Objective To observe the expression ofprobucol on high glucose-induced specificity protein 1 (SP 1),kelchlike ECH associated protein 1 (Keap 1),NF-E2-related factor 2 (Nrf2) and glutamatecysteine ligase catalytic (GCLC) in the cultured human müller cells and preliminary study the antioxidation of the probucol on müller cells.Methods Primary cultured human müller cells were randomly divided into four groups:normoglycaemia group (5.5 mmol/L glucose),normoglycaemia with probucol group (5.5 mmol/L glucose+100 μmol/L probucol),hyperglycemia group (25.0 mmol/L glucose),hyperglycemia with probucol group (25.0 mmol/L glucose + 100 μmol/L probucol).Immunofluorescence staining was used to assess distribution of SP1,Keapl,Nrf2,GCLC in human Müller cells.SP1,Keapl,Nrf2 and GCLC messenger RNA (mRNA) expression was evaluated by quantitative real-time RT-PCR (qRT-PCR).Independent sample t test was used to compare the data between the two groups.Results All müller cells expressed glutamine synthetase (＞ 95％),which confirmed the cultured cells in vitro were the purification of generations of müller cells.The expressions of SP 1,Keap 1,Nrf2,and GCLC protein were positive in human müller cells.qRT-PCR indicated that SP1 (t=28.30,P＜0.000),Keap1 (t=5.369,P=0.006),and Nrf2 (t=10.59,P=0.001) mRNA in the hyperglycemia group increased obviously compared with the normoglycaemia group;GCLC (t=4.633,P=0.010)mRNA in the hyperglycemia group decreased significantly compared with the normoglycaemia group.However,SP1 (t=12.60,P=0.000) and Keapl (t=4.076,P=0.015) in the hyperglycemia with probucol group decreased significantly compared with the hyperglycemia group;Nrf2 (t=12.90,P=0.000) and GCLC (t=l 5.96,P＜0.000)mRNA in the hyperglycemia with probucol group increased obviously compared with with the hyperglycemia group.Conclusion Probucol plays an antioxidant role by inhibiting the expression of SP 1,Keap 1 and upregulating the expression of Nrf2,GCLC in müller cells induced by high glucose.

ObjectiveTo construct and validate a clinical prediction model for diabetic kidney disease （DKD） based on optical coherence tomography angiography （OCTA）. MethodsThis study enrolled 567 diabetes patients. The random forest algorithm as well as logistic regression analysis were applied to construct the prediction model. The model discrimination and clinical usefulness were evaluated by receiver operating characteristic curve （ROC） and decision curve analysis （DCA）， respectively. ResultsThe clinical prediction model for DKD based on OCTA was constructed with area under the curve （AUC） of 0.878 and Brier score of 0.11. ConclusionsThrough multidimensional verification， the clinical prediction nomogram model based on OCTA allowed for early warning and advanced intervention of DKD.