TC-Net: A joint learning framework based on CNN and vision transformer for multi-lesion medical images segmentation.

BACKGROUND: With the rapid advancement of medical imaging technology, the demand for accurate segmentation of medical images is increasing. However, most existing methods are unable to capture locality and long-range dependency information in integrated ways for medical images. METHOD: In this paper, we propose an elegant segmentation framework for medical images named TC-Net, which can utilize both the locality-aware and long-range dependencies in the medical images. As for the locality-aware perspective, we employ a CNN-based encoder and decoder structure. The CNN branch uses the locality of convolution operations to dig out local information in medical images. As for the long-range dependencies, we construct a Transformer branch to focus on the global context. Additionally, we proposed a locality-aware and long-range dependency concatenation strategy (LLCS) to aggregate the feature maps obtained from the two subbranches. Finally, we present a dynamic cyclical focal loss (DCFL) to address the class imbalance problem in multi-lesion segmentation. RESULTS: Comprehensive experiments were conducted on lesion segmentation tasks using two fundus image databases and a skin image database. The TC-Net achieves scores of 0.6985 and 0.5171 in the metric of mean pixel accuracy on the IDRiD and DDR databases, respectively. Moreover, on the skin image database, the TC-Net reached mean pixel accuracy of 0.8886. The experiment results demonstrate that the proposed method achieves better performance than other deep learning segmentation schemes. Furthermore, the proposed DCFL achieves higher performance than other loss functions in multi-lesion segmentation. SIGNIFICANCE: The proposed TC-Net is a promising new framework for multi-lesion medical image segmentation and many other challenging image segmentation tasks. © 2001 Elsevier Science. All rights reserved.

Determination of partial denitrification kinetic model parameters based on batch tests and metagenomic sequencing.

In this study, a model was developed to investigate the partial denitrification(PD) process. The heterotrophic biomass (XH) proportion in the sludge was determined to be 66.4% based on metagenomic sequencing. The kinetic parameters were first calibrated, then validated using the batch tests results. The results showed rapid decreases in the chemical oxygen demand (COD) and nitrate concentrations and gradual increases in the nitrite concentrations in the first four hours, then remained constant from 4 to 8 h. Anoxic reduction factor (ηNO3 and ηNO2) and half saturation constant (KS1 and KS2) were calibrated at 0.097, 0.13, 89.28 mg COD/L, and 102.29 mg COD/L, respectively. Whereas the simulation results demonstrated that the increase in carbon-to-nitrogen (C/N) ratios and the reduction in XH contributed to the increase in the nitrite transformation rate. This model provides potential strategies for optimizing the PD/A process.

Integrated Proteomics and Metabolomics Analyses of Serum in Chinese Patients with Severe and Active Graves' Orbitopathy: A Cross-sectional Study.

OBJECTIVE: The present study aims to investigate the alterations of serum proteomic and metabolomic profiles in Chinese patients with severe and active Graves' Orbitopathy (GO). MATERIALS AND METHODS: Thirty patients with GO and 30 healthy volunteers were enrolled. The serum concentrations of FT3, FT4, T3, T4, and thyroid-stimulating hormone (TSH) were analyzed, after which TMT labeling-based proteomics and untargeted metabolomics were performed. Metabo- Analyst and Ingenuity Pathway Analysis (IPA) was used for integrated network analysis. A nomogram was established based on the model to explore the disease prediction ability of the identified feature metabolites. RESULTS: One hundred thirteen proteins (19 up-regulated and 94 down-regulated) and 75 metabolites (20 increased and 55 decreased) were significantly altered in GO compared to the control group. By combining the lasso regression, IPA network, and protein-metabolite-disease sub-networks, we extracted feature proteins (CPS1, GP1BA, and COL6A1) and feature metabolites (glycine, glycerol 3-phosphate, and estrone sulfate). The logistic regression analysis revealed that the full model with the prediction factors and three identified feature metabolites had better prediction performance for GO compared to the baseline model. The ROC curve also indicated better prediction performance (AUC = 0.933 vs. 0.789). CONCLUSION: A new biomarker cluster combined with three blood metabolites with high statistical power can be used to discriminate patients with GO. These findings provide further insights into the pathogenesis, diagnosis, and potential therapeutic targets for this disease.

Diagnosing Diabetic Retinopathy in OCTA Images Based on Multilevel Information Fusion Using a Deep Learning Framework.

Objective: As an extension of optical coherence tomography (OCT), optical coherence tomographic angiography (OCTA) provides information on the blood flow status at the microlevel and is sensitive to changes in the fundus vessels. However, due to the distinct imaging mechanism of OCTA, existing models, which are primarily used for analyzing fundus images, do not work well on OCTA images. Effectively extracting and analyzing the information in OCTA images remains challenging. To this end, a deep learning framework that fuses multilevel information in OCTA images is proposed in this study. The effectiveness of the proposed model was demonstrated in the task of diabetic retinopathy (DR) classification. Method: First, a U-Net-based segmentation model was proposed to label the boundaries of large retinal vessels and the foveal avascular zone (FAZ) in OCTA images. Then, we designed an isolated concatenated block (ICB) structure to extract and fuse information from the original OCTA images and segmentation results at different fusion levels. Results: The experiments were conducted on 301 OCTA images. Of these images, 244 were labeled by ophthalmologists as normal images, and 57 were labeled as DR images. An accuracy of 93.1% and a mean intersection over union (mIOU) of 77.1% were achieved using the proposed large vessel and FAZ segmentation model. In the ablation experiment with 6-fold validation, the proposed deep learning framework that combines the proposed isolated and concatenated convolution process significantly improved the DR diagnosis accuracy. Moreover, inputting the merged images of the original OCTA images and segmentation results further improved the model performance. Finally, a DR diagnosis accuracy of 88.1% (95%CI ± 3.6%) and an area under the curve (AUC) of 0.92 were achieved using our proposed classification model, which significantly outperforms the state-of-the-art classification models. As a comparison, an accuracy of 83.7 (95%CI ± 1.5%) and AUC of 0.76 were obtained using EfficientNet. Significance. The visualization results show that the FAZ and the vascular region close to the FAZ provide more information for the model than the farther surrounding area. Furthermore, this study demonstrates that a clinically sophisticated designed deep learning model is not only able to effectively assist in the diagnosis but also help to locate new indicators for certain illnesses.

Sn(101) Derived from Metal-Organic Frameworks for Efficient Electrocatalytic Reduction of CO2.

The synthesis of a specific Sn plane as an efficient electrocatalyst for CO2 electrochemical reduction to generate fuels and chemicals is still a huge challenge. Density functional theory (DFT) calculations first reveal that the Sn(101) crystal plane is more advantageous for CO2 electroreduction. A metal-organic framework (MOF) precursor Sn-MOF has been carbonized and then etched to successfully fabricate Sn(101)/SnO2/C composites with good control of the carbonization time and the concentration of hydrochloric acid. The Sn(101) crystal plane of the catalyst could enhance the faradaic efficiency of formate to as high as 93.3% and catalytic stability up to 20 h. The promotion of the selectivity and activity by Sn(101) advances new possibilities for the rational design of high-activity Sn catalysts derived from MOFs.

Development of a sensitive and reliable ELISA kit of urinary haptoglobin to predict progress of diabetic kidney disease.

AIMS: Urinary haptoglobin (UHp) is a potential biomarker for predicting progress of diabetic kidney disease (DKD) to remedy the defects of currently used urinary albumin. The clinical application of UHp is however limited, owing to the extremely low level in urine. This study aims to establish an enzyme-linked immunosorbent assay (ELISA) kit specifically for detecting UHp in urine samples of patients with diabetes and DKD. MATERIALS AND METHODS: Supersensitive human haptoglobin antibodies were generated for ELISA kit development, and the sensitivity, specificity and reproducibility of the kit was evaluated. This kit was used to detect UHp in 246 healthy individuals and 83 patients with type 2 diabetes (T2D). The interference of blood haptoglobin genotypes on UHp measurement was analysed. RESULTS: The UHp ELISA kit had a standard curve ranging from 5 to 200 ng/ml. The low detection limit was 0.11 ng/ml. The coefficients of variation of intra- and interassay were 5.5% and 8.3%, respectively. The kit showed high accuracy with 100.9% mean recovery rate, and linearity R2  = 0.999. The reference range of UHp was 0-42.3 ng/g creatinine (0-Q95) in the healthy individuals. UHp level was significantly higher in T2D patients with microalbuminuria and macroalbuminuria than that in T2D without microalbuminuria (p < 0.01). The UHp concentration measured by this kit was not affected by haptoglobin genotypes. CONCLUSIONS: We have generated an ELISA kit to accurately detect UHp levels, which is potentially a reliable biomarker of DKD.

Heterozygous PAX6 mutations may lead to hyper-proinsulinaemia and glucose intolerance: A case-control study in families with congenital aniridia.

AIM: PAX6 is a transcription factor involved in embryonic development of many organs, including the eyes and the pancreas. Mutations of PAX6 gene is the main cause of a rare disease, congenital aniridia (CA). This case-control study aims to investigate the effects of PAX6 mutations on glucose metabolism and insulin secretion in families with CA. METHODS: In all, 21 families with CA were screened by Sanger sequencing. Patients with PAX6 mutations and CA (cases) and age-matched healthy family members (controls) were enrolled. Oral glucose tolerance test (OGTT) was performed to detect diabetes or impaired glucose tolerance (IGT). Insulin and proinsulin secretion were evaluated. RESULTS: Among 21 CA families, heterozygous PAX6 mutations were detected in five families. Among cases (n = 10) from the five families, two were diagnosed with newly identified diabetes and another two were diagnosed with IGT. Among controls (n = 12), two had IGT. The levels of haemoglobin A1c were 36 ± 4 mmol/mol (5.57 ± 0.46%) and 32 ± 5 mmol/L (5.21 ± 0.54%) in the cases and the controls, respectively (p = 0.049). More importantly, levels of proinsulin in the cases were significantly higher than that of the controls, despite similar levels of total insulin. The areas under the curve of proinsulin in the cases (6425 ± 4390) were significantly higher than that of the controls (3709 ± 1769) (p = 0.032). CONCLUSION: PAX6 may participate in the production of proinsulin to insulin and heterozygous PAX6 mutations may be associated with glucose metabolism in CA patients.

Plasma metabolomic profiling of proliferative diabetic retinopathy.

BACKGROUND: Proliferative diabetic retinopathy (PDR), a sight-threatening retinopathy, is the leading cause of irreversible blindness in adults. Despite strict control of systemic risk factors, a fraction of patients with diabetes develop PDR, suggesting the existence of other potential pathogenic factors underlying PDR. This study aimed to investigate the plasma metabotype of patients with PDR and to identify novel metabolite markers for PDR. Biomarkers identified from this study will provide scientific insight and new strategies for the early diagnosis and intervention of diabetic retinopathy. METHODS: A total of 1024 patients with type 2 diabetes were screened. To match clinical parameters between case and control subjects, patients with PDR (PDR, n = 21) or those with a duration of diabetes of ≥10 years but without diabetic retinopathy (NDR, n = 21) were assigned to the present case-control study. Distinct metabolite profiles of serum were examined using liquid chromatography-mass spectrometry (LC-MS). RESULTS: The distinct metabolites between PDR and NDR groups were significantly enriched in 9 KEGG pathways (P < 0.05, impact > 0.1), namely, alanine, aspartate and glutamate metabolism, caffeine metabolism, beta-alanine metabolism, purine metabolism, cysteine and methionine metabolism, sulfur metabolism, sphingosine metabolism, and arginine and proline metabolism. A total of 63 altered metabolites played important roles in these pathways. Finally, 4 metabolites were selected as candidate biomarkers for PDR, namely, fumaric acid, uridine, acetic acid, and cytidine. The area under the curve for these biomarkers were 0.96, 0.95, 1.0, and 0.95, respectively. CONCLUSIONS: This study suggested that impairment in the metabolism of pyrimidines, arginine and proline were identified as metabolic dysregulation associated with PDR. And fumaric acid, uridine, acetic acid, and cytidine might be potential biomarkers for PDR. Fumaric acid was firstly reported as a novel metabolite marker with no prior reports of association with diabetes or diabetic retinopathy, which might provide insights into potential new pathogenic pathways for diabetic retinopathy.

Prediction of Proliferative Diabetic Retinopathy to Asymptomatic Obstructive Coronary Artery Disease in Chinese Type 2 Diabetes Individuals: An Exploratory Study.

Background: Patients with type 2 diabetes are prone to the asymptomatic obstructive coronary artery disease (AO-CAD). The association of proliferative diabetic retinopathy (PDR) with AO-CAD is unknown. The aim of the study is to explore the specific relationship of PDR with AO-CAD. Methods: We performed coronary angiography and retinal photographs in 1332 participants with unknown CAD status in a retrospective discovery set and 252 patients with non-CAD enrolled in a prospective validation cohort. Main outcome measures are prediction of PDR to AO-CAD. Results: In the case-control retrospective discovery set, investigation included 211 nondiabetic retinopathy (NDR) and 140 PDR. Individuals with PDR had a 2.16 times higher risk of AO-CAD compared with individuals without diabetic retinopathy (P < 0.01). Relative risk between individuals with PDR and the risk of AO-CAD varied by different adjusted covariates, 2.53 (1.48-4.32) by age and gender; 2.16 (1.10-4.31) by additionally other covariates. In the prospective validation set, after adjustment for covariates, the cumulative risk of AO-CAD was significantly higher in the PDR group compared with NDR group, followed up for a median of 4.3 years (hazard ratio = 3.07, 95% confidence interval 1.81-5.21, P < 0.001). Conclusions: PDR showed superior identification performance over traditional risk factors in screening for AO-CAD. PDR may predict persons at high risk of AO-CAD.

Nifuroxazide ameliorates lipid and glucose metabolism in palmitate-induced HepG2 cells.

Inflammation constitutes an important component of non-alcoholic fatty liver disease. STAT3 is a direct target of inflammatory cytokines, but also mediates glycolipid metabolism in the liver. As a potent inhibitor of STAT3, the effect of Nifuroxazide (Nifu) on glycolipid metabolism in liver has not been reported. In this study, we used palmitic acid (PA)-induced HepG2 cells to examine the expression of inflammatory factors and apoptosis-related proteins and the content of triglyceride (TG), total cholesterol (TC), and glycogen. The expression of hepatic lipogenic proteins (ACCα, SREBP-1c, FAS), gluconeogenesis enzymes (PEPCK, G6Pase, and IRS2), the IL-6/STAT3/SOCS3 inflammatory axis, and the insulin signaling pathway was determined. Our study shows that Nifu significantly improves lipid metabolism disorders in the PA-induced HepG2 cells, whereas, it remarkably reduced intracellular free fatty acid (FFA), TG, and TC content, suppressed lipid synthesis, and increased lipid decomposition. Our results also showed that Nifu significantly improved dysregulated glucose metabolism in the PA-treated HepG2 cells, increased glycogen content, and inhibited gluconeogenesis. Further research indicated that Nifu markedly inhibited activation of the IL-6/STAT3/SOCS3 signaling pathway. Finally, due to anti-inflammatory stress, Nifu enhanced insulin signaling in the PA-induced HepG2 cells. Therefore, Nifu can improve glucose and lipid metabolism in the PA-induced HepG2 cells, which provides new evidence that Nifu has a positive effect on PA-induced cellular hepatic steatosis and improves glucose metabolism in HepG2 cells, providing a new perspective for studying drug treatment of glucose and lipid metabolism disorders.

Identification of Rfx6 target genes involved in pancreas development and insulin translation by ChIP-seq.

Regulatory Factor X-box binding transcriptional factor 6 (Rfx6) plays an important role in the differentiation and development of pancreas in mammals. However, the direct target genes of Rfx6 to regulate this process were largely unknown. The present study aimed to investigate the function of Rfx6 on regulating pancreatic differentiation and development in a physiologically-relevant context. We performed the chromatin immunoprecipitation followed by the next generation sequencing analysis (ChIP-seq) using whole pancreatic tissue harvested from C57/BL6 adult mice to find target genes of Rfx6. We captured 4146 unique peaks in the genome region of the adult murine pancreas. Among all these binding peaks, a majority were located in intron or intergenic regions. We further annotated all peaks to their nearest gene, and over 1000 genes were captured as Rfx6-binding genes in the pancreas. Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis found that Rfx6-binding genes to be associated with the pancreas developmental process. A portion of selected ChIP-seq targets related with pancreas differentiation including Pdx1, Neurod1, Hnf1a, Nkx6-1, St18 and Shox2 were selected and validated as true targets by independent qPCR experiments. In addition, Rfx6 can directly bind to upstream of MiR-145, MiR-195, and possibly other non-protein-coding functional RNAs to control adult mouse pancreatic differentiation. Interestingly, our study revealed that Rfx6 played an important role in insulin translation by binding to the Eif2ak1, Upf1, and Eif5. Our data provide direct target genes of Rfx6 during pancreas development and point to Rfx6 as a potential therapeutic target for improving insulin protein content.

From Hyper- to Hypoinsulinemia and Diabetes: Effect of KCNH6 on Insulin Secretion.

Glucose-stimulated insulin secretion from islet ß cells is mediated by KATP channels. However, the role of non-KATP K+ channels in insulin secretion is largely unknown. Here, we show that a non-KATP K+ channel, KCNH6, plays a key role in insulin secretion and glucose hemostasis in humans and mice. KCNH6 p.P235L heterozygous mutation co-separated with diabetes in a four-generation pedigree. Kcnh6 knockout (KO) or Kcnh6 p.P235L knockin (KI) mice had a phenotype characterized by changing from hypoglycemia with hyperinsulinemia to hyperglycemia with insulin deficiency. Islets from the young KO mice had increased intracellular calcium concentration and increased insulin secretion. However, islets from the adult KO mice not only had increased intracellular calcium levels but also had remarkable ER stress and apoptosis, associated with loss of ß cell mass and decreased insulin secretion. Therefore, dysfunction of KCNH6 causes overstimulation of insulin secretion in the short term and ß cell failure in the long term.

Could Intensive Blood Pressure Control Really Reduce Diabetic Retinopathy Outcomes? Evidence from Meta-Analysis and Trial Sequential Analysis from Randomized Controlled Trials.

INTRODUCTION: To explore the accumulated evidence concerning the effect of intensive blood pressure control on the incidence and progression of diabetic retinopathy (DR), proliferative diabetic retinopathy (PDR) and macular edema (ME). METHODS: A number of electronic databases were searched including PubMed, EMBASE, CINAHL, Cochrane Library, conferences and proceedings. Randomized controlled trials comparing intensive blood pressure targets with conventional blood pressure targets in patients with type 2 diabetes were included. The definition of intensive versus conventional blood pressure targets was from the pertinent original studies. Meta-analyses and trial sequential analyses of randomized trials were analyzed in STATA. RESULTS: Eight trials randomizing 6989 patients were assessed and reviewed in full text; 3749 vs. 3240 were in each arm (intensive vs. conventional). All trials had a low risk of bias. Intensive blood pressure control supported a 17% reduction in the incidence of DR (relative risk 0.83, 95% confidence interval 0.72-0.95). Trial sequential analyses confirmed that sufficient evidence indicated a relative risk reduction above 17% for the incidence of DR when intensive blood pressure control was targeted. Heterogeneity was absent (I2 = 0%; P = 0.56). No statistically significant effect was found for intensive blood pressure targeting on the progress of DR (relative risk 0.94, 95% confidence interval 0.81-1.08). TSA showed that insufficient evidence had been found, although the Z value line appeared to have a tendency of approaching the futility boundaries. There were also no statistically significant effects on the incidence of PDR and ME (TSA-adjusted CI 0.84-1.12). CONCLUSION: Intensive blood pressure control reduced the relative risk of incidence of DR by 17%. The available data were insufficient to prove or refute a relative risk reduction for the progression of DR or incidence of PDR and ME at a magnitude of 15%.

Subclinical hypothyroidism and the risk of chronic kidney disease in T2D subjects: A case-control and dose-response analysis.

Evidence indicated a positive association between subclinical hypothyroidism (SCH) and cardiovascular diseases. But the relationship between SCH and chronic kidney diseases (CKD) remains unclear. A case-control study was performed to ascertain this relationship followed by a meta-analysis. In this hospital-based, case-control study, we recruited 3270 type 2 diabetic patients with euthyroidism and 545 type 2 diabetic patients with SCH. All English studies were searched upon the relationship between SCH and CKD up to October 2016. Meta-analysis was performed using STATA 13.0 software. Our case-control study indicated an association between SCH and CKD in patients with type 2 diabetes [OR (95% CI): 1.22 (1.09-1.36)]. Five observational studies reporting risk of CKD in SCH individuals were enrolled. A significant relationship between SCH and CKD was shown [pooled OR 1.80, (95% CI) 1.38-2.35]. Among normal TSH range, individuals with TSH ≥3.0 µIU/ml had a significantly higher rate of CKD (Fisher exact test, P = 0.027). Dose-response linear increase of CKD events was explored [pooled OR 1.09 (95% CI): 1.03-1.16 per1 mIU/L increase of TSH]. The present evidence suggests that SCH is probably a significant risk factor of CKD in T2D. Linear trend is shown between TSH elevation and CKD in T2D. This relationship between serum TSH and renal impairment in type 2 diabetic patients needs further studies to investigate.

Prediction of risk of diabetic retinopathy for all-cause mortality, stroke and heart failure: Evidence from epidemiological observational studies.

To examine and quantify the potential relation between diabetic retinopathy (DR) and risk of all-cause mortality, stroke and heart failure (HF).The resources of meta-analysis of epidemiological observational studies were from Pub-med, EMBASE, CINAHL, Cochrane Library, conference, and proceedings.Random/fixed effects models were used to calculate pooled subgroup analysis stratified by different grades of DR was performed to explore the potential source of heterogeneity. Statistical manipulations were undertaken using program STATA.Of the included 25 studies, comprising 142,625 participants, 19 studies were concluded to find the relation of DR to all-cause mortality, 5 for stroke, and 3 for HF. Risk ratio (RR) for all-cause mortality with the presence of DR was 2.33 (95% CI 1.92-2.81) compared with diabetic individuals without DR. Evidences showed a higher risk of all-cause mortality associated with DR in patients with T2D or T1D (RR 2.25, 95% CI 1.91-2.65. RR 2.68, 95% CI 1.34-5.36). According to different grades of DR in patients with T2D, RR for all-cause mortality varied, the risk of nonproliferative diabetic retinopathy (NPDR) was 1.38 (1.11-1.70), while the risk of proliferative diabetic retinopathy (PDR) was 2.32 (1.75-3.06). There was no evidence of significant heterogeneity (Cochran Q test P = 0.29 vs 0.26, I = 19.6% vs 22.6%, respectively). Data from 5 studies in relation to DR and the risk of stroke showed that DR was significantly associated with increased risk of stroke (RR = 1.74, 95%CI: 1.35-2.24), compared with patients without DR. Furthermore, DR (as compared with individuals without DR) was associated with a marginal increased risk of HF in patients with diabetes mellitus (DM) (n = 3 studies; RR 2.24, 95% CI 0.98-5.14, P = 0.056).Our results showed that DR increased the risk of all-cause mortality, regardless of the different stages, compared with the diabetic individuals without DR. DR predicted increased risk of stroke and HF. Although only 3 studies about HF were available, the association between DR and HF should be careful.

Hypodermin A improves survival of skin allografts.

BACKGROUND: Hypodermin A (HA) is a serine esterase that degrades complement, a key element of the innate immune system. Immunosuppressive properties of HA have previously been studied in vitro. However, such properties have not been fully demonstrated in vivo. The aim of this study was to evaluate the effect of HA in inhibiting allograft rejection in an HA transgenic mouse model. METHODS: FVB (HA transgenic mice or wild-type mice) to BALB/c mice skin transplantation model were used. Skin grafts were analyzed by histology, immunohistochemistry, and Western blotting. RESULTS: HA overexpression resulted in significantly prolonged skin allograft survival. Histologic changes in the skin allografts paralleled the gross appearance of rejection. ELISA and Western blotting showed that HA significantly reduced the content of complement C3 and C9 in HA skin allografts. The expressions of CD4, B7-2, and MHC class II were all significantly suppressed in HA skin allografts compared with the control group. CONCLUSIONS: These findings suggest that HA effectively prolongs skin allograft survival. The study results provide insight into a promising strategy to improve the survival of grafts in humans.

High Prevalence of Diabetic Retinopathy in Diabetic Patients Concomitant with Metabolic Syndrome.

OBJECTIVE: To evaluate the relationship between metabolic syndrome (MetS) and the prevalence of diabetic retinopathy (DR). RESEARCH DESIGN AND METHODS: We conducted a case-controlled study, with data obtained from 2,551 Chinese participants between 18-79 years of age (representing a population of 1,660,500 in a district of Beijing). 74 cases of DR were found following data assessment by two 45° digital retinal images. Subjects without DR (NDR group) selected from the remaining 2,477 subjects were matched 1:1 to the DR group by HbA1c. MetS was defined by incorporating diagnostic criteria of the American Heart Association/National Heart, Lung, and Blood Institute (AHA/NHLBI) and the International Diabetes Federation (IDF). RESULTS: There were no statistical differences between the DR group and NDR group in a number of biological or laboratory tests. However, the percentage of patients with DR increased vs. patients without DR with the number of MetS components from 1 to 5 (14.3% vs. 85.7%, 38.9% vs. 61.1%, 49.1% vs. 50.9%, 61.4% vs. 38.6% and 83.3% vs. 16.7%, respectively) (Pearson χ2 = 9.938, P = 0.037). The trend to develop DR with MetS was significantly higher than that without MetS (NMetS) (χ2 = 5.540, P = 0.019). MetS was an independent statistical indicator of the presence of DR after adjusting for age and sex [odds ratio (95% CI): 2.701(1.248-5.849), P = 0.012], which is still the case with an additional adjustment for WC, SBP, TC, HbA1c and duration of diabetes [odds ratio (95% CI): 2.948(1.134-7.664), P = 0.027]. CONCLUSION: DR is one of the diabetic microvascular complications. Apart from poor glycemic control, the concomitance of other metabolic factors can also influence DR. MetS, defined as a cluster of metabolic risk factors, is a strong and independent indicator of DR, even to the same extent as glycemic control.

Immunosuppressive Effect of Hypodermin C on Complement Component 3 In Vitro.

Hypodermins A (HA), B (HB) and C (HC) are the major proteases secreted by first-instar larvae of Hypoderma lineatum (Diptera: Oestridae). These proteases are involved in the larval migration in the tissue, and prevent the activation of the host immune response. We previously showed that the recombinant HA functions as an immunosuppressive agent which could inhibit the rejection of xenotransplants. In the current study, we cloned the cDNA sequence of HC, which was transfected in Cos7 cells using the pEF1α-IRES-AcGFP expression vector. The Cos7 cells stably expressed HC, and were more resistant to lysis by guinea pig C3 than the control cells. The HC protease degraded the guinea pig C3, and inhibited the complement pathway in vitro. The DNA binding sites of HC were identified using an electrophoretic mobility shift assay. Our findings suggest that the recombinant HC might be useful as an immunosuppressive agent for the inhibition of the xenotransplant rejection.

Heme oxygenase-2 suppress TNF-α and IL6 expression via TLR4/MyD88-dependent signaling pathway in mouse cerebral vascular endothelial cells.

Heme oxygenase (HO) represents an intrinsic antiinflammatory system based on its ability to inhibit expression of proinflammatory cytokines. The constitutive isoform heme oxygenase-2 (HO-2) has high expression and activity in cerebral microvascular endothelial cells (CMVEC). This study was undertaken to evaluate the role of HO-2 in regulation of TLR4/MyD88-dependent signaling and to study the effect of HO-2 on the expression and secretion of the proinflammatory cytokines tumor necrosis factor α (TNF-α) and Interleukin-6 (IL6) in CMVEC. HO-2 short hairpin RNA (shRNA) and HO-2 overexpression plasmids were used to observe the effect of HO-2 on proinflammatory cytokines in CMVEC in vitro, and the results showed that the messenger RNA (mRNA) and protein levels of TNF-α and IL6 were increased and decreased, respectively, compared with control groups. LPS-stimulated TNF-α and IL6 mRNA and protein were also reduced in CMVEC treated with an inhibitor of TLR4 signaling, CLI-095, or HO-2 overexpression. CLI-095 and HO-2 overexpression both reduced TLR4 expression in CMVEC, and HO-2 shRNA blocked these effects of CLI-095. CLI-095 and HO-2 overexpression potently suppressed TLR4/MyD88-dependent proinflammatory cytokine expression in CMVEC. These results suggest that HO-2 plays an important role in protecting CMVEC against cytokine-mediated inflammation.