COVID-19

ClairS: a deep-learning method for long-read tumor-normal pair somatic small variant calling.

Somatic variant discovery in tumors is crucial for clinical analysis, yet most existing methods are designed for short-read sequencing, with few developed specifically for long reads. Here we present Clair-Somatic (ClairS), a deep-learning-based somatic small-variant caller designed for long-read tumor-normal pairs. Trained on synthetic somatic variants with diverse coverages and variant allele fr...

SNAC-DB: An ML-ready database for antibody and NANOBODY® VHH-antigen complexes with expanded structural diversity and real-world benchmarking.

Predicting antibody and NANOBODY® VHH-antigen complexes remains a critical challenge for state-of-the-art structure prediction models, limiting their impact in therapeutic discovery pipelines. We introduce SNAC-DB, an ML-ready database and curation pipeline enriched with structural biology expertise, designed to accelerate model accuracy and generalization by providing 31-37% expanded structural d...

Pinoresinol diglucoside from Eucommia ulmoides attenuates diabetic cardiomyopathy through suppressing the store-operated calcium entry and downregulating the STIM1/Orai1/NFAT3 signaling pathway.

Pinoresinol diglucoside (PDG), an active component derived from Eucommia ulmoides, exhibits therapeutic effects against apoptosis, inflammation, and h...

Protocol-Based Management of Medication Confounders in Brain Death Determination: A Multi-Institutional Review.

BACKGROUND: Determination of death by neurologic criteria (DNC) relies on clinical examination, provided no confounding conditions affect reliability....

Uncertainty quantification of U-Net based segmentation tool using conformal prediction.

BACKGROUND: The radiation therapy treatment process is very labour intensive, and artificial intelligence (AI) based auto contouring tools are increas...

Polygon-Aware Deep Learning Framework for Meal-Level Nutrition Estimation From Food Images.

Accurate estimation of meal-level nutritional content from food images is a challenging yet essential task for automated dietary assessment. Although ...

A Narrative Review of Artificial Intelligence for Drug Repurposing: Lessons From COVID-19 and Oncology (2020-2025).

Drug repurposing presents a cost-effective and time-efficient strategy to identify new therapeutic applications for existing drugs. Recent advances in...

Predicting Pain: Electroencephalography Signatures of Neural Integration During Experimental Tonic Thermal Pain.

BACKGROUND: The identification of reliable neural signatures for pain remains a critical challenge in both clinical and experimental settings. While e...

Advances and prospects in cell therapy for cancer: explorations from T cells to stem cells.

The increasing global burden of cancer necessitates innovative therapeutic strategies. Cell therapy represents a major breakthrough in oncology, evolv...

Air pollution and hepatocellular carcinoma: Integrated network toxicology, machine learning, molecular docking and multiomics analysis.

Air pollution is closely related to the incidence and prognosis of hepatocellular carcinoma (HCC); however, the mechanisms remain elusive. Therefore, ...

Integrated Multi-Omics Identification of Novel Diagnostic Biomarkers and Immunometabolic Therapeutic Targets in Osteoporosis via Machine Learning.

INTRODUCTION: Osteoporosis (OP) is a multifactorial skeletal disorder marked by reduced bone mass and microstructural deterioration. We investigated p...

Count your bits: fingerprint benchmarking to assess broad chemical space representation.

Quantifying molecular similarity is a cornerstone of cheminformatics, underpinning applications from virtual screening and nearest-neighbor search to ...

AI-Driven Design Platforms of Next-Generation Antibody Therapeutics.

Artificial intelligence (AI) is reshaping drug discovery by bridging the gap between traditional computer-aided drug design (CADD) and next-generation...

Iterative Multidisciplinary Development and Evaluation of a Patient-Facing SDoH Chatbot Using Synthetic Data Simulation.

BACKGROUND: Systematic collection of social determinants of health (SDoH) data remains inconsistent across healthcare settings, despite its critical i...

Automated deep learning-based retinoschisis and detachment volume measurement in pathological myopia with posterior scleral contraction.

PURPOSE: This study developed an automated deep learning-based system to quantify retinoschisis and detachment volume (RDV) in pathological myopia (PM...

Deep learning models based on post-procedural angiography for predicting the future risk of in-stent restenosis.

In-stent restenosis (ISR) remains a significant complication after percutaneous coronary intervention. Identifying patients at high risk for ISR from ...

Hybrid deep learning framework for cardiovascular risk prediction in post-COVID-19 patients.

Cardiovascular complications associated with Post-COVID-19 Patients remain difficult to identify at early stages due to heterogeneous physiological ma...

European Cancer Prevention Organization on cancer screening: an expert panel position paper.

BACKGROUND: Cancer screening is a cornerstone of cancer control in Europe yet marked disparities persist in access, implementation, and quality assura...

[A machine learning diagnostic model for hereditary hearing loss based on GJB2 and SLC26A4 genes: construction and interpretability analysis].

Objective: To construct a machine learning diagnostic model for hereditary hearing loss based on GJB2 and SLC26A4 genes and perform interpretability a...

MeLSI: Metric Learning for Statistical Inference in microbiome community composition analysis.

Microbiome beta diversity analysis relies on distance-based methods, including permutational multivariate analysis of variance (PERMANOVA) combined wi...