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    Aire, the defect of which is responsible for the development of autoimmunity, is predominantly expressed in medullary thymic epithelial cells, and it controls a wide variety of genes, including those of tissue-restricted Ags, for establishing thymic tolerance. Aire is also expressed from APCs in the periphery, called extrathymic Aire-expressing cells (eTACs), and their complementing role to thymic tolerance has been suggested. eTACs are composed of two distinct classes of APCs, conventional dendritic cell (cDC)–type and group 3 innate lymphoid cell (ILC3)-like–type expressing retinoic acid receptor–related orphan receptor γt (RORγt). Although the essential role of Aire in the latter in the Th17-mediated immune response against Candida albicans has been reported, the role of Aire in the cDC-type eTACs for this action has not been examined. Furthermore, the significance of Aire in the production of the transcriptome of the cDC-type eTACs remains unknown. We have approached these issues using a high-fidelity Aire-reporter mouse strain. We found that although the cDC-type eTACs dominated ILC3-like–type eTACs in number and they served as efficient APCs for the immune response against an exogenous Ag as well as for the C. albicans–specific Th17 immune response, loss of Aire in cDC-type eTACs showed no clear effect on these functions. Furthermore, loss of Aire showed no major impact on the transcriptome from cDC-type eTACs. These results suggested that Aire in cDC-type eTACs may not have a cell-intrinsic role in the immune response in contrast to the role of Aire in ILC3-like–type eTACs

    Identification of risk factors for the onset of delirium associated with COVID-19 by mining nursing records.

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    COVID-19 has a range of complications, from no symptoms to severe pneumonia. It can also affect multiple organs including the nervous system. COVID-19 affects the brain, leading to neurological symptoms such as delirium. Delirium, a sudden change in consciousness, can increase the risk of death and prolong the hospital stay. However, research on delirium prediction in patients with COVID-19 is insufficient. This study aimed to identify new risk factors that could predict the onset of delirium in patients with COVID-19 using machine learning (ML) applied to nursing records. This retrospective cohort study used natural language processing and ML to develop a model for classifying the nursing records of patients with delirium. We extracted the features of each word from the model and grouped similar words. To evaluate the usefulness of word groups in predicting the occurrence of delirium in patients with COVID-19, we analyzed the temporal changes in the frequency of occurrence of these word groups before and after the onset of delirium. Moreover, the sensitivity, specificity, and odds ratios were calculated. We identified (1) elimination-related behaviors and conditions and (2) abnormal patient behavior and conditions as risk factors for delirium. Group 1 had the highest sensitivity (0.603), whereas group 2 had the highest specificity and odds ratio (0.938 and 6.903, respectively). These results suggest that these parameters may be useful in predicting delirium in these patients. The risk factors for COVID-19-associated delirium identified in this study were more specific but less sensitive than the ICDSC (Intensive Care Delirium Screening Checklist) and CAM-ICU (Confusion Assessment Method for the Intensive Care Unit). However, they are superior to the ICDSC and CAM-ICU because they can predict delirium without medical staff and at no cost

    Effects of Cr and Si addition on the high-temperature oxidation resistance in high-Mn alumina-forming oxide dispersion strengthened austenitic steels

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    Oxide dispersion-strengthened (ODS) steels are promising candidates for constructing nuclear reactors. Considering a high-temperature environment, ODS austenitic steels could provide superior performance compared to the current ODS ferritic steels. To meet the reduced activation requirement, the compositions of ODS austenitic steels have to be carefully adjust. Currently, the authors focus on the ODS austenitic steels with the austenite stabilizer of Mn, and several amounts of Al are added to improve their high-temperature oxidation resistance. This study investigates the third-element effects of Cr and Si on the high-temperature oxidation resistance of high-manganese alumina-forming ODS austenitic steels. Generally, Si-containing steel exhibits superior oxidation resistance owing to the formation of a continuous inner layer of amorphous alumina. In contrast, the Cr-containing steel does not possess a continuous alumina layer, resulting in insufficient oxidation resistance. The reported phenomenon is believed to be a reference for the development of ODS austenitic steels in the future

    Graphs showing the sensitivity, specificity, and odds ratio for predicting disease onset using risk factors.

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    The vertical axis represents the percentage of patients, and the horizontal axis represents 7 days before and after the day of delirium onset (day 0). The blue dotted line indicates the percentage of patients with delirium 1–7 days before its onset. The red dotted line indicates the frequency observed in patients without delirium.</p
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