COVID-19

Identification of ITGB2, ELN, and KLRK1 as stress granule-related biomarkers of pterygium through integrated transcriptomic analysis and machine learning.

BACKGROUND: Stress granules (SGs) play a crucial role in cellular stress responses, but their involvement remains unclear in pterygium. This study aimed to identify SG-related genes (SGRGs) associated with pterygium and explore potential regulatory mechanisms involving these genes. METHODS: Twelve conjunctival and sixteen pterygium samples were collected for RNA sequencing (RNA-seq). Candidate gen...

Developing digital PCR technologies based on wettable substrates.

Since the invention of the polymerase chain reaction (PCR) in 1985, the technology has evolved from qualitative PCR to real-time fluorescent quantitative PCR (qPCR) and ultimately to digital PCR (dPCR). Notably, dPCR based on wettable substrates has attracted considerable attention and application owing to its advantages, which include automated droplet manipulation, low reagent consumption, minim...

Automation and Active Learning for the Multi-Objective Optimization of Antibody Formulations.

Over the last forty years, monoclonal antibodies have become increasingly important therapeutic agents, with most manufactured as preformulated soluti...

Label-Free Prediction of EGFR Mutation Status Using Fluorescence Lifetime Imaging and Deep Learning in Lung Adenocarcinoma.

UNLABELLED: Accurate prediction of epidermal growth factor receptor (EGFR) mutations is essential for guiding targeted therapy in non-small cell lung ...

Machine Learning Models for Local Optimization of Red Fluorescent Protein Variants in a Low-Data Setting.

Fluorescent proteins (FPs) are widely used reporters for visualizing cellular structures and processes. Traditional wet-lab strategies for FP engineer...

Tight and Flexible Antibody Recognition via Quaternization Interface in Metal-AIEgens Frameworks and Collaborating Ultrabright Luminescence for Intelligent Biosensing.

The analytical performance of an immunoassay is critically limited by a fundamental trade-off: achieving tight binding of antibodies (Abs) to signal r...

Groundwater level prediction using deep learning algorithms in a drought-prone area in Bangladesh.

Groundwater is a crucial resource for meeting daily needs such as drinking water and agricultural irrigation. The northwestern region of Bangladesh ex...

Landslide detection in remote sensing images on the basis of feature recursion and sample balance.

To increase the accuracy of landslide identification via high-resolution optical remote sensing images, this paper presents an improved landslide iden...

Machine learning-enabled behavioural and psychological symptoms of dementia management intervention for dementia caregivers: protocol for a hybrid factorial SMART-MRT trial.

BACKGROUND: Behavioural and psychological symptoms of dementia (BPSD) affect over 90% of people living with dementia and are a major contributor to st...

Optimizing the mathematical model and technical standards for unilateral biportal endoscopic spinal surgery through machine learning-based video analysis.

OBJECTIVE: To enhance the efficacy of the unilateral biportal endoscopic spinal procedure, the spinal triangle concept is proposed, integrating a digi...

SERS-based spectral analysis of ITS1 PCR products for differentiation of three old world Leishmania species.

Leishmaniasis, a zoonotic disease caused by parasites of the genus Leishmania, poses a significant medical and veterinary importance worldwide. This s...

Variant-specific pharmacophoric shifts in glucagon-like peptide-1 receptor-orforglipron complexes revealed by Boltz-2 co-folding and membrane molecular dynamics.

BACKGROUND: Orforglipron (ORF), the first orally bioavailable non-peptide glucagon-like peptide-1 receptor (GLP-1R) agonist to complete Phase 3 clinic...

MXene-Configured Intelligent Mask for Long-Term Sleep Breathing Assessment during Assisted Ventilation.

Positive airway pressure therapy serves as a core therapeutic strategy for sleep-disordered breathing, with its efficacy generally evaluated via sleep...

Frequency-decomposed EEG microstate analysis reveals altered cross-frequency coordination in adolescent major depressive disorder.

Adolescent major depressive disorder (MDD) involves alterations in large‑scale brain network dynamics. However, conventional EEG microstate studies ty...

What drives generational differences in subjective well-being? A machine learning study of Chinese migrant workers in the Yangtze River Delta.

The subjective well-being of migrant workers amid China's rapid urbanization has emerged as a critical issue, intersecting social policy and mental he...

Precision therapeutics and innovative clinical trial design in neurodegenerative diseases.

Neurodegenerative diseases are biologically heterogeneous disorders characterized by progressive neuronal dysfunction, overlapping molecular pathologi...

Development and validation of a multimodal deep learning model for the radiographic classification of pediatric femoral neck fractures.

BACKGROUND: An alternative classification system for categorizing pediatric femoral neck fractures (PFNFs) has been shown to have significant clinical...

Specimen quality shapes the actionable genomic landscape in comprehensive cancer genomic profiling.

Comprehensive genomic profiling (CGP) is widely used to identify actionable alterations and guide precision oncology, yet only a minority of tested pa...

A hybrid deep learning and attention fusion framework for intelligent zero-day threat detection in cloud web application firewalls.

Traditional Rule-Based Web Application firewalls (WAFs) are severely limited in defending against sophisticated attacks, such as zero-day exploits, po...

Integrating epigenetic and metabolic indicators for non-invasive endometrial cancer triage: a machine learning approach.

OBJECTIVE: Abnormal uterine bleeding (AUB) is a primary symptom indicative of endometrial cancer (EC), yet its diagnosis still primarily relies on inv...