Ledged Beam Walking Test Automatic Tracker: Artificial intelligence-based functional evaluation in a stroke model.

The quantitative evaluation of motor function in experimental stroke models is essential for the preclinical assessment of new therapeutic strategies that can be transferred to clinical research; however, conventional assessment tests are hampered by the evaluator's subjectivity. We present an artificial intelligence-based system for the automatic, accurate, and objective analysis of target parameters evaluated by the ledged beam walking test, which offers higher sensitivity than the current methodology based on manual and visual counting. This system employs a residual deep network model, trained with DeepLabCut (DLC) to extract target paretic hindlimb coordinates, which are categorized to provide a ratio measurement of the animal's neurological deficit.

Evolving Trends and Patterns of Utilization of Magnetic Resonance-Guided Radiotherapy at a Single Institution, 2018-2024.

: Over the past decade, significant advances have been made in image-guided radiotherapy (RT) particularly with the introduction of magnetic resonance (MR)-guided radiotherapy (MRgRT). However, the optimal clinical applications of MRgRT are still evolving. The intent of this analysis was to describe our institutional MRgRT utilization patterns and evolution therein, specifically as an early adopter within a center endowed with multiple other technology platforms.

Floral traits underlying mating system differentiation in the wind-pollinated sister species and .

The shift from outcrossing to predominantly selfing is one of the most common transitions in plant evolution. This evolutionary shift has received considerable attention from biologists; however, this work has almost exclusively been focused on animal-pollinated systems. Despite the seminal ecological and economic importance of wind-pollinated species, the mechanisms controlling the degree of outcrossing in wind-pollinated taxa remain poorly understood.

Interaction between breastfeeding duration and an obesity genetic risk score to predict body fat composition in European adolescents: The HELENA study.

Background: Although the genetic interplay with the environment has a major impact on obesity development, little is known on whether breastfeeding could modulate the genetic predisposition to obesity.

Objectives: To investigate whether breastfeeding attenuates the effect of an obesity genetic risk score (GRS) on adiposity in European adolescents.

Methods: Totally 751 adolescents from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) cross-sectional study were included, divided according to breastfeeding status into never breastfed, 1-3 months and ≥4 months.