COVID-19

Identification and validation of epithelial‑mesenchymal transition‑related genes for diabetic nephropathy by WGCNA and machine learning.

Diabetic nephropathy (DN) is the main cause of end‑stage renal disease, with epithelial‑mesenchymal transition (EMT) serving a key role in its initiation and progression. Nevertheless, the precise mechanisms involved remain unidentified. The present study aimed to identify the involvement of EMT‑related genes in the advancement of DN. Using the Gene Expression Omnibus database and the dbEMT 2.0 da...

Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.

Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) to guide timely treatments. Traditional culture-based AST methods are slow, while existing whole-genome sequencing (WGS)-based models often suffer from overfitting, poor interpretability, and diminished performance on clinical metagenomic data. In th...

Identifying pivotal sites affecting thermostability of GH11 xylanase via conventional and deep learning-based energy calculation.

The GH11 xylanase XynCDBFV, derived from Neocallimastix patriciarum, is widely used in various industries. However, its relatively low thermostability...

Screening and investigating the regulatory mechanisms of oxidative stress-related biomarkers in thoracic aortic aneurysms.

Excess reactive oxygen species leading to oxidative stress has been identified as a significant factor in cardiovascular disease. However, the molecul...

RadientFusion-XR: A Hybrid LBP-HOG Model for COVID-19 Detection Using Machine Learning.

The rapid and accurate detection of COVID-19 (coronavirus disease 2019) from normal and pneumonia chest x-ray images is essential for timely diagnosis...

Epi4Ab: a data-driven prediction model of conformational epitopes for specific antibody VH/VL families and CDRs sequences.

Antibodies recognize antigens via complementary and structurally dependent mechanisms. Therefore, inclusion of antibody inputs is crucial for accurate...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drivers of this damage remain unclear. This study explo...

Attention-based multimodal deep learning for interpretable and generalizable prediction of pathological complete response in breast cancer.

BACKGROUND: Accurate prediction of pathological complete response (pCR) to neoadjuvant chemotherapy has significant clinical utility in the management...

Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools.

The drawbacks of random sampling not only hinder the development of more reliable and efficient methods but also weaken their accuracy, predictive abi...

TRIM29 alleviates intervertebral disc degeneration through the PI3K/AKT/mTOR pathway.

Intervertebral disc degeneration (IDD), a prevalent spinal condition linked to low back pain, has substantial genetic components, necessitating deeper...

Limited-angle SPECT image reconstruction using deep image prior.

. In single-photon emission computed tomography (SPECT) image reconstruction, limited-angle conditions lead to a loss of frequency components, which d...

High-throughput LDI MS technology decodes the distinct metabolic landscape of prostate cancer in a large-scale cohort.

BACKGROUND: Prostate cancer (PCa) remains a leading global malignancy, yet current diagnostic reliance on prostate-specific antigen (PSA) testing is l...

Prediction of Early Neoadjuvant Chemotherapy Response of Breast Cancer through Deep Learning-based Pharmacokinetic Quantification of DCE MRI.

Purpose To improve the generalizability of pathologic complete response (pCR) prediction following neoadjuvant chemotherapy using deep learning (DL)-...

CRISPR/Cas-Based Biosensing Strategies for Non-Nucleic Acid Contaminants in Food Safety: Status, Challenges, and Perspectives.

Non-nucleic acid targets (non-NATs), such as heavy metals, toxins, and pesticide residues, pose critical threats to food safety. Although CRISPR/Cas s...

Association Between COVID-19 During Pregnancy and Preterm Birth by Trimester of Infection: Retrospective Cohort Study Using Large-Scale Social Media Data.

BACKGROUND: Preterm birth, defined as birth at <37 weeks of gestation, is the leading cause of neonatal death globally and the second leading cause of...

Machine learning using genotype and gene-expression data identifies alterations of genes involved in infection susceptibility, antigen presentation and cytokine signalling as key contributors to JIA risk prediction.

BACKGROUND: Previous genome-wide association studies (GWAS) have identified numerous genetic loci associated with juvenile idiopathic arthritis (JIA)....

Prediction and characterisation of the human B cell response to a heterologous two-dose Ebola vaccine.

Ebola virus disease (EVD) outbreaks are increasing, posing significant threats to affected communities. Effective outbreak management depends on prote...

Enhanced detection of Mpox using federated learning with hybrid ResNet-ViT and adaptive attention mechanisms.

Monkeypox (Mpox), caused by the monkeypox virus, has become a global concern due to its rising cases and resemblance to other rash-causing diseases li...

Real-world deployment of a fine-tuned pathology foundation model for lung cancer biomarker detection.

Artificial intelligence models using digital histopathology slides stained with hematoxylin and eosin offer promising, tissue-preserving diagnostic to...

Insights into the Diagnosis, Treatment, and Management of Prion Diseases.

The normal cellular prion protein (PrPC) can misfold into an infectious and pathogenic form (PrPSc) to produce prion diseases, also known as transmiss...