Infectious Disease

A genetically encoded local learning rule enables physical learning in engineered bacteria

Training physical neural networks directly in matter remains difficult because most platforms do not implement weight storage and weight update within the same physical substrate. Here we show that engineered Escherichia coli can implement a genetically encoded local learning rule acting on a persistent biological memory. In memregulons, analogue weights are stored as plasmid copy-number ratios in...

BVSIMC: Bayesian Variable Selection-Guided Inductive Matrix Completion for Improved and Interpretable Drug Discovery

Recent advances in drug discovery have demonstrated that incorporating side information (e.g., chemical properties about drugs and genomic information about diseases) often greatly improves prediction performance. However, these side features can vary widely in relevance and are often noisy and high-dimensional. We propose Bayesian Variable Selection-Guided Inductive Matrix Completion (BVSIMC), a ...

LLM-Augmented Computational Phenotyping of Long Covid

Phenotypic characterization is essential for understanding heterogeneity in chronic diseases and for guiding personalized interventions. Long COVID, a...

Sentiment in Clinical Notes: A Predictor for Length of Stay?

Background: Length of stay (LOS) is a critical metric for hospital operational efficiency. While structured clinical data is widely used to predict LO...

kinGEMs: A Robust and Scalable Framework forResource-Constraint Models through StochasticTuning of Deep Learning-Predicted KineticParameters

The construction of accurate enzyme-constrained genome-scale models (ecGEMs) remains a critical challenge in systems biology, limited by sparse kineti...

Predicting Trajectories of Long COVID in Adult Women: The Critical Role of Causal Disentanglement

Early prediction of Post-Acute Sequelae of SARS-CoV-2 severity is a critical challenge for women's health, particularly given the diagnostic overlap b...

Non-perturbative Bacterial Identification Directly from Solid Agar Plates Using Raman

Raman spectroscopy is a promising tool for microbial identification, yet its implementation in microbiology and clinical workflow is still restricted ...

Integrated Artificial Intelligence and Quantum Chemistry Approach for the Rational Design of Novel Antibacterial Agents against Ralstonia solanacearum.

Antimicrobial resistance (AMR) in plant pathogenic bacteria poses a serious threat to global agriculture, necessitating the development of novel antib...

Automated identification of Ichneumonoidea wasps via YOLO-based deep learning: Integrating HiresCam for Explainable AI

Accurate taxonomic identification of parasitoid wasps within the superfamily Ichneumonoidea is essential for biodiversity assessment, ecological monit...

LysinFusion: Integrating Multi-Feature Encoding and Hybrid CNN-Transformer Architecture for Phage Lysin Prediction

The growing threat of antimicrobial resistance underscores the demand for new therapeutic modalities. Phage lysins are promising candidates, yet their...

Rapid Bacterial Identification and Antibiotic Susceptibility Testing through Interferometry-based Surface Topography Measurement

Antimicrobial resistance poses a critical global health threat. For many bacterial infections, such as bacteremia, treatment can fail due to the time ...

Reinforcement Learning for Antibiotic Stewardship: Optimizing Prescribing Policies Under Antimicrobial Resistance Dynamics

Antimicrobial resistance (AMR) threatens antibiotic effectiveness, but quantitatively evaluating stewardship strategies under partial observability an...

A Retrospective Multi-Source Clinical Validation of Lenek Intelligent Radiology Assistant: An Artificial Intelligence-Based Chest Radiograph Screening and Triage System for High-Burden Pulmonary and Cardiac Conditions in India

Background: A critical radiologist shortage exists in India, leading to delayed chest radiograph (CXR) interpretation. This leads to disease progressi...

Halfway to 3D: Ensembling 2.5D and 3D Models for Robust COVID-19 CT Diagnosis

We propose a deep learning framework for COVID-19 detection and disease classification from chest CT scans that integrates both 2.5D and 3D representa...

Vision-Language Model Based Multi-Expert Fusion for CT Image Classification

Robust detection of COVID-19 from chest CT remains challenging in multi-institutional settings due to substantial source shift, source imbalance, and ...

A Heterogeneous Ensemble for Multi-Center COVID-19 Classification from Chest CT Scans

The COVID-19 pandemic exposed critical limitations in diagnostic workflows: RT-PCR tests suffer from slow turnaround times and high false-negative rat...

Comparative Evaluation of Logistic Regression and Gradient Boosting Models for Influenza Outbreak Early-Warning Using U.S. CDC ILINet Surveillance Data (2010-2025)

Background Timely detection of seasonal influenza outbreaks is critical for healthcare system preparedness and public health response. Although numero...

GCN-Mamba: Graph Convolutional Network with Mamba for Antibacterial Synergy Prediction

The escalating crisis of antimicrobial resistance necessitates novel therapeutic strategies, among which drug combination therapy shows great promise ...

Eukaryotic MAGs recovered from deep metagenomic sequencing of the seagrass, Zostera marina, include a novel chytrid in the order Lobulomycetales

Fungi play pivotal roles in terrestrial ecosystems as decomposers, pathogens, and endophytes, yet their significance in marine environments is often u...

Genomic streamlining of seagrass-associated Colletotrichum sp. may be related to its adaptation to a marine monocot host

Colletotrichum spp. have a complicated history of association with land plants. Perhaps most well-known as plant pathogens for the devastating effect ...