The neuroprotective mechanism of Rg1 was studied in this paper by means of its obvious anti-apoptotic effect on human SHSY5Y cells. SHSY5Y cells were treated with MPP+ (1-methyl-4-phenyl-pyridinium) for 72 hours to induce apoptosis. During the apoptosis, production of reactive oxygen species (ROS), activation of c-Jun N-terminal kinase (JNK) and activation of caspase-3 were observed. The results showed that the signal transduction pathway of MPP+-induced apoptosis might be ROS to JNK, then to caspase-3. MPP+-induced apoptosis in SHSY5Y cells was obviously inhibited in both NAC (N-acetylcysteine) pretreated groups and Rg1 pretreated groups. Meanwhile, compared to that of the controls, our results showed decreased level of ROS, less JNK activity and lower expression of cleaved caspase-3 in pretreated NAC groups and in Rg1 pretreated groups. The protection by Rg1 might be mediated by removing of ROS. The removal of ROS might inhibit the activity of JNK and the expression of cleaved caspase-3. These results suggest that ginsenoside Rg1 may take effect through its anti-apoptotic activity in neurodegenerative diseases.

No abstract

No abstract

Introduction: A prediction model for the 1-, 3-, and 5-year survival rates of metastatic colon cancer (mCC) patients was developed by analyzing important risk factors for the prognosis of mCC patients based on the SEER database.Method: The characteristic of 10,946 patients diagnosed with mCC between 2010 and 2015 was obtained from the SEER database. The population was randomly divided into a training cohort and an internal validation cohort in a 7:3 ratio. Univariate and multivariate cox for independent predictors of mCC prognosis were performed, and nomogram was constructed. The accuracy of the model was verified by calibration curves, ROC curves, and C-index, and the clinical utility of the model was analyzed using decision analysis curves.Result: Age, primary site, grade, surgery, and other eight factors were significantly associated with the prognosis of mCC patients, and these predictors were included in the construction of the nomogram. The C-index was 0.731 (95% CI 0.725–0.737) and 0.736 (95% CI 0.726–0.746) for the training cohort and the validation set, respectively. The results of the ROC curve analysis indicated that the area under the curve (AUC) exceeded 0.7 for both the training cohort and the validation set at 1, 3, and 5 years.Conclusion: The constructed prediction model had an excellent predictive accuracy, which will help clinical decision-making of mCC patients after surgery and individualized treatment.