Dihydroartemisinin Promoted Bone Marrow Mesenchymal Stem Cell Homing and Suppressed Inflammation and Oxidative Stress against Prostate Injury in Chronic Bacterial Prostatitis Mice Model.

Although bone marrow mesenchymal stem cells (BMMSCs) are effective in treating chronic bacterial prostatitis (CBP), the homing of BMMSCs seems to require ultrasound induction. Dihydroartemisinin (DHA) is an important derivative of artemisinin (ART) and has been previously reported to alleviate inflammation and autoimmune diseases. But the effect of DHA on chronic prostatitis (CP) is still unclear. This study aims to clarify the efficacy and mechanism of DHA in the treatment of CBP and its effect on the accumulation of BMMSCs. The experimental CBP was produced in C57BL/6 male mice via intraurethrally administered E. coli solution. Results showed that DHA treatment concentration-dependently promoted the accumulation of BMMSCs in prostate tissue of CBP mice. In addition, DHA and BMMSCs cotreatment significantly alleviated inflammation and improved prostate damage by decreasing the expression of proinflammatory factors such as TNF-α, IL-1ß, and chemokines CXCL2, CXCL9, CXCL10, and CXCL11 in prostate tissue of CBP mice. Moreover, DHA and BMMSCs cotreatment displayed antioxidation property by increasing the production of glutathione peroxidase (GSH-Px), SOD, and decreasing malondialdehyde (MDA) expression. Mechanically, DHA and BMMSCs cotreatment significantly inhibited the expression of TGFß-RI, TGFß-RII, phosphor (p)-Smad2/3, and Smad4 in a dose-dependent manner while stimulated Smad7 expression in the same manner. In conclusion, our findings provided evidence that DHA effectively eliminated inflammatory and oxidative stress against prostate injury, and this effect involved the TGF-ß/Smad signaling pathway in CBP.

A simple nomogram prediction model to identify relatively young patients with mild cognitive impairment who may progress to Alzheimer's disease.

AIM: Construct a clinical predictive model based on easily accessible clinical features and imaging data to identify patients 65 years of age and younger with mild cognitive impairment(MCI) who may progress to Alzheimer's disease(AD). METHODS: From the ADNI database, patients with MCI who were less than or equal to 65 years of age and who had been followed for 6-60 months were selected.We collected demographic data, neuropsychological test scale scores, and structural magnetic images of these patients. Clinical characteristics were then screened, and VBM and SBM analyses were performed using structural nuclear magnetic images to obtain imaging histology characteristics. Finally, predictive models were constructed combining the clinical and imaging histology characteristics. RESULTS: The constructed nomogram has a cross-validated AUC of 0.872 in the training set and 0.867 in the verification set, and the calibration curve fits well.We also provide an online model-based forecasting tool. CONCLUSION: The model has good performance and uses convenience,it should be able to provide assistance in clinical work to screen relatively young MCI patients who may progress to AD.