Genetics

SLA and DDX60L as potential diagnostic biomarkers for subclinical atherosclerosis in systemic lupus erythematosus: a transcriptomic and clinical validation study.

BACKGROUND: Systemic lupus erythematosus (SLE) patients face a 5-tenfold increased risk of atherosclerosis (AS), with subclinical lesions often progressing asymptomatically until life-threatening cardiovascular events occur. This study aimed to identify reliable molecular biomarkers for the early detection of SLE-associated AS. METHODS: Transcriptomic datasets (GSE154851 for SLE, GSE100927 for AS)...

Genome-wide variation in cell-free DNA end motif entropy predicts immunotherapy response in head and neck cancer.

BACKGROUND: Minimally invasive biomarkers predicting immunotherapy response in head and neck squamous cell carcinoma (HNSCC) remain an unmet clinical need. METHODS: Using patients from a prospective, multi-institutional phase II trial, we performed whole-genome sequencing of 185 longitudinal plasma cell-free DNA (cfDNA) samples from 68 patients with locally advanced, surgically resectable HNSCC wh...

Synonymous mutations in viral evolution and vaccine design.

Synonymous mutations, long regarded as evolutionarily neutral, are increasingly recognized as important determinants of viral evolution and adaptation...

Zero-shot de novo peptide sequencing with open posttranslational modification discovery.

De novo peptide sequencing directly infers sequences from mass spectrometry data without relying on protein databases. Although recent deep learning m...

Inferring stochastic dynamics by biophysical Neural ODE using single-cell transcriptomics.

Single-cell RNA sequencing has revolutionized our ability to dissect cellular heterogeneity and study cell fate mechanisms, yet inferring stochastic d...

Fisher duty interval and particle swarm optimization for neural architecture search.

Automatically constructing Deep Neural Networks (DNNs) has become a key focus in artificial intelligence research, as their performance is highly depe...

Interpretable fine-tuned large language models facilitate making genetic test decisions for rare diseases.

Clinical decision making often relies on expert judgment guided by established guidelines, which can be challenging to standardize and abstract to imp...

HELIX: a scalable model for predicting context-dependent regulation of RNA splicing and isoform usage.

Context-dependent alternative splicing plays a critical role in disease pathogenesis and organ development, but its complex regulation remains challen...

Generative artificial intelligence in animal genomics for smart agriculture: Applications, challenges, and future prospects.

Generative artificial intelligence (AI) is becoming a groundbreaking paradigm in the field of animal genomics and is providing the possibility to take...

Prediction of HIV-1 sensitivity to broadly neutralizing antibodies using statistical distribution sampling (SDS) technology.

Accurately predicting HIV-1 sensitivity to broadly neutralizing antibodies (bNAbs) is a critical step in advancing the development of effective therap...

DivideFold+: an AI-based tool for RNA secondary structure prediction with subdomains identification and visualization and data augmentation.

Predicting the secondary structure of RNAs, particularly long RNAs, remains a challenging problem despite its importance in identifying the structural...

Resolving multiscale challenges in neuroscience: A frequency-aware network and benchmarks for live-cell and nuclear foci segmentation.

BACKGROUND: Neuroscience image analysis is crucial for understanding neuronal dynamics and gene expression. However, two key tasks remain challenging:...

A novel NLP-based method and algorithm to discover RNA-binding protein (RBP) motifs, contexts, binding preferences, and interactions.

RNA-binding proteins (RBPs) are essential modulators in the regulation of mRNA processing. The binding patterns, interactions, and functions of most R...

An Integrated Data-Mining Strategy via Transcriptomics and DIA Quantitative Proteomics to Unveil Chemical Attribution Signature Peptides for Tracing Origins of Castor Beans.

The increasing frequency of castor bean or ricin-induced intoxication or terror events threatens public safety and national security, making the traci...

Radiation biomarker screening and dose reconstruction based on machine learning.

PURPOSE: Nuclear emergency medical rescue is a critical component of the nuclear emergency response system, playing a vital role in safeguarding publi...

Peptides as integrative modulators for clinical prognosis and targeted therapy in pancreatic cancer.

Pancreatic cancer remains a formidable global health challenge, ranking as the twelfth most common malignancy yet claiming an outsized toll with disma...

Unraveling Atherosclerosis through Multi-omics: Systematic Insights into the Unique Applications and Clinical Perspectives.

PURPOSE OF REVIEW: Atherosclerosis (AS) is a progressive disease of the arterial wall characterized by metabolic dysregulation, inflammatory activatio...

Global whole-genome, phylodynamic, and machine-learning analysis of Glaesserella parasuis serovars 2, 5, and 12.

Glaesserella parasuis is a respiratory pathogen of swine and the causative agent of Glässer's disease. Among the 15 serotypes, serotypes 2, 5, and 12 ...

Calcite nanoparticles as advanced, pH-responsive platforms for cancer therapy: a comprehensive and critical review.

Nanomedicine offers powerful opportunities to overcome the pharmacokinetic and microenvironmental limitations of conventional chemotherapy, particular...

Artificial Intelligence Based High Resolution Melting Analysis for Comprehensive Calreticulin Mutation Screening and Novel Variant Detection in Myeloproliferative Neoplasms.

INTRODUCTION: Current CALR mutation screening in myeloproliferative neoplasms (MPNs) faces a trade-off between coverage and cost: allele-specific qPCR...