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Radiation therapy for head and neck cancer damages local stem cells and epithelial cells in salivary glands (SG), leading to irreversible SG dysfunction. Biological understanding of the responses of tissue-resident stem cells to gravity is required to develop therapeutic strategies for damaged tissue regeneration. In this study, we successfully isolated human minor salivary gland stem cells (huMSGSCs), which have high proliferation rates, express multiple stem markers, and can be differentiated into mesenchymal cell types. Cell proliferation, sphere-forming ability, stemness marker expressions, and epithelial differentiation potentials were checked after exposing huMSGSCs short-term to hypergravity (HyperG) or microgravity (MicroG). Proliferation after exposure to HyperG (40 G ) was greater than exposure to 1G, but no difference was observed between MicroG (10− 3 G) and 1G. Numbers of large spheres were significantly higher post-HyperG and lower post-MicroG than at 1G, whereas numbers of small spheres were significantly lower post-HyperG and higher post-MicroG. The expressions of stemness markers (CD90, LGR5, CD29, and CD24) and junction markers (ZO-1 and ZO-2) were increased post-HyperG. Furthermore, increases in PAS staining and the gene expressions of albumin and CK19 confirmed that HyperG enhances the epithelial differentiation potential of huMSGSCs. This study shows that cultivating huMSGSCs under HyperG conditions enhances stemness and that a gravity control system could be applied to modulate huMSGSC functions.

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Nowadays, wearable devices for human health monitoring are increasingly become popular and widely used. Typically, the wearable device is small size and operates with batteries. Therefore, the wearable device acquires bio-signals and transfers to smartphones or personal computers (PC) via WiFi/ Bluetooth for processing data. To reduce power consumption is one of the most important challenges of designing wearable devices. To solve this problem, the proposed signal quality valuation (SQV) method can be select the high-quality signal and reduce the transfer time to other devices. In this paper, the proposed SQV and data compression method rely on real-time PPG signals analysis to retain important information of PPG signal, improve performance and power consumption of PPG devices. Besides, we also proposed Heuristic rules for heart rate (HR) estimation with compression data. The experimental results show that the highest compression ratio (CR) is 387.8 with BIDMC Physionet database (sampling frequencies of 125 Hz) and HR error as 1.43 bpm for averaging absolute error (avAE), the standard deviation absolute error (sdAE as 0.4) and relative error mean (avRE as 0.019). The proposed real-time PPG measurement system (sampling frequency as 100/ 200/ 400 Hz) reduce power consumption and open the new structure for healthcare application systems