Infectious Disease

Machine learning-guided discovery of spirocyclic inhibitors targeting Mycobacterium tuberculosis FtsZ.

Tuberculosis continues to pose serious threats to global public health and calls for the design of new drugs that can target key bacterial proteins. This research used an integrated approach involving computational techniques to discover new drugs that can inhibit the FtsZ protein of Mycobacterium tuberculosis using the Life Chemicals compound library as a starting point. Sequence analysis reveale...

Efficacy evaluation of artificial intelligence in radiological imaging diagnosis based on randomized controlled trials: a scoping review.

OBJECTIVE: Artificial intelligence (AI) demonstrates significant potential in medical imaging diagnosis, yet its real-world clinical value requires validation through high-quality randomized controlled trials (RCTs). Existing RCTs report heterogeneous results across settings and outcomes, motivating a scoping review to map current evidence and identify gaps. MATERIALS AND METHODS: This scoping rev...

Two faces of drug repurposing data in machine learning-driven structure-based virtual screening supported by interaction fingerprints.

Ensemble docking is a prominent source of protein-ligand complex structures, which could be conveniently analyzed with interaction fingerprints approa...

Explainable machine learning deciphers and quantifies material-microbe-methane pathways in zero-valent iron-enhanced anaerobic digestion.

Zero-valent iron (ZVI) has been widely applied to enhance methane recovery in anaerobic digestion (AD), but how ZVI material properties and operating ...

Compartment-specific host association and mobility shape ARG risk in aquaculture systems.

Antimicrobial resistance in aquaculture threatens environmental and public health, but the risk of ARGs cannot be inferred from abundance alone; host ...

High-accuracy SNV calling for bacterial isolates using deep learning with AccuSNV.

Accurate detection of mutations within bacterial species is critical for fundamental studies of microbial evolution, reconstructing transmission event...

Differentially private federated learning for localized control of infectious disease dynamics.

In times of epidemics, swift reaction is necessary to mitigate epidemic spreading. For this reaction, localized approaches have several advantages, li...

A population-based retrospective machine learning study of COVID-19 severity using integrated clinical and viral genomic data in Jiangsu Province, China.

BACKGROUND: As coronavirus disease 2019 (COVID-19) has transitioned into an endemic phase characterized by sustained transmission and widespread hybri...

Physics-guided framework for climate dependent disease prediction: coupling compartment model with deep learning.

BACKGROUND: Influenza-like illness (ILI) serves as a representative climate dependent disease due to its climate sensitivity, widespread transmission,...

Machine learning prediction of postoperative pulmonary infection in patients who underwent thoracoscopic lung cancer resection: a retrospective case-control study.

BACKGROUND: Accurate identification of patients at high risk of pulmonary infection after thoracoscopic lung cancer resection is important for timely ...

Conserved 3' stem-loop structures enable comprehensive analysis of bacterial transcription termination in metagenomes.

BACKGROUND: Bacterial transcription termination is a critical yet underexplored layer of gene regulation in microbial ecosystems. Existing computation...

Decrypting the allosteric network: multi-scale dynamics of SARS-CoV-2 main protease inhibition by Moringa oleifera flavonoids.

The SARS-CoV-2 main protease (Mpro) is a prototypical enzyme whose activity is governed by long-range allosteric communication within its dynamic stru...

Artificial intelligence and CRISPR-based approaches for targeted delivery of bacteriophages.

The rapid emergence of multidrug-resistant (MDR) bacteria has increased interest in bacteriophage therapy as a promising alternative to conventional a...

Machine learning-based prediction of E. coli infection in hospitalized patients using a no-code analytical framework.

Hospital-acquired infections (HAIs) remain a major global concern, contributing significantly to increased morbidity, mortality, and healthcare costs....

Deep learning & PSO-based optimisation of data centre energy costs using renewable sources.

In this research work, an energy management framework for a data centre powered by a combination of solar and grid energy is proposed. A service-level...

An AI-augmented review of childhood atopic dermatitis biomarkers across genetic, immune, microbial, and metabolic domains.

BACKGROUND: Atopic dermatitis (AD) is a prevalent inflammatory skin disease and a major source of disease burden in children. Biomarker studies in chi...

Sex Hormone Receptors, HBV Integrations and Their Prognostic Predictive Value Among Hepatocellular Carcinoma Patients.

Hepatocellular carcinoma (HCC) related to hepatitis B virus (HBV) infection predominantly affects males, yet few studies have investigated the associa...

Mining negative sequential patterns to improve viral genomic feature representation and classification.

Viruses represent the most abundant biological entities on Earth and play a pivotal role in microbial ecosystems, yet, as prominent human pathogens, t...

Genomic insights into antimicrobial resistance and isolation source classification of Cronobacter sakazakii from infant and toddler food in the United States.

Cronobacter sakazakii is an opportunistic foodborne pathogen associated with severe infections in infants, linked to powdered infant formula (PIF) and...

Rationally engineered essential oil-loaded nanocarriers for acne vulgaris: integrating multiscale molecular modeling, machine learning, and response surface optimization.

BACKGROUND: Acne vulgaris is a prevalent inflammatory dermatosis in which Cutibacterium acnes, Staphylococcus epidermidis, and, to a lesser extent, St...