As the population ages, the demand for elderly care services will continue to increase, which includes providing specialized care, daily life support, and medical health services. As a result, informal caregiving provided by non-professionals such as family, friends, neighbors, and volunteers is becoming more prevalent. Injuries that occur during caregiving can affect the caregiving’s life, especially their mental and physical health. Therefore, the correct positioning and posture during caregiving are crucial to prevent musculoskeletal disorders among caregivers. Although training programs are useful to reduce the risk of musculoskeletal disorders for informal caregivers, many of them express that it is still difficult for them to grasp the correct caregiving postures. Moreover, they struggle to obtain professional advice to correct their posture through long-term practice. Therefore, finding a targeted ergonomic posture risk assessment and guidance method is crucial to improve caregivers' posture-related risks, enhance work efficiency, and safeguard their physical health. Rapid Entire Body Assessment (REBA) is a postural risk assessment method based on ergonomics that has been attracting attention recently, and it basically evaluates the risk from the angle of each joint of the body. However, in caregiving movements, the way of load placed on the caregiver and the time to maintain the movements vary greatly depending on the weight and posture of the cared person, so the current risk assessment using REBA is insufficient for caregiving movements. Additionally, posture recognition algorithms such as OpenPose are often used to extract skeletons. With these techniques, problems such as missing skeletons or misrecognition often occur due to image conditions or the overlapping of multiple people, and skeleton extraction may sometimes fail. In this research, the Spatial Temporal Graph Convolution Network (ST-GCN) is applied to develop a technique for complementing missing skeletons based on behavioral features and a technique for correcting skeletons that are misrecognized due to overlapping people, and to improve the accuracy of calculating skeletal joint angles. In order to evaluate caregiving posture risk more appropriately, some parameters such as center of gravity trajectory, load duration, asymmetric load during caregiving movements are investigated and a new REBA method is proposed. This paper consists of six chapters. In Chapter 2, to solve the problems of skeleton misidentification and missing information by OpenPose an improved skeleton reconstruction method based on ST-GCN is propose. The method compensates for missing skeletons in terms of behavioral features and corrects incorrectly identified skeletons based on skeleton weight features. This approach improves the accuracy and robustness of pose recognition and allows more accurate estimation of skeletal joint angles and its REBA score. In Chapter 3, to address the issue of REBA evaluation scores being too high for caregiving scenarios, a postural risk assessment method (C-REBA) is proposed by considering the characteristics of caregiving task. Customize the traditional REBA method and add parameters such as center of gravity trajectory, load duration, and asymmetric loading to the evaluation score. the caregiving movements to assist in transferring from a bed to a wheelchair on a group of experienced nurses and a group of inexperienced caregivers are analyzed and the effectiveness of the C-REBA method is verified. In Chapter 4, a method that combines the ST-GCN framework and C-REBA for postural risk assessment is proposed. The deep neural network algorism is applied to learn motion features and additional features such as load duration, motion frequency, center of gravity variation, and asymmetric load. So that all evaluation parameters for C-REBA rules can be obtained automatically. With this method, postural risk assessment processes in caregiving operations can be performed automatically. In Chapter 5, "Behavior Analysis and Posture Assessment System" (BAPAS) is developed. BAPAS is a system aimed at assessing the risk of musculoskeletal disorders related to working postures in medical support work. This chapter introduces the functions and usefulness of this system and demonstrates how this system can be extended to other medical fields easily by setting parameter is settings. Chapter 6 provides a summary of the paper as a whole and future prospect.

In recent years, not only mRNA (messenger RNA) but also other small non-coding RNA have focused on molecular diagnosis and therapy in oncology fields. Especially in human medicine, many studies elucidate the ability and function of many microRNAs, which are small non-coding RNAs. However, there are still not many studies in the veterinary field. In my PhD study, I focused on the non-coding small RNA in canine oncology fields. In the first chapter, I studied the dysregulated micro RNA in canine oral melanoma. At first, I performed the microarray-based miRNA profiling of canine malignant melanoma (CMM) tissue obtained from the oral cavity. Then, I also confirmed the differentially expressed microRNA by quantitative reverse transcription-PCR (qRT-PCR). An analysis of the microarray data revealed 17 dysregulated miRNAs; 5 were up-regulated, and 12 were downregulated. qRT-PCR analysis was performed for 2 up-regulated (miR-204 and miR-383), 3 down-regulated (miR-122, miR-143, and miR-205) and 6 additional oncogenic miRNAs (oncomiRs; miR-16, miR-21, miR-29b, miR-92a, miR-125b and miR-222). The expression levels of seven of the miRNAs, miR16, miR-21, miR-29b, miR-122, miR-125b, miR-204, and miR-383 were significantly up-regulated, while the expression of miR-205 was down- 2 regulated in CMM tissues compared with normal oral tissues. The microarray and qRT-PCR analyses validated the up-regulation of two potential oncomiRs, miR-204 and miR-383. I also constructed a protein interaction network and a miRNA–target regulatory interaction network using STRING and Cytoscape. In the proposed network, was a target for miR-383, and were targets for miR-204, and was a target for both. The miR-383 and miR-204 were potential oncomiRs that may be involved in regulating melanoma development by evading DNA repair and apoptosis. In my second chapter, I focused on non-coding RNA other than microRNA, and I compared canine hepatocellular carcinomas (HCC) and hepatocellular adenomas (HCA). I elucidated the differential expression of Y RNA-derived fragments because Y RNA-derived fragments have yet to be investigated in canine HCC and HCA. I used qRT-PCR to determine Y RNA expression in clinical tissues, plasma, and plasma extracellular vesicles, and two HCC cell lines (95-1044 and AZACH). Y RNA was significantly decreased in tissue, plasma, and plasma extracellular vesicles for canine HCC versus canine HCA and healthy controls. Y RNA was decreased in 95-1044 and AZACH cells versus normal liver tissue and 3 in AZACH versus 95-1044 cells. In plasma samples, Y RNA levels were decreased in HCC versus HCA and Healthy controls and increased in HCA versus Healthy controls. Receiver operating characteristic analysis showed that Y RNA could be a promising biomarker for distinguishing HCC from HCA and healthy controls. Overall, the dysregulated expression of Y RNA can distinguish canine HCC from HCA. However, further research is necessary to elucidate the underlying Y RNA-related molecular mechanisms in hepatocellular neoplastic diseases. To the best of my knowledge, this is the first report on the relative expression of Y RNA in canine HCC and HCA. In conclusion, I have demonstrated the up-regulation of potential oncomiRs, miR-16, miR-21, miR-29b, miR-122, miR-125b, miR-204 and miR383 in CMM tissues. In particular, the strong up-regulation of miR-383 in CMM tissues compared with normal oral tissues identified by microarray screening was confirmed by qRT-PCR. I conclude that miR-383 and miR-204 may promote melanoma development by regulating the DNA repair/checkpoint and apoptosis. Then, I also demonstrated the Y RNA dysregulation in the cHCC. Especially to my knowledge, this is the first report on Y RNA in canine tumors. Interestingly, this ncRNA has distinctive characteristics and differentiates malignant tumors (HCC) from benign 4 tumors (HCA). The expression pattern of Y RNA is consistent across clinical samples and cell lines. Thus, Y RNA has promising potential for differentiating HCC from HCA. Further research is required to fully elucidate the role of Y RNA in the development and progression of canine HCC and HCA.

In Japan, China, and Singapore, several studies have reported increased incidences of peripheral venous catheter-related bloodstream infection by Bacillus cereus during the summer. Therefore, we hypothesized that bed bathing with a B. cereus-contaminated “clean” towels increases B. cereus contact with the catheter and increases the odds of contaminating the peripheral parenteral nutrition (PPN). We found that 1) professionally laundered “clean” towels used in hospitals have B. cereus (3.3×10^4 colony forming units (CFUs) / 25cm^2), 2) B. cereus is transferable onto the forearms of volunteers by wiping with the towels (n=9), and 3) B. cereus remain detectable (80∼660 CFUs /50cm^2) on the forearms of volunteers even with subsequent efforts of disinfection using alcohol wipes. We further confirmed that B. cereus grow robustly (10^2 CFUs /mL to more than 10^6 CFUs /mL) within 24hours at 30°C in PPN. Altogether we find that bed bathing with a towel contaminated with B. cereus leads to spore attachments to the skin, and that B. cereus can proliferate at an accelerated rate at 30°C compared to 20°C in PPN. We therefore highly recommend ensuring the use of sterile bed bath towels prior to PPN administration with catheter in patients requiring bed bathing.