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The current situation in which the humanities are disparaged affects all university disciplines, including nursing, in whose historical evolution the humanities have always been present in one form or another. Looking beyond this disrepute, this study proposes that nursing renew its attention to classical philosophy. Specifically, it invites a close reading of Xenophon's Anabasis and Plato's Meno, to get three related goals: to show how the use of ancient texts are very valuable tools for the philosophical initiation of nursing students and can help them reflect on their choice of nursing as a practical activity; to reflect on the problem of virtue and the nature of the good life; and to show how the interaction with ancient texts allows students to reflect on questions and issues of life, theirs and others, that are not open to investigation through a purely scientific method. Consequently, both Anabasis and Meno readings strengthen the intellectual relationship between philosophy and nursing, enabling the latter to delve deeper into the key questions of its own thought as a discipline.  相似文献   
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Prevalence of osteoporosis is more than 50% in older adults, yet current clinical methods for diagnosis that rely on areal bone mineral density (aBMD) fail to detect most individuals who have a fragility fracture. Bone fragility can manifest in different forms, and a “one-size-fits-all” approach to diagnosis and management of osteoporosis may not be suitable. High-resolution peripheral quantitative computed tomography (HR-pQCT) provides additive information by capturing information about volumetric density and microarchitecture, but interpretation is challenging because of the complex interactions between the numerous properties measured. In this study, we propose that there are common combinations of bone properties, referred to as phenotypes, that are predisposed to different levels of fracture risk. Using HR-pQCT data from a multinational cohort (n = 5873, 71% female) between 40 and 96 years of age, we employed fuzzy c-means clustering, an unsupervised machine-learning method, to identify phenotypes of bone microarchitecture. Three clusters were identified, and using partial correlation analysis of HR-pQCT parameters, we characterized the clusters as low density, low volume, and healthy bone phenotypes. Most males were associated with the healthy bone phenotype, whereas females were more often associated with the low volume or low density bone phenotypes. Each phenotype had a significantly different cumulative hazard of major osteoporotic fracture (MOF) and of any incident osteoporotic fracture (p < 0.05). After adjustment for covariates (cohort, sex, and age), the low density followed by the low volume phenotype had the highest association with MOF (hazard ratio = 2.96 and 2.35, respectively), and significant associations were maintained when additionally adjusted for femoral neck aBMD (hazard ratio = 1.69 and 1.90, respectively). Further, within each phenotype, different imaging biomarkers of fracture were identified. These findings suggest that osteoporotic fracture risk is associated with bone phenotypes that capture key features of bone deterioration that are not distinguishable by aBMD. © 2021 American Society for Bone and Mineral Research (ASBMR).  相似文献   
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