COVID-19

A multi-feature resting-state EEG framework for candidate EEG feature discovery in central vertigo.

Central vertigo (CV) lacks objective electrophysiological measures for severity assessment and rehabilitation monitoring. We aimed to characterize multiscale resting-state EEG alterations and identify clinically interpretable candidate features in stroke-related CV. Approach: Resting-state EEG was analyzed in 50 patients with stroke-related CV (31 moderate, 19 severe) and 31 age-matched health...

Machine learning for thalassemia detection: A critical review of diagnostic pathways and emerging technologies.

Thalassemia is still challenging to diagnose due to heterogeneous genotypes, overlapping hematologic phenotypes (e.g., other anemias), and limited access to standardized molecular testing. Current methods of diagnosis, like complete blood count (CBC) indices, smear analysis, electrophoresis/high-performance liquid chromatography (HPLC), and targeted genetics, work effectively in the clinic. Howeve...

Discovery and design of potent cell surface display elements.

Cell surface display (CSD) elements are a major class of bioengineering modules, but systematic rules linking CSD sequence to functional potency are l...

Biomarkers of nivolumab benefit in resectable non-small cell lung cancer.

Perioperative nivolumab significantly improved event-free survival (EFS) compared with placebo in patients with resectable non-small cell lung cancer ...

AbAgKer: A Unified Semi-Supervised Framework for Antigen-Antibody Binding Affinity and Kinetics Prediction.

MOTIVATION: The rapid advancement of generative artificial intelligence has enabled the high-throughput design of therapeutic antibody candidates. How...

DELTA: Strengthening human biological resilience with an N=1 digital health and dynamic biomarker protocol.

Societies are aging rapidly in parallel with the increasingly earlier onset of serious diseases in younger populations. These and other factors are cr...

Predictive models of the genetic bases underlying budding yeast fitness in multiple environments.

The ability of organisms to adapt and survive depends on the effects of genes and the environment on fitness. However, the multigenic nature of fitnes...

An integrated methodological roadmap for real-world biomarker studies: advancing oncology precision medicine through robust methodologies and machine learning integration.

The selection of biomarker-specific patient populations is essential in targeted cancer therapies to enhance precision and efficacy. To ensure a succe...

Integration of the circulating miRNome and clinical information to predict 90-day mortality in elderly COVID-19 subphenotypes.

Elderly patients with coronavirus disease 2019 (COVID-19) exhibit high mortality rates. We assessed whether microRNA (miRNA) profiling provides progno...

Rational drug design for Alzheimer's disease: from approved therapies to next-generation clinical candidates and AI-guided innovation.

Alzheimer's disease (AD) is a progressive neurodegenerative disorder characterized by multifactorial pathology, including amyloid-β (Aβ) aggregation, ...

ARID-sf: A Physics-Informed Deep Learning Scoring Function to Improve Antibody-Antigen Docking Model Ranking.

Accurate prediction of antibody-antigen (Ab-Ag) complexation is crucial for understanding immune responses, diagnostics, and the development of therap...

rs57494551 increases CXCR5 expression and IgM+ CXCR5+ B-cell infiltration in the portal area of primary biliary cholangitis.

BACKGROUND: Primary biliary cholangitis (PBC) is a chronic, progressive, cholestatic liver disease caused by autoimmune reactions. A previous internat...

The diagnostic value of the circadian rhythm gene KLF10 in anxiety-depressive disorders and its neuroimmune regulatory mechanisms.

BACKGROUND: Anxiety-depressive disorder (ADD) is one of the important subtypes of depression, which has been shown to be closely related to neuroimmun...

SIMLINK Enables Accurate Variant Pathogenicity Prediction through Modeling the Gene-Variant-Feature Association Structure.

MOTIVATION: Predicting variant pathogenicity is crucial for clinical genetics. Existing approaches face two primary limitations. First, biologically, ...

A blood-based test for detection of advanced adenomas and colorectal cancer (DENEB): a multicentre diagnostic accuracy study.

BACKGROUND: Colorectal cancer is the third most common and second deadliest cancer in the USA, but cases and deaths are preventable through appropriat...

Robustness of radiomics-based machine learning to real-world MRI distribution shifts: a phantom study.

This study systematically investigates the robustness of radiomics-based machine learning models to distribution shifts caused by variations in MRI ac...

Comment on "Evaluation of Semi-Automated Versus Fully Automated Technologies for Computed Tomography Scalable Body Composition Analyses in Patients with Severe Acute Respiratory Syndrome Coronavirus-2".

[Advance in the application of molecular ruler-based RNA 3D dynamic analysis for the interpretation of variants of uncertain significance].

Functional interpretation of genetic variants is a core issue in precision medicine. A large number of "variants of uncertain significance" (VUS) have...

Interpreting antibody identification tests with large language models: Critical role of tabular data formatting.

BACKGROUND: Antibody identification testing is essential for preventing hemolytic transfusion reactions from unexpected red cell antibodies. Although ...

Explainable machine learning for spatial risk assessment of Hyphantria cunea (Lepidoptera: Erebidae) in China.

The fall webworm, Hyphantria cunea (Drury) (Lepidoptera: Erebidae), is a highly polyphagous invasive pest that poses increasing economic and ecologica...