Genetics

Evolving techniques to optimize ERCP-based sampling and evaluation of malignant biliary strictures.

Endoscopic retrograde cholangiopancreatography (ERCP)-based tissue acquisition is the cornerstone for assessment of suspected malignant biliary strictures. Conventional techniques, including biliary brush cytology and transpapillary forceps biopsy, are highly specific but are limited by modest sensitivity for detection of malignancy, often leaving a substantial proportion of individuals without a ...

Secondary prevention of recurrent ischemic stroke: from guidelines to precision medicine.

Recurrent ischemic stroke remains a major global health challenge, accounting for substantial disability and mortality despite advances in acute management. Secondary prevention has undergone a fundamental paradigm shift-from standardized, population-based regimens toward individualized, mechanism-targeted precision medicine. This review integrates evidence from recent AHA/ASA and ESO guidelines[2...

Agentic Artificial Intelligence-Driven Explainable Deep Learning for Deciphering Noncoding Pathogenic Mechanisms of Delirium Through Genomic Big Data Integration.

Delirium is a prevalent neuropsychiatric syndrome affecting up to 50% of hospitalized elderly patients, associated with increased mortality, cognitive...

Bioactive Natural Products in Cardiovascular Disease: Focus on Thrombotic Events.

Bioactive compounds derived from natural products (NPs) continue to attract considerable scientific interest due to their wide range of beneficial bio...

Integrative transcriptional regulatory networks governing cereal root responses to heavy metals and drought.

Cereal root systems perceive the onset of drought and heavy metal toxicity, which rapidly triggers signal transduction and extensive transcriptional r...

NanoRAPID: A Deep Learning-based Framework for Single-molecule RNA Structure Analysis Using Nanopore Direct RNA Sequencing.

RNA structure is fundamental to its diverse biological functions. Current chemical probing methods, coupled with next-generation sequencing, offer ins...

Somatic variant-calling beyond cancer: Repurposing algorithms to map low‑allele‑fraction variants across genomics.

BACKGROUND: Somatic variant callers were originally developed to identify tumour-specific mutations in mixed tumour-normal samples. Increasingly, disc...

Integrating stemness and epithelial-mesenchymal transition signatures with machine learning identifies RUNX1 as a therapeutic vulnerability in colorectal cancer.

Colorectal cancer (CC) arises from a complex interplay between genetic and epigenetic alterations within the colorectal mucosa, resulting in unchecked...

Bacterial keratitis: a global review of current practices, challenges and innovations.

Bacterial keratitis is a major cause of corneal blindness worldwide, with marked differences in clinical presentation and risk factors across regions....

Diverse molecular mechanisms of in vivo haploid induction in plants: from fertilization interference to genome programming.

In vivo haploid induction has revolutionized crop breeding by shifting it from experience-driven selection to precision design methodologies. This rev...

Identification and validation of biomarkers associated with mitochondria and glycometabolism in gestational diabetes mellitus.

Gestational diabetes mellitus (GDM) can elevate the likelihood of developing high blood pressure during pregnancy. It is one of the most common compli...

Explainable machine learning identifies small high-performance gene signatures from full transcriptomes in human liver preservation cohorts.

Transcriptomic studies of liver preservation and ischemia-reperfusion injury (IRI) often report large gene lists that are difficult to translate into ...

Integrated multi-omics analysis reveals folate metabolism-related genes as prognostic markers and therapeutic targets in clear cell renal cell carcinoma.

BACKGROUND: Clear cell renal cell carcinoma (ccRCC) is an aggressive tumor with high metastatic potential and therapeutic resistance, yet the role of ...

An interpretable machine learning model integrating peripheral blood lncRNAs and clinical variables for phase classification in chronic myeloid leukemia.

BACKGROUND: Accurate disease phase assessment remains clinically important in chronic myeloid leukemia (CML), as progression to accelerated or blast p...

Decoding glioblastoma evolution and heterogeneity through mechanistic modeling: implications for clinical translation.

Glioblastoma (GBM) is one of the most aggressive and lethal primary brain tumors in adults, characterized by dynamic clonal evolution and extensive ge...

Identification of distinct subgroups in Chinese patients with Behçet's syndrome via cluster analysis of immune cells and clinical features.

OBJECTIVES: This study aimed to use machine learning to explore Behçet's syndrome (BS) heterogeneity by integrating immunocyte subpopulations and clin...

Deep contrastive learning framework identifies cell-type-specific drug targets in Alzheimer's disease.

INTRODUCTION: Identifying disease-modifying drug targets is crucial for developing effective Alzheimer's disease (AD) treatments. METHODS: We present ...

Nanocarrier-Based Gene Delivery Systems: Mechanisms, Clinical Translation, and Future Perspectives.

Gene therapy holds revolutionary potential for managing genetic disorders, cancers and infectious illnesses. However, one of the biggest challenges is...

Minimizing Off-Target Effects of CRISPR-Cas9 With Optimized sgRNA: Evaluation of Efficiency and Specificity in the Tumor Protein 53 (TP53) Region.

CRISPR-Cas9 is a widely used genetic tool with therapeutic potential in molecular biology. CRISPR-Cas9 enables precise genome editing by its ability t...

Benchmarking docking and ML re-scoring screening performance for KRAS G12D in pancreatic cancer.

The KRAS G12D mutation is commonly found in pancreatic cancer and is integral to the cell signaling pathway, making it a critical target for drug deve...