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e., to delete data segments). Taken together, our results indicate generally positive attitudes to remote in-home monitoring technologies and studies for infant research but highlight specific considerations such as safety, privacy and family practicalities (e.g. multiple caregivers, visitors and varying schedules) that must be taken into account when developing future studies.Patients consented to biobanking studies typically do not specify research conducted on their samples and data. Our objective was to gauge cancer biobanking participant preferences on research topics. Patient-participants of a biobanking study at a comprehensive cancer center who had an appointment within the last 5 years, had a valid email address, and with a last known vital status of alive, were emailed a newsletter containing a link to a survey about preferences and priorities for research. The survey assessed demographics and research interest in three domains cancer site, cancer-related topics, and issues faced by cancer patients. 37,384 participants were contacted through email to participate in the survey. 16,158 participants (43.2%) opened the email, 1,626 (4.3% overall, 10% of those who opened the email) completed the survey, and 1,291 (79.4% of those who completed the survey) selected at least one research priority. Among those who selected at least one research priorities for cancer-relevant topics, the most commonly selected were cancer treatment (66%), clinical trials (54%), and cancer prevention (53%). Similarly, the most selected priorities for cancer-related issues faced by patients were physical side effects of cancer (57%), talking to the oncologist (53%), and emotional challenges due to cancer (47%). Differences by gender were observed, with females reporting more interest in research generally. Cancer patients participating in a biobanking protocol prioritized research on treatments, prevention and side effects, which varied by gender.Risk assessment of in-hospital mortality of patients at the time of hospitalization is necessary for determining the scale of required medical resources for the patient depending on the patient's severity. Because recent machine learning application in the clinical area has been shown to enhance prediction ability, applying this technique to this issue can lead to an accurate prediction model for in-hospital mortality prediction. In this study, we aimed to generate an accurate prediction model of in-hospital mortality using machine learning techniques. Patients 18 years of age or older admitted to the University of Tokyo Hospital between January 1, 2009 and December 26, 2017 were used in this study. The data were divided into a training/validation data set (n = 119,160) and a test data set (n = 33,970) according to the time of admission. The prediction target of the model was the in-hospital mortality within 14 days. To generate the prediction model, 25 variables (age, sex, 21 laboratory test items, length of stay, and mortality) were used to predict in-hospital mortality. Logistic regression, random forests, multilayer perceptron, and gradient boost decision trees were performed to generate the prediction models. To evaluate the prediction capability of the model, the model was tested using a test data set. Mean probabilities obtained from trained models with five-fold cross-validation were used to calculate the area under the receiver operating characteristic (AUROC) curve. In a test stage using the test data set, prediction models of in-hospital mortality within 14 days showed AUROC values of 0.936, 0.942, 0.942, and 0.938 for logistic regression, random forests, multilayer perceptron, and gradient boosting decision trees, respectively. Machine learning-based prediction of short-term in-hospital mortality using admission laboratory data showed outstanding prediction capability and, therefore, has the potential to be useful for the risk assessment of patients at the time of hospitalization.Homotypic or heterotypic internalization of another, either living or necrotic cell is currently in the center of research interest. The active invasion of a living cell called entosis and cannibalism of cells by rapidly proliferating cancers are prominent examples. Additionally, normal healthy tissue cells are capable of non-professional phagocytosis. This project studied the relationship between non-professional phagocytosis, individual proliferation and cell cycle progression. Three mesenchymal and two epithelial normal tissue cell lines were studied for homotypic non-professional phagocytosis. Homotypic dead cells were co-incubated with adherent growing living cell layers. Living cells were synchronized by mitotic shake-off as well as Aphidicolin-treatment and phagocytotic activity was analyzed by immunostaining. Cell cycle phases were evaluated by flow cytometry. Mesenchymal and epithelial normal tissue cells were capable of internalizing dead cells. Epithelial cells had much higher non-professional phagocytotic rates than mesenchymal cells. Cells throughout the entire cell cycle were able to phagocytose. selleck The phagocytotic rate significantly increased with progressing cell cycle phases. Mitotic cells regularly phagocytosed dead cells, this was verified by Nocodazole and Colcemid treatment. Taken together, our findings indicate the ability of human tissue cells to phagocytose necrotic neighboring cells in confluent cell layers. The origin of the cell line influences the rate of cell-in-cell structure formation. The higher cell-in-cell structure rates during cell cycle progression might be influenced by cytoskeletal reorganization during this period or indicate an evolutionary anchorage of the process. Recycling of nutrients during cell growth might also be an explanation.

Obesity is a growing global health concern. The increased body mass and altered mass distribution associated with obesity may be related to increases in plantar shear that putatively leads to physical functional deficits. Therefore, measurement of plantar shear may provide unique insights on the effects of body mass and body distribution on physical function or performance.

1) To investigate the effects of body mass and distribution on plantar shear. 2) To examine how altered plantar shear influences postural control and gait kinetics.

1) a weighted vest forward distributed (FV) would shift the center of pressure (CoP) location forward during standing compared with a weighted vest evenly distributed (EV), 2) FV would increase plantar shear spreading forces more than EV during standing, 3) FV would increase postural sway during standing while EV would not, and 4) FV would elicit greater compensatory changes during walking than EV.

Twenty healthy young males participated in four different tests 1) static test (for measuring plantar shear and CoP location without acceleration, 2) bilateral-foot standing postural control test, 3) single-foot standing postural test, and 4) walking test.