Gene-by-environment interactions involving maternal exposures with orofacial cleft risk in Filipinos.

Maternal exposures are known to influence the risk of isolated cleft lip with or without cleft palate (CL/P) - a common and highly heritable birth defect with a multifactorial etiology. To identify new CL/P risk loci, we conducted a genome-wide gene-environment interaction (GEI) analysis of CL/P on a sample of 540 cases and 260 controls recruited from the Philippines, incorporating the interaction effects of genetic variants with maternal smoking and vitamin use. As GEI analyses are typically low in power and the results can be difficult to interpret, we used multiple testing frameworks to evaluate potential GEI effects: 1 degree-of-freedom (1df) GxE test, the 3df joint test, and the two-step EDGE approach.

The Southern Center for Maternal Health Equity (SCMHE): a multisector multifaceted community-based approach to reduce disparities in maternal morbidity and mortality in the Gulf South.

Introduction: The maternal mortality crisis in the United States disproportionately affects women who are Black, especially those living in the Gulf South. These disparities result from a confluence of healthcare, policy, and social factors that systematically place Black women at greater risk of maternal morbidities and mortality. This study protocol describes the Southern Center for Maternal Health Equity (SCMHE), a research center funded by the National Institutes of Health in 2023 to reduce preventable causes of maternal morbidity and mortality while improving health equity.

Ultraprecise Determination of Cs(nS_{1/2}) and Cs(nD_{J}) Quantum Defects for Sensing and Computing: Evaluation of Core Contributions.

We make absolute frequency measurements of Cs Rydberg transitions, |6S_{1/2},F=3⟩→|nS_{1/2}(n=23-90)⟩ and |nD_{3/2,5/2}(n=21-90)⟩, with an accuracy of less than 72 kHz. The quantum defect parameters for the measured Rydberg series are the most precise obtained to date. The quantum defect series is terminated at δ_{4}, showing that prior fits requiring higher order quantum defects reflect uncertainties in the observations.

Retinal Vessel Plexus Differentiation Based on OCT Angiography Using Deep Learning.

Purpose: Although structural OCT is traditionally used to differentiate the vascular plexus layers in OCT angiography (OCTA), the vascular plexuses do not always obey the retinal laminations. We sought to segment the superficial, deep, and avascular plexuses from OCTA images using deep learning without structural OCT image input or segmentation boundaries.

Design: Cross-sectional study.