COVID-19

Artificial intelligence in food allergen detection and prediction: advances, methodologies, and challenges.

Food allergies affect over 220 million individuals worldwide and present increasing challenges due to complex food matrices and processing-induced protein modifications. Conventional detection methods, including immunoassays, PCR, and mass spectrometry, provide reliable analytical tools but are often limited by matrix interference, cross-reactivity, and labor-intensive workflows. Artificial intell...

Prediction of hospitalisation in young children with pneumonia in Malawi: A machine learning-based approach.

BACKGROUND: Globally, pneumonia remains the single biggest cause of mortality in children under 5 years of age. This study sought to train and test a prediction model for hospitalisation within 7 days after initial presentation in 2- to 59-month-old Malawian children with WHO-defined pneumonia in primary care and compare its performance to existing risk prediction models. METHODS AND FINDINGS: BIO...

Acanthamoeba Keratitis: Recent Advances in Diagnosis and Management.

PURPOSE: To review recent advances in the diagnosis and management of acanthamoeba keratitis (AK), emphasizing clinically relevant developments from t...

Heat shock protein-mediated remodeling of the bone immune microenvironment: mechanisms and precision therapeutic strategies for osteoporosis.

BACKGROUND: Osteoporosis is a systemic bone disorder marked by reduced bone mass and deteriorating bone microstructure, commonly associated with infla...

Development and interpretability of a machine learning-derived model for the identification of latent prostate cancer in patients initially diagnosed with benign prostatic hyperplasia: a retrospective cohort study.

BACKGROUND: Prostate cancer (PCa) is characterized by pronounced intratumoral heterogeneity and multifocality, presenting ongoing challenges for early...

Organic Materials of Tomorrow: Horizons of Artificial Intelligence.

Artificial intelligence (AI) is transforming organic materials discovery by enabling the rapid exploration of chemical space. This review examines mac...

Molecular Encoding during Amplification Enables Multiplex Nanopore Profiling of Small Noncoding RNAs.

Many cancers are characterized by the coordinated dysregulation of multiple small noncoding RNAs (sncRNAs), yet fluorescence-based assays such as quan...

Machine learning-driven optimization of specific, compact, and efficient base editors via single-round diversification.

Base editing shows great potential in research and clinical applications. Current iterations of the deaminases used to create precise single-nucleotid...

Deep Learning Predicts Mutations and Outcomes in Gastrointestinal Stromal Tumors from Whole-Slide Images.

Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase (KIT) and platelet-deri...

Dynamics of collectivistic language and emotional expression in China's early pandemic: A social media analysis.

Crises can produce contradictory responses in collectivistic cultures, yielding both solidarity and fragmentation. We propose these paradoxes can be u...

Cropland mask dataset for the Canadian Prairies derived from Google satellite embedding imagery.

This article presents a spatially explicit persistent cropland mask for the Canadian prairies covering Alberta, Saskatchewan, Manitoba. Data was gener...

Machine learning methods identified cellular senescence-related hub molecules in sepsis-induced acute respiratory distress syndrome (ARDS) and their upstream regulatory network.

BACKGROUND: Sepsis-induced ARDS demonstrated greater severity and higher mortality compared to ARDS triggered by other factors. In this article, we co...

Multimodal Artificial Intelligence Prediction of Abiraterone Efficacy in Two STAMPEDE Phase 3 Trials of Non-Metastatic Very High-Risk Prostate Cancer.

BACKGROUND: Long-term androgen deprivation therapy (LT-ADT) with radiotherapy is standard-of-care for high-risk localized prostate cancer, with abirat...

End to End Proximal Anastomosis is the Sole Modifiable Variable in Risk Score for Loss of Patency of Aortobifemoral Artery Bypass After Index Operative Hospitalization.

OBJECTIVE: The purpose of this study was to create a risk score for loss of aorto-bifemoral artery bypass (ABF) patency utilizing preoperative, periop...

Integrated multi-omics and experimental validation reveal CSK and FBLN1 as key targets of stanozolol in accelerating atherosclerosis.

BACKGROUND: Stanozolol, a synthetic anabolic androgenic steroid (AAS) widely abused to enhance performance, has poorly defined toxicological mechanism...

Resolving variants of uncertain significance in neurofibromatosis: An integrated approach combining deep learning and minigene assays.

Neurofibromatosis (NF) comprises genetic disorders mainly caused by pathogenic variants, yet its phenotypic and genotypic heterogeneity complicates di...

Public announcements and mask use during COVID-19 bridging regression and machine learning.

The effectiveness of public health policies has a major impact on society. Throughout the COVID-19 pandemic, policy-makers worldwide introduced variou...

Identification of potential key efferocytosis-related genes in rheumatoid arthritis using machine learning.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by synovial inflammation and joint destruction. Efferocytosis is a...

A decision-oriented framework for genomic testing across the prostate cancer continuum.

Genomic testing is now embedded in contemporary prostate cancer care, yet the clinical meaning of different genomic platforms varies substantially by ...

Understanding resistance in glioblastoma: insights into personalized and targeted therapeutic strategies.

Glioblastoma multiforme (GBM) is the most common and aggressive primary malignant brain tumor. Despite combined treatments, including surgical removal...