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- All Subjects: Physiology
- All Subjects: SOLS
- Creators: DeNardo, Dale
2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers, but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.
Before developing a theory for all animals, a model needs to be developed for a single model animal, such as fruit flies, that can be used to empirically examine how organisms thermoregulate under competition. My work examines how flies behave around other flies and develops a game theory model predicting how they should optimally behave. More specifically, my research accounts for competition among larvae by using game theory to predict how mothers should select sites when laying eggs. Although flies prefer to lay their eggs in places that will offer suitable temperatures for the development of their larvae, these sites become less suitable when crowded. Therefore, at some density of eggs, cooler sites should become equally beneficial to larvae when considering both temperature and competition. Given this tradeoff, an evolutionarily stable strategy (ESS) emerges where some flies should lay eggs in cooler sites while other flies should lay eggs at the warmer temperature. By looking at the fitness of genotypes in habitats of differing quality (competition, temperature, food quality, space), I modeled the ESS for flies laying eggs in a heterogeneous environment. I then tested these predictions by observing how flies compete for patches with different temperatures.