Infectious Disease

AI Risk Prediction Tools for Autologous Breast Reconstruction.

BACKGROUND: Autologous breast reconstruction offers patients a durable and natural-appearing option after mastectomy. However, complication risks include flap loss, infection, and delayed wound healing. This study developed both traditional statistical and machine learning (ML) models to predict the risk of developing a 90-day postoperative complication after autologous reconstruction. METHODS: Pa...

From sequence space to ecological function: microbiome-derived antimicrobial peptides as community effectors and therapeutic leads.

Antimicrobial peptide research has long centred on host defence molecules, yet microbiomes themselves encode a diverse and increasingly important repertoire of peptide-based antimicrobials. These microbiome-derived antimicrobial peptides include bacteriocins, ribosomally synthesised and post-translationally modified peptides, cryptic short open reading frame-encoded peptides, embedded antimicrobia...

Chemical-Sensing Catheters for Long-Term and Personalized Therapeutic Management.

Long-term intravenous catheterization is vital for delivering chemotherapy to cancer patients and parenteral nutrition to those with intestinal failur...

Evolution of swine influenza surveillance and one health governance in Taiwan: from zoonotic risk management to integrated preparedness.

Influenza A viruses (IAVs) remain a persistent global threat because of rapid antigenic change, frequent genetic reassortment, and cross-species trans...

ALPAR: Automated Learning Pipeline for Antimicrobial Resistance.

SUMMARY: The field of machine learning in antimicrobial resistance (AMR) research has experienced rapid growth, fueled by advancements in high-through...

Multi-omics and artificial intelligence nominate PCLAF as a prognostic and druggable target for hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: PCLAF (PCNA clamp-associated factor) is a protein involved in DNA replication and DNA repair. Aberrant PCLAF expression has been reported ...

VN1K is a pangenome-informed multi-omics and phenomics resource for the Vietnamese population.

The population of Vietnam remains underrepresented in global genomic databases. Here, we present VN1K, a resource of multi-omics and phenotypic inform...

Interpretable prediction of DNA replication origins in S. cerevisiae using DNABERT and DNABERT-2.

BACKGROUND: DNA replication is a biological process in which a single DNA molecule is duplicated, initiating from multiple genomic sites known as repl...

Bacterial heteroresistance mechanisms, dynamics, and emerging diagnostic approaches.

Antibiotic heteroresistance is a form of within-isolate susceptibility heterogeneity in which an apparently susceptible bacterial population contains ...

In silico identification and biophysical characterization of candidate antimicrobial peptides from the Indian marine microbiome targeting multidrug-resistant ESKAPE pathogens.

The global health crisis of antimicrobial resistance necessitates the discovery of new antibacterial agents. Underexplored marine microbiomes, particu...

Multi-omics analysis reveals the aging mechanism during Baobaoqu storage for the production of Wuliangye Baijiu.

The quality of Baobaoqu directly influences the quality of Baijiu. In this study, metatranscriptomics, metaproteomics and metabolomics were utilized, ...

Comparing traditional and AI-enhanced strategies for developing patient decision aids: a multiple case study.

OBJECTIVES: Our objective was to develop and test prompts designed to generate balanced, evidence-based information from artificial intelligence (AI) ...

Hybrid circular-square complementary split-ring resonator sensor for monitoring abnormal blood protein levels for disease diagnosis.

The proposed work aims to develop a compact, low-cost, and commercially viable microwave sensor for early monitoring of high protein content in blood,...

Interpretable Machine Learning Model for Predicting Sepsis and Septic Shock Among Patients with Documented Fever at Emergency Department Triage Using Patients' Historical Data.

This study aimed to develop an interpretable machine learning-based scoring system for predicting sepsis and septic shock among febrile patients at em...

Machine learning-based clinical models for prediction of urinary incontinence after robot-assisted laparoscopic radical prostatectomy.

OBJECTIVE: To investigate risk factors for urinary incontinence (UI) after robot-assisted laparoscopic radical prostatectomy (RARP) using interpretabl...

Evaluating the reliability and information quality of ChatGPT responses on vaccine hesitancy: an expert panel study.

BACKGROUND: Vaccine hesitancy is a major public health problem that threatens global immunisation programmes. The use of artificial intelligence-based...

Environmental and management drivers of gastrointestinal nematodes in shelter dogs across mainland Portugal revealed by ecological niche modelling.

Gastrointestinal nematodes (GIN) are a major health concern in dogs, particularly in high-density environments such as shelters. Toxocara canis, Ancyl...

Predicting the absence of World Health Organization fungal priority pathogens in agricultural soils using machine learning and ITS metabarcoding.

Environmental fungal pathogens relevant to human and animal health pose significant risks, particularly in regions with intensive farming and climate ...

Explainable Machine Learning for Public Health Informatics in HEDIS Childhood Immunization Status Combo 10.

BACKGROUND: HEDIS Childhood Immunization Status (CIS) Combination 10 is a pediatric quality measure within a widely used health care performance frame...

Post COVID-19 condition diagnosis among older people: findings from Swedish national register data.

INTRODUCTION: Post COVID-19 condition (PCC) denotes the persistence of symptoms following Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2)...