Age-related macular degeneration is one of the major causes of blindness in the elderly. As an important pathway of cell metabolism, autophagy maintains intracellular homeostasis through the degradation and recycle of damaged organelles and macromolecules. Understanding its mechanism may promote discoveries to delay aging process, reduce the incidence of age-related diseases. In mammals, silent information regulator protein 6 (SIRT6) plays its deacetylase and ribonucleotransferase activity in multiple signaling pathways, including inhibition of cellular senescence, tumorigenesis, metabolic diseases, regulating cellular lifespan. It has a significant impact on the structure and function of tissues and organs. SIRT6 regulates intracellular autophagy mainly through the insulin-like growth factor-protein kinase B-mammalian target of rapamycin, reducing the accumulation of toxic metabolites and cellular senescence. The function of SIRT6 in age-related macular degeneration need to be combined with the genetic background, pathogenesis, clinical manifestations and other aspects of the disease, and it is expected to be further studied in subsequent studies.
Diabetic retinopathy is a vascular complication of diabetes, and homocysteine is an intermediate product of methionine metabolism. Hyperhomocysteinemia can directly or indirectly damage vascular endothelial cells, causing vascular endothelial cells dysfunction and participating in the occurrence and development of diabetic retinopathy. Uric acid is the final product of purine metabolism. Hyperuricemia can cause vascular endothelial dysfunction, oxidative metabolism, platelet adhesion and aggregation dysfunction, thus participating in the occurrence and development of diabetic retinopathy. In recent years, there have been many studies on the correlation between diabetic retinopathy and levels of homocysteine and uric acid. This article reviews the relevant literature at home and abroad in order to provide new information for the prevention and treatment of diabetic retinopathy.
ObjectiveTo compare the consistency of artificial analysis and artificial intelligence analysis in the identification of fundus lesions in diabetic patients.MethodsA retrospective study. From May 2018 to May 2019, 1053 consecutive diabetic patients (2106 eyes) of the endocrinology department of the First Affiliated Hospital of Zhengzhou University were included in the study. Among them, 888 patients were males and 165 were females. They were 20-70 years old, with an average age of 53 years old. All patients were performed fundus imaging on diabetic Inspection by useing Japanese Kowa non-mydriatic fundus cameras. The artificial intelligence analysis of Shanggong's ophthalmology cloud network screening platform automatically detected diabetic retinopathy (DR) such as exudation, bleeding, and microaneurysms, and automatically classifies the image detection results according to the DR international staging standard. Manual analysis was performed by two attending physicians and reviewed by the chief physician to ensure the accuracy of manual analysis. When differences appeared between the analysis results of the two analysis methods, the manual analysis results shall be used as the standard. Consistency rate were calculated and compared. Consistency rate = (number of eyes with the same diagnosis result/total number of effective eyes collected) × 100%. Kappa consistency test was performed on the results of manual analysis and artificial intelligence analysis, 0.0≤κ＜0.2 was a very poor degree of consistency, 0.2≤κ＜0.4 meant poor consistency, 0.4≤κ＜0.6 meant medium consistency, and 0.6≤κ＜1.0 meant good consistency.ResultsAmong the 2106 eyes, 64 eyes were excluded that cannot be identified by artificial intelligence due to serious illness, 2042 eyes were finally included in the analysis. The results of artificial analysis and artificial intelligence analysis were completely consistent with 1835 eyes, accounting for 89.86%. There were differences in analysis of 207 eyes, accounting for 10.14%. The main differences between the two are as follows: (1) Artificial intelligence analysis points Bleeding, oozing, and manual analysis of 96 eyes (96/2042, 4.70%); (2) Artificial intelligence analysis of drusen, and manual analysis of 71 eyes (71/2042, 3.48%); (3) Artificial intelligence analyzes normal or vitreous degeneration, while manual analysis of punctate exudation or hemorrhage or microaneurysms in 40 eyes (40/2042, 1.95%). The diagnostic rates for non-DR were 23.2% and 20.2%, respectively. The diagnostic rates for non-DR were 76.8% and 79.8%, respectively. The accuracy of artificial intelligence interpretation is 87.8%. The results of the Kappa consistency test showed that the diagnostic results of manual analysis and artificial intelligence analysis were moderately consistent (κ=0.576, P＜0.01).ConclusionsManual analysis and artificial intelligence analysis showed moderate consistency in the diagnosis of fundus lesions in diabetic patients. The accuracy of artificial intelligence interpretation is 87.8%.
ObjectiveTo observe the longterm effect of suramin on the inhibition of proliferation of human retinal pigment epithelial (RPE) cells in vitro. MethodsRPE cells grown in 9 pieces of 96well plate (12 wells each plate) were divided into experimental and control group, with 6 wells in each group. The concentration of 0.1 ml RPE cells in each well is 5×104 cells/ml. After the change of the medium, RPE cells were treated with suramin (250 μg/ml) in experimental group while treated with nothing in the control group. The medium of the 2 groups were changed to the normal medium after 4 days. At the 1st, 2nd, and 4thday after the addition of suramin and at the 1st, 2nd, 3rd, 5th, 6th, 7th, 9th , 11th and 13th day after removing suramin, 1 plate was randomly selected to stop culturing, and the proliferation of RPE cells were detected by methyl thiazolyl tetrazolium (MTT) assay. ResultsUnder reversed microscope, RPE cells in control group were fused completely at the 7th day after inoculation. The extracellular space of RPE cells in experimental groups was larger than that in the control group, and remained unfused at the 13th day after inoculation. The inhibitory rate of proliferation of RPE cells at the first day after treated with suramin was 14.85% and increased to the highest 25.79% at the 4th day. The first day after the suramincontaining media was removed, the inhibitory rate decreased to 12.35%, and then raised gradually to over 20% at the 3rd to 5th day. Finally, the rate drop to 14.71%. ConclusionSuramin has the long-term effect on the inhibition of RPE cells induced by serum, especially the inhibitive effect after the remove of suramin, which indicates the specific double-peak inhibition during the whole process.(Chin J Ocul Fundus Dis, 2005,21:25-27)
The prevalence of diabetes mellitus in adults of China has reached 12.8%. Diabetic retinopathy (DR) accounts for approximately 1/4-1/3 of the diabetic population. Several millions of people are estimated suffering the advanced stage of DR, including severe non-proliferative DR (NPDR), proliferative DR (PDR) and diabetic macular edema (DME), which seriously threat to the patients’ vision. On the basis of systematic prevention and control of diabetes and its complications, prevention of the moderate and high-risk NPDR from progressing to the advanced stage is the final efforts to avoid diabetic blindness. The implementation of the DR severity scale is helpful to assess the severity, risk factors for its progression, treatment efficacy and prognosis. In the eyes with vision-threatening DR, early application of biotherapy of anti-vascular endothelial growth factor can improve DR with regression of retinal neovascularization, but whether it is possible to induce capillary re-canalization in the non-perfusion area needs more investigation. Laser photocoagulation remains the mainstay treatment for non-center-involved DME and PDR.
Objective Methods Ninety male Wister rats were randomly divided into normal control group, diabetic group and FTY720 group, thirty rats in each group. Diabetes was induced by giving a single intraperitoneal injection of streptozocin. FTY720 group was administered with FTY720 at a dose of 0.3 mg/kg by oral gavage daily for 3 months after establishment of diabetes. All rats were used for experiments following intervention for 3 months in FTY720 group. Immunohistochemical staining was used to observe the expression and distribution of intercellular adhesion molecule (ICAM-1) and vascular cell adhesion molecule (VCAM-1), and the positive cells were counted. Real-time reverse transcription PCR was used to measure mRNA expression of ICAM-1 and VCAM-1. Fluorescein isothiocyanate-Concanavalin A perfusion was used to detect retinal leukocytes adhesion. Evans blue (EB) perfusion was used to analyze retinal vascular permeability. Immunofluorescence staining was used to detect retinal inflammatory cells infiltration. Results In diabetic group, both ICAM-1(t=12.81) and VCAM-1 (t=11.75) positive cells as well as their mRNA expression (t=16.14, 9.59) were increased compared with normal control group, with statistical significance (P < 0.05). In FTY720 group, both ICAM-1(t=-9.93) and VCAM-1 (t=-6.61) positive cells as well as their mRNA expression (t=-15.28, -6.10) were decreased compared with diabetic group, with statistical significance (P < 0.05). Retinal leukocytes adhesion (t=16.32) and EB permeability (t=17.83) were increased in diabetic group compared with normal control group, while they were decreased in FTY720 group compared with diabetic group(t=-9.93, -11.82),with statistical significance (P < 0.05). There were many CD45 positive leukocytes infiltration in retina of diabetic group, including CD11b positive macrophage/activated microglia, while both of them were little in FTY720 group. Conclusions FTY720 can decrease retinal leukocytes adhesion, reduce retinal vascular permeability and inflammatory cells infiltration, which is associated with down-regulation of ICAM-1 and VCAM-1.
The pathogenesis of diabetic retinopathy (DR) is complex and there are many related risk factors. It is related to the course of diabetes, blood glucose, blood pressure, and blood lipids, among which the course of disease and hyperglycemia are recognized main risk factors. In addition, other factors which include heredity, gender, age, obesity, pregnancy, insulin use, can also affect the occurrence and development of DR, but there is no unified conclusion about its correlation. A comprehensive understanding of the risk factors that affect DR can provide new ideas for the prevention, diagnosis, treatment, and intervention of DR.