Infectious Disease

Rethinking aging biomarkers in HIV: from measures to meaning.

PURPOSE OF REVIEW: People with HIV (PWH) on effective antiretroviral therapy continue to experience a disproportionate burden of age-related comorbidities and multimorbidity. This review explores HIV-associated aging as a systems-level dysregulation and loss of resilience and evaluates emerging biomarker strategies for capturing its biological and clinical heterogeneity. RECENT FINDINGS: Recent ev...

Generative AI Chatbots for Global HIV Treatment and Care: A Commentary.

Addressing stigma, mental health, and health care access challenges for people living with HIV requires a multifaceted approach. Generative artificial intelligence (GenAI) chatbots may be one component of this approach. GenAI chatbots can reduce travel costs and save time. They provide opportunities to offer users a discreet alternative to human interaction, helping reduce stigma and improve comfo...

PAN4, an AI-designed host-directed immunomodulatory peptide, promotes PGRP-SC1a-associated intestinal immune homeostasis in Drosophila melanogaster.

We identify PAN4 (GAYTFKIRRK), an AI-designed host-directed immunomodulatory peptide, as a modulator of intestinal immune homeostasis in Drosophila me...

A federated attention-based stacked LSTM framework for interpretable malaria diagnosis under simulated non-IID federated conditions.

Malaria remains a major global health burden, particularly in low-resource regions where microscopic diagnosis relies heavily on expert interpretation...

The future of pediatric gene therapy: CRISPR-Cas9, AI, and personalized medicine.

The future of pediatric gene therapy is being fundamentally reshaped by the convergence of CRISPR-Cas9 genome editing, artificial intelligence (AI), a...

AI-assisted fragment-based drug discovery of SARS-CoV-2 macrodomain binders validated by NMR and X-ray crystallography.

Fragment-based drug discovery (FBDD) is an effective approach for exploring chemical space using small, low-affinity fragments as starting points to f...

Using interpretable machine learning to analyze the trajectory changes of serum albumin to predict the mortality rate of sepsis: a cohort study based on MIMIC-IV.

BACKGROUND: Although hypoalbuminemia at ICU admission is associated with increased in-hospital mortality in septic patients, the prognostic value of s...

A CT-based deep learning model for the automated risk stratification of refractory Mycoplasma pneumoniae pneumonia in children.

BACKGROUND: The accurate identification of children with refractory Mycoplasma pneumoniae pneumonia (RMPP) remains challenging. This study aimed to de...

Detection of malaria infection from parasite-free blood smears.

Malaria affects almost 263 million people worldwide, most of whom live in sub-Saharan countries. In a strategy to reduce malaria-related mortality and...

Artificial intelligence powered decoding of Plasmodium falciparum sporozoite motility patterns.

Sporozoites (SPZ), the infective mosquito stage of Plasmodium falciparum malaria, are widely studied as therapeutic targets for antibodies either endo...

Disentangling factors affecting bacterial transcriptional regulatory network inference.

The rapid growth of bacterial gene expression databases has enabled computational inference of transcriptional regulatory networks (TRNs), yet it rema...

Cancer Vaccine Development: Toward Artificial Intelligence-Assisted Personalized Cell Membrane Nanovaccine.

Cancer vaccines are an attractive immunotherapeutic approach, and numerous clinical trials are ongoing. However, most candidates have not achieved sta...

Leptospira-host interactions: advancing next-generation vaccines and diagnostics.

SUMMARYLeptospirosis, a widespread zoonotic disease caused by pathogenic Leptospira species, remains a major public health challenge, particularly in ...

From sites to structure to serology: a roadmap for structure-aware molecular evolution of antigenically evolving viruses.

The genomic deluge has pushed viral molecular evolution into a site-resolved era. For antigenically evolving viruses such as influenza and severe acut...

The Role of Artificial Intelligence and Machine Learning in Predictive Virology: Forecasting, Tracking, and Combating Viral Threats.

The escalating threat of viral pandemics, dramatically illustrated by the COVID-19 crisis, has exposed the critical shortcomings of conventional react...

Development and internal validation of an interpretable machine learning model using routine laboratory data for systemic sclerosis-associated pulmonary arterial hypertension.

This study aimed to develop and validate an interpretable machine learning (ML) model using routine laboratory data to support clinical decision-makin...

Machine Learning-Augmented Traditional Analysis of Lactate vs Lactate-to-Albumin Ratio for Predicting Mortality Risk in Patients With Sepsis: Large-Scale Retrospective Study.

BACKGROUND: Effective risk stratification in sepsis remains a critical clinical challenge. Serum lactate is a cornerstone biomarker of metabolic dysfu...

Revisiting biofilm quantification: crystal violet assay and the emerging role of hyperspectral imaging.

Bacterial biofilms are major contributors to persistent and chronic infections. Conventional methods used to quantify biofilms, such as the crystal vi...

Physics-Informed LSTM Neural Network for Personalized Pharmacokinetic Modeling of Polymyxin B in Critically Ill Patients.

Polymyxin B represents a critical last-resort antibiotic for carbapenem-resistant Gram-negative infections, yet its narrow therapeutic window and subs...

AlphaGEM enables precise genome-scale metabolic modelling by integrating protein structure alignment with deep-learning-based dark metabolism mining.

Constructing high-quality genome-scale metabolic models (GEMs) for non-model organisms remains challenging. To address this, we developed AlphaGEM, a ...