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
The present study investigates the effectiveness of platelet-rich plasma (PRP) gel without adjunct to induce cartilage regeneration in large osteochondral defects in a rabbit model. A bilateral osteochondral defect was created in the femoral trochlear groove of 14 New Zealand white rabbits. The right knees were filled with PRP gel and the contralateral knees remained untreated and served as control sides. Some animals were killed at week 3 and others at week 12 postoperatively. The joints were harvested and assessed by Magnetic Resonance Observation of Cartilage Repair Tissue (MOCART) MRI scoring system, and examined using the International Cartilage Repair Society (ICRS) macroscopic and ICRS histological scoring systems. Additionally, the collagen type II content was evaluated by the immunohistochemical staining.Aims
Methods
