Infectious Disease

Artificial intelligence for early detection and risk prediction of antimicrobial resistance in aquatic ecosystems.

Aquatic environments are key reservoirs and dissemination pathways of antimicrobial resistance (AMR). However, current water-based surveillance remains fragmented and inefficient for the timely detection of emerging threats. Integrating artificial intelligence with embedded metadata provides a powerful pathway to identify novel antimicrobial resistance genes, characterize resistome profiles, and p...

Lessons learned from bat and rodent reservoir hosts of zoonotic viruses.

Zoonotic virus emergence is a continued threat to global health, though more than two-thirds originate in wildlife. Within natural reservoirs, bats and rodents are host to a remarkable diversity of highly pathogenic viruses, including coronaviruses, filoviruses, hantaviruses, and more. Yet, reservoir hosts rarely develop disease. In bats, functional adaptations related to inflammasome activation, ...

Integrating Molecular Dynamics and Deep Learning to Elucidate Conformational Plasticity Underlying the Reduced Activity of Glycocin F.

The escalating crisis of multidrug-resistant bacteria demands a new generation of antibiotics. Glycocin F (GccF), a potent bacteriocin, is a promising...

Deep Learning-Based Method for Damage Severity Grading of Black Shell Disease in Hong Kong Oyster (Crassostrea hongkongensis) Caused by Polydora Complex.

The Polydora complex is a globally widespread polychaete parasite known for secreting acidic substances to bore tunnels into oyster shells. This proce...

Computational Discovery of MERS-CoV Main Protease Inhibitors Through Screening and Molecular Dynamics Simulations.

Targeting the main protease (Mpro) of coronaviruses has emerged as a promising therapeutic strategy for combating viral infections. Despite the global...

Forecasting Thailand's mobility trends using Feature Engineered XGBoost for pandemic crisis movement management.

The COVID-19 pandemic significantly disrupted global mobility patterns, with widespread population movement playing a key role in the transmission of ...

SGA-DT: An adaptive fusion framework for missing data imputation and interpretable healthcare classification.

Despite advances in machine learning and medical data processing, handling missing values remains a critical and complex challenge in healthcare analy...

Evaluation of large language models in supporting autoimmune liver disease diagnosis and clinical decision-making: advantages of reasoning-based models.

INTRODUCTION: Large-language models (LLMs) have demonstrated increasing potential in healthcare, including applications in clinical information retrie...

Coupling ensemble learning with multi-omics: a novel data-driven strategy for Daqu quality assessment and validation.

Daqu, a fermentation starter for traditional fermented foods, is produced by complex microbial communities; it is generally evaluated using convention...

Atlas of predicted protein complex structures across kingdoms.

Protein complexes are fundamental to all biological processes. Public repositories have expanded to include millions of potential protein-protein inte...

Engineering of CoA-Acylating Butyraldehyde Dehydrogenase for Enhanced 1,3-Butanediol Production in Escherichia coli.

Microbial production of 1,3-butanediol (1,3-BDO) offers a renewable route to this versatile C4 chemical. However, the low performance of CoA-acylating...

Metagenomic profiling and predictive modeling of the gut microbiome reveal signatures of gestational disease.

The gut microbiome plays a vital role in maternal health and pregnancy outcomes, yet its impact on conditions like gestational hypertension (GH) and g...

Machine learning-augmented lateral flow assays for point-of-care infectious disease diagnostics.

Lateral flow assays (LFAs) are among the most widely used point-of-care (PoC) diagnostic platforms for infectious diseases due to their rapid operatio...

Drug repurposing against viral infections (2020-2025): clinical trials, computational strategies, and therapeutic interventions.

Metagenomic analysis of the gut microbiota in Cryptosporidium-infected Tibetan sheep.

Cryptosporidium are important causative parasitic protozoa that cause gastrointestinal discomfort and diarrhea in humans and animals, posing a huge th...

Biotechnology advances and the parasitology paradigm: From genomes to multi-omics and translation.

Parasitic diseases impose a substantial and often underestimated burden on human and animal health, food security and economic development. Over recen...

Optimising pandemic response through vaccination strategies using neural networks.

Epidemic risk assessment poses inherent challenges, with traditional approaches often failing to balance health outcomes and economic constraints. Thi...

Temporal Learning with Dynamic Range (TLDR) for modeling recurrent exposure and treatment outcomes.

The temporal sequence of clinical events is crucial in outcomes research, yet standard machine learning (ML) approaches often overlook this aspect in ...

Enzyme-constrained genome-scale model of Yarrowia lipolytica predicts growth-phase specific metabolic engineering targets.

The oleaginous yeast Yarrowia lipolytica has been gaining increasing importance as an industrial biotech platform, supported by several available meta...

Integrated analysis of the gut mycobiota and plasma metabolome reveals mortality and age-specific characteristics in sepsis.