Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1086/595557 | DOI Listing |
HIV Res Clin Pract
December 2025
Division of Infectious Diseases and Global Public Health, School of Medicine, University of California San Diego (UCSD), La Jolla, CA, USA.
Background: HIV remains a major challenge in KwaZulu-Natal, South Africa, particularly for young women who face disproportionate risks and barriers to prevention and treatment. Most HIV cure trials, however, occur in high-income countries.
Objective: To examine the perspectives of young women diagnosed with acute HIV in a longitudinal study, focusing on their perceptions on ATI-inclusive HIV cure trials and the barriers and facilitators to participation.
Clin Nurs Res
January 2025
Mayo Clinic, Jacksonville, FL, USA.
This study aimed to explore contextual elements of the cancer experience that are consistently distressing and/or psychologically traumatic, as well as explore perceptions of Accelerated Resolution Therapy® (ART®) and its influence on the cancer experience. Using a qualitative descriptive design, semi-structured interviews were completed by 12 participants following the completion of ART. Interview data were analyzed using content analysis to identify major themes and patterns.
View Article and Find Full Text PDFBone Marrow Transplant
January 2025
Université de Franche-Comté, EFS, INSERM, UMR RIGHT, F-, 25000, Besançon, France.
The accessibility of CAR-T cells in centralized production models faces significant challenges, primarily stemming from logistical complexities and prohibitive costs. However, European Regulation EC No. 1394/2007 introduced a pivotal provision known as the hospital exemption.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Psychology, Faculty of Behavioural and Social Sciences, University of Groningen, Grote Kruisstraat 2/1, 9712TS, Groningen, The Netherlands.
Recruits are exposed to high levels of psychological and physical stress during the special forces selection period, resulting in dropout rates of up to 80%. To identify who likely drops out, we assessed a group of 249 recruits, every week of the selection program, on their self-efficacy, motivation, experienced psychological and physical stress, and recovery. Using linear regression as well as state-of-the-art machine learning techniques, we aimed to build a model that could meaningfully predict dropout while remaining interpretable.
View Article and Find Full Text PDFSci Rep
January 2025
College of Information Science and Technology, Hainan Normal University, Haikou, 571158, China.
Breast cancer is one of the most aggressive types of cancer, and its early diagnosis is crucial for reducing mortality rates and ensuring timely treatment. Computer-aided diagnosis systems provide automated mammography image processing, interpretation, and grading. However, since the currently existing methods suffer from such issues as overfitting, lack of adaptability, and dependence on massive annotated datasets, the present work introduces a hybrid approach to enhance breast cancer classification accuracy.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!