Check out the amazing research we’re working on
The aims of the Ms. LILAC grant are to: 1) create age-standardized muscle mass percentile curves and z-scores to characterize the distribution of D3Cr- muscle mass in cancer survivors and non-cancer controls, 2) compare muscle mass, physical function, and functional decline in cancer survivors and non- cancer controls, and 3) use machine learning approaches to generate multivariate risk-prediction algorithms to detect low muscle mass.
The aims of the MASS grant are to: 1) provide insight into longitudinal patterns of change in D3Cr-muscle mass in postmenopausal women as they age, and their risk for functional decline increases, by race/ethnicity, diabetes status, and according to level of glycemic control, 2) examine the cyclical relationship between impaired insulin-glucose homeostasis and change in D3Cr-muscle mass using advanced statistical approaches, and 3) use machine learning methods to develop multivariate risk stratification algorithms, including D3Cr-muscle mass, indices of impaired insulin-glucose homeostasis, and objective measures of functional capacity (grip strength, gait speed), to identify postmenopausal women at highest risk of functional impairment, falls and fractures.
