Addictions

Prompt-engineering improves clinical safety of large language models for opioid equipotency conversion

Background: Large language models (LLMs) are increasingly used in medical education and clinical decision-making, but their reliability in high-risk medication dosing remains unclear. Opioid rotation is a common task requiring precise calculations where errors may result in overdose or inadequate pain relief. Methods: Thirteen LLMs were tested using an API-based framework to ensure independent que...

A widespread internal brain state for fentanyl withdrawal

Opioid addiction is characterized by escalating drug use, driven in part by negative reinforcement from withdrawal, but the neural processes linking withdrawal to increased drug-taking remain poorly understood. Here, we use multisite local field potential recordings and interpretable machine learning to identify large-scale brain networks engaged by repeated opioid exposure and withdrawal. After d...

TRACED: In vivo imaging of extracellular intrinsic diffusivity, tortuosity, cell size distribution and cell density in human glioma patients

The lack of analytical models describing diffusion time dependence at intermediate time scales in complex tissue microstructure limits the accurate qu...

Dual GLP-1/FGF21 agonism suppresses voluntary alcohol consumption, alcohol choice, and nucleus accumbens dopamine modulation

Excessive alcohol consumption remains a major public health challenge with limited therapeutic options. Both glucagon-like peptide-1 (GLP-1) and fibro...

Prediction of Alzheimer's Disease Risk Factors from Retinal Images via Deep Learning: Development and Validation of Biologically Relevant Morphological Associations in the UK Biobank

The systemic, metabolic, lifestyle factors have established associations with Alzheimer's Disease (AD) through epidemiologic and AD-specific biomarker...

Multidimensional Mechanistic Study of Panax Notoginseng Saponins in the Treatment of Alcohol-Induced Osteonecrosis of the Femoral Head: Integrating Network Pharmacology, Molecular Dynamics Simulation and In Vivo Validation

Background: Alcohol-induced osteonecrosis of the femoral head (AIONFH) is an orthopedic disorder from chronic alcohol abuse, characterized by disrupte...

Predicting one-year postoperative functional status in contrast-enhancing glioma

Background and Objectives Preoperative prediction of functional outcomes in contrast-enhancing glioma could support surgical decision-making and patie...

Deep-testing: the case of dependence detection

Deep learning methods have proved highly effective for classification and image recognition problems. In this paper, we ask whether this success can b...

TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical...

TopoMamba: Topology-Aware Scanning and Fusion for Segmenting Heterogeneous Medical Visual Media

Visual state-space models (SSMs) have shown strong potential for medical image segmentation, yet their effectiveness is often limited by two practical...

A Deep Learning-Based Scoring Framework for Large-Scale Multi-Donor Cardiotoxicity Screening

Cardiotoxicity remains a major cause of drug attrition and post-market withdrawal, yet the vast majority of environmental chemicals to which humans ma...

A Machine Learning Based Causal Interface for Time-Varying Environmental Predictors of Substance Use Initiation in the ABCD Study

Background: The Adolescent Brain Cognitive Development (ABCD) Study provides rich longitudinal data on environmental, genetic, and behavioral factors ...

Reinforcement learning for closed-loop optimisation of spatiotemporal stimulation in patterned neuronal networks

Understanding how neuronal circuits transform inputs into outputs requires systematic perturbation under controlled conditions. In vitro neuronal netw...

Sustaining Control and Agency Under Threat: Computational Pathways to Persistence and Escape

Adaptive behavior requires deciding when to persist and when to disengage under uncertainty and partial outcome control. Avoidance has often been stud...

Case-Grounded Evidence Verification: A Framework for Constructing Evidence-Sensitive Supervision

Evidence-grounded reasoning requires more than attaching retrieved text to a prediction: a model should make decisions that depend on whether the prov...

Development and Temporal Evaluation of Multimodal Machine Learning Models to Predict High Inpatient Opioid Exposure

High inpatient opioid exposure is associated with increased risk of persistent opioid use. Early identification of high-risk patients may improve opio...

Evolutionary exploration of drug-like chemical space utilizing generative AI and virtual screening

The identification of suitable lead molecules in the vast chemical space is a critical and challenging task in drug discovery campaigns. Recently, it ...

Altered EEG markers of reward learning during abstinence in alcohol dependence: a probabilistic reversal learning study

Maladaptive reward learning and decision-making circuity are key factors in the onset and progression of alcohol use disorder and have therefore emerg...

Opioids Overdose Death Prediction with Graph Neural Networks

The opioid crisis has severely impacted Ohio, with overdose death rates surpassing national averages and disproportionately affecting rural and Appala...

Seismic full-waveform inversion based on a physics-driven generative adversarial network

Objectives: Full-waveform inversion (FWI) is a high-resolution geophysical imaging technique that reconstructs subsurface velocity models by iterative...