Genetics

Integrating MRI radiomics and transcriptomics to predict IDH mutation status and prognosis in glioma.

OBJECTIVE: To investigate MRI-based radiomic features in glioma and key genes related to IDH mutations, and to analyze their correlation. METHODS: 61 MRI files from TCIA were divided into training and validation sets (7:3). An external validation set included 66 pathologically confirmed glioma patients. Regions of interest (ROIs) were manually delineated, extracting 1,037 radiomic features. Mann-W...

Precision culturomics enabled by unlabeled single-cell morphology and Raman spectra.

Selective enrichment of target bacteria from complex communities, such as the human microbiome, has remained a challenge. Here, we report precision single-cell culturomics based on label-free morphology, Raman spectrometry, and Laser-Induced Forward Transfer (LIFT) technology. This approach operates at the level of single microbial cells, many generations before these cells form visible colonies. ...

Metaheuristic-driven LSTM framework for advanced cyberthreat detection and response using a hybrid firefly-whale-grey wolf optimization pipeline.

Conventional intrusion detection systems (IDSs) based on static, signature-based rules are becoming insufficient in response to more advanced, dynamic...

Interpretable machine learning model for predicting kidney failure among CAKUT children in multicenter large-scale study.

Congenital anomalies of the kidney and urinary tract (CAKUT) are the leading cause of pediatric kidney failure, but predicting individual progression ...

Protein-Nucleic Acid Binding Site Prediction Using Interpretable Kolmogorov-Arnold Networks with Hypergraph Representation Learning.

MOTIVATION: In recent years, protein language models (pLMs) and graph neural networks (GNNs) have demonstrated powerful expressive and reasoning capab...

Engineered Neutrophils in Translational Medicine: Gene Editing, Nanotechnology, and AI-Driven Clinical Breakthroughs.

Engineered neutrophils, modified via advanced biotechnological tools, are emerging as pivotal agents in translational medicine. By integrating gene ed...

Biases of large language models in diagnosing Cushing's syndrome.

The diagnosis of endogenous Cushing's syndrome (CS) can be complicated and often delayed, given its low incidence (estimated globally at 1.8 cases to ...

Integrative multi-omics analysis and machine learning identify M2 macrophage-induced ferroptosis resistance in glioblastoma.

Glioblastoma (GBM) is characterized by profound intratumoral heterogeneity and an immunosuppressive microenvironment that drive therapeutic resistance...

Gene delivery for cerebral neurodegenerative disorders - current advancements and limitations.

Gene delivery for neurodegenerative cerebral disorders faces formidable structural and practical challenges. The blood-brain, blood- cerebrospinal flu...

VariantMedium: sensitive and generalizable somatic point mutation calling with 3D DenseNets trained and evaluated on experimental data.

BACKGROUND: Accurately identifying somatic variants from genomic sequencing is crucial for understanding and treating cancer. Previously, methods base...

Explainable epigenetic aging clocks: an overview of existing AI models and approaches.

INTRODUCTION: There is a growing demand to make epigenetic aging clocks that are interpretable and actionable. Here, we identify and describe explaina...

Blood-based Biomarkers in Cervical Cancer: The Emerging Role of Circulating Human Papillomavirus and Tumor Deoxyribonucleic Acid.

Cervical cancer (CC) remains a major global health burden, particularly in low- and middle-income countries (LMICs), where access to timely diagnosis ...

Integrated network toxicology and experimental validation to investigate potential mechanisms associated with aspartame-induced malignant phenotypic changes in colorectal cancer.

To investigate the potential molecular mechanisms underlying aspartame (APM)-induced malignant phenotypic changes in colorectal cancer (CRC). Candidat...

IBS-CNN: a novel computer vision-based kinship classification model for high-density SNP microarray.

This study addresses multiple challenges in applying forensic genealogy to Chinese populations by exploring novel kinship classification strategies ba...

Identification and validation of exosome-related biomarkers in pediatric glioblastoma.

Pediatric glioblastoma (pGBM) is an aggressive central nervous system (CNS) tumor whose pathological progression is significantly influenced by exosom...

Harvesting insights from recent advances in yeast genomics for predictable and precision wine fermentation.

Wine fermentation remains inherently variable because of the genetic and phenotypic diversity of Saccharomyces cerevisiae and non-Saccharomyces yeasts...

Gut microbiome signatures discriminate deep vein thrombosis through machine learning and metabolic analysis.

Deep vein thrombosis (DVT) remains difficult to distinguish because of its often silent presentation and the limited specificity of current diagnostic...

DeepDisSNP: Predicting disease-associated SNPs by representation learning on disease and SNP linkage disequilibrium networks.

Genome-wide association studies (GWAS) have identified numerous disease-associated single nucleotide polymorphisms (SNPs), yet many potential disease-...

A Risk Score for Polycystic Ovary Syndrome Based on Meta-Analysis and Machine Learning of Gut Microbiota Signatures.

Polycystic Ovary Syndrome (PCOS) is a prevalent endocrine and metabolic disorder among reproductive-age women, in which emerging evidence suggests a s...

Exploring the immune landscape and immunotherapy relevance of ER stress-related lncRNAs in melanoma through multi-omics and explainable machine learning.

BACKGROUND: Melanoma is a highly aggressive malignancy with poor clinical outcomes, and endoplasmic reticulum (ER) stress plays an important role in t...