BackgroundThis study aimed to develop an artificial intelligence predictive model for predicting the probability of developing BM in CRC patients.MethodsFrom SEER database, 50,566 CRC patients were identified between January 2015 and December 2019 without missing data. SVM and LR models were trained and tested on the dataset. Accuracy, area under the curve (AUC), and IDI were used to evaluate and compare the models.ResultsFor bone metastases in the entire cohort, SVM model with poly as kernel function presents the best performance, whose accuracy is 0.908, recall is 0.838, and AUC is 0.926, outperforming LR model. The top three most important factors affecting the model's prediction of BM include extraosseous metastases (EM), CEA, and size.ConclusionOur study developed an SVM model with poly as kernel function for predicting BM in CRC patients. SVM model could improve personalized clinical decision-making, help rationalize the bone metastasis screening process, and reduce the burden on healthcare systems and patients.
Context Morroniside (MOR) possesses antiosteoporosis (OP) effects, but its molecular target and relevant mechanisms remain unknown. Objective We investigated the effects of MOR on glucocorticoid-induced OP and osteoblastogenesis and its underlying mechanisms. Materials and methods The effects of MOR (10–100 μM) on the proliferation and differentiation of MC3T3-E1 cells were studied in vitro . The glucocorticoid-induced zebrafish OP model was treated with 10, 20 and 40 μM MOR for five days to evaluate its effects on vertebral bone density and related osteogenic markers. In addition, molecular targets prediction and molecular docking analysis were carried out to explore the binding interactions of MOR with the target proteins. Results In cultured MC3T3 - E1 cells, 20 μM MOR significantly increased cell viability (1.64 ± 0.12 vs. 0.95 ± 0.16; p < 0.01) and cell differentiation (1.57 ± 0.01 vs. 1.00 ± 0.04; p < 0.01) compared to the control group. MOR treatment significantly ameliorated vertebral bone loss in the glucocorticoid-induced OP zebrafish model (0.86 ± 0.02 vs. 0.40 ± 0.03; p < 0.01) and restored the expression of osteoblast-specific markers, including ALP, Runx2 and Col-І. Ligand-based target prediction and molecular docking revealed the binding interaction between MOR and the glucose pockets in sodium-glucose cotransporter 2 (SGLT2). Discussion and conclusions These findings demonstrated that MOR treatment promoted osteoblastogenesis and ameliorated glucocorticoid-induced OP by targeting SGLT2, which may provide therapeutic potential in managing glucocorticoid-induced OP.
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