MATERIALS AND METHODS: Diabetic ADSCs were treated with DFO and compared to normal and non-treated diabetic ADSCs for expression of HIF-1α, VEGF, FGF-2 and SDF-1, at mRNA and protein levels, using qRT-PCR, western blotting and ELISA assay. Activity of matrix metalloproteinases -2 and -9 were measured using a gelatin zymography assay. Angiogenic potential of conditioned media derived from normal, DFO-treated and non-treated diabetic ADSCs were determined by in vitro (in HUVECs) and in vivo experiments including scratch assay, three-dimensional tube formation testing and surgical wound healing models.
RESULTS: DFO remarkably enhanced expression of noted genes by mRNA and protein levels and restored activity of matrix metalloproteinases -2 and -9. Compromised angiogenic potential of conditioned medium derived from diabetic ADSCs was restored by DFO both in vitro and in vivo experiments.
CONCLUSION: DFO preconditioning restored neovascularization potential of ADSCs derived from diabetic rats by affecting the HIF-1α pathway.
METHODS: This was a prospective observational study performed at the Glaucoma Research Centre, Montchoisi Clinic, Lausanne. In total 40 eyes with open-angle glaucoma were included. OCT-A scans were performed before glaucoma surgery, and at 1-month, 3-month, 6-month, and 12-month post-operatively. AngioVue AngioAnalytic (Optovue Inc, Fremont, CA) software was used to analyse the RNFL, FAZ, peripapillary and macular VD. Changes were analysed using analysis of variance (ANOVA) models.
RESULTS: Mean IOP dropped from 19.4 (±7.0) mmHg pre-surgery and stabilized at 13.0 (±3.1) mmHg at 12 months (p
METHODS: All relevant studies were extracted by searching national and international databases of SID, MagIran, ProQuest, PubMed, Science Direct, Scopus, Web of Science (WoS), and Google Scholar without time limit until October 2020. Finally, the meta-analysis was performed with the 11 remaining studies containing 14 different drug supplements. The standardized mean difference (SMD) was calculated at a 95% confidence interval (CI) to evaluate the effects of each treatment group compared with placebo. A random-effect model was used to evaluate the effect of individual studies on the final result. Heterogeneity and incompatibility of the network were assessed by Cochran's Q and Higgins I2, and the Net Heat chart, respectively. Data analysis was performed using R software.
RESULTS: Our results showed that there were significant mean effects in people intervened with Phentermine 15.0 mg + Topiramate 92.0 mg, Phentermine 7.5 mg + Topiramate 46.0 mg, Pramlintide, Naltrexone + Bupropion 32, and Liraglutide, with SMD effects size = - 9.1, - 7.4, - 6.5, - 5.9, - 5.35, respectively.
CONCLUSION: This study was performed to compare the effect of different drugs used for weight loss in obese patients. The most effective drugs for weight loss were phentermine and topiramate, pramlintide, naltrexone, bupropion, and liraglutide compared to placebo treatment, respectively. This study provides new insights into anti-obesity drugs and hopes to shed new light on future research to manage and treat obesity.