Genetics

Biosensor-based diagnosis for infectious diseases: Nano-enabled revolution.

Infectious diseases (IDs) pose a significant global health threat, exacerbated by the rise of multidrug-resistant (MDR) and antimicrobial-resistant (AMR) pathogens. The conventional diagnostic methods, such as culture characteristics, microscopical examinations, and polymerase chain reaction (PCR), are reliable but often face challenges like long turnaround times, high costs, and demanding infrast...

A simulation-based deep learning framework for spatially explicit malaria modeling of CRISPR suppression gene drive mosquitoes.

Engineered CRISPR gene drives are a promising new strategy for fighting malaria and other vector-borne diseases. One useful approach to predict the outcome of a drive release is individual-based modeling, allowing simulation of the chasing phenomenon. However, the computational demand significantly increases when including many parameters, such as those for disease transmission. To overcome this, ...

Critical evaluation of the theory and practice of feed-forward neural networks for genomic prediction.

Genomic prediction (GP) has catalyzed increased rates of genetic gain in animal and plant breeding. Recently, deep learning (DL) has been explored to ...

Maternal Gut Microbiome as a Predictor of Insulin Therapy Requirement in Gestational Diabetes.

BACKGROUND: Gestational diabetes mellitus (GDM) often requires pharmacological intervention beyond lifestyle modification to achieve optimal glycemic ...

Single-Feature Identification of α2-8 Linked Sialoglycans Using Engineered Aerolysin Nanopores: A Paradigm for Glycan Linkage Analysis.

Nanopore single-molecule sensing has emerged as a transformative platform in glycoscience and nanotechnology because of its inherent potential to deco...

Deep learning linking mechanistic models to single-cell transcriptomics data reveals transcriptional bursting in response to DNA damage.

Cells must adopt flexible regulatory strategies to make decisions regarding their fate, including differentiation, apoptosis, or survival in the face ...

Cell-free DNA fragmentomes for noninvasive detection of liver cirrhosis and other diseases.

Accessible liquid biopsies, including analyses of genome-wide cell-free DNA (cfDNA) fragmentation, are emerging for early detection of cancer but rema...

Machine Learning-Based Preoperative Predicting TERT Promoter Mutation and EGFR Gene Amplification Phenotype in IDH Wild-Type Glioblastoma Using Advanced MR Habitat Imaging.

BACKGROUND AND PURPOSE: The telomerase reverse transcriptase (TERT) gene promoter mutation is a crucial factor for identifying an isocitrate dehydroge...

Cell-free chromatin state tracing reveals disease origin and therapy responses.

Cell-free DNA in blood originates from fragmented chromatin released by dying cells from both healthy and diseased tissues1,2. These fragments carry r...

Integrating ensemble machine-learning and fibril docking to discover potent, novel triazole-naphthalene tau-aggregation inhibitors.

Tau-protein aggregation is a central pathological feature of Alzheimer's disease, so blocking fibril growth is an attractive therapeutic goal. We cura...

Prosta-omics: machine learning-driven TPSA prediction and molecular modeling of ASPM-inhibitors for prostate cancer treatment.

Prostate cancer exhibits complex transcriptional heterogeneity that underlies disease progression and therapeutic resistance. We developed an integrat...

RNA therapeutics 2.0: Expanding the landscape from mRNA vaccines to splicing modulators and beyond.

RNA therapeutics have progressed into a disruptive drug class quickly, replacing a variety of primary experimental agents which included vaccines, ant...

scDCL: A multi-view single-cell RNA sequencing clustering method based on dual contrastive learning.

Single-cell RNA sequencing (scRNA-seq) has become a pivotal tool for resolving cellular heterogeneity and uncovering novel cell states. While deep lea...

Integration of multi-omics and machine learning to reveal the anti-osteoporosis effects of Hederagenin by inhibiting lipid peroxidation via the GPX4/p-STAT1/PTGS2 axis.

Osteoporosis (OP) is a multifactorial disease, leading to abnormal bone remodeling, requiring targeted therapeutic interventions. This study investiga...

Neoadjuvant Systemic Therapy in Kidney and Bladder Cancer: Current Evidence and Emerging Paradigms.

Neoadjuvant systemic therapy has emerged as a strategy to improve outcomes in high-risk localized genitourinary malignancies. In bladder cancer, neoad...

Integrating machine learning of bulk and single cell RNA data to characterize immune mechanism of m6A related mitophagy genes in malignant gastric cancer.

BACKGROUND AND OBJECTIVE: Gastric cancer is a heterogeneous and complicated epithelial cancers. Chronic H. pylori and EBV infection, as well as intest...

YTHDF2 promotes m6A-modified HSPA2 translation to restrict Newcastle Disease Virus.

Newcastle disease virus (NDV), a highly contagious avian pathogen, causes devastating economic losses in poultry worldwide, yet the role of epitranscr...

Global analysis of protein degradation reveals instability of diverse regulators in Escherichia coli.

Regulated protein degradation underlies the timely execution of essential gene expression programs in bacteria. Here, we deployed time-resolved chemop...

Benzo[a]pyrene promotes gastric cancer progression via activation of the Correa cascade through modulation of the STAT3-TP53-MMP9 molecular axis.

To investigate the role of Benzo[a]pyrene (BaP) in driving the Correa cascade during gastric cancer development, we employed an integrated strategy co...

The role of ionotropic glutamate receptors in Alzheimer's disease: A scientometric analysis.

BackgroundAlzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by amyloid-β plaques, neurofibrillary tangles, and synapt...