Developing a Charlson Comorbidity Index for the American Indian Population Using the Epidemiologic Data from the Strong Heart Study.

Background: The Charlson Comorbidity Index (CCI) is a frequently used mortality predictor based on a scoring system for the number and type of patient comorbidities health researchers have used since the late 1980s. The initial purpose of the CCI was to classify comorbid conditions, which could alter the risk of patient mortality within a 1-year time frame. However, the CCI may not accurately reflect risk among American Indians because they are a small proportion of the US population and possibly lack representation in the original patient cohort.

Response of the ductus arteriosus to acetaminophen or indomethacin in extremely low birth weight infants.

Objective: Acetaminophen and indomethacin are used for medical management of a patent ductus arteriosus. This study compared the efficacy of these agents in ELBW infants.

Study Design: This was a retrospective study of all courses of indomethacin and acetaminophen.

Regional differences in three-dimensional fiber organization, smooth muscle cell phenotype, and contractility in the pregnant mouse cervix.

The orientation and function of smooth muscle in the cervix may contribute to the important biomechanical properties that change during pregnancy. Thus, this study examined the three-dimensional structure, smooth muscle phenotype, and mechanical and contractile functions of the upper and lower cervix of nongravid (not pregnant) and gravid (pregnant) mice. In gravid cervix, we uncovered region-specific changes in the structure and organization of fiber tracts.

Intrinsic-dimension analysis for guiding dimensionality reduction and data fusion in multi-omics data processing.

Multi-omics data have revolutionized biomedical research by providing a comprehensive understanding of biological systems and the molecular mechanisms of disease development. However, analyzing multi-omics data is challenging due to high dimensionality and limited sample sizes, necessitating proper data-reduction pipelines to ensure reliable analyses. Additionally, its multimodal nature requires effective data-integration pipelines.