FDA General

Cross-Scale Coupling Perspective: A New Pathway to Break the Selectivity Dilemma of Electrocatalytic Energy Conversion Reactions.

Against the backdrop of global energy transition and carbon neutrality goals, electrocatalysis stands as a core technology for efficient conversion of renewable energy and green chemical synthesis, and its selectivity regulation has become a prominent research hotspot. Nevertheless, most existing studies focus merely on a single scale, such as atomic-level electronic structures or macroscopic mass...

Deep Learning-Based Enhancement of Already Diagnostic-Quality MRI for Alzheimer's Disease Classification: Effects on Model Performance and Training Data Requirements.

BACKGROUND: Deep learning (DL)-based image enhancement is widely used to improve suboptimal medical imaging. Whether it also benefits diagnostic-quality MRI in downstream task performance and data-efficiency remains unclear. PURPOSE: To investigate the impact of DL-based enhancement applied to diagnostic quality structural MRI for Alzheimer's disease (AD) classification. STUDY TYPE: Retrospective....

From user to manufacturer: How substantial modification of medical AI crosses the product liability threshold under the revised PLD.

The revised Product Liability Directive (rPLD) introduces a pivotal shift in the liability landscape for healthcare professionals using artificial int...

Smart-delivery systems for intestinal mucosal homeostasis: From barrier penetration to precision regulation.

As an important barrier tissue, the intestinal mucosa is responsible for regulating immunity, absorbing nutrients, and maintaining microbial homeostas...

Shedding light on neural learning to rank models for anticancer drug prioritization.

Learning to Rank (LeToR) methods have gained increasing attention in drug response prediction, offering a direct way to prioritize effective treatment...

Stabilizing Anion-Derived Interphase by Machine-Learning-Accelerated Screening of Out-of-Shell Co-Solvents for Aqueous Zinc Batteries.

Aqueous zinc batteries (AZBs) lack a stable anion-derived solid electrolyte interphase (SEI) on the Zn anode, resulting in severe competition between ...

Rapid Resolution of Hypoxemia is Common and Associated with Lower Mortality Among Intubated Patients with Acute Hypoxemic Respiratory Failure.

ObjectiveTo evaluate the prevalence, clinical trajectory, and biologic phenotype of patients with rapidly improving acute hypoxemic respiratory failur...

Short-Term Efficacy of the Artificial Intelligence HeartBot II in Increasing Awareness and Knowledge of Heart Attack in Women: Protocol for a Randomized Controlled Trial With a Waitlist Control.

BACKGROUND: Heart disease remains a leading cause of death for women in the United States. Despite this burden, awareness that heart disease is the le...

Structural basis of enzymatic functional divergence in the PAL gene family of Salix brachista: Allosteric regulation and catalytic activity mediated by non-catalytic sites.

Phenylalanine ammonia-lyase (PAL) is the rate-limiting enzyme of the plant phenylpropanoid pathway, and its functional divergence is closely associate...

Autonomous Ultrasound Systems: Are We Approaching the Era of Self-Directed Imaging?

BACKGROUND: Ultrasound remains one of the most widely used imaging modalities in clinical practice; however, its effectiveness is highly dependent on ...

Artificial intelligence in dermatologic pharmacokinetics: quantitative modeling, clinical translation, and optimization of precision therapeutics.

INTRODUCTION: Dermatology is rapidly transitioning from broad-spectrum therapies toward biologics, nanotechnology-based drug delivery, and precision t...

Reliability of AI Methods in Drug Discovery: Evaluation of Boltz-2 for Structure and Binding Affinity Prediction.

Despite continuing hype about the role of AI in drug discovery, no "AI-discovered drugs" have so far received regulatory approval. Here we assess one ...

Network-guided transcriptomics identifies drug-linked host-response biomarkers in tuberculosis disease-state transition.

Distinguishing active tuberculosis (ATB) from the post-therapy state remains a key challenge in disease monitoring, as host-response signatures are of...

Real-world analysis of depression-related adverse events associated with the adsorbed anthrax vaccine: integrating pharmacovigilance signals, machine learning risk prediction, and transcriptomic mechanisms.

BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...

AI-assisted software for chronic wound detection: Development, validation, and certification strategy.

AIMS: This study evaluates the feasibility of an artificial intelligence (AI)-assisted software tool for early identification and classification of ch...

Social Media as a Driver of Obesity in Children and Adolescents (Aged 6-18 Years): It Is Time for Regulatory Action.

Obesity in children and adolescents is rising in China and globally, with health consequences that are already evident during childhood. This Viewpoin...

Adaptive voice interaction as a cognitive regulation mechanism during second-language listening: The roles of learner agency and listening anxiety.

The increasing integration of artificial intelligence into learning environments has created new opportunities to examine how adaptive technologies in...

Integrated design of an efficient multi spectral imaging and federated learning framework for precision crop disease diagnosis in low-resource farming communities.

Crop diseases pose significant challenges to productivity in resource-constrained settings, often remaining undiagnosed when diagnostic tools and infr...

Consumer Perceptions of the German Food-Based Dietary Guidelines and the Complementary Potential of AI-Based Nutrition Tools.

Food-based dietary guidelines (FBDGs) are a key instrument for communicating healthy nutrition principles that are implemented in most countries. Howe...

Exploring the mediating role of willingness to communicate between self-regulation, professor-student rapport, and learner engagement in GenAI-supported learning: A mixed-methods study.

The present study investigates the relationships among self-regulation, professor-student rapport, willingness to communicate, and learner engagement ...