Objective Neighborhood-Level Disorder Versus Subjective Safety as Predictors of HIV Transmission Risk and Momentary Well-Being.

Mental health and HIV risk behavior have been studied with ecological momentary assessment (EMA), but this approach has not been combined with tracking of activity space (where people go and what they encounter there) in people with HIV and their social relations, who may be HIV+ or HIV-. Activity space represents a modifiable risk or protective factor for behavior related to health status and quality of life, in both clinical and nonclinical populations. We conducted an observational study with 286 participants (243 HIV+ and 43 HIV-), roughly matched for socioeconomic status and neighborhood of residence via three waves of snowball sampling.

Predictability of buprenorphine-naloxone treatment retention: A multi-site analysis combining electronic health records and machine learning.

Background And Aims: Opioid use disorder (OUD) and opioid dependence lead to significant morbidity and mortality, yet treatment retention, crucial for the effectiveness of medications like buprenorphine-naloxone, remains unpredictable. Our objective was to determine the predictability of 6-month retention in buprenorphine-naloxone treatment using electronic health record (EHR) data from diverse clinical settings and to identify key predictors.

Design: This retrospective observational study developed and validated machine learning-based clinical risk prediction models using EHR data.

Targeting 14-3-3θ-mediated TDP-43 pathology in amyotrophic lateral sclerosis and frontotemporal dementia mice.

Amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD) are characterized by cytoplasmic deposition of the nuclear TAR-binding protein 43 (TDP-43). Although cytoplasmic re-localization of TDP-43 is a key event in the pathogenesis of ALS/FTD, the underlying mechanisms remain unknown. Here, we identified a non-canonical interaction between 14-3-3θ and TDP-43, which regulates nuclear-cytoplasmic shuttling.

Health Outcomes by Neighborhood (HON): Effects of Neighborhood, Social Instability, and Health Factors on 12-Month Trajectories of Substance-Use Disorder Symptoms.

Background: Previous studies have shown that environment and health can influence drug use trajectories and the effects of substance use disorder (SUD) treatments. We hypothesized that trajectories of drug use-related problems, based on changes in DSM-5 symptoms, would vary by type(s) of drugs used, health factors, and neighborhood characteristics.

Methods: We assessed mental and physical health, stress, social instability, neighborhood characteristics (disorderliness and home value), and DSM-5 symptom counts at two study visits, 12 months apart, in a community sample (baseline  = 735) in Baltimore, MD.