We aimed to develop and validate a novel prediction model for osteoporosis based on serotonin, fat-soluble vitamins, and bone turnover markers to improve prediction accuracy of osteoporosis. Postmenopausal women aged 55 to 65 years were recruited and divided into three groups based on DXA (normal, osteopenia, and osteoporosis). A total of 109 participants were included in this study and split into healthy (39/109, 35.8%), osteopenia (35/109, 32.1%), and osteoporosis groups (35/109, 32.1%). Serum concentrations of serotonin, fat-soluble vitamins, and bone turnover markers of participants were measured. Stepwise discriminant analysis was performed to identify efficient predictors for osteoporosis. The prediction model was developed based on Bayes and Fisher’s discriminant functions, and validated via leave-one-out cross-validation. Normal and empirical volume under the receiver operating characteristic (ROC) surface (VUS) tests were used to evaluate predictive effects of variables in the prediction model.Aims
Methods
Mesenchymal stem cells (MSCs) are usually cultured in a normoxic atmosphere (21%) in vitro, while the oxygen concentrations in human tissues and organs are 1% to 10% when the cells are transplanted in vivo. However, the impact of hypoxia on MSCs has not been deeply studied, especially its translational application. In the present study, we investigated the characterizations of human umbilical cord-derived mesenchymal stem cells (hUC-MSCs) in hypoxic (1%) and normoxic (21%) atmospheres with a long-term culture from primary to 30 generations, respectively. The comparison between both atmospheres systematically analyzed the biological functions of MSCs, mainly including stemness maintenance, immune regulation, and resistance to chondrocyte apoptosis, and studied their joint function and anti-inflammatory effects in osteoarthritis (OA) rats constructed by collagenase II.Aims
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