Challenges in Total Ankle Replacement in Post-Traumatic Ankle Osteoarthritis.

A previous trauma is the most common origin of ankle osteoarthritis. Patients with post-traumatic osteoarthritis are generally younger. Due to the previous trauma and surgical treatment, the surrounding soft tissues are often scarred and inelastic.

HERC1 E3 Ubiquitin Ligase Is Necessary for Autophagy Processes and for the Maintenance and Homeostasis of Vesicles in Motor Nerve Terminals, but Not for Proteasomal Activity.

The ubiquitin proteasome system (UPS) is implicated in protein homeostasis. One of the proteins involved in this system is HERC1 E3 ubiquitin ligase, which was associated with several processes including the normal development and neurotransmission at the neuromuscular junction (NMJ), autophagy in projection neurons, myelination of the peripheral nervous system, among others. The tambaleante (tbl) mouse model carries the spontaneous mutation Gly483Glu substitution in the HERC1 E3 protein.

Coping and Social Support in Relation to Minority Stress and Cigarette Smoking Among Lesbian, Gay, and Bisexual Veterans.

The intersection between a minoritized sexual orientation identity and a U.S. military Veteran status places lesbian, gay, and bisexual (LGB) Veterans at increased risk for cigarette smoking.

Evaluation of PFAS extraction and analysis methods for biosolids.

Per- and polyfluoroalkyl substances (PFAS) in the environment is a growing concern leading to a focus on PFAS occurrence in biosolids, a byproduct of wastewater treatment processes, often applied to improve soil health. This led to the need for analytical method development for assessing PFAS in biosolids. This study compares three methods for PFAS quantitation, evaluating solvent extraction, clean-up techniques, and final injection solvents.

An explainable analysis of diabetes mellitus using statistical and artificial intelligence techniques.

Background: Diabetes mellitus (DM) is a chronic disease prevalent worldwide, requiring a multifaceted analytical approach to improve early detection and subsequent mitigation of morbidity and mortality rates. This research aimed to develop an explainable analysis of DM by combining sociodemographic and clinical data with statistical and artificial intelligence (AI) techniques.

Methods: Leveraging a small dataset that includes sociodemographic and clinical profiles of diabetic and non-diabetic individuals, we employed a diverse set of statistical and AI models for predictive purposes and assessment of DM risk factors.