COVID-19

Identification of PANoptosis-related gene SIK1 in MASLD by bioinformatics, machine learning and experimental validation.

OBJECTIVE: Metabolic dysfunction-associated steatotic liver disease (MASLD) constitutes a chronic inflammatory condition within the spectrum of metabolic liver diseases, characterized by the accumulation of hepatic lipids in the absence of significant alcohol consumption, however, the contribution of PANoptosis to its pathobiology remains largely undefined. METHODS: We retrieved MASLD transcriptom...

Navigating high-order protein fitness landscapes via deep learning on directed evolution trajectories.

Accurately predicting the fitness effects of high-order mutations is a grand challenge in understanding and engineering proteins. Existing models, including pretrained protein language models, struggle to capture the multiresidue interactions that govern these effects. Here, we introduce DENet, a deep learning framework that harnesses the rich comutation information within directed evolution (DE) ...

Efficient in vivo assembly of DNA encoded multivalent BTEs for dual antigen targeting for broadening therapeutic impact in ovarian cancer.

The clinical potential of bispecific T cell engagers (BTEs) is limited by their short serum half-life and the complexity and cost of recombinant prote...

Predicting neoadjuvant breast cancer therapy response using BRIDGE from tumor transcriptomics and histopathology.

BACKGROUND: While expression-based signatures inform adjuvant therapy in breast cancer (BC), no approved molecular biomarkers exist for the neoadjuvan...

Decoding variants of uncertain significance in systemic autoinflammatory diseases.

The development and implementation of genetic testing has revolutionized the diagnostic landscape of autoinflammatory diseases, leading to an exponent...

Detection of maxillary sinusitis of endodontic origin in cone-beam CT images using deep learning algorithms.

Cone-Beam Computed Tomography (CBCT) scans were retrospectively collected and examined to acquire a balanced dataset representative of Normal Maxillar...

Phosphorylation tunes strain-specific protein condensation during rotavirus replication organelle assembly.

In many viruses, intrinsically disordered proteins (IDPs) drive the formation of replicative organelles via liquid-liquid phase separation (LLPS). In ...

Personalized neoadjuvant treatment regimen selection in locally advanced rectal cancer based on regimen-specific response modeling.

Neoadjuvant therapy is standard for locally advanced rectal cancer (LARC), yet regimen selection remains population-based, risking over- or undertreat...

Leveraging the non-contrast CT component of PET/CT: an AI-driven delta-radiomics approach to monitor treatment response in metastatic breast cancer.

PURPOSE: 18 F-FDG PET/CT is the standard modality for monitoring treatment response in metastatic breast cancer. This study aims to evaluate the predi...

Fine-tuning sequence-to-expression models on personal genome and transcriptome data.

BACKGROUND: Genomic sequence-to-expression deep learning models, which are trained to predict gene expression and other molecular phenotypes across th...

Multi-epitope tick vaccines: From computational design to field deployment, immunoinformatics approaches, validation challenges, and translational pathways.

Ticks are major vectors of pathogens affecting both humans and animals, yet effective and sustainable control strategies remain limited. Conventional ...

T-cell-mediated immunity to influenza A (H2N3): implications for caccine efficacy and cross-subtype protection.

Influenza A viruses pose a significant pandemic threat, with H2N3 in particular representing a subtype of particular concern due to limited population...

Explainable machine learning-guided integrated multiomics analysis reveals macrophage-driven immune suppression in breast cancer.

Despite thorough characterizations of cellular compositions within the breast tumor microenvironment (TME), their implications for disease progression...

Research progress and development strategies of antibody-oligonucleotide conjugates.

Antibody-oligonucleotide conjugates (AOCs) effectively integrate the delivery capability of antibodies with the specific gene regulatory function of o...

Scaling antibody language models improves structure aware representation for antibody engineering.

Antibody language models have emerged as powerful tools in antibody engineering by capturing patterns in sequences to innovate discovery and optimizat...

In silico discovery of novel small-molecule PD-L1 inhibitors through a multi-stage computational workflow integrating machine learning and molecular dynamics.

Cancer immunotherapy targeting the PD-1/PD-L1 pathway has transformed modern oncology; however, developing small-molecule inhibitors as viable alterna...

Standardizing antiviral response metrics for mono- and combination therapies in acute, chronic and latent viral infections.

The COVID-19 pandemic showed that heterogeneous antiviral assay designs, endpoints and reporting practices can obscure which candidate drugs and combi...

Identification and Validation of Glycosylation-Related Biomarkers in the Hippocampus for Alzheimer's Disease Diagnosis and Drug Repurposing.

As a crucial type of post-translational modification, glycosylation plays a fundamental role in maintaining cellular homeostasis and is closely associ...

Decoding immunity: AI-driven insights into T-cell receptor antigen recognition and immune function.

In this research highlight, we discuss key studies published in 2025 that advance our understanding of TCR biology, spanning mechanistic insights into...

From memorization to generalization: Why physics will improve machine learning -based prediction of protein complexes.

AlphaFold-like models have transformed monomer structure prediction yet reliable, generalizable prediction of protein-protein interactions (PPIs) rema...