Play Nicely Program in the prevention of violence against children: strengthening sustainable development.

Objective: to understand the perception of teachers and health professionals regarding the use of the Play Nicely Program for parents/caregivers in the prevention of violence against children.

Method: a descriptive and exploratory qualitative study was conducted through three focus groups with twenty primary school teachers and primary health care professionals who implemented the Program for parents/caregivers in 2022. The data analysis was guided by French discourse analysis, interpreted through the lens of Urie Bronfenbrenner's theory.

A multi-analytical study of the Montelirio beaded attires: Marine resources, sumptuary crafts, and female power in copper age Iberia.

Excellent indicators of technology, social organization, exchange patterns, and even beliefs, beads are a topic of research in their own right. Findings made between 2010 and 2011 at the Montelirio tholos burial, part of the Valencina Copper Age mega-site, in south-western Spain, revealed what amounts to the largest single-burial ever-documented assemblage of beads. Furthermore, the Montelirio beads were part of unparalleled beaded attires worn by some of the people buried in the grave, mostly females.

Impact of Endorectal Coil Use on Extraprostatic Extension Detection in Prostate MRI: A Retrospective Monocentric Study.

Rationale And Objectives: Accurate preoperative mpMRI-based detection of extraprostatic extension (EPE) in prostate cancer (PCa) is critical for surgical planning and patient outcomes. This study aims to evaluate the impact of endorectal coil (ERC) use on the diagnostic performance of mpMRI in detecting EPE.

Materials And Methods: This retrospective study with prospectively collected data included participants who underwent mpMRI and subsequent radical prostatectomy for PCa between 2007 and 2024.

Masked Image Modeling Meets Self-Distillation: A Transformer-Based Prostate Gland Segmentation Framework for Pathology Slides.

Detailed evaluation of prostate cancer glands is an essential yet labor-intensive step in grading prostate cancer. Gland segmentation can serve as a valuable preliminary step for machine-learning-based downstream tasks, such as Gleason grading, patient classification, cancer biomarker building, and survival analysis. Despite its importance, there is currently a lack of a reliable gland segmentation model for prostate cancer.