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Moran, T. H.

Publications and source records attributed to Moran, T. H..

2 recordsLinked to original sources

Perinatal high-fat diet induces systemic inflammation via altered tight junction complex organization during development and decreases expression of intestinal satiety peptides in male offspring.

Objective Epidemiological evidence suggests that maternal obesity increases risk for offspring obesity and comorbidities, pointing to the significance of critical periods of development. Adverse metabolic effects of high fat (HF) diet consumption on the gut microbiome and inflammation have been well documented in obesity models. Emerging evidence demonstrates that the gut microbiome may play a role in transgenerational obesity, however, underlying mechanisms still need to be elucidated to identify intervention targets. Methods A rat model was used to demonstrate whether maternal HF diet during gestation and lactation results in gut-brain axis deficits in rat offspring. Gene expression of small intestinal satiety hormones and C-fiber innervation in the nucleus of the solitary tract (NTS) were measured in adult offspring. At weaning, circulating inflammatory mediators and colonic microbial metabolites were measured in offspring. Results In adulthood, HF males had reduced vagal innervation in the NTS and reduced small intestinal expression of CCK, GLP-1, and PYY. At weaning, HF offspring had elevated levels of CRP and IL-1{beta} and depleted levels of microbially produced colonic short chain fatty acids (SCFAs), which are critical for maintaining intestinal barrier function. HF males had reduced colocalization between tight junction proteins, Claudin-1 and ZO-1 at weaning, while HF females did not. Conclusion Disorganization of tight junction complexes in HF male offspring during development may play a role in the gut-brain axis deficits seen in HF males in adulthood. Together, these data demonstrate that inflammation-induced by HF diet can negatively impact gut-brain axis development and function.

physiology↗

A predictive model of rats’ calorie intake as a function of diet energy density

Easy access to high-energy food has been linked to high rates of obesity in the world. Understanding the way that access to palatable (high fat or high calorie) food can lead to overconsumption is essential for both preventing and treating obesity. Although the body of studies focused on the effects of high energy diets is growing, our understanding of how different factors contribute to food choices is not complete. In this study, we present a mathematical model that is able to predict rats calorie intake to a high-energy diet based on their ingestive behavior to a standard chow diet. Specifically, we propose an equation that describes the relation between the body weight (W), energy density (E), time elapsed from the start of diet (T), and daily calorie intake (C). We tested our model on two independent data sets. Our results show that the suggested model is able to predict the calorie intake patterns with high accuracy. Additionally, the only free parameter of our proposed equation ({rho}), which is unique to each animal, has a strong correlation with their calorie intake and weight gain. Additionally, we discuss the relevance of our derived parameter in the context of measuring reward sensitivity in reinforcement learning based studies.

bioinformatics↗