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Self-care interventions for legal and safe abortions: lessons learned from a woman-centered approach to sexual and reproductive healthcare in Uruguay.
Lancet Reg Health Am
February 2025
Department of Sexual and Reproductive Health and Research, Including the UNDP-UNFPA-UNICEF-WHO-World Bank Special Programme of Research, Development and Research Training in Human Reproduction (HRP), World Health Organization, Geneva, Switzerland.
Problem: In the 1990s, almost 40% of maternal deaths in Uruguay were caused by unsafe abortions.
Approach: A harm reduction model implemented in Uruguay, which addressed the risks associated with unsafe abortion practices by promoting and supporting the self-management of medical abortions by women in their homes, encouraged women's autonomy.
Local Setting: Since 2005, an accelerated decrease in maternal mortality has been recorded in Uruguay, coinciding with the implementation of two major actions: a harm reduction approach with active promotion of self-care through self-management of medical abortions; and in 2012, a change in legislation, which made abortion legal within sexual and reproductive health facilities when requested by women up to 12 weeks of pregnancy or later for specific indications.
Background: Quadriceps dysfunction is ubiquitous after anterior cruciate ligament (ACL) reconstruction (ACLR). Addressing quadriceps dysfunction is crucial to improve function, reduce the reinjury risk, and maintain long-term knee health. While deficits specific to the quadriceps are well documented, less is known about the effect of an ACL injury on other lower extremity muscle groups.
View Article and Find Full Text PDFEnhancing quantitative coronary angiography (QCA) with advanced artificial intelligence: comparison with manual QCA and visual estimation.
Int J Cardiovasc Imaging
January 2025
Division of Cardiology, Department of Internal Medicine, Asan Medical Center, University of Ulsan College of Medicine, Seoul, South Korea.
Artificial intelligence-based quantitative coronary angiography (AI-QCA) was introduced to address manual QCA's limitations in reproducibility and correction process. The present study aimed to assess the performance of an updated AI-QCA solution (MPXA-2000) in lesion detection and quantification using manual QCA as the reference standard, and to demonstrate its superiority over visual estimation. This multi-center retrospective study analyzed 1,076 coronary angiography images obtained from 420 patients, comparing AI-QCA and visual estimation against manual QCA as the reference standard.
View Article and Find Full Text PDFMachine learning models for predicting interaction affinity energy between human serum proteins and hemodialysis membrane materials.
Sci Rep
January 2025
Division of Biomedical Engineering, University of Saskatchewan, 57 Campus Drive, Saskatoon, Saskatchewan, S7N 5A9, Canada.
Membrane incompatibility poses significant health risks, including severe complications and potential fatality. Surface modification of membranes has emerged as a pivotal technology in the membrane industry, aiming to improve the hemocompatibility and performance of dialysis membranes by mitigating undesired membrane-protein interactions, which can lead to fouling and subsequent protein adsorption. Affinity energy, defined as the strength of interaction between membranes and human serum proteins, plays a crucial role in assessing membrane-protein interactions.
View Article and Find Full Text PDFMachine learning and AVO class II workflow for hydrocarbon prospectivity in the Messinian offshore Nile Delta Egypt.
Sci Rep
January 2025
Rashpetco Company, Cairo, Egypt.
This study presents a comprehensive workflow to detect low seismic amplitude gas fields in hydrocarbon exploration projects, focusing on the West Delta Deep Marine (WDDM) concession, offshore Egypt. The workflow integrates seismic spectral decomposition and machine learning algorithms to identify subtle anomalies, including low seismic amplitude gas sand and background amplitude water sand. Spectral decomposition helps delineate the fairway boundaries and structural features, while Amplitude Versus Offset (AVO) analysis is used to validate gas sand anomalies.
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