FDA General

AI-Assisted Chest X-Ray Interpretation in Resource-Limited Settings: LuAna Stepped-Wedge Trial Protocol.

BACKGROUND: Artificial intelligence (AI) has the potential to transform chest radiography interpretation by enhancing diagnostic accuracy, identifying subtle findings, reducing errors, and helping prioritize patient care. Although chest radiography remains a cost-effective and widely used imaging tool, its effectiveness is limited by overlapping anatomy and variability in clinical expertise. Integ...

An autonomous YOLOv9-edge-to-cloud intelligence system for proactive honeybee mortality mitigation.

Honeybee mortality caused by environmental toxins and natural factors poses a significant threat to global apiculture and biodiversity. While manual hive inspections are labor-intensive, early detection of pesticide-associated mortality is critical for timely evidence collection before residues degrade and for enabling rapid beekeeper response. This study presents an automated early-warning system...

Pharmacologic and expectancy effects in depression: Associations with inter-network resting-state connectivity.

Depression involves dysregulation across large-scale neural networks, yet substantial heterogeneity in resting-state functional connectivity (rsFC) ac...

Machine Learning-Based PAT Tool for Real-Time Residual Moisture Monitoring in Lyophilized Biopharmaceuticals Using NIR Spectroscopy.

There is a growing demand in the pharmaceutical industry to optimize analytical methodologies, reducing time and resource consumption while ensuring r...

Disparities in severe infection risk associated with systemic lupus erythematosus: evidence from a causal forest analysis.

OBJECTIVES: Severe infections are a primary cause of morbidity and premature mortality in patients with Systemic Lupus Erythematosus (SLE). Although S...

Tunable Surface Chemistry of Molten Salt Derived MXenes for Data-Driven Electrochemical Materials Discovery.

The surface chemistry of MXenes is a central factor governing electrochemical performance and has become increasingly complex with the emergence of mo...

Prediction and mechanistic insights into drug-induced reproductive toxicity through integrated machine learning, FAERS-based signal comparison, and network toxicology analyses.

Drug-induced reproductive toxicity is a critical concern in drug safety evaluation, whereas conventional assessment methods are often constrained by h...

Cyclin-dependent kinases as signaling integrators in cancer: Structural evolution, functional plasticity, and drug discovery.

Cyclin-dependent kinases (CDKs), traditionally recognized for their pivotal role in cell cycle control, have emerged as versatile regulators orchestra...

Prioritising search for virtual screening via preliminary interpretable low-feature likelihood-based rankings of drug-target activity measures.

BACKGROUND: Current AI-based Virtual Screening (VS) methods seek to manage ultra-large molecular libraries. To this end, they develop increasingly eff...

Cell wall dynamics and their regulation by biomolecular condensates in plants.

Plant cell walls are dynamic composite structures whose biogenesis, remodelling, and integrity maintenance require coordinated regulation across biosy...

Artificial Intelligence-Based CTA Software for Real-World Detection of Large Vessel Occlusion in Acute Ischemic Stroke.

Background and purpose Artificial intelligence (AI)-based tools for CT angiography (CTA) have been introduced to support rapid detection of large vess...

Artificial Intelligence for Evidence Synthesis of Emerging Biologics to Improve Skeletal Health in Osteogenesis Imperfecta: Systematic Review and Meta-Analysis.

BACKGROUND: Osteogenesis imperfecta (OI) is a rare genetic disorder characterized by bone fragility and recurrent fractures. Emerging biologics demons...

De novo synthesis of large-scale metabolic pathways for natural products and their optimization strategies.

Natural products constitute a vital source for drug discovery, yet extraction from producers is inefficient and chemical synthesis involves complex, l...

Non-advanced age-related macular degeneration: current concepts and future perspectives.

Non-advanced age-related macular degeneration (AMD), encompassing early and intermediate stages, represents a critical therapeutic window before irrev...

Identification of therapeutic targets and postoperative recurrence prediction model construction for hepatocellular carcinoma based on systematic mendelian randomization.

BACKGROUND AND STUDY AIMS: Hepatocellular carcinoma (HCC) has a high risk of postoperative recurrence. This study aimed to develop a transcriptome-bas...

A vision transformer deep learning model for assessing pediatric ileocolic intussusception severity using ultrasound images.

Timely identification of children with ileocolic intussusception likely to fail air-enema reduction is critical to avoid delays and bowel perforation....

Dihydroergotamine alleviates circadian rhythm disorders through predicted interaction with to CRY1.

Circadian rhythm disorders (CRDs) significantly affect human health, yet therapeutic options remain limited. This study employed a multi-scale virtual...

Pedagogical strategies for enhancing critical thinking in nursing students using large language models: a mixed-methods systematic review protocol.

INTRODUCTION: Large language models (LLMs) are rapidly normalising in nursing education. However, evidence regarding their impact on critical thinking...

Development and validation of a disease-syndrome integrated assessment model for AECOPD severity: protocol for a nationwide multicentre cross-sectional study.

INTRODUCTION: Acute exacerbations of chronic obstructive pulmonary disease (AECOPD) accelerate disease progression and increase mortality. Accurate se...

Effects of an AI-VR enhanced flipped classroom on English achievement, metacognitive self-regulation, and learning motivation among EFL learners: the moderating role of technological literacy.

Traditional flipped classrooms often fail to sustain young EFL learners' engagement due to passive pre-class tasks and high self-regulation demands. W...