Infectious Disease

Deep learning unlocks sequence-divergent synthetic promoters to empower Streptomyces natural product engineering.

Streptomyces are renowned for their unparalleled capacity to produce bioactive natural products, making them prime candidates for industrial antibiotic manufacturing. However, Streptomyces lags behind E. coli and yeast in genetic tool development, as its promoters often constrained by narrow strength ranges, poor availability, and minimal diversity, hindering advanced synthetic biology application...

Machine learning models for predicting metabolic syndrome to support clinical decision-making in ART-treated adults living with HIV.

BACKGROUND: Metabolic syndrome (MetS) is an emerging complication among people living with HIV (PLHIV) receiving long-term antiretroviral therapy (ART), particularly with protease and integrase inhibitor regimens. Early identification of high-risk individuals remains challenging, and predictive tools are limited in African settings. This study evaluated nine machine learning (ML) algorithms for pr...

Machine-learning algorithms identifies sTREM1 has a key biomarker for outcome prediction in critically ill.

INTRODUCTION: Prognostic assessment in critically ill patients traditionally relies on severity scores or single biomarkers, each with limited ability...

Machine learning, whole genome sequencing, and Mendelian randomization support a role of CRP on COVID-19 severity.

BACKGROUND: The coronavirus disease 2019 (COVID-19) ranges from asymptomatic to very severe infection and death, largely depending on host factors, in...

The Next Wave of Workplace Bullying in Health Care.

BACKGROUND AND INTRODUCTION: Workplace bullying and incivility have continued to escalate across health care and pose serious risks to workforce well-...

Application of Sparse Autoencoders to Enhance Mechanistic Interpretability of Large Language Models in Medicine.

Large language models (LLMs) are being increasingly incorporated into clinical workflows due to their ability to synthesize medical knowledge and supp...

Predicting antifolate resistance in the unculturable fungal pathogen Pneumocystis jirovecii.

Pneumocystis jirovecii is an opportunistic fungal pathogen responsible for Pneumocystis pneumonia (PCP) in immunocompromised patients. Antifolate drug...

AI-Enhanced High-Precision Segmentation and Perfusion Analysis in Myocardial Contrast Echocardiography.

Myocardial contrast echocardiography (MCE) facilitates the quantification of myocardial perfusion and aids in diagnosing coronary artery disease (CAD)...

Usability and Usefulness of Machine Learning-Based Clinical Decision Support Software in Primary Care: Survey of Users in a Prospective Observational Study.

BACKGROUND: The successful implementation of decision support systems promises to enhance high-quality care. However, the successful implementation of...

Gut microbiome composition and functional potential associate with incident type 2 diabetes in 4,685 adults from a Swedish prospective cohort.

Cross-sectional studies link gut microbiome alterations to type 2 diabetes (T2D), but prospective evidence remains limited. We aim to identify taxonom...

Stage-Associated Subgingival Dysbiosis Across the Periodontal Disease Spectrum in a Thai Cohort.

AIMS: This cross-sectional study aimed to investigate the subgingival microbiota and predict functional profiles across the 2018 EFP/AAP periodontal d...

A deep mutational scanning-informed protein language model predicts SARS-CoV-2 evolution dynamics with spatiotemporal resolution.

Early identification of emerging dominant variants of pathogens such as SARS-CoV-2 is important for effective public health responses, yet existing ap...

Advancing poultry health: A meta-analysis of epitope-based and peptide-based vaccines against Avian Pathogenic E. coli with machine learning insights.

INTRODUCTION: Avian Pathogenic Escherichia coli (APEC) causes colibacillosis in poultry, which leads to tremendous economic losses. Traditional contro...

Environmental drivers of high-risk antibiotic resistance genes propagation in the plastisphere unveiled by meta-analysis and interpretable machine learning.

The plastisphere serves as an expanding reservoir and dissemination vector for antibiotic resistance genes (ARGs), yet the environmental driving facto...

Predictive modeling and network analysis uncover novel regulators of multi-stress tolerance in Saccharomyces cerevisiae.

BACKGROUND: Understanding molecular responses to multi-stress conditions in Saccharomyces cerevisiae is crucial for optimizing industrial strains and ...

Multi-dimensional risk prediction and genetic architecture of aspiration pneumonia: a population-based analysis.

BACKGROUND: Aspiration pneumonia represents a significant but understudied cause of morbidity and mortality, particularly among aging populations with...

Vaccination attitudes and intentions reported by Canadian children and their parents in the CHILD Cohort Study during the COVID-19 pandemic.

BACKGROUND: Understanding if and how vaccination attitudes are shared among family members can help inform strategies to increase uptake. We assessed ...

Diagnostic value of integrated albumin-to-leukocyte ratio risk modeling stratification and machine learning approaches for prediction of spontaneous bacterial peritonitis in cirrhotic patients.

BACKGROUND: Spontaneous bacterial peritonitis (SBP) remains a life-threatening complication of liver cirrhosis, requiring accurate and rapid predictio...

High-resolution automated mapping of potential Aedes larval container habitats using drone imagery and supervised machine learning in Dar es Salaam, Tanzania.

Larval source management is a key strategy to control the spread of Aedes-borne viral diseases including dengue, Zika, chikungunya, and yellow fever. ...

Prediction of antimicrobial minimum inhibitory concentration from bacterial genomes using a scalable and interpretable machine learning approach.

Although machine learning models can predict antimicrobial susceptibility from bacterial whole genome sequencing (WGS), state-of-the-art approaches ar...