Infectious Disease

Immunogenic cell death biomarkers for sepsis diagnosis and mechanism via integrated bioinformatics.

Immunogenic cell death (ICD) has been implicated in sepsis, a condition with high mortality, through mechanisms involving endoplasmic reticulum stress and other pathophysiological pathways. This study aimed to identify and validate ICD-related biomarkers for sepsis diagnosis and to elucidate their underlying mechanisms. Publicly available datasets (GSE65682, GSE95233 and GSE69528) and 57 ICD-relat...

Evaluating the usability of an HIV-prevention artificial intelligence chatbot in Malaysia: national observational study.

BACKGROUND: Malaysia, an upper middle-income country in the Asia-Pacific region, has an HIV epidemic that has transitioned from needle sharing to sexual transmission, mainly in MSM. Men who have sex with men (MSM) are the most vulnerable population for HIV in Malaysia. In 2022, our team developed a web-based artificial intelligence (AI) chatbot and tested its feasibility and acceptability among MS...

Discovering the metabolic pathway of liver disease by breath mass spectrometry combined with machine learning.

On account of the low concentration and complex background, most methods for detecting VOCs in exhaled breath samples required preconcentration prior ...

A Deep Neural Network Framework for the Detection of Bacterial Diseases from Chest X-Ray Scans.

AIMS: This research aims to develop an advanced deep-learning framework for detecting respiratory diseases, including COVID-19, pneumonia, and tubercu...

Can ChatGPT Counter Vaccine Hesitancy? An Evaluation of ChatGPT's Responses to Simulated Queries from the General Public.

Vaccines have eradicated deadly diseases, yet vaccine hesitancy persists, leading to reduced uptake. Some individuals, mistrustful of healthcare prov...

Deep learning architectures for influenza dynamics and treatment optimization: a comprehensive review.

As a major worldwide health concern, influenza still requires precise modeling of flu dynamics and efficient treatment approaches. Deep learning archi...

Enhancing liver disease diagnosis with hybrid SMOTE-ENN balanced machine learning models-an empirical analysis of Indian patient liver disease datasets.

INTRODUCTION: The liver is one of the vital organs of human body that performs some of the most crucial biological processes such as protein and bioch...

Optimizing phage therapy with artificial intelligence: a perspective.

Phage therapy is emerging as a promising strategy against the growing threat of antimicrobial resistance, yet phage and bacteria are incredibly divers...

Risk-reward trade-off during carbon starvation generates dichotomy in motility endurance among marine bacteria.

Copiotrophic marine bacteria contribute to the control of carbon storage in the ocean by remineralizing organic matter. Motility presents copiotrophs ...

Leveraging pre-vaccination antibody titres across multiple influenza H3N2 variants to forecast the post-vaccination response.

BACKGROUND: Despite decades of research on the influenza virus, we still lack a predictive understanding of how vaccination reshapes each person's ant...

Robust Self-Healing Polyurethane-Based Solid-State Ion-Conductive Elastomers with Exceptional Strength and Ionic Conductivity for Multifunctional Strain Sensors and Triboelectric Nanogenerators.

Flexible ionic conductors hold potential for wearable sensors and energy harvesting. However, most gel-based conductors suffer from solvent evaporatio...

Multi-Omics Analysis of the virulence factors and designing of next-generation multi-epitopes Vaccines against Rickettsia prowazekii: a computer-aided vaccine designing approach.

Rickettsia is a genus of bacteria that are obligate intracellular parasites and are responsible for the febrile diseases known collectively as Rickett...

In-silico evaluation of Azadirachta indica-derived Daucosterol against key viral proteins of Ebolavirus using ML and MD simulations approach.

Ebola virus disease (EVD) is an acute life-threatening disease caused by highly pathogenic Ebolavirus (EBOV), with reported case fatality rates reachi...

Leveraging Hospital Information Data for Effective Antibiotic Stewardship.

Clinical informatics has emerged as a valuable approach to enhance antimicrobial stewardship programs in healthcare settings. By integrating informati...

Unlocking antimicrobial resistance with multiomics and machine learning.

The global antimicrobial resistance (AMR) emergency is driven by complex and evolving molecular mechanisms. Cutting-edge machine learning methods and ...

Messenger Ribonucleic Acid (mRNA)-Based Universal Vaccines: Engineering Broad-Spectrum Immunity Against Future Pandemics.

The rapid emergence and evolution of infectious pathogens, including the COVID-19 pandemic and recurring influenza outbreaks, underscore the need for ...

An integrative and comprehensive analysis of blood transcriptomes combined with machine learning models reveals key signatures for tuberculosis diagnosis and risk stratification.

Tuberculosis (TB) remains a major global health challenge, contributing substantially to morbidity and mortality worldwide. The progression from (Mtb...

Retrospective cohort study of infection and risk stratification using 6-year UBT data.

BACKGROUND: () infection is a major global health concern, linked to gastric cancer and metabolic disorders. Despite its widespread prevalence, accur...

Deep learning-based framework for Mycobacterium tuberculosis bacterial growth detection for antimicrobial susceptibility testing.

Tuberculosis (TB) kills more people annually than any other pathogen. Resistance is an ever-increasing global problem, not least because diagnostics r...

Analysis of the heterogeneous treatment effect of vasoactive drug dosage and time on hospital mortality across different sepsis phenotypes: a retrospective cohort study.

BACKGROUND: The heterogeneity of sepsis poses challenges for the individualized treatment of vasoactive drugs.