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Summary: Background: To date, comprehensive data on the distribution of chronic kidney disease (CKD), the most prevalent comorbidity in diabetes, among Chinese adults with diabetes is lacking. Additionally, research gaps exist in understanding the association between CKD and cardiovascular health (CVH), an integrated indicator of lifestyle and metabolic control, within a nationwide sample of Chinese adults with diabetes. Methods: A nationally community-based cross-sectional survey was conducted in 2018–2020. 58,560 residents diagnosed with diabetes aged 18–74 years nationwide were invited to participate, and 52,000 participants with complete CKD data were included in this study. CKD was identified by the presence of albuminuria (urine albumin-to-creatinine ratio ≥30 mg/g) and/or decreased estimated glomerular filtration rate (eGFR,

BackgroundDiabetes, a chronic disease necessitating long-term treatment and self-management, presents significant challenges for patients who spend most of their treatment time outside of hospitals. The potential of digital therapeutics for diabetes has garnered recognition from different organizations. Although some prior studies have demonstrated successful reductions in patients’ blood glucose levels and body weight through digital diabetes programs, many studies were limited by including patients with prediabetes, including patients treated with mostly premixed insulin, or evaluating user engagement outcomes rather than clinical outcomes. Consequently, limited evidence remains regarding the effectiveness of health management mobile apps specifically designed for patients with type 2 diabetes mellitus (T2DM) initiating basal insulin (BI). Based on this, a data-based and artificial intelligence management system named “TRIO” was developed to provide patients with more personalized intervention methods in stages, in groups, and around the clock. TRIO assists doctors and nurses in achieving better blood glucose controls, truly carries out standardized management around patients, and allows them to have a higher quality of life. TRIO represents the 3 essential pillars in comprehensive diabetes management: physician, nurse, and patient. ObjectiveThis prospective observational study evaluated the effectiveness and safety of the TRIO optimal health management program for patients with T2DM initiating BI therapy in a real-world setting. MethodsPatients aged 18-85 years with inadequate glycemic control (baseline hemoglobin A1c [HbA1c] ≥7%) starting BI therapy were enrolled in outpatient and inpatient settings. The study lasted 3 months, with health education and phone-based follow-up assessments. Data collected included patient characteristics, medical history, baseline diabetes conditions, treatment compliance, glycemic control, and safety indicators. ResultsA total of 199,431 patients were included, and 118,134 patients completed the 3-month follow-up between December 1, 2019, and December 31, 2021, involving 574 hospitals in China. The mean baseline HbA1c was 9.2%, the mean duration of diabetes was 7.3 years, and 80.4% (1,59,930/1,98,969) of patients were using BI with oral antihyperglycemic drugs. After the intervention, mean HbA1c decreased by –2.59% from baseline, with 55.6% (28,858/51,912) achieving the target HbA1c level of

Abstract Background The incidence of male reproductive dysfunction is increasing annually, and many studies have shown that obesity can cause severe harm to male reproductive function. The mechanism of male reproductive dysfunction caused by obesity is unclear, and there is no ideal treatment. Identification of effective therapeutic drugs and elucidation of the molecular mechanism involved in male reproductive health are meaningful. In this study, we investigated the effects of the GLP-1 receptor agonist liraglutide on sex hormones, semen quality, and testicular AC3/cAMP/PKA levels in high-fat-diet-induced obese mice. Methods Obese mice and their lean littermates were treated with liraglutide or saline for 12 weeks. Body weight was measured weekly. Fasting blood glucose (FBG) was measured using a blood glucose test strip. The serum levels of insulin (INS), luteinizing hormone (LH), follicle stimulating hormone (FSH), testosterone (T), free testosterone (F-TESTO), estradiol (E2), and sex hormone binding globulin (SHBG) were detected using ELISA. The sperm morphology and sperm count were observed after Pap staining. The mRNA and protein expression levels of testicular GLP-1R and AC3 were measured by RT-qPCR and Western blot, respectively. Testicular cAMP levels and PKA activity were detected using ELISA. Results Liraglutide treatment can decrease body weight, FBG, INS, HOMA-IR, E2 and SHBG levels; increase LH, FSH, T, and F-TESTO levels; increase sperm count; decrease the sperm abnormality rate; and increase GLP-1R and AC3 expression levels and cAMP levels and PKA activity in testicular tissue. Conclusions Liraglutide can improve the sex hormone levels and semen quality of obese male mice. In addition to its weight loss effect, liraglutide can improve the reproductive function of obese male mice, which may also be related to the upregulation of AC3/cAMP/PKA pathway in the testis. This work lays the groundwork for future clinical studies.

BackgroundProviding comprehensive and individualized diabetes care remains a significant challenge in the face of the increasing complexity of diabetes management and a lack of specialized endocrinologists to support diabetes care. Clinical decision support systems (CDSSs) are progressively being used to improve diabetes care, while many health care providers lack awareness and knowledge about CDSSs in diabetes care. A comprehensive analysis of the applications of CDSSs in diabetes care is still lacking. ObjectiveThis review aimed to summarize the research landscape, clinical applications, and impact on both patients and physicians of CDSSs in diabetes care. MethodsWe conducted a scoping review following the Arksey and O’Malley framework. A search was conducted in 7 electronic databases to identify the clinical applications of CDSSs in diabetes care up to June 30, 2022. Additional searches were conducted for conference abstracts from the period of 2021-2022. Two researchers independently performed the screening and data charting processes. ResultsOf 11,569 retrieved studies, 85 (0.7%) were included for analysis. Research interest is growing in this field, with 45 (53%) of the 85 studies published in the past 5 years. Among the 58 (68%) out of 85 studies disclosing the underlying decision-making mechanism, most CDSSs (44/58, 76%) were knowledge based, while the number of non-knowledge-based systems has been increasing in recent years. Among the 81 (95%) out of 85 studies disclosing application scenarios, the majority of CDSSs were used for treatment recommendation (63/81, 78%). Among the 39 (46%) out of 85 studies disclosing physician user types, primary care physicians (20/39, 51%) were the most common, followed by endocrinologists (15/39, 39%) and nonendocrinology specialists (8/39, 21%). CDSSs significantly improved patients’ blood glucose, blood pressure, and lipid profiles in 71% (45/63), 67% (12/18), and 38% (8/21) of the studies, respectively, with no increase in the risk of hypoglycemia. ConclusionsCDSSs are both effective and safe in improving diabetes care, implying that they could be a potentially reliable assistant in diabetes care, especially for physicians with limited experience and patients with limited access to medical resources. International Registered Report Identifier (IRRID)RR2-10.37766/inplasy2022.9.0061

Background Recent studies have shown that the accumulation of free iron and lipid peroxides will trigger a new form of cell death—ferroptosis. This form of cell death is associated with a variety of diseases, including type 2 diabetes. We hypothesize that iron overload may play a role in driving glucose metabolism abnormalities by inducing endoplasmic reticulum stress that mediates ferroptosis in islet β cells. In this study, we tested this conjecture from in vivo and in vitro experiments. Methods We established a mouse iron overload model by intraperitoneal injection of iron dextrose (50 mg/kg) and an iron overload cell model by treating MIN6 cells with ferric ammonium citrate (640 μmol/L, 48 h) in vitro. The iron deposition in pancreatic tissue was observed by Prussian blue staining, and the pathological changes in pancreatic tissues by HE staining and the protein expression level by pancreatic immunohistochemistry. In the cellular experiments, we detected the cell viability by CCK8 and observed the cellular ultrastructure by transmission electron microscopy. We also used MDA and ROS kits to detect the level of oxidative stress and lipid peroxidation in cells. Western blotting was performed to detect the expression levels of target proteins. Results Iron overload induces MIN6 cell dysfunction, leading to increased fasting blood glucose, impaired glucose tolerance, and significantly decreased insulin sensitivity in mice. This process may be related to the ferroptosis of islet β cells and the activation of ASK1/P-P38/CHOP signaling pathway.

ObjectiveIron overload plays an important role in the pathogenesis of diabetes and acute kidney injury (AKI). The aim of this present study was to explore the relationship between iron metabolism and AKI in patients with diabetes.MethodsThe clinical data of diabetes patients from MIMIC-III database in intensive care unit (ICU) were retrospectively analyzed. Regression analyses were used to explore the risk factors of AKI and all-cause death in critical patients with diabetes. Area under the receiver operating characteristic curves (AUROCs) were used to analyze serum ferritin (SF), and regression model to predict AKI in critical patients with diabetes. All diabetes patients were followed up for survival at 6 months, and Kaplan–Meier curves were used to compare the survival rate in patients with different SF levels.ResultsA total of 4,997 diabetic patients in ICU were enrolled, with a male-to-female ratio of 1.37:1 and a mean age of 66.87 ± 12.74 years. There were 1,637 patients in the AKI group (32.8%) and 3,360 patients in the non-AKI group. Multivariate logistic regression showed that congestive heart failure (OR = 2.111, 95% CI = 1.320–3.376), serum creatinine (OR = 1.342, 95% CI = 1.192–1.512), Oxford Acute Severity of Illness Score (OR = 1.075, 95% CI = 1.045–1.106), increased SF (OR = 1.002, 95% CI = 1.001–1.003), and decreased transferrin (OR = 0.993, 95% CI = 0.989–0.998) were independent risk factors for AKI in critical patients with diabetes. Multivariate Cox regression showed that advanced age (OR = 1.031, 95% CI = 1.025–1.037), AKI (OR = 1.197, 95% CI = 1.011–1.417), increased Sequential Organ Failure Assessment score (OR = 1.055, 95% CI = 1.032–1.078), and increased SF (OR = 1.380, 95% CI = 1.038–1.835) were independent risk factors for 6-month all-cause death in critical diabetic patients. The AUROCs of SF and the regression model to predict AKI in critical patients with diabetes were 0.782 and 0.851, respectively. The Kaplan–Meier curve showed that the 6-month survival rate in SF-increased group was lower than that in SF-normal group (log-rank χ2 = 16.989, P < 0.001).ConclusionCritically ill diabetic patients with AKI were easily complicated with abnormal iron metabolism. Increase of SF is an important risk factor for AKI and all-cause death in critically ill patients with diabetes.

The origin of life involved complicated evolutionary processes. Computer modeling is a promising way to reveal relevant mechanisms. However, due to the limitation of our knowledge on prebiotic chemistry, it is usually difficult to justify parameter-setting for the modeling. Thus, typically, the studies were conducted in a reverse way: the parameter-space was explored to find those parameter values "supporting" a hypothetical scene (that is, leaving the parameter-justification a later job when sufficient knowledge is available). Exploring the parameter-space manually is an arduous job (especially when the modeling becomes complicated) and additionally, difficult to characterize as regular "Methods" in a paper. Here we show that a machine-learning-like approach may be adopted, automatically optimizing the parameters. With this efficient parameter-exploring approach, the evolutionary modeling on the origin of life would become much more powerful. In particular, based on this, it is expected that more near-reality (complex) models could be introduced, and thereby theoretical research would be more tightly associated with experimental investigation in this field-hopefully leading to significant steps forward in respect to our understanding on the origin of life.

ObjectiveWe aimed to analyze the risk factors affecting all-cause mortality in diabetic patients with acute kidney injury (AKI) and to develop and validate a nomogram for predicting the 90-day survival rate of patients.MethodsClinical data of diabetic patients with AKI who were diagnosed at The First Affiliated Hospital of Guangxi Medical University from April 30, 2011, to April 30, 2021, were collected. A total of 1,042 patients were randomly divided into a development cohort and a validation cohort at a ratio of 7:3. The primary study endpoint was all-cause death within 90 days of AKI diagnosis. Clinical parameters and demographic characteristics were analyzed using Cox regression to develop a prediction model for survival in diabetic patients with AKI, and a nomogram was then constructed. The concordance index (C-index), receiver operating characteristic curve, and calibration plot were used to evaluate the prediction model.ResultsThe development cohort enrolled 730 patients with a median follow-up time of 87 (40–98) days, and 86 patients (11.8%) died during follow-up. The 90-day survival rate was 88.2% (644/730), and the recovery rate for renal function in survivors was 32.9% (212/644). Multivariate analysis showed that advanced age (HR = 1.064, 95% CI = 1.043–1.085), lower pulse pressure (HR = 0.964, 95% CI = 0.951–0.977), stage 3 AKI (HR = 4.803, 95% CI = 1.678–13.750), lower 25-hydroxyvitamin D3 (HR = 0.944, 95% CI = 0.930–0.960), and multiple organ dysfunction syndrome (HR = 2.056, 95% CI = 1.287–3.286) were independent risk factors affecting the all-cause death of diabetic patients with AKI (all p

Liraglutide is a glucagon-like peptide-1 analogue widely used in the treatment of type 2 diabetes mellitus. However, the effects of liraglutide on osteoblast proliferation and differentiation in MC3T3-E1 cells have not been fully elucidated. In the present study, the promoting effects of liraglutide were investigated in MC3T3-E1 cells. The results indicated that cell viability was affected following the treatment of the cells with different concentrations of liraglutide (0, 10, 100, and 1000 nM) at different time periods of culture (24, 48, and 72 h). Moreover, the activity levels of alkaline phosphatase and the number of mineralized nodules in MC3T3-E1 cells were significantly increased following treatment with 100 nM liraglutide. The mRNA and protein levels of Col-1, OPG, and OCN in MC3T3-E1 cells were also markedly increased following 100 nM liraglutide treatment compared with those of the control group. The expression levels of the ERK5 signaling pathway key proteins (MEK5, p-ERK5, ERK5, and NUR77) were increased following liraglutide treatment in MC3T3-E1 cells, and the gene expression levels of the ERK5 signaling pathway were also elevated. Moreover, the ERK5 inhibitor XMD8-92 significantly decreased the expression levels of p-ERK5 and NUR77 as well as the proliferation of osteoblasts. However, these changes could be rescued by liraglutide to some extent. Therefore, these results revealed that liraglutide may promote osteoblastic differentiation and proliferation in MC3T3-E1 cells via the activation of the ERK5 signaling pathway.

Arsenate [As(V)] soil contamination is a great concern worldwide because of its high toxicity, carcinogenicity, and mobility. The adsorption of As(V) on soil minerals such as ferrihydrite and δ-MnO2 controls the transport and bioavailability of As(V) in the soil environment. A large number of studies have investigated the equilibrium and mechanisms of As(V) adsorption onto ferrihydrite and δ-MnO2 individually. However, both ferrihydrite and δ-MnO2, commonly coexisting within soils has been overlooked and little information is available for the kinetics of As(V) adsorption and desorption in this mixed mineral system. Therefore, in this work, kinetics of As(V) adsorption and desorption onto ferrihydrite and δ-MnO2 mixed minerals is studied using the stirred-flow method. A kinetics model for the mixed mineral system was developed using the component additivity approach, which incorporated the nonlinear binding of As(V) to both ferrihydrite and δ-MnO2 simultaneously. The kinetics model successfully predicted the kinetics of As(V) adsorption and desorption in the mixed mineral system under varying solution chemistry conditions and properly accounted for the heterogeneity of the binding sites of both ferrihydrite and δ-MnO2. For As(V) adsorption kinetics, the ferrihydrite bidentate non-protonated sites (Fh-bi-np) played a dominant role, followed by the δ-MnO2 binding sites and the ferrihydrite bidentate protonated sites (Fh-bi-p). After the 4-h desorption, As(V) was mainly retained on ferrihydrite binding sites. This study helps to quantitatively elucidate the kinetic behavior and mechanisms of As(V) in the Fe oxide and Mn oxide systems, thus enhancing our understanding of the fate and transport of As in soil environments. [ABSTRACT FROM AUTHOR]

Arsenate [As(V)] soil contamination is a great concern worldwide because of its high toxicity, carcinogenicity, and mobility. The adsorption of As(V) on soil minerals such as ferrihydrite and δ-MnO2 controls the transport and bioavailability of As(V) in the soil environment. A large number of studies have investigated the equilibrium and mechanisms of As(V) adsorption onto ferrihydrite and δ-MnO2 individually. However, both ferrihydrite and δ-MnO2, commonly coexisting within soils has been overlooked and little information is available for the kinetics of As(V) adsorption and desorption in this mixed mineral system. Therefore, in this work, kinetics of As(V) adsorption and desorption onto ferrihydrite and δ-MnO2 mixed minerals is studied using the stirred-flow method. A kinetics model for the mixed mineral system was developed using the component additivity approach, which incorporated the nonlinear binding of As(V) to both ferrihydrite and δ-MnO2 simultaneously. The kinetics model successfully predicted the kinetics of As(V) adsorption and desorption in the mixed mineral system under varying solution chemistry conditions and properly accounted for the heterogeneity of the binding sites of both ferrihydrite and δ-MnO2. For As(V) adsorption kinetics, the ferrihydrite bidentate non-protonated sites (Fh-bi-np) played a dominant role, followed by the δ-MnO2 binding sites and the ferrihydrite bidentate protonated sites (Fh-bi-p). After the 4-h desorption, As(V) was mainly retained on ferrihydrite binding sites. This study helps to quantitatively elucidate the kinetic behavior and mechanisms of As(V) in the Fe oxide and Mn oxide systems, thus enhancing our understanding of the fate and transport of As in soil environments. [ABSTRACT FROM AUTHOR]

Sorptive fractionation of organic matter (OM) at mineral-water interfaces alters the composition of OM and therefore affects the fate, transport, and bioavailability of nutrients and contaminants in terrestrial and aquatic environments. It is essential to identify the fractions of OM that are selectively sorbed on minerals and to elucidate the mechanisms of sorptive fractionation. In this study, the partition between mineral and water for a large set of organic molecules covering the most relevant OM functional groups and building blocks were predicted using the mechanistic Polyparameter Linear Free Energy Relationships (pp-LFERs). The results were used to infer the sorptive fractionation tendency of OM moieties. It is found that for a OM moiety belonging to the chemical classes of alkanes, alkenes, or benzenes, its sorption to bentonite is the strongest, followed by kaolinite, talc or hematite, and Al2O3 or quartz, relative to water. For a moiety with either double bond, or -OH, or -COOH, or R-COO-R, or R-O-R, or R-COH, or R-CO-R or -NH2, its partition to water is enhanced as compared to the respective alkane moiety. Opposite is found for thiols and sulfides. Meanwhile, a correlation is developed, that is, as the double bond equivalence decreases and the number of C atoms increases, the degree of sorption increases. Overall, the key factors controlling the sorptive fractionation are polarity, H-bonding, van de Waals dispersion, and the energy for cavity formation. This work provides insights into the OM sorption at the mineral and water interface at the molecular level. [ABSTRACT FROM AUTHOR]

Understanding the effect of ferrihydrite morphology on the kinetic reactions of metals with ferrihydrite is essential for predicting the dynamic behavior of metals in soil. In this study, kinetics of Pb(II) and Cu(II) adsorption and desorption on two types of ferrihydrite, the freshly precipitated gellike ferrihydrite and freeze-dried dense ferrihydrite representing two typical morphologies under extreme soil conditions, were studied. The high-resolution transmission electron microscopy (TEM) images revealed that the gellike ferrihydrite loosely aggregated with open structure, while the dense ferrihydrite compactly aggregated with more consolidated and thicker structure. The energy dispersive spectroscopy (EDS), at the nanometer scale, showed that Pb(II) and Cu(II) distributed evenly on gellike ferrihydrite but localized on dense ferrihydrite after adsorption. The stirred-flow kinetic experiments showed that higher pH and higher influent metal concentrations increased metal adsorption for both types of ferrihydrite. The dense ferrihydrite adsorbed slower and much less metals than gellike ferrihydrite because of less reactive sites. The desorption of heavy metals from ferrihydrite was affected by combined factors of the ferrihydrite morphology, adsorbed metal concentrations, pH, and metal re-adsorption rates. The mechanic kinetics model based on the CD-MUSIC model successfully described the adsorption and desorption kinetics of Pb(II) and Cu(II) on both gellike and dense ferrihydrite under various chemistry conditions. Our model provided quantitative tools for considering the effects of ferrihydrite morphology and heterogeneous binding sites under varying solution chemistry conditions when predicting the dynamic behavior of Pb(II) and Cu(II) in soil environment. [ABSTRACT FROM AUTHOR]

Nicotinamide phosphoribosyltransferase (Nampt) is a key enzyme in the nicotinamide adenine dinucleotide (NAD+) biosynthetic pathway. Exogenous extra cellular Nampt has been reported to increase the synthesis of pro-fibrotic molecules in various types of renal cells. However, the role of endogenous Namptenzymatic activity in diabetic renal cells, particularly those associated with inflammation and fibrosis through the nuclear factor (NF)-κB p65 and sirtuin 1 (Sirt1) pathway is still unknown. In the present study, a possible mechanism by which endogenous Nampt upregulation affects the expression of pro-inflammatory and pro-fibrotic cytokines in vivo and in vitro, is reported. The present results demonstrate that the expression of vimentin and fibronectin was directly implicated in endogenous Nampt upregulation. The expression levels of Poly(ADP-ribose) polymerase-1, NF-κB p65, forkhead box protein O1 and B-cell lymphoma 2-like protein 4 were also significantly increased at 96 h compared with control group (P<0.01) respectively in response to endogenous Nampt upregulation. Furthermore, the expression level of Sirt1 was significantly reduced (P<0.05), and the NAD and NADH levels, and the NAD/NADH ratio are significantly altered in STZ-induced diabetic rats (P<0.01). Treatment with FK866 and nicotinamide mononucleotide (NMN) led to downregulation of vimentin and fibronectin, respectively. These results suggest a novel role of Nampt as a pro-inflammatory cytokine of mesangial fibrotic signaling. The Nampt-NF-κB p65 and Sirt1 signaling pathway serves a pivotal role in affecting the expression of fibrosis factors in diabetic nephropathy (DN) glomerular fibrosis processing. It is also suggested that prevention of endogenous Nampt upregulation may be critical in the treatment of DN pro-inflammatory fibrosis and NMN is likely to be a potential pharmacological agent for the treatment of resistant DN nephritic fibrosis. [ABSTRACT FROM AUTHOR]

A partitioning-based model is presented to estimate the bioconcentration of five munitions compounds and two munition-like compounds in grasses. The model uses polyparameter linear free energy relationships (pp-LFERs) to estimate the partition coefficients between soil organic carbon and interstitial water and between interstitial water and the plant cuticle, a lipid-like plant component. Inputs for the pp-LFERs are a set of numerical descriptors computed from molecular structure only that characterize the molecular properties that determine the interaction with soil organic carbon, interstitial water, and plant cuticle. The model is validated by predicting concentrations measured in the whole plant during independent uptake experiments with a root-mean-square error (log predicted plant concentration-log observed plant concentration) of 0.429. This highlights the dominant role of partitioning between the exposure medium and the plant cuticle in the bioconcentration of these compounds. The pp-LFERs can be used to assess the environmental risk of munitions compounds and munition-like compounds using only their molecular structure as input. [ABSTRACT FROM AUTHOR]

Background: Papillary thyroid carcinoma (PTC) is a common subtype of thyroid carcinoma with a rising incidence rate. The purpose of this study was to provide a better understanding of age and PTC using the Surveillance, Epidemiology, and End Results (SEER) Program. Methods: The study derived patients' information from the SEER Program (2010-2015). Chi-square or Fisher exact tests, and Kaplan-Meier method were used to analyze survival. Prognostic factors associated with survival were analyzed by Cox multivariate regression. Results: A total of 1738 records were included from SEER, with 1079 PTC in the age group <55 years, and 659 PTC in the age group ≥55 years. The 5-year survival rate was 94% and the overall survival (OS) curve in different age groups indicated that patients younger than 55yr have a longer survival time (P < 0.05). In multivariate Cox regression, age, M stage and surgery treatment were independent risk factors (P < 0.05). Regarding PTC-specific survival, age and surgery treatment were the two main independent prognostic factors in multivariate regression. However, AJCC and M stage were not in the disease specific survival. Conclusion: Age is a prognostic factor in OS and PCT specific survival. AJCC I stage and surgery treatment are also significant in predicting prognosis. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy is one of the common complications of diabetes and is the leading cause for patients' visual dysfunction and sight loss. However, the mechanism of diabetic retinopathy is not clearly defined. The present study was undertaken to investigate neuroretinal apoptosis in different stages in a mouse model for type 2 diabetes mellitus and the mechanism of diabetic retinopathy. KKAY mouse with genetic diabetes, an animal model for type 2 diabetes, was used in this study. Mice were divided into a control group and a diabetic group. The mice in both groups were sacrificed at one month and three months, and the mouse eyeballs were used for making retinal histologic sections. We showed in this study that the apoptotic cell numbers for retinal neural cells in the ganglion cell layer were significantly greater in the diabetic group than in the control group (p<0.01), as determined by the TUNEL assay. In addition, many more apoptotic retinal neuronal cells were found in the retinal ganglion cell layer and medial part of the inner nuclear layer in the diabetic group when the mice were sacrificed at three months as compared to those sacrificed at one month (p<0.01). We also studied the ultrastructure of the retinal nerve cells and microvesseles by electron microscopy and demonstrated that the ultrastructure changes for retinal neural cells and retinal microangiopathy were observed in, as early as, the early stage of diabetes. These findings indicate that: i). retinal neuropathy and microangiopathy occur in the early stage of diabetes, ii). apoptosis may be an important mechanism through which retinal neurodegeneration is developed, and iii). both retinal neurodegeneration and retinal microangiopathy should be considered as the diabetic retinopathy.