, it is thought that prevention of emergence of INH resistance may help the prevention of resistance to other drugs. In this manuscript we present the prognostic potential of specific mutations in predicting the emergence of the three most common canonical INH resistance (katG315, inhA-15, and inhA-8) with the hope that majority of resistance cases can be predicted and avoided. Here we present evidence that resistance to INH occurs in steps that in most cases follow specific evolutionary trajectory. Identifying these steps can therefore be used to predict and avoid the most common INH resistance mechanism. In our approach, we used genomic and phenotypic data from over 16,000 samples collected by two large databases, the TB Portals and the CRyPTIC consortium. We used classical sensitivity and specificity values as well as a deep learning neural models to identify promising predictive mutations using TB Portals data. We then tested the prognostic potential of the identified mutations using the CRyPTIC consortium data. Here we report two mutations (Rv1258c 581 indel & mshA A187V) as those carrying the highest potential for predicting the emergence of the three canonical mutations (accuracy of 73% and specificity of 96%). Our results point to a stepwise evolutionary trajectory toward the emergence of the three canonical mutations. Furthermore, the high negative predictive values provide an opportunity for clinicians to continue using INH in new regiments designed for nonresponsive patients whose samples do not contain the two precursor mutations. Finally, we present testable hypotheses describing the role of the precursor mutations in emergence of the three canonical mutations and the predicted trajectories. Mutagenesis experiments can confirm these hypotheses. Additional time course samples and analysis will undoubtedly uncover additional prognostic markers for other trajectories toward high-level INH resistance.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: The molecular basis for prognosis of isoniazid resistance in Mycobacterium tuberculosis Abstract: Tuberculosis (TB), a disease that kills 1.5 million people every year, is a major global public health concern. The emergence of drug resistance in M. tuberculosis, the obligate pathogen of TB is a major challenge. The emergence of resistance seems to follow an order that might be exploited for novel therapeutic strategies. In most cases resistance to isoniazid (INH) emerges first, followed by rifampicin, then either pyrazinamide or ethambutol, and finally followed by resistance to second-line drugs. For this reason, it is thought that prevention of emergence of INH resistance may help the prevention of resistance to other drugs. In this manuscript we present the prognostic potential of specific mutations in predicting the emergence of the three most common canonical INH resistance (katG315, inhA-15, and inhA-8) with the hope that majority of resistance cases can be predicted and avoided. Here we present evidence that resistance to INH occurs in steps that in most cases follow specific evolutionary trajectory. Identifying these steps can therefore be used to predict and avoid the most common INH resistance mechanism. In our approach, we used genomic and phenotypic data from over 16,000 samples collected by two large databases, the TB Portals and the CRyPTIC consortium. We used classical sensitivity and specificity values as well as a deep learning neural models to identify promising predictive mutations using TB Portals data. We then tested the prognostic potential of the identified mutations using the CRyPTIC consortium data. Here we report two mutations (Rv1258c 581 indel & mshA A187V) as those carrying the highest potential for predicting the emergence of the three canonical mutations (accuracy of 73% and specificity of 96%). Our results point to a stepwise evolutionary trajectory toward the emergence of the three canonical mutations. Furthermore, the high negative predictive values provide an opportunity for clinicians to continue using INH in new regiments designed for nonresponsive patients whose samples do not contain the two precursor mutations. Finally, we present testable hypotheses describing the role of the precursor mutations in emergence of the three canonical mutations and the predicted trajectories. Mutagenesis experiments can confirm these hypotheses. Additional time course samples and analysis will undoubtedly uncover additional prognostic markers for other trajectories toward high-level INH resistance.","summary":"The study investigates the molecular basis for predicting isoniazid resistance in Mycobacterium tuberculosis, which is a major challenge in treating TB due to its high mortality rate. The researchers analyzed genomic and phenotypic data from over 16,000 samples and identified specific mutations that can predict the emergence of three common canonical INH resistance mechanisms with an accuracy of 73% and specificity of 96%."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Preventive interventions for post Covid-19 condition: systematic review update","url":"http://medrxiv.org/cgi/content/short/2024.09.18.24313918v1?rss=1","abstract":"Background: Post COVID-19 condition (PCC) can affect individuals regardless of the severity of their initial illness, and its impact on daily life can be significant. There are uncertainties about whether treatments in the acute or post-acute phase of infection can prevent PCC. We report an update to a previous systematic review on the effects of interventions to prevent PCC. Methods: We updated our previous peer-reviewed searches on February 9, 2024. We searched bibliographic databases and grey literature resources to identify trials and comparative observational studies reporting on any intervention provided during the acute (symptom onset to 4 weeks) or post-acute phase (4-8 weeks) of COVID-19 and our primary outcome of incidence of PCC, ascertained at 3 months or longer following infection and capturing, at a minimum, symptoms of fatigue, dyspnea and one or more aspects of cognitive function. Non-recovery from COVID-19 was included if necessary. Secondary outcomes included fatigue, breathlessness/dyspnea, post-exertional malaise, health-related quality of life, psychopathology, cognitive impairment, hospitalization, return to work/education, and adverse effects of the intervention. For screening we employed artificial intelligence to prioritize records and modified our methods to rely on single-reviewer screening after 50% of citations were screened in duplicate. Study selection and risk of bias assessments were conducted independently by two reviewers and data extraction relied on verification of another reviewers work. We grouped studies by intervention type and timing, and by acute-care setting, and performed meta-analysis where appropriate. Sensitivity analyses were conducted for the primary outcome, excluding studies with high risk of bias, using non-recovery as a proxy outcome, and evaluating the outcome at more than 12 months of follow-up. We assessed the certainty of evidence using GRADE. Results: Twenty-four studies (5 randomized and 19 non-randomized), all among adults, were included. The acute care setting in nine studies was outpatient and in 15 studies was in-patient; all but one intervention was administered during the acute-phase of illness. The use of convalescent plasma in outpatient acute COVID-19 care probably does not reduce the risk of PCC (relative risk [RR]: 0.93, 95% CI: 0.77-1.12; 1 RCT; moderate certainty). There was low-certainty evidence suggesting that probiotics (RR [95% CI]: 0.32 [0.13-0.78]; 1 RCT) and metformin (0.50 [0.25-0.99]; 1 RCT among individuals with a BMI >=25 kg/m2) reduce PCC to a small-to-moderate extent in outpatients, while ivermectin (outpatients), antivirals (outpatients), steroids (in-patients), and therapeutic-dose heparin (vs. prophylactic dose; in-patients) may not be effective. Evidence was very low certainty for several other acute-phase pharmacologic intervention and post-acute outpatient assessment and referrals. For outpatient antiviral treatment, while overall PCC risk may not decrease, there might be a slight reduction in psychopathology. Similarly, inpatient antiviral use may not prevent PCC but may offer a small reduction in prolonged general malaise after light exertion. Therapeutic-dose heparin may slightly reduce the risk of cognitive impairment compared to prophylactic-dose heparin among in-patients. The findings remained consistent across all these sensitivity analyses. Conclusions: Evidence suggests that PCC can be prevented to some extent among outpatients with the use of probiotics and metformin during the acute phase of COVID-19. Effects from interventions used among in-patients and within the post-acute phase are uncertain at this time. Evidence on commonly recommended interventions including rehabilitation or multidisciplinary care was lacking. Protocol registration: CRD42024513247","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Preventive interventions for post Covid-19 condition: systematic review update Abstract: Background: Post COVID-19 condition (PCC) can affect individuals regardless of the severity of their initial illness, and its impact on daily life can be significant. There are uncertainties about whether treatments in the acute or post-acute phase of infection can prevent PCC. We report an update to a previous systematic review on the effects of interventions to prevent PCC. Methods: We updated our previous peer-reviewed searches on February 9, 2024. We searched bibliographic databases and grey literature resources to identify trials and comparative observational studies reporting on any intervention provided during the acute (symptom onset to 4 weeks) or post-acute phase (4-8 weeks) of COVID-19 and our primary outcome of incidence of PCC, ascertained at 3 months or longer following infection and capturing, at a minimum, symptoms of fatigue, dyspnea and one or more aspects of cognitive function. Non-recovery from COVID-19 was included if necessary. Secondary outcomes included fatigue, breathlessness/dyspnea, post-exertional malaise, health-related quality of life, psychopathology, cognitive impairment, hospitalization, return to work/education, and adverse effects of the intervention. For screening we employed artificial intelligence to prioritize records and modified our methods to rely on single-reviewer screening after 50% of citations were screened in duplicate. Study selection and risk of bias assessments were conducted independently by two reviewers and data extraction relied on verification of another reviewers work. We grouped studies by intervention type and timing, and by acute-care setting, and performed meta-analysis where appropriate. Sensitivity analyses were conducted for the primary outcome, excluding studies with high risk of bias, using non-recovery as a proxy outcome, and evaluating the outcome at more than 12 months of follow-up. We assessed the certainty of evidence using GRADE. Results: Twenty-four studies (5 randomized and 19 non-randomized), all among adults, were included. The acute care setting in nine studies was outpatient and in 15 studies was in-patient; all but one intervention was administered during the acute-phase of illness. The use of convalescent plasma in outpatient acute COVID-19 care probably does not reduce the risk of PCC (relative risk [RR]: 0.93, 95% CI: 0.77-1.12; 1 RCT; moderate certainty). There was low-certainty evidence suggesting that probiotics (RR [95% CI]: 0.32 [0.13-0.78]; 1 RCT) and metformin (0.50 [0.25-0.99]; 1 RCT among individuals with a BMI >=25 kg/m2) reduce PCC to a small-to-moderate extent in outpatients, while ivermectin (outpatients), antivirals (outpatients), steroids (in-patients), and therapeutic-dose heparin (vs. prophylactic dose; in-patients) may not be effective. Evidence was very low certainty for several other acute-phase pharmacologic intervention and post-acute outpatient assessment and referrals. For outpatient antiviral treatment, while overall PCC risk may not decrease, there might be a slight reduction in psychopathology. Similarly, inpatient antiviral use may not prevent PCC but may offer a small reduction in prolonged general malaise after light exertion. Therapeutic-dose heparin may slightly reduce the risk of cognitive impairment compared to prophylactic-dose heparin among in-patients. The findings remained consistent across all these sensitivity analyses. Conclusions: Evidence suggests that PCC can be prevented to some extent among outpatients with the use of probiotics and metformin during the acute phase of COVID-19. Effects from interventions used among in-patients and within the post-acute phase are uncertain at this time. Evidence on commonly recommended interventions including rehabilitation or multidisciplinary care was lacking. Protocol registration: CRD42024513247","summary":"Interventions aimed at preventing post-COVID-19 condition (PCC) were tested in various studies, with some showing promise while others failed to demonstrate efficacy. Probiotics and metformin, when administered during the acute phase of COVID-19, may reduce the risk of PCC in outpatients by small to moderate extents."}
{"source":"medRxiv","subject":"infectious_diseases","title":"CRISPR-Cas12a2-based rapid and sensitive detection system for target nucleic acid","url":"http://medrxiv.org/cgi/content/short/2024.09.20.24314102v1?rss=1","abstract":"Infectious diseases are extremely important public health issues, where the design of effective, rapid, and convenient detection platforms is critical. In this study, we used conventional PCR coupled with SuCas12a2, a novel Cas12 family RNA-targeting nuclease, to develop a detection approach. SuCas12a2 possesses collateral cleavage activity and cuts the additional single-stranded RNA (ssRNA) added to the reaction system once the ternary complex RNA-SuCas12a2-CRISPR RNA (crRNA) is formed. SuCas12a2 is specifically activated, where the cleaved fluorescent-labeled probes release fluorescent signals, with the strength of the fluorescent signal being proportional to the concentration of nucleic acids specifically bound to crRNA. Simultaneous transcription and SuCas12a2 detection can be performed in a single tube by introducing the T7 promoter sequence into the forward primer. Entamoeba histolytica was used to evaluate the performance of the platform. PCR-SuCas12a2 has excellent capabilities, including high specificity with no cross-reactivity from other species and ultra-sensitivity that achieves a detection of one copy per reaction. There were five samples from amoebiasis patients confirmed by indirect immunofluorescence assay that were used as proof specimens, where the PCR-SuCas12a2 assay demonstrated 100% specificity. Furthermore, we replaced conventional PCR with recombinase polymerase amplification (RPA) to simplify the procedure for producing amplicons harboring the T7 promoter sequence. The sensitivity of the RPA-SuCas12a2 assay was 102 copies per reaction, which was inferior to PCR-SuCas12a2, and demonstrated 100% specificity. The technique shows robust performance and suggests great potential for point-of-care testing of other pathogens to facilitate effective management and control of the spread of diseases.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: CRISPR-Cas12a2-based rapid and sensitive detection system for target nucleic acid Abstract: Infectious diseases are extremely important public health issues, where the design of effective, rapid, and convenient detection platforms is critical. In this study, we used conventional PCR coupled with SuCas12a2, a novel Cas12 family RNA-targeting nuclease, to develop a detection approach. SuCas12a2 possesses collateral cleavage activity and cuts the additional single-stranded RNA (ssRNA) added to the reaction system once the ternary complex RNA-SuCas12a2-CRISPR RNA (crRNA) is formed. SuCas12a2 is specifically activated, where the cleaved fluorescent-labeled probes release fluorescent signals, with the strength of the fluorescent signal being proportional to the concentration of nucleic acids specifically bound to crRNA. Simultaneous transcription and SuCas12a2 detection can be performed in a single tube by introducing the T7 promoter sequence into the forward primer. Entamoeba histolytica was used to evaluate the performance of the platform. PCR-SuCas12a2 has excellent capabilities, including high specificity with no cross-reactivity from other species and ultra-sensitivity that achieves a detection of one copy per reaction. There were five samples from amoebiasis patients confirmed by indirect immunofluorescence assay that were used as proof specimens, where the PCR-SuCas12a2 assay demonstrated 100% specificity. Furthermore, we replaced conventional PCR with recombinase polymerase amplification (RPA) to simplify the procedure for producing amplicons harboring the T7 promoter sequence. The sensitivity of the RPA-SuCas12a2 assay was 102 copies per reaction, which was inferior to PCR-SuCas12a2, and demonstrated 100% specificity. The technique shows robust performance and suggests great potential for point-of-care testing of other pathogens to facilitate effective management and control of the spread of diseases.","summary":"Infectious diseases pose a significant public health issue, highlighting the need for rapid and convenient detection platforms. A novel CRISPR-Cas12a2-based detection system was developed by coupling conventional PCR with SuCas12a2, a nuclease that possesses collateral cleavage activity. The system uses crRNA to specifically target nucleic acids, resulting in cleaved fluorescent-labeled probes that release fluorescent signals proportional to the concentration of bound nucleic acids.   The assay demonstrated excellent specificity and sensitivity, including high accuracy without cross-reactivity with other species, and could detect as few as one copy per reaction. Five samples from amoebiasis patients confirmed by indirect immunofluorescence assay were used to evaluate the platform's performance, showing 100% specificity in all cases. A simpler alternative, combining RPA with SuCas12a2, was also developed to produce amplicons harboring a T7 promoter sequence, yielding 102 copies per reaction and 100% specificity. The detection system shows robust performance and great potential for point-of-care testing of other pathogens to facilitate effective disease management and control."}
{"source":"medRxiv","subject":"infectious_diseases","title":"COVID-19 Vaccine effectiveness among Healthcare Workers during the Omicron Period in the country of Georgia, January - June 2022","url":"http://medrxiv.org/cgi/content/short/2024.09.19.24314033v1?rss=1","abstract":"IntroductionUnderstanding COVID-19 vaccine effectiveness (VE) in healthcare workers (HCWs) is critical to inform vaccination policies. We measured COVID-19 VE against laboratory-confirmed symptomatic infection in HCWs in the country of Georgia from January - June 2022, during a period of Omicron circulation.MethodsWe conducted a cohort study of HCWs in six hospitals in Georgia. HCWs were enrolled in early 2021. Participants completed weekly symptom questionnaires. Symptomatic HCWs were tested by RT-PCR and/or rapid antigen test (RAT). Participants were also routinely tested, at varying frequencies during the study period, for SARS-CoV-2 by RT-PCR or RAT, regardless of symptoms. Serology was collected quarterly throughout the study and tested by electrochemiluminescence immunoassay for SARS-CoV-2 antibodies. We estimated absolute and relative VE of a first booster dose compared to a primary vaccine series as (1-hazard ratio)*100 using Cox proportional hazards models.ResultsAmong 1253 HCWs, 141 (11%) received a primary vaccine series (PVS) and a first booster, 855 (68%) received PVS only, and 248 (20%) were unvaccinated. Most boosters were BNT162b2 (Comirnaty original monovalent) vaccine (90%) and BIBP-CorV vaccine (Sinopharm) (9%). Most PVS were BNT162b2 vaccine (68%) and BIBP-CorV vaccine (24%). Absolute VE for a first booster was 40% (95% Confidence Interval (CI) -56 - 77) at 7- 29 days following vaccination, -9% (95% CI -104 - 42) at 30 - 59 days, and - 46% (95% CI -156 - 17) at [&ge;] 60 days. Relative VE of first booster dose compared to PVS was 58% (95% CI 1 - 82) at 7- 29 days following vaccination, 21% (95% CI -33 - 54) at 30 - 59 days, and -9% (95% CI -82 - 34) at [&ge;] 60 days.ConclusionIn Georgia, first booster dose VE against symptomatic SARS-CoV-2 infection among HCWs was moderately effective but waned very quickly during Omicron. Increased efforts to vaccinate priority groups in Georgia, such as healthcare workers, prior to periods of anticipated high COVID-19 incidence are essential.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: COVID-19 Vaccine effectiveness among Healthcare Workers during the Omicron Period in the country of Georgia, January - June 2022 Abstract: IntroductionUnderstanding COVID-19 vaccine effectiveness (VE) in healthcare workers (HCWs) is critical to inform vaccination policies. We measured COVID-19 VE against laboratory-confirmed symptomatic infection in HCWs in the country of Georgia from January - June 2022, during a period of Omicron circulation.MethodsWe conducted a cohort study of HCWs in six hospitals in Georgia. HCWs were enrolled in early 2021. Participants completed weekly symptom questionnaires. Symptomatic HCWs were tested by RT-PCR and/or rapid antigen test (RAT). Participants were also routinely tested, at varying frequencies during the study period, for SARS-CoV-2 by RT-PCR or RAT, regardless of symptoms. Serology was collected quarterly throughout the study and tested by electrochemiluminescence immunoassay for SARS-CoV-2 antibodies. We estimated absolute and relative VE of a first booster dose compared to a primary vaccine series as (1-hazard ratio)*100 using Cox proportional hazards models.ResultsAmong 1253 HCWs, 141 (11%) received a primary vaccine series (PVS) and a first booster, 855 (68%) received PVS only, and 248 (20%) were unvaccinated. Most boosters were BNT162b2 (Comirnaty original monovalent) vaccine (90%) and BIBP-CorV vaccine (Sinopharm) (9%). Most PVS were BNT162b2 vaccine (68%) and BIBP-CorV vaccine (24%). Absolute VE for a first booster was 40% (95% Confidence Interval (CI) -56 - 77) at 7- 29 days following vaccination, -9% (95% CI -104 - 42) at 30 - 59 days, and - 46% (95% CI -156 - 17) at [&ge;] 60 days. Relative VE of first booster dose compared to PVS was 58% (95% CI 1 - 82) at 7- 29 days following vaccination, 21% (95% CI -33 - 54) at 30 - 59 days, and -9% (95% CI -82 - 34) at [&ge;] 60 days.ConclusionIn Georgia, first booster dose VE against symptomatic SARS-CoV-2 infection among HCWs was moderately effective but waned very quickly during Omicron. Increased efforts to vaccinate priority groups in Georgia, such as healthcare workers, prior to periods of anticipated high COVID-19 incidence are essential.","summary":"Absolute VE for a first booster dose compared to a primary vaccine series was 40% at 7-29 days following vaccination, -9% at 30-59 days, and -46% at ≥60 days. Relative VE of first booster dose compared to PVS was 58% at 7-29 days following vaccination, 21% at 30-59 days, and -9% at ≥60 days."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control","url":"http://medrxiv.org/cgi/content/short/2024.09.19.24313985v1?rss=1","abstract":"BackgroundCurrent methods are insufficient alone for outbreak detection in hospitals. Real-time genomic surveillance using offers the potential to detect otherwise unidentified outbreaks. We initiated and evaluated the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT), a real-time genomic surveillance program for outbreak detection and mitigation.MethodsThis study was conducted at UPMC Presbyterian Hospital from November 2021 to October 2023. Whole genome sequencing (WGS) was performed weekly on healthcare-associated clinical bacterial isolates to identify otherwise undetected outbreaks. Interventions were implemented in real-time based on identified transmission. A clinical and economic impact analysis was conducted to estimate infections averted and net cost savings.ResultsThere were 3,921 bacterial isolates from patient healthcare-associated infections that underwent WGS, of which 476 (12.1%) clustered into 172 outbreaks (size range 2-16 patients). Of the outbreak isolates, 292 (61.3%) had an identified epidemiological link. Among the outbreaks with interventions, 95.6% showed no further transmission on the intervened transmission route. The impact analysis estimated that, over the two-year period, 62 infections were averted, with gross cost savings of $1,011,146, and net savings of $695,706, which translates to a 3.2-fold return on investment. Probabilistic sensitivity analysis showed EDS-HAT was cost-saving and more effective in 98% of simulations.ConclusionReal-time genomic surveillance enabled the rapid detection and control of outbreaks in our hospital and resulted in economic benefits and improvement in patient safety. This study demonstrates the feasibility and effectiveness of integrating genomic surveillance into routine infection prevention practice, offering a paradigm shift in healthcare outbreak detection and control.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Genomic Surveillance for Enhanced Healthcare Outbreak Detection and Control Abstract: BackgroundCurrent methods are insufficient alone for outbreak detection in hospitals. Real-time genomic surveillance using offers the potential to detect otherwise unidentified outbreaks. We initiated and evaluated the Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT), a real-time genomic surveillance program for outbreak detection and mitigation.MethodsThis study was conducted at UPMC Presbyterian Hospital from November 2021 to October 2023. Whole genome sequencing (WGS) was performed weekly on healthcare-associated clinical bacterial isolates to identify otherwise undetected outbreaks. Interventions were implemented in real-time based on identified transmission. A clinical and economic impact analysis was conducted to estimate infections averted and net cost savings.ResultsThere were 3,921 bacterial isolates from patient healthcare-associated infections that underwent WGS, of which 476 (12.1%) clustered into 172 outbreaks (size range 2-16 patients). Of the outbreak isolates, 292 (61.3%) had an identified epidemiological link. Among the outbreaks with interventions, 95.6% showed no further transmission on the intervened transmission route. The impact analysis estimated that, over the two-year period, 62 infections were averted, with gross cost savings of $1,011,146, and net savings of $695,706, which translates to a 3.2-fold return on investment. Probabilistic sensitivity analysis showed EDS-HAT was cost-saving and more effective in 98% of simulations.ConclusionReal-time genomic surveillance enabled the rapid detection and control of outbreaks in our hospital and resulted in economic benefits and improvement in patient safety. This study demonstrates the feasibility and effectiveness of integrating genomic surveillance into routine infection prevention practice, offering a paradigm shift in healthcare outbreak detection and control.","summary":"The authors implemented a real-time genomic surveillance program to detect healthcare-associated transmission and evaluated its effectiveness at UPMC Presbyterian Hospital from November 2021 to October 2023. The Enhanced Detection System for Healthcare-associated Transmission (EDS-HAT) successfully detected 172 outbreaks, with 95.6% of interventions resulting in no further transmission on the intervened transmission route."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Performance evaluation of nine reference centers for effective surveillance of Leishmania-infected Phlebotomine sand flies and basis for technical recommendations","url":"http://medrxiv.org/cgi/content/short/2024.09.19.24313901v1?rss=1","abstract":"BackgroundLeishmaniasis, caused by Leishmania protozoan parasites transmitted by Phlebotomine sand flies, is a significant public health concern in the Mediterranean basin. Effective monitoring of Leishmania-infected sand flies requires standardized tools for comparing their distribution and infection prevalence. Consistent quantitative PCR (qPCR) conditions and efficient DNA extraction protocols are crucial for reliable results over time and across regions. However, there is currently a lack of technical recommendations for Leishmania DNA detection, which needs to be addressed. This study aimed to compare various DNA extraction protocols and conduct a qPCR based External Quality Assessment (EQA) through a multicenter study involving nine reference laboratories.Methodology/Principal findingsEQA samples were prepared using Leishmania infantum and L. major strains, at different concentration from 101 to 104 parasites/mL and distributed to participating centers. All centers, except one, detected all Leishmania concentrations, demonstrating diagnostic proficiency. The ability to detect low concentrations highlighted the robustness of the qPCR assay used, although Cq value variations suggested differences in sensitivity due to technical capabilities and/or extraction kit performances.Reported comparative analysis of seven DNA extraction methods identified the EZ1 DSP Virus(R) Kit and QIAamp(R) DNA mini-kit as the most efficient, supporting their use for standardized protocols. The study also evaluated the impact of lyophilization and shipment conditions, finding no compromise in Leishmania detection, despite slight Cq value variations. In addition to EQA samples, experimentally infected sand fly have been included to mimic sample field condition. All centers detected positive samples, with variable Cq values, reflecting differences in individual infection load.Conclusion and significanceOverall, the study underscores the importance of standardized protocols and continuous quality assurance to maintain high diagnostic validity, crucial for effective surveillance of leishmaniasis, especially in field settings with low infection densities. Continuous training and calibration are essential to ensure uniform diagnostic performance across laboratories, enhancing epidemiological surveillance and disease control strategies.Author SummaryLeishmaniasis is a disease caused by Leishmania parasites, transmitted by sand flies, and poses a major health risk in the Mediterranean region. Monitoring the spread of nfected sand flies is crucial for controlling the disease. This study focused on improving the methods used to detect Leishmania in sand flies by comparing different DNA extraction techniques and assessing the accuracy of these methods across nine reference laboratories. All centers, except one, efficiently detected all Leishmania concentrations, demonstrating proficiency in diagnostic protocols. Moreover, we found that two specific DNA extraction kits, the EZ1 DSP Virus(R) Kit and QIAamp(R) DNA mini-kit, were the most effective for Leishmania detection. We also tested how sample preparation and shipping conditions affected the results, ensuring that our methods would work in real-world settings. Even under these conditions, the detection methods proved reliable. This work helps to standardize the detection of Leishmania, making surveillance more accurate and consistent. Continuous training and calibration are essential to ensure uniform diagnostic performance across laboratories, enhancing epidemiological surveillance and disease control strategies","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Performance evaluation of nine reference centers for effective surveillance of Leishmania-infected Phlebotomine sand flies and basis for technical recommendations Abstract: BackgroundLeishmaniasis, caused by Leishmania protozoan parasites transmitted by Phlebotomine sand flies, is a significant public health concern in the Mediterranean basin. Effective monitoring of Leishmania-infected sand flies requires standardized tools for comparing their distribution and infection prevalence. Consistent quantitative PCR (qPCR) conditions and efficient DNA extraction protocols are crucial for reliable results over time and across regions. However, there is currently a lack of technical recommendations for Leishmania DNA detection, which needs to be addressed. This study aimed to compare various DNA extraction protocols and conduct a qPCR based External Quality Assessment (EQA) through a multicenter study involving nine reference laboratories.Methodology/Principal findingsEQA samples were prepared using Leishmania infantum and L. major strains, at different concentration from 101 to 104 parasites/mL and distributed to participating centers. All centers, except one, detected all Leishmania concentrations, demonstrating diagnostic proficiency. The ability to detect low concentrations highlighted the robustness of the qPCR assay used, although Cq value variations suggested differences in sensitivity due to technical capabilities and/or extraction kit performances.Reported comparative analysis of seven DNA extraction methods identified the EZ1 DSP Virus(R) Kit and QIAamp(R) DNA mini-kit as the most efficient, supporting their use for standardized protocols. The study also evaluated the impact of lyophilization and shipment conditions, finding no compromise in Leishmania detection, despite slight Cq value variations. In addition to EQA samples, experimentally infected sand fly have been included to mimic sample field condition. All centers detected positive samples, with variable Cq values, reflecting differences in individual infection load.Conclusion and significanceOverall, the study underscores the importance of standardized protocols and continuous quality assurance to maintain high diagnostic validity, crucial for effective surveillance of leishmaniasis, especially in field settings with low infection densities. Continuous training and calibration are essential to ensure uniform diagnostic performance across laboratories, enhancing epidemiological surveillance and disease control strategies.Author SummaryLeishmaniasis is a disease caused by Leishmania parasites, transmitted by sand flies, and poses a major health risk in the Mediterranean region. Monitoring the spread of nfected sand flies is crucial for controlling the disease. This study focused on improving the methods used to detect Leishmania in sand flies by comparing different DNA extraction techniques and assessing the accuracy of these methods across nine reference laboratories. All centers, except one, efficiently detected all Leishmania concentrations, demonstrating proficiency in diagnostic protocols. Moreover, we found that two specific DNA extraction kits, the EZ1 DSP Virus(R) Kit and QIAamp(R) DNA mini-kit, were the most effective for Leishmania detection. We also tested how sample preparation and shipping conditions affected the results, ensuring that our methods would work in real-world settings. Even under these conditions, the detection methods proved reliable. This work helps to standardize the detection of Leishmania, making surveillance more accurate and consistent. Continuous training and calibration are essential to ensure uniform diagnostic performance across laboratories, enhancing epidemiological surveillance and disease control strategies","summary":"The study aimed to compare DNA extraction protocols and conduct a qPCR-based External Quality Assessment (EQA) through a multicenter study involving nine reference laboratories. The EQA samples showed that all centers, except one, detected all Leishmania concentrations, demonstrating diagnostic proficiency and highlighting the robustness of the qPCR assay used."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Molecular Detection of Multi-drug resistant tuberculosis in clinical isolates from two urban centres in Malawi","url":"http://medrxiv.org/cgi/content/short/2024.09.19.24313870v1?rss=1","abstract":"IntroductionSuboptimal chemotherapy allows Mycobacterium tuberculosis to develop drug resistance owing to development of resistant mutants in the mycobacterial population. Early diagnosis of TB and identification of drug-resistance is of particular importance in human immunodeficiency virus (HIV)-infected individuals, as delay of therapy and subsequent development of drug-resistant TB can be devastating due to compromised immune systems.MethodologyWe conducted a cross-sectional evaluation study using presumptive M. tuberculosis positive clinical isolates at two urban sites in Malawi (Blantyre and Lilongwe) to assess the presence of mutant genes on first and second line TB drugs using Line Probe Assay (LPA) and the gold standard drug susceptibility test (DST)ResultsFor the Lilongwe site, the incidence of MDR-TB by Line Probe Assay (LPA) was found to be 14.06% (95% CI: 8%-20%) whereas that for Rif mono-resistance was 6.25% (95% CI: 2%-10%). Contrastingly, MDR-TB by DST was 23.44% (95 CI:16% - 21%) while mono-resistance was 6.25% (95% CI:2% -10). There was a substantial agreement on the detection of MDR-TB (kappa statistic was 0.75 with 95% CI of 0.62-0.88). Blantyre site, at 9.5% confidence interval, the point estimate for MDR-TB was 0% while for INH mono-resistance TB was 3.3%.ConclusionsThere is high incidence of MDR-TB among patients whose samples are sent to the Lilongwe site than previously thought. A short turnaround time to diagnosis, and the ability to simultaneously detect rifampicin and isoniazid resistance, makes LPA a reliable tool for the early detection of multidrug-resistant tuberculosis.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Molecular Detection of Multi-drug resistant tuberculosis in clinical isolates from two urban centres in Malawi Abstract: IntroductionSuboptimal chemotherapy allows Mycobacterium tuberculosis to develop drug resistance owing to development of resistant mutants in the mycobacterial population. Early diagnosis of TB and identification of drug-resistance is of particular importance in human immunodeficiency virus (HIV)-infected individuals, as delay of therapy and subsequent development of drug-resistant TB can be devastating due to compromised immune systems.MethodologyWe conducted a cross-sectional evaluation study using presumptive M. tuberculosis positive clinical isolates at two urban sites in Malawi (Blantyre and Lilongwe) to assess the presence of mutant genes on first and second line TB drugs using Line Probe Assay (LPA) and the gold standard drug susceptibility test (DST)ResultsFor the Lilongwe site, the incidence of MDR-TB by Line Probe Assay (LPA) was found to be 14.06% (95% CI: 8%-20%) whereas that for Rif mono-resistance was 6.25% (95% CI: 2%-10%). Contrastingly, MDR-TB by DST was 23.44% (95 CI:16% - 21%) while mono-resistance was 6.25% (95% CI:2% -10). There was a substantial agreement on the detection of MDR-TB (kappa statistic was 0.75 with 95% CI of 0.62-0.88). Blantyre site, at 9.5% confidence interval, the point estimate for MDR-TB was 0% while for INH mono-resistance TB was 3.3%.ConclusionsThere is high incidence of MDR-TB among patients whose samples are sent to the Lilongwe site than previously thought. A short turnaround time to diagnosis, and the ability to simultaneously detect rifampicin and isoniazid resistance, makes LPA a reliable tool for the early detection of multidrug-resistant tuberculosis.","summary":"The study evaluated the presence of mutant genes on first and second line TB drugs in clinical isolates from two urban sites in Malawi. The incidence of multi-drug resistant tuberculosis (MDR-TB) was found to be 14.06% at the Lilongwe site, with a substantial agreement between Line Probe Assay (LPA) and drug susceptibility test (DST)."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Tracing SARS-CoV-2 Clusters Across Local-scales Using Genomic Data","url":"http://medrxiv.org/cgi/content/short/2024.09.18.24313896v1?rss=1","abstract":"Understanding local-scale transmission dynamics of SARS-CoV-2 is crucial for planning effective prevention strategies. This study analyzed over 26,000 genomes and their associated metadata collected between January and October 2021 to explore the introduction and dispersal patterns of SARS-CoV-2 in Greater Houston, a major metropolitan area noted for its demographic diversity. We identified more than a thousand independent introduction events, resulting in clusters of varying sizes, with earlier clusters presenting larger sizes and posing greater control challenges. Characterization of the sources of these introductions showed that domestic origins were more significant than international ones. Further examination of locally circulating clusters across different subregions of Greater Houston revealed varied transmission dynamics. Notably, subregions that served as primary viral sources sustained the local epidemic effectively, evidenced by: (1) a smaller proportion of new cases driven by external viral importations, and (2) longer persistence times of circulating lineages. Overall, our high-resolution spatiotemporal reconstruction of the epidemic in Greater Houston enhances understanding of the heterogeneous transmission landscape, providing key insights into regional response strategies and public health planning.Significance StatementThe growing recognition of genome sequencing as critical for outbreak response has led to a rapid increase in the availability of sequence data. In this context, we put forward an analytical workflow within the Bayesian phylodynamic framework to identify and trace imported SARS-CoV-2 clusters using large-scale genome datasets. By utilizing metrics such as the Source-Sink Score, Local Import Score, and Persistent Time, our approach characterizes transmission patterns in each subregion and elucidates transmission heterogeneity. As new variants continue to emerge, the insights provided by our analysis are crucial for addressing the challenges of current and future pandemics effectively.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Tracing SARS-CoV-2 Clusters Across Local-scales Using Genomic Data Abstract: Understanding local-scale transmission dynamics of SARS-CoV-2 is crucial for planning effective prevention strategies. This study analyzed over 26,000 genomes and their associated metadata collected between January and October 2021 to explore the introduction and dispersal patterns of SARS-CoV-2 in Greater Houston, a major metropolitan area noted for its demographic diversity. We identified more than a thousand independent introduction events, resulting in clusters of varying sizes, with earlier clusters presenting larger sizes and posing greater control challenges. Characterization of the sources of these introductions showed that domestic origins were more significant than international ones. Further examination of locally circulating clusters across different subregions of Greater Houston revealed varied transmission dynamics. Notably, subregions that served as primary viral sources sustained the local epidemic effectively, evidenced by: (1) a smaller proportion of new cases driven by external viral importations, and (2) longer persistence times of circulating lineages. Overall, our high-resolution spatiotemporal reconstruction of the epidemic in Greater Houston enhances understanding of the heterogeneous transmission landscape, providing key insights into regional response strategies and public health planning.Significance StatementThe growing recognition of genome sequencing as critical for outbreak response has led to a rapid increase in the availability of sequence data. In this context, we put forward an analytical workflow within the Bayesian phylodynamic framework to identify and trace imported SARS-CoV-2 clusters using large-scale genome datasets. By utilizing metrics such as the Source-Sink Score, Local Import Score, and Persistent Time, our approach characterizes transmission patterns in each subregion and elucidates transmission heterogeneity. As new variants continue to emerge, the insights provided by our analysis are crucial for addressing the challenges of current and future pandemics effectively.","summary":"The study analyzed genomic data from over 26,000 genomes collected between January and October 2021 to understand local-scale transmission dynamics of SARS-CoV-2 in Greater Houston. We identified more than a thousand independent introduction events resulting in clusters of varying sizes, with earlier clusters posing greater control challenges, and found that domestic origins were more significant than international introductions."}
{"source":"medRxiv","subject":"infectious_diseases","title":"The potential global impact and cost-effectiveness of next-generation influenza vaccines: a modelling analysis","url":"http://medrxiv.org/cgi/content/short/2024.09.19.24313950v1?rss=1","abstract":"BackgroundNext-generation influenza vaccines (NGIVs) are in development and have the potential to achieve greater reductions in influenza burden, with resulting widespread health and economic bene[fi]ts. Understanding the prices at which their market can be sustained and which vaccination strategies may maximise impact and cost-effectiveness, particularly in low- and middle-income countries, can provide a valuable tool for vaccine development and investment decision-making at a national and global level. To address this evidence gap, we projected the health and economic impact of NGIVs in 186 countries and territories.Methods and FindingsWe inferred current influenza transmission parameters from World Health Organization (WHO) FluNet data in regions de[fi]ned by their transmission dynamics, and projected thirty years of influenza epidemics, accounting for demographic changes. Vaccines considered included current seasonal vaccines, vaccines with increased efficacy, duration, and breadth of protection, and universal vaccines, de[fi]ned in line with the WHO Preferred Product Characteristics. We estimated cost-effectiveness of different vaccination scenarios using novel estimates of key health outcomes and costs.NGIVs have the potential to substantially reduce influenza burden: compared to no vaccination, vaccinating 50% of children aged under 18 annually prevented 1.3 (95% uncertainty range (UR): 1.2-1.5) billion infections using current vaccines, 2.6 (95% UR: 2.4-2.9) billion infections using vaccines with improved efficacy or breadth, and 3.0 (95% UR: 2.7-3.3) billion infections using universal vaccines. In many countries, NGIVs were cost-effective at higher prices than typically paid for existing seasonal vaccines. However, cross-subsidy may be necessary for improved vaccines to be cost-effective in lower income countries.This study is limited by the availability of accurate data on influenza incidence and influenza-associated health outcomes and costs. Furthermore, the model involves simplifying assumptions around vaccination coverage and administration, and does not account for societal costs or budget impact of NGIVs. How NGIVs will compare to the vaccine types considered in this model when developed is unknown. We conducted sensitivity analyses to investigate key model parameters.ConclusionsThis study highlights the considerable potential health and economic bene[fi]ts of NGIVs, but also the variation in cost-effectiveness between high-income and low- and middle-income countries. This work provides a framework for long-term global cost-effectiveness evaluations, and contributes to a full value of influenza vaccines assessment to inform recommendations by WHO, providing a pathway to developing NGIVs and rolling them out globally.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: The potential global impact and cost-effectiveness of next-generation influenza vaccines: a modelling analysis Abstract: BackgroundNext-generation influenza vaccines (NGIVs) are in development and have the potential to achieve greater reductions in influenza burden, with resulting widespread health and economic bene[fi]ts. Understanding the prices at which their market can be sustained and which vaccination strategies may maximise impact and cost-effectiveness, particularly in low- and middle-income countries, can provide a valuable tool for vaccine development and investment decision-making at a national and global level. To address this evidence gap, we projected the health and economic impact of NGIVs in 186 countries and territories.Methods and FindingsWe inferred current influenza transmission parameters from World Health Organization (WHO) FluNet data in regions de[fi]ned by their transmission dynamics, and projected thirty years of influenza epidemics, accounting for demographic changes. Vaccines considered included current seasonal vaccines, vaccines with increased efficacy, duration, and breadth of protection, and universal vaccines, de[fi]ned in line with the WHO Preferred Product Characteristics. We estimated cost-effectiveness of different vaccination scenarios using novel estimates of key health outcomes and costs.NGIVs have the potential to substantially reduce influenza burden: compared to no vaccination, vaccinating 50% of children aged under 18 annually prevented 1.3 (95% uncertainty range (UR): 1.2-1.5) billion infections using current vaccines, 2.6 (95% UR: 2.4-2.9) billion infections using vaccines with improved efficacy or breadth, and 3.0 (95% UR: 2.7-3.3) billion infections using universal vaccines. In many countries, NGIVs were cost-effective at higher prices than typically paid for existing seasonal vaccines. However, cross-subsidy may be necessary for improved vaccines to be cost-effective in lower income countries.This study is limited by the availability of accurate data on influenza incidence and influenza-associated health outcomes and costs. Furthermore, the model involves simplifying assumptions around vaccination coverage and administration, and does not account for societal costs or budget impact of NGIVs. How NGIVs will compare to the vaccine types considered in this model when developed is unknown. We conducted sensitivity analyses to investigate key model parameters.ConclusionsThis study highlights the considerable potential health and economic bene[fi]ts of NGIVs, but also the variation in cost-effectiveness between high-income and low- and middle-income countries. This work provides a framework for long-term global cost-effectiveness evaluations, and contributes to a full value of influenza vaccines assessment to inform recommendations by WHO, providing a pathway to developing NGIVs and rolling them out globally.","summary":"NGIVs have the potential to substantially reduce influenza burden: compared to no vaccination, vaccinating 50% of children aged under 18 annually prevented 1.3 (95% uncertainty range (UR): 1.2-1.5) billion infections using current vaccines, 2.6 (95% UR: 2.4-2.9) billion infections using vaccines with improved efficacy or breadth, and 3.0 (95% UR: 2.7-3.3) billion infections using universal vaccines. In many countries, NGIVs were cost-effective at higher prices than typically paid for existing seasonal vaccines, but cross-subsidy may be necessary to make them affordable in lower income countries."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Humoral Immune Responses in German Dialysis Patients after mRNA Omicron JN.1 Vaccination","url":"http://medrxiv.org/cgi/content/short/2024.09.17.24313789v1?rss=1","abstract":"To assess the effect of the updated mRNA JN.1 omicron vaccine (bretovameran, BioNTech/Pfizer, Mainz, Germany) in an immunocompromised and elderly population, we measured humoral immune responses after mRNA omicron JN.1 vaccination in 37 haemodialysis patients before and 21 days after vaccination.We observed a 3-fold change in anti-S IgG, and a 4{middle dot}7-fold change in anti-S omicron IgG. Memory B cells (MBC) exclusively binding the receptor binding domain (RBD) of JN.1 displayed a median frequency of 0{middle dot}11% before vaccination and changed significantly 3{middle dot}9-fold to a median of 0{middle dot}43%. Cross reactive JN.1 RBD and Wuhan-Hu-1 S-binding MBCs and MBCs only binding to Wuhan-Hu-1 S changed 2{middle dot}3-fold and 1{middle dot}8-fold, respectively. Using a vesicular stomatitis virus-based pseudovirus particle (pp) neutralisation assay, baseline response rates were 86% for XBB.1.5pp, 78% for JN.1pp, 73% for and KP.2pp, 65% for KP.2.3pp and KP.3pp, and 68% for LB.1pp. After vaccination, the response rates for all pseudoviruses increased significantly, and we observed a mean increase in neutralisation of XBB.1.5pp, JN.1pp, KP.2pp, KP.2.3pp, KP.3pp, and LB.1pp of 8{middle dot}3-fold, 18{middle dot}7-fold, 22{middle dot}5-fold, 18{middle dot}7-fold, 25{middle dot}5-fold, and 23{middle dot}5-fold, respectively. In summary, our report provides first evidence for a firm humoral immune response in dialysis patients after mRNA omicron JN.1 vaccination.Our data suggest that the vaccine could be highly effective at enhancing protection of vulnerable populations against evolving SARS-CoV-2 variants.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Humoral Immune Responses in German Dialysis Patients after mRNA Omicron JN.1 Vaccination Abstract: To assess the effect of the updated mRNA JN.1 omicron vaccine (bretovameran, BioNTech/Pfizer, Mainz, Germany) in an immunocompromised and elderly population, we measured humoral immune responses after mRNA omicron JN.1 vaccination in 37 haemodialysis patients before and 21 days after vaccination.We observed a 3-fold change in anti-S IgG, and a 4{middle dot}7-fold change in anti-S omicron IgG. Memory B cells (MBC) exclusively binding the receptor binding domain (RBD) of JN.1 displayed a median frequency of 0{middle dot}11% before vaccination and changed significantly 3{middle dot}9-fold to a median of 0{middle dot}43%. Cross reactive JN.1 RBD and Wuhan-Hu-1 S-binding MBCs and MBCs only binding to Wuhan-Hu-1 S changed 2{middle dot}3-fold and 1{middle dot}8-fold, respectively. Using a vesicular stomatitis virus-based pseudovirus particle (pp) neutralisation assay, baseline response rates were 86% for XBB.1.5pp, 78% for JN.1pp, 73% for and KP.2pp, 65% for KP.2.3pp and KP.3pp, and 68% for LB.1pp. After vaccination, the response rates for all pseudoviruses increased significantly, and we observed a mean increase in neutralisation of XBB.1.5pp, JN.1pp, KP.2pp, KP.2.3pp, KP.3pp, and LB.1pp of 8{middle dot}3-fold, 18{middle dot}7-fold, 22{middle dot}5-fold, 18{middle dot}7-fold, 25{middle dot}5-fold, and 23{middle dot}5-fold, respectively. In summary, our report provides first evidence for a firm humoral immune response in dialysis patients after mRNA omicron JN.1 vaccination.Our data suggest that the vaccine could be highly effective at enhancing protection of vulnerable populations against evolving SARS-CoV-2 variants.","summary":"Humoral immune responses were observed in 37 haemodialysis patients before and 21 days after mRNA omicron JN.1 vaccination, with a 3-fold change in anti-S IgG and a 4.7-fold change in anti-S omicron IgG levels. Memory B cells binding the receptor binding domain of JN.1 showed a significant increase from a median frequency of 0.11% before vaccination to 0.43% after vaccination, with cross-reactive responses also observed against Wuhan-Hu-1 S-binding MBCs and MBCs only binding to Wuhan-Hu-1 S."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Mapping and sequencing of cases from an ongoing outbreak of Clade Ib monkeypox virus in South Kivu, Eastern Democratic Republic of the Congo between September 2023 to June 2024","url":"http://medrxiv.org/cgi/content/short/2024.09.18.24313835v1?rss=1","abstract":"BackgroundIn September 2023, an mpox outbreak was reported in the eastern part, South Kivu Province, of Democratic Republic of the Congo. This outbreak is still ongoing and expanding to other regions and countries. Here, we describe the epidemiological and genomic evolution of the outbreak from September 2023 to June 2024.MethodsConsenting patients with mpox-like symptoms admitted to the Kamituga and the Kamanyola hospitals were recruited to the study. Samples from throat, lesions, breast milk and placenta were collected for PCR testing and sequencing. For the patients from Kamituga hospital, data on place of residence and possible exposures were collected by interviews. The location and numbers of employees were collected for all bars with sex workers. Where possible, exposures were linked to the genomic sequencing data for cluster analysis.FindingsIn total, 670 (suspected) mpox cases were admitted to the Kamituga hospital. There were slightly more female than male cases (351/670 [52,4%] versus 319/670, [47,6%], and cases were reported from 17 different health areas. The majority of cases were reported in Mero (205/670 [30,6%]), followed by Kimbangu (115/670 [17,2%]), Kabukungu (105/670 [16,7%]), and Asuku (73/670 [10.9%]). During this period, 7 deaths occurred and 8 out of 14 women who were pregnant had fetal loss. Three healthcare workers acquired mpox infection when caring for patients. In depth case ascertainment showed that 83,4% of patients reported recent visits to bars for (professional) sexual interactions as a likely source of infection. Whole genome sequencing resulted in the generation of 58 genome sequences. Three main clusters characterized by specific mutations were identified and several miniclusters of 2 or more sequences with over two shared mutations. No clear link between sequence cluster, bar or health area was observed. The more recent sequences from Kamanyola were related to the sequences in Kamituga and confirmed to be Clade Ib. However, relatively long branches were observed and one of the sequences clustered with publicly released sequences from travelers in Kenya, Uganda, Sweden and Thailand, indicating more undocumented ongoing spread for cluster A than for the other clusters. Most observed mutations were APOBEC-3 related mutations indicative of ongoing human-to-human transmission.InterpretationThese data suggests that the rapid transmission of monkeypox virus until June 2024 was mostly related to interactions with professional sex workers (PSW) within densely populated health areas. The expanding number of cases and the recent expansion to 29 other nearby health zones of South -Kivu as well as Rwanda, Burundi, Uganda and Kenya stresses the need for cross border surveillance and collaboration. Urgent enhanced response action is needed, including case finding, diagnostic capacity building, health education programmes focussing on sex workers, and possibly vaccination to limit further escalation and stop this outbreak.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Mapping and sequencing of cases from an ongoing outbreak of Clade Ib monkeypox virus in South Kivu, Eastern Democratic Republic of the Congo between September 2023 to June 2024 Abstract: BackgroundIn September 2023, an mpox outbreak was reported in the eastern part, South Kivu Province, of Democratic Republic of the Congo. This outbreak is still ongoing and expanding to other regions and countries. Here, we describe the epidemiological and genomic evolution of the outbreak from September 2023 to June 2024.MethodsConsenting patients with mpox-like symptoms admitted to the Kamituga and the Kamanyola hospitals were recruited to the study. Samples from throat, lesions, breast milk and placenta were collected for PCR testing and sequencing. For the patients from Kamituga hospital, data on place of residence and possible exposures were collected by interviews. The location and numbers of employees were collected for all bars with sex workers. Where possible, exposures were linked to the genomic sequencing data for cluster analysis.FindingsIn total, 670 (suspected) mpox cases were admitted to the Kamituga hospital. There were slightly more female than male cases (351/670 [52,4%] versus 319/670, [47,6%], and cases were reported from 17 different health areas. The majority of cases were reported in Mero (205/670 [30,6%]), followed by Kimbangu (115/670 [17,2%]), Kabukungu (105/670 [16,7%]), and Asuku (73/670 [10.9%]). During this period, 7 deaths occurred and 8 out of 14 women who were pregnant had fetal loss. Three healthcare workers acquired mpox infection when caring for patients. In depth case ascertainment showed that 83,4% of patients reported recent visits to bars for (professional) sexual interactions as a likely source of infection. Whole genome sequencing resulted in the generation of 58 genome sequences. Three main clusters characterized by specific mutations were identified and several miniclusters of 2 or more sequences with over two shared mutations. No clear link between sequence cluster, bar or health area was observed. The more recent sequences from Kamanyola were related to the sequences in Kamituga and confirmed to be Clade Ib. However, relatively long branches were observed and one of the sequences clustered with publicly released sequences from travelers in Kenya, Uganda, Sweden and Thailand, indicating more undocumented ongoing spread for cluster A than for the other clusters. Most observed mutations were APOBEC-3 related mutations indicative of ongoing human-to-human transmission.InterpretationThese data suggests that the rapid transmission of monkeypox virus until June 2024 was mostly related to interactions with professional sex workers (PSW) within densely populated health areas. The expanding number of cases and the recent expansion to 29 other nearby health zones of South -Kivu as well as Rwanda, Burundi, Uganda and Kenya stresses the need for cross border surveillance and collaboration. Urgent enhanced response action is needed, including case finding, diagnostic capacity building, health education programmes focussing on sex workers, and possibly vaccination to limit further escalation and stop this outbreak.","summary":"The study analyzed 670 suspected mpox cases from September 2023 to June 2024 in South Kivu Province, Democratic Republic of the Congo, with a majority of female cases reported from various health areas, including Mero, Kimbangu, Kabukungu, and Asuku. The majority of patients (83.4%) reported recent visits to bars for professional sex interactions as a likely source of infection, and whole genome sequencing identified three main clusters characterized by specific mutations indicative of ongoing human-to-human transmission."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Effectiveness of Ghanas COVID-19 policy responses and lessons learnt for the future: A multi-methods evaluation","url":"http://medrxiv.org/cgi/content/short/2024.09.16.24313785v1?rss=1","abstract":"Ghana implemented various mitigating policies in response to the COVID-19 outbreak. This study examined the effectiveness of these policies to contribute to the ongoing discussions on proactive and pre-emptive interventions for similar future outbreaks.A mix of qualitative and quantitative methods were used for the analysis. Data were drawn from multiple sources, including peer-reviewed and grey literature, and academic experts from Ghanaian universities. The data from the literature informed a questionnaire that was sent to independent academic experts to explore their opinions on whether the policies met their intended objectives. The experts opinions were collected on a 5-point Likert scale and from an open-ended question using an online data collection platform, Qualtrics. The data were evaluated using narrative synthesis, descriptive statistics and thematic analysis.We identified and evaluated eight key COVID-19 policy responses in Ghana: (1) partial lockdown of epicentres; (2) COVID-19 public awareness campaigns; (3) ban on public gatherings; (4) COVID-19 vaccination; (5) border closures; (6) entry border COVID-19 screening; (7) incentives for healthcare workers (HCWs); and (8) the Ghana Alleviation and Revitalisation of Enterprises Support (GCARES). Two policies - the COVID-19 awareness campaigns and border closure - effectively improved public awareness of COVID-19 and helped to reduce COVID-19 case importation (median score [&ge;]4).Ghanas COVID-19 public awareness campaigns and border closure policies could serve as a valuable model for informing proactive interventions to address future infectious disease outbreaks.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Effectiveness of Ghanas COVID-19 policy responses and lessons learnt for the future: A multi-methods evaluation Abstract: Ghana implemented various mitigating policies in response to the COVID-19 outbreak. This study examined the effectiveness of these policies to contribute to the ongoing discussions on proactive and pre-emptive interventions for similar future outbreaks.A mix of qualitative and quantitative methods were used for the analysis. Data were drawn from multiple sources, including peer-reviewed and grey literature, and academic experts from Ghanaian universities. The data from the literature informed a questionnaire that was sent to independent academic experts to explore their opinions on whether the policies met their intended objectives. The experts opinions were collected on a 5-point Likert scale and from an open-ended question using an online data collection platform, Qualtrics. The data were evaluated using narrative synthesis, descriptive statistics and thematic analysis.We identified and evaluated eight key COVID-19 policy responses in Ghana: (1) partial lockdown of epicentres; (2) COVID-19 public awareness campaigns; (3) ban on public gatherings; (4) COVID-19 vaccination; (5) border closures; (6) entry border COVID-19 screening; (7) incentives for healthcare workers (HCWs); and (8) the Ghana Alleviation and Revitalisation of Enterprises Support (GCARES). Two policies - the COVID-19 awareness campaigns and border closure - effectively improved public awareness of COVID-19 and helped to reduce COVID-19 case importation (median score [&ge;]4).Ghanas COVID-19 public awareness campaigns and border closure policies could serve as a valuable model for informing proactive interventions to address future infectious disease outbreaks.","summary":"The study evaluated the effectiveness of eight COVID-19 policy responses implemented by Ghana, using a mix of qualitative and quantitative methods. Two policies, COVID-19 public awareness campaigns and border closures, were found to be particularly effective in improving public awareness of COVID-19 and reducing case importation, with median scores above 4."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Genomic recombination of rapidly evolving mpox Ib strains compounds the challenges of the 2024 outbreak","url":"http://medrxiv.org/cgi/content/short/2024.09.18.24313912v1?rss=1","abstract":"The World Health Organization recently declared the 2024 mpox virus (MPXV Ib) outbreak a public health emergency of international concern. We report that in 2023-2024, MPXV clade Ib genomes are diverging at a faster rate than clade IIb (2022), primarily due to an unusually high incidence of recombination. Phylogenetic analysis revealed that Ib strains have diverged into four lineages, and they have evolved into 14 subgroups based on nine tandem repeat (TR) polymorphisms. These findings confirms that TRs in MPXV Ib are mutating at a significantly higher frequency compared to the 2022 outbreak (clade IIb, 11 subgroups). Linkage disequilibrium analysis also identified 10 recombination clusters among all 4 lineages, with recombination incidence in Ib being twice as high as in IIb. This suggests that a higher rate of superinfection is contributing to ongoing recombination among populations infected with clade Ib. Prompt action is necessary to prevent the emergence of more lethal mpox strains.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Genomic recombination of rapidly evolving mpox Ib strains compounds the challenges of the 2024 outbreak Abstract: The World Health Organization recently declared the 2024 mpox virus (MPXV Ib) outbreak a public health emergency of international concern. We report that in 2023-2024, MPXV clade Ib genomes are diverging at a faster rate than clade IIb (2022), primarily due to an unusually high incidence of recombination. Phylogenetic analysis revealed that Ib strains have diverged into four lineages, and they have evolved into 14 subgroups based on nine tandem repeat (TR) polymorphisms. These findings confirms that TRs in MPXV Ib are mutating at a significantly higher frequency compared to the 2022 outbreak (clade IIb, 11 subgroups). Linkage disequilibrium analysis also identified 10 recombination clusters among all 4 lineages, with recombination incidence in Ib being twice as high as in IIb. This suggests that a higher rate of superinfection is contributing to ongoing recombination among populations infected with clade Ib. Prompt action is necessary to prevent the emergence of more lethal mpox strains.","summary":"MPXV clade Ib genomes are diverging at a faster rate than clade IIb due to an unusually high incidence of recombination, primarily caused by rapid mutation of tandem repeat (TR) polymorphisms in 14 subgroups identified across four lineages of the virus. The higher rate of recombination among populations infected with clade Ib is contributing to ongoing superinfection and emergence of more lethal mpox strains, prompting urgent action from public health authorities."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Overview and evaluation of a nationwide hospital-based surveillance system for Influenza and COVID-19 in Switzerland (CH-SUR): 2018-2023","url":"http://medrxiv.org/cgi/content/short/2024.09.18.24313869v1?rss=1","abstract":"BackgroundIn 2018, a hospital-based surveillance system for influenza (CH-SUR) was established in six tertiary care hospitals in Switzerland. From March 2020 onwards, this surveillance system was expanded to include more institutions, as well as COVID-19.AimTo evaluate quantitatively and qualitatively the surveillance system CH-SUR.MethodsAll patients admitted to one of the participating centres for more than 24 hours and who had a laboratory-confirmed influenza virus or SARS-CoV-2 infection were included in CH-SUR. For all cases, we evaluated the quality of the CH-SUR data, including timeliness and completeness of reporting. A qualitative survey among CH-SUR stakeholders assessed perceived importance, understanding, reliability and adaptability of CH-SUR.ResultsUp to 20 centres participated in CH-SUR. Between December 2018 and October 2023, 7,375 cases of influenza were reported and between March 2020 and October 2023, 49,235 cases of COVID-19 were reported to CH-SUR. During the COVID-19 pandemic, time to data entry and completeness improved over time; the median delay of data entry in CH-SUR was 5 days (IQR=2-23) for COVID-19 and 4 days (IQR=2-15) for influenza during the period 2018-2023. The completeness of variables was high (99.4%), with the exception of COVID-19 or annual influenza vaccination status (respectively 15% and 72% of \"Unknown\" responses). Stakeholders perceived the system as important, relevant, understandable and adaptable.ConclusionCH-SUR has provided critical epidemiological and clinical information on hospitalised influenza and COVID-19 cases across Switzerland during the pandemic. Our evaluation highlighted the importance and relevance of this system among CH-SUR stakeholders, as well as its importance for preparedness and response to future infectious disease outbreaks.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Overview and evaluation of a nationwide hospital-based surveillance system for Influenza and COVID-19 in Switzerland (CH-SUR): 2018-2023 Abstract: BackgroundIn 2018, a hospital-based surveillance system for influenza (CH-SUR) was established in six tertiary care hospitals in Switzerland. From March 2020 onwards, this surveillance system was expanded to include more institutions, as well as COVID-19.AimTo evaluate quantitatively and qualitatively the surveillance system CH-SUR.MethodsAll patients admitted to one of the participating centres for more than 24 hours and who had a laboratory-confirmed influenza virus or SARS-CoV-2 infection were included in CH-SUR. For all cases, we evaluated the quality of the CH-SUR data, including timeliness and completeness of reporting. A qualitative survey among CH-SUR stakeholders assessed perceived importance, understanding, reliability and adaptability of CH-SUR.ResultsUp to 20 centres participated in CH-SUR. Between December 2018 and October 2023, 7,375 cases of influenza were reported and between March 2020 and October 2023, 49,235 cases of COVID-19 were reported to CH-SUR. During the COVID-19 pandemic, time to data entry and completeness improved over time; the median delay of data entry in CH-SUR was 5 days (IQR=2-23) for COVID-19 and 4 days (IQR=2-15) for influenza during the period 2018-2023. The completeness of variables was high (99.4%), with the exception of COVID-19 or annual influenza vaccination status (respectively 15% and 72% of \"Unknown\" responses). Stakeholders perceived the system as important, relevant, understandable and adaptable.ConclusionCH-SUR has provided critical epidemiological and clinical information on hospitalised influenza and COVID-19 cases across Switzerland during the pandemic. Our evaluation highlighted the importance and relevance of this system among CH-SUR stakeholders, as well as its importance for preparedness and response to future infectious disease outbreaks.","summary":"The hospital-based surveillance system CH-SUR was established in six tertiary care hospitals in Switzerland in 2018 and expanded to include COVID-19 reporting from March 2020 onwards. Between December 2018 and October 2023, a total of 56,610 cases (7,375 influenza, 49,235 COVID-19) were reported to CH-SUR, with improvements in data entry time and completeness over the study period."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Reactogenicity and immunogenicity against MPXV of the intradermal administration of Modified V Vaccinia Ankara compared to the standard subcutaneous route.","url":"http://medrxiv.org/cgi/content/short/2024.09.17.24313609v1?rss=1","abstract":"The recent resurgence of Mpox in central Africa has been declared again a Public Health Emergency of International Concern (PHEIC) requiring coordinated international responses. Vaccination is a priority to expand protection and enhance control strategies, but the vaccines need exceeds the currently available doses. Intradermal administration of one-fifth of the standard Modified-Vaccinia-Ankara (MVA-BN) dose was temporarily authorized during the 2022 PHEIC. Studies conducted before 2022 provided evidence about the humoral response against the Vaccinia virus (VACV) after vaccination but not against the Mpox virus (MPXV). Moreover, no data are available on the T-cell response elicited by MVA-BN administered subcutaneously or intradermally. Here, we compare the two vaccine administration routes according to reactogenicity and immunogenicity based on data from 943 vaccine recipients during the 2022 vaccination campaign in Rome, Italy. We found that the intradermal route elicited slightly higher titers of MPXV-specific IgG and nAbs than the subcutaneous one. At the same time, no differences in cellular response were detected. MVA-BN was globally well tolerated despite higher reactogenicity for the intradermal than the subcutaneous route, especially for the reactions at the local injection site. The intradermal dose-sparing strategy was proven safe and immunogenic and would make vaccination available to more people.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Reactogenicity and immunogenicity against MPXV of the intradermal administration of Modified V Vaccinia Ankara compared to the standard subcutaneous route. Abstract: The recent resurgence of Mpox in central Africa has been declared again a Public Health Emergency of International Concern (PHEIC) requiring coordinated international responses. Vaccination is a priority to expand protection and enhance control strategies, but the vaccines need exceeds the currently available doses. Intradermal administration of one-fifth of the standard Modified-Vaccinia-Ankara (MVA-BN) dose was temporarily authorized during the 2022 PHEIC. Studies conducted before 2022 provided evidence about the humoral response against the Vaccinia virus (VACV) after vaccination but not against the Mpox virus (MPXV). Moreover, no data are available on the T-cell response elicited by MVA-BN administered subcutaneously or intradermally. Here, we compare the two vaccine administration routes according to reactogenicity and immunogenicity based on data from 943 vaccine recipients during the 2022 vaccination campaign in Rome, Italy. We found that the intradermal route elicited slightly higher titers of MPXV-specific IgG and nAbs than the subcutaneous one. At the same time, no differences in cellular response were detected. MVA-BN was globally well tolerated despite higher reactogenicity for the intradermal than the subcutaneous route, especially for the reactions at the local injection site. The intradermal dose-sparing strategy was proven safe and immunogenic and would make vaccination available to more people.","summary":"Intradermal administration of Modified V Vaccinia Ankara (MVA-BN) elicited higher titers of Mpox virus-specific IgG and neutralizing antibodies (nAbs) compared to the standard subcutaneous route, with no differences detected in cellular response. MVA-BN was generally well-tolerated, but showed slightly higher reactogenicity at the local injection site for the intradermal route than for the subcutaneous route."}
{"source":"medRxiv","subject":"infectious_diseases","title":"A next generation CRISPR diagnostic tool to survey drug resistance in Human African Trypanosomiasis.","url":"http://medrxiv.org/cgi/content/short/2024.09.15.24313552v1?rss=1","abstract":"The WHO aims to eliminate the gambiense form of human African trypanosomiasis (HAT) by 2030. With the decline of reported cases, maintaining efficient epidemiological surveillance is essential, including the emergence of drug-resistant strains. We have developed new highly specific diagnostic tools using Specific High-Sensitivity Reporter Enzymatic UnLOCKing (SHERLOCK) technology for monitoring the presence of drug-resistant genotypes that (1) are already circulating, such as the AQP2/3(814) chimera providing resistance to pentamidine and melarsoprol, or (2) could emerge, such as TbCPSF3 (N232H), associated to acoziborole resistance in lab conditions. The melarsoprol - pentamidineAQP2/3(814) SHERLOCK assay detected RNA from both cultured parasites and field isolated strains from gHAT patients in relapse following treatment. The acoziborole CPSF3(SNV)SHERLOCK assay discriminated between wild-type CPSF3 RNA and CPSF3 with a single A-C mutation that confers resistance to acoziborole in vitro.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: A next generation CRISPR diagnostic tool to survey drug resistance in Human African Trypanosomiasis. Abstract: The WHO aims to eliminate the gambiense form of human African trypanosomiasis (HAT) by 2030. With the decline of reported cases, maintaining efficient epidemiological surveillance is essential, including the emergence of drug-resistant strains. We have developed new highly specific diagnostic tools using Specific High-Sensitivity Reporter Enzymatic UnLOCKing (SHERLOCK) technology for monitoring the presence of drug-resistant genotypes that (1) are already circulating, such as the AQP2/3(814) chimera providing resistance to pentamidine and melarsoprol, or (2) could emerge, such as TbCPSF3 (N232H), associated to acoziborole resistance in lab conditions. The melarsoprol - pentamidineAQP2/3(814) SHERLOCK assay detected RNA from both cultured parasites and field isolated strains from gHAT patients in relapse following treatment. The acoziborole CPSF3(SNV)SHERLOCK assay discriminated between wild-type CPSF3 RNA and CPSF3 with a single A-C mutation that confers resistance to acoziborole in vitro.","summary":"The World Health Organization aims to eliminate the gambiense form of human African trypanosomiasis by 2030, highlighting the need for efficient epidemiological surveillance including monitoring drug-resistant strains. The developed SHERLOCK technology-based diagnostic tools can detect drug-resistant genotypes already circulating or emerging in the disease."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Hospital-onset bacteraemia and fungaemia as a novel automated surveillance indicator: results from four European university hospitals","url":"http://medrxiv.org/cgi/content/short/2024.09.16.24310433v1?rss=1","abstract":"BackgroundConventional manual surveillance of healthcare-associated infections is labour-intensive and therefore often restricted to areas with high-risk patients. Fully automated surveillance of hospital-onset bacteraemia and fungaemia (HOB) may facilitate hospital-wide surveillance.AimTo develop an algorithm and minimal dataset (MDS) required for automated surveillance of HOB and apply it to real-life routine data in four European hospitals.MethodsThrough consensus discussion a HOB definition with MDS suitable for automated surveillance was developed and applied in a retrospective multicentre observational study including all admitted adult patients (2018-2022). HOB was defined as a positive blood culture with a recognised pathogen two or more days after hospital admission. For common commensals, two blood cultures with the same commensal within two days were required. Annual HOB rates were calculated per 1,000 patient days for the hospital and for intensive care units (ICU) and non-ICU.ResultsHOB rates were comparable between the four hospitals (1.0 to 2.2 per 1,000 patient days). HOB rates were substantially higher in ICU than non-ICU across the four hospitals, and HOB with common commensals accounted for 14.8-28.2% of all HOB. HOB rates per 1,000 patient days were rather consistent over time, but were higher in 2020 and 2021. HOB caused by Staphylococcus aureus accounted for 8.4-16.0% of all HOB.ConclusionAutomated HOB surveillance using a common definition was feasible and reproducible across four European hospitals. Future studies should investigate clinical relevance and preventability of HOB, and focus on strategies to make the automated HOB metric an actionable infection control tool.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Hospital-onset bacteraemia and fungaemia as a novel automated surveillance indicator: results from four European university hospitals Abstract: BackgroundConventional manual surveillance of healthcare-associated infections is labour-intensive and therefore often restricted to areas with high-risk patients. Fully automated surveillance of hospital-onset bacteraemia and fungaemia (HOB) may facilitate hospital-wide surveillance.AimTo develop an algorithm and minimal dataset (MDS) required for automated surveillance of HOB and apply it to real-life routine data in four European hospitals.MethodsThrough consensus discussion a HOB definition with MDS suitable for automated surveillance was developed and applied in a retrospective multicentre observational study including all admitted adult patients (2018-2022). HOB was defined as a positive blood culture with a recognised pathogen two or more days after hospital admission. For common commensals, two blood cultures with the same commensal within two days were required. Annual HOB rates were calculated per 1,000 patient days for the hospital and for intensive care units (ICU) and non-ICU.ResultsHOB rates were comparable between the four hospitals (1.0 to 2.2 per 1,000 patient days). HOB rates were substantially higher in ICU than non-ICU across the four hospitals, and HOB with common commensals accounted for 14.8-28.2% of all HOB. HOB rates per 1,000 patient days were rather consistent over time, but were higher in 2020 and 2021. HOB caused by Staphylococcus aureus accounted for 8.4-16.0% of all HOB.ConclusionAutomated HOB surveillance using a common definition was feasible and reproducible across four European hospitals. Future studies should investigate clinical relevance and preventability of HOB, and focus on strategies to make the automated HOB metric an actionable infection control tool.","summary":"Automated surveillance of hospital-onset bacteraemia and fungaemia (HOB) using a developed algorithm and minimal dataset was applied to real-life routine data in four European hospitals. HOB rates were comparable between the hospitals, ranging from 1.0 to 2.2 per 1,000 patient days, with higher rates observed in intensive care units compared to non-ICU areas."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Co-circulating pathogens of humans: A systematic review of mechanistic transmission models","url":"http://medrxiv.org/cgi/content/short/2024.09.16.24313749v1?rss=1","abstract":"Historically, most mathematical models of infectious disease dynamics have focused on a single pathogen, despite the ubiquity of co-circulating pathogens in the real world. We conducted a systematic review of 311 published papers that included a mechanistic, population-level model of co-circulating human pathogens. We identified the types of pathogens represented in this literature, techniques used, and motivations for conducting these studies. We also created a complexity index to quantify the degree to which co-circulating pathogen models diverged from single-pathogen models. We found that the emergence of new pathogens, such as HIV and SARS-CoV-2, precipitated modeling activity of the emerging pathogen with established pathogens. Pathogen characteristics also tended to drive modeling activity; for example, HIV suppresses the immune response, eliciting interesting dynamics when it is modeled with other pathogens. The motivations driving these studies were varied but could be divided into two major categories: exploration of dynamics and evaluation of interventions. Finally, we found that model complexity quickly increases as additional pathogens are added. Future potential avenues of research we identified include investigating the effects of misdiagnosis of clinically similar co-circulating pathogens and characterizing the impacts of one pathogen on public health resources available to curtail the spread of other pathogens.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Co-circulating pathogens of humans: A systematic review of mechanistic transmission models Abstract: Historically, most mathematical models of infectious disease dynamics have focused on a single pathogen, despite the ubiquity of co-circulating pathogens in the real world. We conducted a systematic review of 311 published papers that included a mechanistic, population-level model of co-circulating human pathogens. We identified the types of pathogens represented in this literature, techniques used, and motivations for conducting these studies. We also created a complexity index to quantify the degree to which co-circulating pathogen models diverged from single-pathogen models. We found that the emergence of new pathogens, such as HIV and SARS-CoV-2, precipitated modeling activity of the emerging pathogen with established pathogens. Pathogen characteristics also tended to drive modeling activity; for example, HIV suppresses the immune response, eliciting interesting dynamics when it is modeled with other pathogens. The motivations driving these studies were varied but could be divided into two major categories: exploration of dynamics and evaluation of interventions. Finally, we found that model complexity quickly increases as additional pathogens are added. Future potential avenues of research we identified include investigating the effects of misdiagnosis of clinically similar co-circulating pathogens and characterizing the impacts of one pathogen on public health resources available to curtail the spread of other pathogens.","summary":"The review analyzed 311 papers with mechanistic models of co-circulating human pathogens, identifying common types of pathogens, modeling techniques, and motivations for these studies. The complexity index revealed that model complexity increases rapidly as additional pathogens are added, suggesting a need to balance detail against tractability in modeling co-circulating disease dynamics."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Integration of Group A Streptococcus Rapid Tests with the Open Fluidic CandyCollect Device","url":"http://medrxiv.org/cgi/content/short/2024.09.16.24312510v1?rss=1","abstract":"The CandyCollect device is a lollipop-inspired open fluidic oral sampling device designed to provide a comfortable user sampling experience. We demonstrate that the CandyCollect device can be coupled with a rapid antigen detection test (RADT) kit designed for Group A Streptococcus (GAS). Through in vitro experiments with pooled saliva spiked with Streptococcus pyogenes we tested various reagents and elution volumes to optimize the RADT readout from CandyCollect device samples. The resulting optimized protocol uses the kit-provided reagents and lateral flow assay (LFA) while replacing the kits pharyngeal swab with the CandyCollect device, reducing the elution solution volume, and substituting the tube used for elution to accommodate the CandyCollect device. Positive test results were detected by eye with bacterial concentrations as low as the manufacturers \"minimal detection limit\" - 1.5x105 CFU/mL. LFA strips were also scanned and quantified with image analysis software to determine the signal-to-baseline ratio (SBR) and categorize positive test results without human bias. We tested our optimized protocol for integrating CandyCollect and RADT using CandyCollect clinical samples from pediatric patients (n=6) who were previously diagnosed with GAS pharyngitis via pharyngeal swabs tested with RADT as part of their clinical care. The LFA results of these CandyCollect devices and interspersed negative controls were determined by independent observers, with positive results obtained in four of the six participants on at least one LFA replicate. Taken together, our results show that CandyCollect devices from children with GAS pharyngitis can be tested using LFA rapid tests.Table of Contents/Abstract Figure","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Integration of Group A Streptococcus Rapid Tests with the Open Fluidic CandyCollect Device Abstract: The CandyCollect device is a lollipop-inspired open fluidic oral sampling device designed to provide a comfortable user sampling experience. We demonstrate that the CandyCollect device can be coupled with a rapid antigen detection test (RADT) kit designed for Group A Streptococcus (GAS). Through in vitro experiments with pooled saliva spiked with Streptococcus pyogenes we tested various reagents and elution volumes to optimize the RADT readout from CandyCollect device samples. The resulting optimized protocol uses the kit-provided reagents and lateral flow assay (LFA) while replacing the kits pharyngeal swab with the CandyCollect device, reducing the elution solution volume, and substituting the tube used for elution to accommodate the CandyCollect device. Positive test results were detected by eye with bacterial concentrations as low as the manufacturers \"minimal detection limit\" - 1.5x105 CFU/mL. LFA strips were also scanned and quantified with image analysis software to determine the signal-to-baseline ratio (SBR) and categorize positive test results without human bias. We tested our optimized protocol for integrating CandyCollect and RADT using CandyCollect clinical samples from pediatric patients (n=6) who were previously diagnosed with GAS pharyngitis via pharyngeal swabs tested with RADT as part of their clinical care. The LFA results of these CandyCollect devices and interspersed negative controls were determined by independent observers, with positive results obtained in four of the six participants on at least one LFA replicate. Taken together, our results show that CandyCollect devices from children with GAS pharyngitis can be tested using LFA rapid tests.Table of Contents/Abstract Figure","summary":"The study demonstrates the integration of a Group A Streptococcus rapid test (RADT) kit with the Open Fluidic CandyCollect device. The optimized protocol uses the RADT kit's reagents and lateral flow assay to detect GAS in saliva samples from patients, reducing elution solution volume and substituting traditional pharyngeal swabs for the device."}
{"source":"medRxiv","subject":"infectious_diseases","title":"Deep Learning Models for Predicting the Nugent Score to Diagnose Bacterial Vaginosis","url":"http://medrxiv.org/cgi/content/short/2024.09.16.24313614v1?rss=1","abstract":"The Nugent score is a commonly used tool for diagnosing bacterial vaginosis; however, its accuracy depends on the skills of laboratory technicians. We aimed to evaluate the performance of deep learning models in predicting the Nugent score, with the goal of improving diagnostic consistency and accuracy. A total of 1,510 vaginal images collected from a hospital in Japan between 2021 and 2023 were assessed. Each image was annotated by laboratory technicians into one of four categories based on the Nugent score--normal vaginal flora, absence of vaginal flora, altered vaginal flora, or bacterial vaginosis. Deep learning models were developed to predict these categories, and their performance was evaluated by comparing the predicted scores with technician annotations. A high magnification model was further optimized and evaluated using an independent test set of 106 images to assess its performance relative to that of the technicians. The deep learning models demonstrated an accuracy of 84% at low magnification and 89% at high magnification in predicting the Nugent score categories. After optimization, the high magnification model achieved 94% accuracy, surpassing the average 92% accuracy of the technicians. The agreement between deep learning model predictions and technician annotations was 92% for normal vaginal flora, 100% for absence of vaginal flora, 91% for altered vaginal flora, and 100% for bacterial vaginosis. The deep learning models demonstrated accuracy comparable to that of laboratory technicians, which indicates their potential utility in improving the diagnostic accuracy of bacterial vaginosis.IMPORTANCEBacterial vaginosis is a global health issue affecting women, causing symptoms such as abnormal vaginal discharge and discomfort. The Nugent score is the standard method for diagnosing bacterial vaginosis and is based on manual interpretation of Gram-stained vaginal smears. However, this method relies on the skill and experience of trained professionals, leading to variability in results and challenges in facilities with limited access to such experts. This poses significant challenges for settings with limited access to experienced technicians. The deep learning models developed in this study predict the Nugent score with high accuracy; thus, they can be used to standardize the diagnosis of bacterial vaginosis, reduce observer variability, and enable reliable diagnosis even in settings without experienced personnel. Although larger scale validation is needed, our results suggest that deep learning models may represent a new approach for the diagnosis of bacterial vaginosis.","prompt":"I am giving you a paper's title and abstract. Summarize the paper in as many sentences as I instruct. Do not include any preamble text to the summary just give me the summary with no preface or intro sentence. Number of sentences in summary: 2 Title: Deep Learning Models for Predicting the Nugent Score to Diagnose Bacterial Vaginosis Abstract: The Nugent score is a commonly used tool for diagnosing bacterial vaginosis; however, its accuracy depends on the skills of laboratory technicians. We aimed to evaluate the performance of deep learning models in predicting the Nugent score, with the goal of improving diagnostic consistency and accuracy. A total of 1,510 vaginal images collected from a hospital in Japan between 2021 and 2023 were assessed. Each image was annotated by laboratory technicians into one of four categories based on the Nugent score--normal vaginal flora, absence of vaginal flora, altered vaginal flora, or bacterial vaginosis. Deep learning models were developed to predict these categories, and their performance was evaluated by comparing the predicted scores with technician annotations. A high magnification model was further optimized and evaluated using an independent test set of 106 images to assess its performance relative to that of the technicians. The deep learning models demonstrated an accuracy of 84% at low magnification and 89% at high magnification in predicting the Nugent score categories. After optimization, the high magnification model achieved 94% accuracy, surpassing the average 92% accuracy of the technicians. The agreement between deep learning model predictions and technician annotations was 92% for normal vaginal flora, 100% for absence of vaginal flora, 91% for altered vaginal flora, and 100% for bacterial vaginosis. The deep learning models demonstrated accuracy comparable to that of laboratory technicians, which indicates their potential utility in improving the diagnostic accuracy of bacterial vaginosis.IMPORTANCEBacterial vaginosis is a global health issue affecting women, causing symptoms such as abnormal vaginal discharge and discomfort. The Nugent score is the standard method for diagnosing bacterial vaginosis and is based on manual interpretation of Gram-stained vaginal smears. However, this method relies on the skill and experience of trained professionals, leading to variability in results and challenges in facilities with limited access to such experts. This poses significant challenges for settings with limited access to experienced technicians. The deep learning models developed in this study predict the Nugent score with high accuracy; thus, they can be used to standardize the diagnosis of bacterial vaginosis, reduce observer variability, and enable reliable diagnosis even in settings without experienced personnel. Although larger scale validation is needed, our results suggest that deep learning models may represent a new approach for the diagnosis of bacterial vaginosis.","summary":"Deep learning models were developed to predict the Nugent score categories from vaginal images, with high magnification models achieving accuracy comparable to that of laboratory technicians in 94% and 92% cases respectively. The models demonstrated high accuracy rates across all categories, surpassing the average 92% accuracy of the technicians, indicating their potential utility in improving diagnostic accuracy for bacterial vaginosis."}