Behavioral Engagement and Activation Model Study (BEAMS): A latent class analysis of adopters and non-adopters of digital health technologies among people with Type 2 diabetes.

Many people with Type 2 diabetes (T2D) who could benefit from digital health technologies (DHTs) are either not using DHTs or do use them, but not for long enough to reach their behavioral or metabolic goals. We aimed to identify subgroups within DHT adopters and non-adopters and describe their unique profiles to better understand the type of tailored support needed to promote effective and sustained DHT use across a diverse T2D population. We conducted latent class analysis of a sample of adults with T2D who responded to an internet survey between December 2021 and March 2022.

Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study.

Background: In 2017, an estimated 17.3 million adults in the United States experienced at least one major depressive episode, with 35% of them not receiving any treatment. Underdiagnosis of depression has been attributed to many reasons, including stigma surrounding mental health, limited access to medical care, and barriers due to cost.

Development and qualification of a machine learning algorithm for automated hair counting.

Objective: Determining the amount of hair on the scalp has always been an important metric of patient satisfaction for hair growth and hair retention technologies. While simple in concept, this measurement is a difficult, resource intensive task for the dermatologist and the research scientist. Specifically, counting and measuring hair in phototrichogram images is very time consuming and labour intensive.

Age-induced and photoinduced changes in gene expression profiles in facial skin of Caucasian females across 6 decades of age.

Background: Intrinsic and extrinsic factors, including ultraviolet irradiation, lead to visible signs of skin aging.

Objective: We evaluated molecular changes occurring in photoexposed and photoprotected skin of white women 20 to 74 years of age, some of whom appeared substantially younger than their chronologic age.

Methods: Histologic and transcriptomics profiling were conducted on skin biopsy samples of photoexposed (face and dorsal forearm) or photoprotected (buttocks) body sites from 158 women.

Tissue-engineered constructs of human oral mucosa examined by Raman spectroscopy.

A noninvasive quality monitoring of tissue-engineered constructs is a required component of any successful tissue-engineering technique. During a 2-week production period, ex vivo produced oral mucosa-equivalent constructs (EVPOMEs) may encounter adverse culturing conditions that might compromise their quality and render them ineffective. We demonstrate the application of near-infrared Raman spectroscopy to in vitro monitoring of EVPOMEs during their manufacturing process, with the ultimate goal of applying this technology in situ to monitor the grafted EVPOMEs.