COVID-19

CDKN3, PKP2, ADM, MS4A1, FAM83A, and DKK1 Define a Posttranslational Modification (PTM)-Associated Prognostic Model for Lung Adenocarcinoma.

INTRODUCTION: Posttranslational modification (PTM) plays an important role in protein regulation and may influence tumor initiation and progression. However, the role of PTM-related programs in lung adenocarcinoma (LUAD) remains incompletely understood. MATERIALS AND METHODS: Single-cell RNA sequencing (scRNA-seq) data were analyzed to quantify the activity of PTM-related gene set using the AUCell...

An integrated systems biology and machine learning framework for identifying potential biomarkers and pathways in autism spectrum disorder.

BACKGROUND: Autism spectrum disorders (ASD) are a group of neurodevelopmental disorders whose underlying molecular mechanisms and biological processes remain incompletely understood. In this study, we used a multi-layered systems biology approach to prioritize candidate genes and regulatory factors associated with ASD. METHOD: Gene expression data from peripheral blood samples were obtained from t...

Targeting GLS and LPIN2 in renal fibroblasts: potential therapeutic targets for kidney stone disease identified by integrated multi-omics analysis.

Kidney stones (KS) are a common urological condition, the aetiology of which remains incompletely understood. This study aimed to investigate the key ...

Super-resolution MRI and 2.5D deep learning for intratumoral-peritumoral radiomics in preoperative prediction of rectal cancer perineural invasion.

OBJECTIVES: Preoperative prediction of perineural invasion (PNI) in rectal cancer (RC) is challenging due to limited MRI resolution and the neglect of...

Comparative identification of abiotic stress-responsive differentially expressed genes in chickpea using unsupervised machine learning, and traditional meta-analysis.

BACKGROUND: Climate change poses a growing threat to chickpea production through abiotic stresses such as drought, heat, and salinity. Understanding t...

Equity in Neurotoxicity Care in the Era of Cancer Immunotherapy.

Immunotherapies such as chimeric antigen receptor T cell (CAR-T) therapy and immune checkpoint inhibitors have improved cancer survival but are associ...

A Systematic Evaluation of Cohort Selection Criteria and Their Impact on Machine Learning Model Performance and Demographic Disparities in COVID-19 Outcomes: Cohort Study.

BACKGROUND: Cohort selection criteria play a critical role in shaping machine learning (ML) model performance and the equity of clinical outcome predi...

CLDN18.2 antibody design with protein language models: A deep learning optimization framework.

CLDN18.2 is a promising tumor-specific antigen; however, the development of therapeutic antibodies against it is challenged by the need for simultaneo...

Deep mapping of structural perturbations to energetics enables precise TCR design.

Affinity optimization and cross-reactivity profiling are pivotal for T cell receptor (TCR) engineering but remain hindered by repertoire diversity and...

EEG-Based Effective Connectivity for Automated Detection of Major Depressive Disorder.

Major depressive disorder (MDD) is a prevalent mental health condition with profound consequences on daily functioning and quality of life. Existi...

[Paeoniflorin alleviates cancer-related fatigue during chemotherapy for breast cancer by targeting EZH2/CCNE1 to regulate cell cycle and inflammatory microenvironment].

OBJECTIVES: To explore the molecular mechanisms and key pharmacodynamic basis of Baishao for alleviating cancer-related fatigue (CRF) during chemother...

[Reflections on surgical management strategies for locally advanced gastric cancer after neoadjuvant immunotherapy].

Neoadjuvant immunotherapy is reshaping the treatment landscape of locally advanced gastric cancer (GC). The central clinical challenge has expanded fr...

Integrated evaluation of rapid diagnostic testing, genotypic-phenotypic resistance profiling, and AI-Assisted prediction models for antimicrobial stewardship and clinical outcomes in a resource-limited setting.

INTRODUCTION: Antimicrobial resistance (AMR) remains a major global health concern, necessitating timely and accurate diagnostic approaches to guide a...

The genetic architecture of epilepsy across molecular mechanisms and clinical heterogeneity.

Epilepsy comprises a highly heterogeneous group of neurological disorders unified by a persistent predisposition to recurrent seizures, yet driven by ...

Simulation-Based Machine Learning as a Benchmarking Tool for the Retrospective Identification of IV Fluid Contamination in Basic Metabolic Panels.

BACKGROUND: Current laboratory workflows fail to reliably capture intravenous fluid contamination of chemistry results, leading to diagnostic uncertai...

Mechanistic insights into Claudin-14 dysfunction implicated in veins of Galen malformation.

Claudin-14 (CLDN14) is a key component of tight junctions (TJs) critical for maintaining paracellular barrier function. Variants of CLDN14 have been l...

A blinded, prospective benchmark of in silico antibody discovery anchored to experimental affinity and developability.

Experimentally validated prospective, blinded benchmarks are needed to separate durable advances from hype in computational antibody design. Here AInt...

Nanotechnology-based immunotherapy: integrating Artificial Intelligence (AI) with current strategies in combating brain cancer disease.

Brain cancer is one of the most challenging malignancies and a major contributor to worldwide morbidity and mortality. Glioblastoma, the most aggressi...

Characterization of Genetic Risk Factors of Cerebral Small Vessel Disease Based on Large-scale Transcriptome Profiling.

Cerebral small vessel disease (CSVD) is a major contributor to stroke and dementia, and it endangers the health of older individuals (>50 years old). ...

External validation of a machine learning-based web application for personalized testing of objective functioning using the five-repetition sit-to-stand test.

PURPOSE: Simple generalized thresholds for assessing functional impairment in clinical testing are limited, as they fail to consider patient-specific ...