Public Health & Policy

Tenuigenin ameliorates Alzheimer's disease by targeting MAP2K1: integrated evidence from network pharmacology and experimental validation.

OBJECTIVE: Alzheimer's disease (AD) is a prevalent neurodegenerative disorder primarily characterized by progressive cognitive impairment and synaptic dysfunction. Despite substantial research efforts, effective therapeutic options remain limited. Tenuigenin (TEN), a principal bioactive constituent isolated from the traditional Chinese medicinal herb Polygala tenuifolia, has demonstrated promising...

From Nutritional Epidemiology to Clinical Translation: Machine Learning Uncovers Antioxidant-Driven Prevention Strategies for Mitigating Cardiovascular-Arthritis Multimorbidity.

BACKGROUND: The aim of this study was to construct a machine learning (ML) model to predict the effect of dietary antioxidants on cardiovascular-arthritis comorbidity. METHODS: In this study, 44 dietary antioxidants were selected based on the National Health and Nutrition Examination Survey data from 2007 to 2010 and from 2017 to 2018, and demographic covariates such as gender and age were include...

The global epidemiology of botulism outbreaks from open-source intelligence, 2017-2024.

BACKGROUND: Botulism is a rare but potentially fatal illness caused by botulinum neurotoxin, with outbreaks reported globally in humans, animals, and ...

Novel Psychoactive Substances: Slaying the Dragon With Artificial Intelligence.

BACKGROUND: The emergence of novel psychoactive substances (NPSs) has overwhelmed forensic, health care, and regulatory systems. Conventional analytic...

Predicting perceived likelihood of future suicide attempts in youth with non-suicidal self-injury: A machine learning approach using LightGBM and SHAP.

OBJECTIVES: Non-suicidal self-injury (NSSI) is a strong predictor and a gateway to suicide attempts (SA) among youth. Therefore, understanding how ind...

Advances in occult cancer screening for patients with unprovoked venous thromboembolism: A narrative review of epidemiology, risk, and clinical strategies.

BACKGROUND: Venous thromboembolism (VTE) and cancer exhibit a bidirectional correlation. The probability of detecting occult cancer in unprovoked VTE ...

Leveraging the Concentration-Gradient Diffusion within a Catalyst-Containing Hydrogel Bilayer Enables Safe and Effective Tooth Whitening and Caries Prevention.

Tooth whitening has attracted considerable attention as it can enhance appearance and improve oral health. Nanocatalysts with peroxidase-like activity...

Machine learning to improve analysis of disability in electronic health records: an untapped opportunity for health inequities research.

Electronic Health Records (EHRs) are a leading source of epidemiological data, but often lack information on a patient's disability status. This gap h...

Development of an Infectious Disease Vulnerability Index (IDVI) for dairy farms: A data-driven approach to assessing risk and informing biosecurity practices.

Dairy farms are vulnerable to a wide range of infectious diseases, which can have significant economic and public health consequences. However, there ...

Cross-sectional analysis of accuracy versus interpretability in Medicare Advantage risk adjustment.

BACKGROUND: Risk adjustment models in Medicare Advantage determine annual payments of over $300 billion in public funds to private companies. Policyma...

Decipher the molecular network of PFOA in inflammatory bowel disease through integrating machine learning, molecular docking strategies, and validation in vitro.

OBJECTIVE: Perfluorooctanoic Acid (PFOA), widely recognized as an enduring environmental pollutant, is associated with immune system disruption and po...

Global mapping of pharmaceutical ecological risk in rivers using machine learning: drivers, hotspots, and compounded water stress.

Pharmaceuticals serve as a double-edged sword: while essential for health care, they are also ubiquitous pollutants that threaten ecosystem. The vast ...

Circadian rhythm: An emerging force for colorectal cancer treatment.

The relationship between circadian rhythm disorder and the occurrence and progression of colorectal cancer (CRC) has received attention. The circadian...

Genetic and epigenetic determinants of injury risk and recovery in elite athletes: toward precision sports medicine.

Musculoskeletal injuries and interindividual variability in recovery remain critical challenges for sustaining elite athletic performance. Despite adv...

Integrating Kolmogorov-Arnold networks with ordinary differential equations for efficient, interpretable, and robust deep learning: Epidemiology of infectious diseases as a case study.

This study extends universal differential equation (UDE) frameworks by integrating the Kolmogorov-Arnold Network (KAN) with ordinary differential equa...

Leveraging artificial intelligence for surgical site infection surveillance: A comparison of 5 large language models.

We conducted a retrospective study to evaluate the performance of 5 large language models in detecting surgical site infections (SSIs), compared with ...

Molecular diagnostics in clinical microbiology: Advances, applications, and future directions.

Molecular diagnostics have transformed clinical microbiology by enabling rapid, accurate, and highly sensitive detection of infectious agents, signifi...

Artificial Intelligence Across the Obesity Continuum: From Mechanistic Insights to Global Precision Prevention and Therapy.

Obesity is a complex, rapidly escalating global health challenge that demands innovation across biology, clinical care, and public health. This review...

Use of human data for risk assessment of pesticides: A review including an evaluation of trichlorfon as case study.

Pesticides are suspected to cause health effects in humans, but human-based data on their toxicity are often insufficient to establish associations an...

Self-reported periodontitis: A multiethnic community-based validation study.

OBJECTIVE: Self-reported periodontal measures offer a practical alternative to clinical examinations in large-scale studies, but few validation effort...