University of Ottawa
Machine-learning algorithms for integrating HDT bed rest data and measuring the deconditioning of physiological systems — During spaceflight, astronauts experience deconditioning; the simultaneous reduction of the functional capacity of multiple body systems leading to weakness and inability to perform activities. Impairments span multiple systems from cardiovascular, musculoskeletal, to immunity all contributing to deconditioning. The scarcity of astronauts’ biological samples combined with technical challenges in space hampers our ability to monitor how the human body copes with space hazards. However, head-down tilt (HDT) bed rest studies represent an Earth-based analogue to microgravity and an opportunity to decipher the molecular mechanisms leading to deconditioning. The research team secured access to European Space Agency (ESA) data collected for the monitoring of participants. We will apply machine-learning algorithms to integrated ESA data and gene expression data collected from the same participants by our Team. Results will reveal predictor and physiological responses for early detection of dec