Development and Validation of a Stressor-Coping Style Scale for Students in a Public Medical School.

Background: The medical curriculum is one of the most stressful academic curricula worldwide. Studies indicate that great levels of stress, that encompass academics to personal life, may be connected to a number of worrying statistics for the mental health of Philippine medical students.

Objectives: To develop a validated stressor-coping style scale for students in a public medical school.

Cardio-Obstetrics Practice in Latin America: A Regional Survey of General Cardiologists.

Background: Cardiovascular (CV) disease is a leading cause of death in pregnant women globally, especially in low- and middle-income countries including Latin America (LATAM), where there is lack of data on how cardiologists are trained in cardio-obstetrics (CO) and the practice patterns in the care of pregnant patients.

Objectives: The authors aimed to identify CO competency and practice patterns among LATAM general cardiologists.

Methods: An anonymous cross-sectional Google-based electronic survey was sent via email to clinical cardiologists through local American College of Cardiology chapters and CV societies.

Neuronal traveling waves form preferred pathways using synaptic plasticity.

Traveling waves of neuronal spiking activity are commonly observed across the brain, but their intrinsic function is still a matter of investigation. Experiments suggest that they may be valuable in the consolidation of memory or learning, indicating that consideration of traveling waves in the presence of plasticity might be important. A possible outcome of this consideration is that the synaptic pathways, necessary for the propagation of these waves, will be modified by the waves themselves.

Seroepidemiology of human leptospirosis in the Dominican Republic: A multistage cluster survey, 2021.

Little is known about the epidemiology of leptospirosis in the Dominican Republic, the second most populous country in the Caribbean. We report on findings from a multi-stage household survey across two regions in the country that reveals a previously under-estimated burden of human Leptospira infection. Our findings, based on the reference-standard microscopic agglutination test, indicate a complex picture of serogroup diversity, spatial heterogeneity in infection and risk, and a marked discrepancy between reported cases and serologically estimated infections.

Towards Automated Semantic Segmentation in Mammography Images for Enhanced Clinical Applications.

Mammography images are widely used to detect non-palpable breast lesions or nodules, aiding in cancer prevention and enabling timely intervention when necessary. To support medical analysis, computer-aided detection systems can automate the segmentation of landmark structures, which is helpful in locating abnormalities and evaluating image acquisition adequacy. This paper presents a deep learning-based framework for segmenting the nipple, the pectoral muscle, the fibroglandular tissue, and the fatty tissue in standard-view mammography images.