Distribution-based sub-population selection (DSPS): A method for in-silico reproduction of clinical trials outcomes.

Diabetes presents a significant challenge to healthcare due to the short- and long-term complications associated with poor blood sugar control. Computer simulation platforms have emerged as promising tools for advancing diabetes therapy by simulating patient responses to treatments in a virtual environment. The University of Virginia Virtual Lab (UVLab) is a new simulation platform engineered to mimic the metabolic behavior of individuals with type 2 diabetes (T2D) using a mathematical model of glucose homeostasis in T2D and a large population of 6062 virtual subjects.

The Virtual DCCT: Adding Continuous Glucose Monitoring to a Landmark Clinical Trial for Prediction of Microvascular Complications.

Using a multistep machine-learning procedure, add virtual continuous glucose monitoring (CGM) traces to the original sparse data of the landmark Diabetes Control and Complications Trial (DCCT). Assess the association of CGM metrics with the microvascular complications of type 1 diabetes observed during the DCCT and establish time-in-range (TIR) as a viable marker of glycemic control. Utilizing the DCCT glycated hemoglobin data obtained every 1 or 3 months plus quarterly 7-point blood glucose (BG) profiles in a multistep procedure: (i) utilized archival BG traces to model interday BG variability and estimate glycated hemoglobin; (ii) trained across the DCCT BG profiles and associated each profile with an archival BG trace; and (iii) used previously identified CGM "motifs" to associate a CGM trace to a BG trace, for each DCCT participant.

Bat RNA viruses employ viral RHIMs orchestrating species-specific cell death programs linked to Z-RNA sensing and ZBP1-RIPK3 signaling.

RHIM is a protein motif facilitating the assembly of large signaling complexes triggering regulated cell death. A few DNA viruses employ viral RHIMs mimicking host RHIMs and counteract cell death by interacting with host RHIM-proteins to alleviate antiviral defenses. Whether RNA viruses operate such viral RHIMs remains unknown.

Unmet Needs, Pain, Shame, Regret, and Loss of Identity among Men with Urethral Injuries Resulting from Traffic Accidents; A Qualitative Study.

Introduction: Urethral injuries are the most severe injuries caused by high-energy mechanisms such as traffic accidents, which have significant long-term serious consequences on the quality of life of the injured.

Objectives: Exploration of lived experiences of urethral injury in traffic accident victims is the main goal of this study.

Methods: This is a phenomenological qualitative study among men suffering from urethral injuries due to traffic accidents and referred to hospitals for urethroplasty in Iran.