Rats bred for low intrinsic aerobic exercise capacity link obesity with brain inflammation and reduced structural plasticity of the hippocampus.

BACKGROUND: Increasing evidence shows obesity and poor metabolic health are associated with cognitive deficits, but the mechanistic connections have yet to be resolved. We studied rats selectively bred for low and high intrinsic aerobic capacity in order to test the association between low physical fitness, a genetic predisposition for obesity, and brain health. We hypothesized that low-capacity runner (LCR) rats with concurrently greater levels of adiposity would have increased hippocampal inflammation and reduced plasticity compared to the more physically fit high-capacity runner (HCR) rats. METHODS: We examined markers for inflammation and brain plasticity in the hippocampi of LCR rats and compared them to HCR rats. The effect of age was determined by studying the rats at a young age (8 weeks) and later in life (40 weeks). We used western blots and immunohistochemistry to quantify the expression of target proteins. RESULTS: Our study showed that the number of adult-born new neurons in the hippocampus was significantly lower in LCR rats than it was in HCR rats already at a young age and that the difference became more pronounced with age. The expression of synaptic proteins was higher in young animals relative to older ones. Brain inflammation tended to be higher in LCR rats than it was in the HCR rats, and more prominent in older rats than in young ones. CONCLUSION: Our study is the first to demonstrate that low intrinsic aerobic fitness that is associated with obesity and poor metabolic health is also linked with reduced hippocampal structural plasticity at a young age. Our results also suggest that inflammation of the brain could be one factor mediating the link between obesity and poor cognitive performance.

Video image-based analysis of single human induced pluripotent stem cell derived cardiomyocyte beating dynamics using digital image correlation.

BACKGROUND: The functionality of a cardiomyocyte is primarily measured by analyzing the electrophysiological properties of the cell. The analysis of the beating behavior of single cardiomyocytes, especially ones derived from stem cells, is challenging but well warranted. In this study, a video-based method that is non-invasive and label-free is introduced and applied for the study of single human cardiomyocytes derived from induced pluripotent stem cells. METHODS: The beating of dissociated stem cell-derived cardiomyocytes was visualized with a microscope and the motion was video-recorded. Minimum quadratic difference, a digital image correlation method, was used for beating analysis with geometrical sectorial cell division and radial/tangential directions. The time series of the temporal displacement vector fields of a single cardiomyocyte was computed from video data. The vector field data was processed to obtain cell-specific, contraction-relaxation dynamics signals. Simulated cardiomyocyte beating was used as a reference and the current clamp of real cardiomyocytes was used to analyze the electrical functionality of the beating cardiomyocytes. RESULTS: Our results demonstrate that our sectorized image correlation method is capable of extracting single cell beating characteristics from the video data of induced pluripotent stem cell-derived cardiomyocytes that have no clear movement axis, and that the method can accurately identify beating phases and time parameters. CONCLUSION: Our video analysis of the beating motion of single human cardiomyocytes provides a robust, non-invasive and label-free method to analyze the mechanobiological functionality of cardiomyocytes derived from induced pluripotent stem cells. Thus, our method has potential for the high-throughput analysis of cardiomyocyte functions.