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Background: Beyond physical health, managing type 1 diabetes (T1D) also encompasses a psychological component, including diabetes distress, that is, the worries, fears, and frustrations associated with meeting self-care demands over the lifetime. While digital health solutions have been increasingly used to address emotional health in diabetes, these technologies may not uniformly meet the unique concerns and technological savvy across all age groups.

Objective: This study aimed to explore the mental health needs of adolescents with T1D, determine their preferred modalities for app-based mental health support, and identify desirable design features for peer-delivered mental health support modeled on an app designed for adults with T1D.

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Background: Depression significantly impacts an individual's thoughts, emotions, behaviors, and moods; this prevalent mental health condition affects millions globally. Traditional approaches to detecting and treating depression rely on questionnaires and personal interviews, which can be time consuming and potentially inefficient. As social media has permanently shifted the pattern of our daily communications, social media postings can offer new perspectives in understanding mental illness in individuals because they provide an unbiased exploration of their language use and behavioral patterns.

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Current literature is unclear on the safety and optimal timing of delivery for pregnant individuals with gestational diabetes mellitus, which inspired our study team to conduct a web-based survey study exploring patient and provider opinions on delivery options. However, an incident of fraudulent activity with survey responses prompted a shift in the focus of the research project. Unfortunately, despite the significant rise of web-based surveys used in medical research, there remains very limited evidence on the implications of and optimal methods to handle fraudulent web-based survey responses.

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The Canadian Genomics Research and Development Initiative for Antimicrobial Resistance (GRDI-AMR) uses a genomics-based approach to understand how health care, food production and the environment contribute to the development of antimicrobial resistance. Integrating genomics contextual data streams across the One Health continuum is challenging because of the diversity in data scope, content and structure. To better enable data harmonization for analyses, a contextual data standard was developed.

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Application of the 6-SNP elevated LDL-cholesterol polygenic risk score in individuals with familial hypercholesterolemia phenotype from an Argentine population.

Gac Med Mex

January 2025

Universidad de Buenos Aires, Facultad de Farmacia y Bioquímica, Departamento de Bioquímica Clínica, Laboratorio de Lípidos y Aterosclerosis, Ciudad Autónoma de Buenos Aires.

Introduction: LDL-cholesterol greater than 190 mg/dL indicates severe hypercholesterolemia (HS) of monogenic and/or polygenic origin. Genetic risk scores (GRS) evaluate potential polygenic causes.

Objective: we applied a GRS of 6-SNP (GRS-6) in HS individuals.

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