Genetics

Epigenetic entropy, socioeconomic differences, and health and lifespan in the Women's Health Initiative.

BACKGROUND: Aging is marked by changes in DNA methylation (DNAm) including an increase in randomness or entropy in the epigenome. Here, we computed epigenetic entropy using DNAm data from the Women's Health Initiative (WHI) ancillary study AS315 (n = 2192), and tested for replication in WHI ancillary studies, BA23 (n = 1989) and AS311 (n = 868). We investigated how different metrics of epigenetic ...

Pathway-level epigenetic modeling illuminates the methylation architecture to asthma risk across tissues.

BACKGROUND: Asthma is a clinically heterogeneous airway disorder characterized by complex interactions between environmental exposures, immune activation, and molecular regulatory programs, whose underlying mechanisms are not fully elucidated by known genetic loci. DNA methylation serves as a mechanistic interface bridging genetic predisposition and environmental influences; however, most epigenet...

Radiotherapy quality assurance in the PRO-GLIO trial: results from a dummy run comparing experts across twelve institutions in two Scandinavian countries.

BACKGROUND: Target volume and organ of interest (OOI) contouring and treatment planning for IDH-mutated gliomas CNS WHO grades 2 and 3 are subject to ...

Polycystin-1 and Cardiac Remodeling: From Mechanotransduction to Clinical Consequences.

PC1 (polycystin-1), traditionally viewed through the lens of renal pathophysiology in autosomal dominant polycystic kidney disease, has emerged as a c...

Incorporating dietary information to enhance polygenic prediction models with applications to body mass index and type 2 diabetes.

BACKGROUND: Polygenic predictors can enhance screening for metabolism-related traits such as body mass index (BMI) and type 2 diabetes (T2D). However,...

Single-cell and bulk transcriptomic sequencing reveals tryptophan metabolism-linked biomarkers of obesity.

Obesity remains a major public health challenge, and the contribution of tryptophan metabolism to obesity-associated inflammation remains incompletely...

Integrated Bioinformatics and Explainable Machine Learning Analyses Reveal Mesenchymal Stem Cell Exosome-Related Biomarkers for Diabetic Retinopathy.

PURPOSE: This study aims to identify potential biomarkers for diabetic retinopathy (DR) by focusing on genes associated with mesenchymal stem cell-der...

Metagenomic analysis of water column samples collected from Green Canyon 233 prior to the Deepwater Horizon incident.

UNLABELLED: The Gulf of Mexico/Gulf of America provides ecosystem services derived from marine biodiversity and oil and gas resources. Threats posed b...

Neuroimmune mechanisms in PTSD: inflammatory heterogeneity, circuit dysfunction, and biomarker-based subtypes.

Post-traumatic stress disorder (PTSD) is characterized by exaggerated fear response, anxiety, hyperarousal and sleep disturbances. One of the major pa...

Integrated bioinformatics and machine learning for shared diagnostic genes and mechanisms between periodontitis and psoriasis.

BACKGROUND: Periodontitis and psoriasis are two prevalent conditions that are bidirectionally associated. However, the molecular basis remains poorly ...

GENIE: A Two-Stage Interpretable Deep Learning Framework for Revealing the High-Order Genetic Interaction Network of Alzheimer's Disease.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive impairment and memory loss. The underlying mechanisms ...

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell-Cell Interaction Inference.

Spatial transcriptomics (ST) enables the study of tissue architecture by resolving gene expression in space, but current ST platforms are constrained ...

AI-Assisted Digital Single-Molecule Activity Tracker for Decoupling Intrinsic Heterogeneity from Photo-Oxidative Damage in High-Photon-Flux Enzymology.

Single-molecule enzymes serve as molecular motors for long-read sequencing, where laser tolerance under high photon flux is a critical limiting factor...

Studying the Deep Evolution of Viruses in the Era of Artificial Intelligence Structure Prediction.

High mutation rates erode viral sequence similarity, obscuring deep evolutionary history. While protein structure is far more conserved than sequence,...

Mapping the TCR landscape: computational tools empowering translational immunology and therapy design.

T cell receptors (TCRs) are central to adaptive immunity, yet their vast sequence and structural diversity present a significant challenge to fully un...

Real-Time Segmentation and Classification of Birdsong Syllables for Learning Experiments.

Songbirds are essential for studying neuronal mechanisms of learned vocalizations. Closed-loop interventions require online recognition of a specific ...

Deep learning-guided engineering of SpuFz1 and rational miniaturization of ωRNA enables efficient genome editing.

Advancing the performance of programmable genome editing nucleases remains a key challenge in expanding their research and therapeutic applications. H...

A universal deep learning framework for empowering nanopore identification by reinforcing temporal signals.

Nanopore sensing holds transformative potential for revolutionizing protein and glycan sequencing. However, translating this potential into practical,...

Inferring translational efficiency from transcriptomes improves noncanonical neoantigen prioritization and cancer patient stratification.

Accurate assessment of protein translation is crucial for understanding disease variant functions, but mRNA-protein discrepancy limits transcriptomics...

Identifying breast cancer subtypes and exploring spatial expression patterns of the key subtype-specific gene based on pathological images, single-cell sequencing, and spatial transcriptomic data.

BACKGROUND: Breast cancer (BRCA) is a heterogeneous disease. Accurate prognosis and molecular subtypes are critical for personalized treatment in BRCA...