Prescriptions

MPLID (Membrane Protein-Lipid Interaction Database): A Large-Scale Experimental Resource of Residue-Level Protein-Lipid Contacts.

BACKGROUND: Membrane proteins constitute approximately 20-30% of all proteomes and represent over 60% of current drug targets. Although protein-lipid interactions play important structural and regulatory roles in membrane-associated proteins, most existing structural resources focus on identifying whether a residue lies within a membrane region, typically inferred from computational hydrophobicity...

Systematic Benchmarking of CRISPR-Cas9 Off-Target Prediction Tools Reveals Limitations and Implications for Preclinical Assessment.

Accurate identification of CRISPR-Cas9 off-target sites is essential for the safety assessment of genome-editing-based therapies. While numerous in silico prediction tools have been developed, their comparative performance and practical utility in preclinical workflows remain incompletely defined. We performed a systematic benchmarking of 14 in silico CRISPR-Cas9 off-target prediction tools, inclu...

Physics-informed interaction modeling for warning targeting in multi-risk driving scenarios.

In multi-risk traffic, a warning is valuable only if it directs the driver's limited attention to the right interaction counterpart early enough to pr...

Diagnostic Performance of Large Language Models for Orthopedic-Related Rare Diseases and Their Impact on Physicians' Diagnostic Accuracy: 2-Stage Comparative Evaluation Study Based on the Chinese Rare Disease Catalog.

BACKGROUND: Orthopedic-related rare diseases are difficult to diagnose because of their low prevalence, heterogeneous phenotypes, and fragmented knowl...

First-pass aspiration versus stent retriever thrombectomy: machine learning study of treatment effect heterogeneity.

BACKGROUND: Randomized trials have shown equivocal outcomes between a direct aspiration as first-pass technique (ADAPT) and stent retriever (SR) strok...

TextDTI: A Multimodal Context Representation Learning Framework for Drug-Target Interaction Prediction.

Predicting Drug-Target Interactions (DTIs) is a crucial task in drug discovery. Recent advances in deep learning, particularly the application of Larg...

Machine learning classification of frailty using wearable-derived sleep metrics in community-dwelling older adults.

INTRODUCTION: Frailty is a multifactorial geriatric syndrome, and sleep disturbances have emerged as a potential contributing factor. However, convent...

Rapid Development and Testing of Behavioral Text Message Reminders for Antidepressant Adherence via Online Panels: Survey Study.

BACKGROUND: SMS text message reminders have been used to promote many health behaviors, such as improving diet and physical activity, managing chronic...

Risk-Tiered Governance for Hospital Artificial Intelligence: A Framework Synthesis and Implementation Pathway.

OBJECTIVES: Hospital artificial intelligence (AI) is increasingly embedded in electronic health record workflows, cloud inference pipelines, imaging, ...

Double deletion mutation induced active site remodelling modulates substrate specificity in KPC-14 β-lactamase.

The emergence of KPC variants with altered substrate profiles poses a major challenge for β-lactam antibiotic therapy. KPC-14, which contains a double...

A large-scale comparative study of YOLO-based detectors for ischemic stroke lesion localization on diffusion-weighted imaging.

Ischemic stroke lesion localization on diffusion-weighted imaging (DWI) remains challenging because acute lesions may be small, faint, irregular, or m...

Machine learning-based prediction of shigellosis in children under five: development and internal validation of a prediction model.

OBJECTIVES: Shigella remains a major cause of diarrhoea and mortality in children under five in low- and middle-income countries, where laboratory con...

Artificial intelligence in impurity prediction: current landscape, challenges, and future directions.

Earlier identification, regulation of impurities in pharmaceutical products is critical throughout the medication development process because they hav...

[Translated article] Protocol for the development and validation of a questionnaire to evaluate user-robot interaction in the compounding of hazardous drugs in a hospital setting.

INTRODUCTION: The automation of hazardous drug preparation in hospitals using robotic systems is an effective strategy to enhance safety, quality, and...

Mol2Image: an enhanced DDI prediction framework leveraging drug molecular descriptors.

Drug-drug interactions (DDIs) are a critical safety issue in clinical practice, as they can lead to severe and often unpredictable adverse effects. Th...

Development of a risk prediction model for rheumatoid arthritis-associated interstitial lung disease based on interpretable machine learning.

OBJECTIVE: This study constructed a predictive model for interstitial lung disease (ILD) in patients with rheumatoid arthritis (RA) and explored the v...

The Challenge of Integrating Artificial Intelligence into Clinical Reasoning by Augmenting the Physician's Central Cognitive Role.

Artificial intelligence is reshaping how physicians reason, yet the cognitive dimension of sustained physician-LLM interaction remains conceptually un...

Diagnosis of Neurological Dysfunction from EEG Signals Using DuelQ-SeizureNet and Meta Black Ant Optimization for Epileptic Seizure Detection.

BACKGROUND: Early diagnosis of neurological dysfunctions, particularly epilepsy, is vital for early intervention and improvement of patients' quality ...

Multi-omics and artificial intelligence nominate PCLAF as a prognostic and druggable target for hepatitis B virus-associated hepatocellular carcinoma.

BACKGROUND: PCLAF (PCNA clamp-associated factor) is a protein involved in DNA replication and DNA repair. Aberrant PCLAF expression has been reported ...

Deep Learning-Driven Anticancer Drug Discovery: Emodepside as a Potential Therapeutic Candidate for Triple-Negative Breast Cancer.

Triple-negative breast cancer (TNBC) is an aggressive breast cancer subtype with a poor prognosis. The absence of effective targeted therapies and end...