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BACKGROUND: Human health status can be measured on the basis of many different parameters. Statistical relationships among these different health parameters will enable several possible health care applications and an approximation of the current health status of individuals, which will allow for more personalized and preventive health care by informing the potential risks and developing personalized interventions. Furthermore, a better understanding of the modifiable risk factors related to lifestyle, diet, and physical activity will facilitate the design of optimal treatment approaches for individuals. OBJECTIVE: This study aims to provide a high-dimensional, cross-sectional data set of comprehensive health care information to construct a combined statistical model as a single joint probability distribution and enable further studies on individual relationships among the multidimensional data obtained. METHODS: In this cross-sectional observational study, data were collected from a population of 1000 adult men and women (aged ≥20 years) matching the age ratio of the typical adult Japanese population. Data include biochemical and metabolic profiles from blood, urine, saliva, and oral glucose tolerance tests; bacterial profiles from feces, facial skin, scalp skin, and saliva; messenger RNA, proteome, and metabolite analyses of facial and scalp skin surface lipids; lifestyle surveys and questionnaires; physical, motor, cognitive, and vascular function analyses; alopecia analysis; and comprehensive analyses of body odor components. Statistical analyses will be performed in 2 modes: one to train a joint probability distribution by combining a commercially available health care data set containing large amounts of relatively low-dimensional data with the cross-sectional data set described in this paper and another to individually investigate the relationships among the variables obtained in this study. RESULTS: Recruitment for this study started in October 2021 and ended in February 2022, with a total of 997 participants enrolled. The collected data will be used to build a joint probability distribution called a Virtual Human Generative Model. Both the model and the collected data are expected to provide information on the relationships between various health statuses. CONCLUSIONS: As different degrees of health status correlations are expected to differentially affect individual health status, this study will contribute to the development of empirically justified interventions based on the population. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/47024.
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BACKGROUND: The in vivo lesion morphologies and plaque components of coronary chronic total occlusion (CTO) lesions remain unclear.MethodsâandâResults:We investigated 57 consecutive CTO lesions in 57 patients with stable angina pectoris undergoing elective percutaneous coronary intervention with intravascular ultrasound (IVUS) and coronary angioscopy (CAS) examination. All CTO lesions were classified according to the proximal angiographic lumen pattern; tapered-type (T-CTO) and abrupt-type (A-CTO). The differences in the intracoronary images of these lesion types were evaluated according to the location within the CTO segment. A total of 35 lesions (61.4%) were T-CTO. T-CTO lesions had higher frequencies of red thrombi (proximal 71.4%; middle 74.3%; distal 31.4%; P<0.001) and bright-yellow plaques (yellow-grade 2-3) (48.6%; 74.3%; 2.9%; P<0.001) at the proximal or middle than at the distal subsegment; A-CTO lesions showed no significant differences among the 3 sub-segments. At the middle subsegment, T-CTO lesions showed higher frequencies of positive remodeling (51.4% vs. 18.2%, P=0.01) and bright-yellow plaques (74.3% vs. 13.6%, P<0.001) compared with A-CTO lesions. Multivariate analysis identified bright-yellow plaque as an independent predictor (odds ratio, 7.25; 95% confidence interval, 1.25-42.04; P=0.03) of the occurrence of periprocedural myocardial necrosis. CONCLUSIONS: The combination of IVUS and CAS analysis may be useful for identifying lesion morphology and plaque components, which may help clarify the pathogenetic mechanism of CTO lesions.