Magnetic Porous Hydrogel-Enhanced Wearable Patch Sensor for Sweat Zinc Ion Monitoring.

Wearable sensors for sweat trace metal monitoring have the challenges of effective sweat collection and the real-time recording of detection signals. The existing detection technologies are implemented by generating enough sweat through exercise, which makes detecting trace metals in sweat cumbersome. Generally, it takes around 20 min to obtain enough sweat, resulting in dallied and prolonged detection signals that cannot reflect the endogenous fluctuations of the body. To solve these problems, we prepared a multifunctional hydrogel as an electrolyte and combined it with a flexible patch electrode to realize real-time monitoring of sweat Zn2+. Such hydrogel has magnetic and porous properties, and the porous structure of hydrogel enables a fast absorption of sweat, and the magnetic property of the addition of fabricated Fe3O4 NPs not only improves the conductivity but also ensures the adjustable internal structures of the hydrogel. Such a sensing platform for sweat Zn2+ monitoring shows a satisfied linear relationship in the concentration range of 0.16-16 µg/mL via differential pulsed anodic striping voltammetry (DPASV) and successfully detects the sweat Zn2+ of four volunteers during exercise and resting, displaying a promising path for commercial application.

SERS determination of dopamine using metal-organic frameworks decorated with Ag/Au noble metal nanoparticle composite after azo derivatization with p-aminothiophenol.

A specific surface-enhanced Raman scattering (SERS) assay for dopamine (DA) based on an azo derivatization reaction is proposed for the first time by preparation of p-aminothiophenol (PATP)-modified composite SERS substrate, composed of metal-organic framework (MIL-101) decorated with Au and Ag nanoparticles. As the result, the SERS method for detection of the azo reaction between PATP and DA exhibits superior sensitivity, selectivity, and stability. A reasonable linearity in the range 10-6 to 10-10 mol∙L-1 is achieved, and the limit of detection is 1.2 × 10-12 mol∙L-1. The reactive SERS assay is free from interference in complex physiological fluid. The feasibility of the proposed SERS method for the detection of DA levels in fetal bovine serum (FBS) samples and human serum samples is validated by HPLC-MS methods, displaying promising application potential in early disease diagnosis.

Transcriptome sequencing of circular RNA reveals a novel circular RNA-has_circ_0114427 in the regulation of inflammation in acute kidney injury.

Acute kidney injury (AKI) is a common serious syndrome characterized by rapid decrease of glomerular filtration rate and the progressive increase of serum creatinine. Circular RNAs (circRNAs) are regulatory RNAs that recently became popular among various diseases. However, the expression profile and function of circRNAs in AKI remain largely unknown. The main function of circRNAs is acting as competing endogenous RNAs (ceRNAs) by binding with microRNAs (miRNAs), as indicated by recent research. In the present study, we established cisplatin-induced AKI model in mice and isolated renal tubular tissues to extract circRNAs for next-generation sequencing (NGS) and bioinformatics analysis. We analyzed the composition, distribution and Gene Ontology terms of circRNAs in cisplatin-induced AKI and revealed differentially expressed circRNAs related to AKI. By finding homologous genes between mouse and human, we identified circRNA- circ-0114427 in humans. We further investigated its function in AKI cell model. Circ-0114427 expression was significantly up-regulated in different AKI cell models. Knockdown of circ-0114427 indicated that circ-0114427 bound to miR-494 as a miRNA sponge to regulate ATF3 expression and further affected the expression of downstream cytokine IL-6. Circ-0114427 regulates inflammatory progression in AKI's early stage via circ-0114427/miR-494/ATF3 pathway. Our findings reveal the expression profile of circRNAs in cisplatin-induced AKI and provide a novel insight into the regulatory mechanism of circRNAs, which may become a new molecular target resource for early diagnosis and treatment strategies.

Identification of prognosis-related alternative splicing events in kidney renal clear cell carcinoma.

Alternative splicing (AS) contributes to protein diversity by modifying most gene transcriptions. Cancer generation and progression are associated with specific splicing events. However, AS signature in kidney renal clear cell carcinoma (KIRC) remains unknown. In this study, genome-wide AS profiles were generated in 537 patients with KIRC in the cancer genome atlas. With a total of 42 522 mRNA AS events in 10 600 genes acquired, 8164 AS events were significantly associated with the survival of patients with KIRC. Logistic regression analysis of the least absolute shrinkage and selection operator was conducted to identify an optimized multivariate prognostic predicting mode containing four predictors. In this model, the receptor-operator characteristic curves of the training set were built, and the areas under the curves (AUCs) at different times were >0.88, thus indicating a stable and powerful ability in distinguishing patients' outcome. Similarly, the AUCs of the test set at different times were >0.73, verifying the results of the training set. Correlation and gene ontology analyses revealed some potential functions of prognostic AS events. This study provided an optimized survival-predicting model and promising data resources for future in-depth studies on AS mechanisms in KIRC.

Immune cell infiltration characteristics and related core genes in lupus nephritis: results from bioinformatic analysis.

BACKGROUND: Lupus nephritis (LN) is a common complication of systemic lupus erythematosus that presents a high risk of end-stage renal disease. In the present study, we used CIBERSORT and gene set enrichment analysis (GSEA) of gene expression profiles to identify immune cell infiltration characteristics and related core genes in LN. RESULTS: Datasets from the Gene Expression Omnibus, GSE32591 and GSE113342, were downloaded for further analysis. The GSE32591 dataset, which included 32 LN glomerular biopsy tissues and 14 glomerular tissues from living donors, was analyzed by CIBERSORT. Different immune cell types in LN were analyzed by the Limma software. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis based on GSEA were performed by clusterProfiler software. Lists of core genes were derived from Spearman correlation between the most significant GO term and differentially expressed immune cell gene from CIBERSORT. GSE113342 was employed to validate the association between selected core genes and clinical manifestation. Five types of immune cells revealed important associations with LN, and monocytes emerged as having the most prominent differences. GO and KEGG analyses indicated that immune response pathways are significantly enriched in LN. The Spearman correlation indicated that 15 genes, including FCER1G, CLEC7A, MARCO, CLEC7A, PSMB9, and PSMB8, were closely related to clinical features. CONCLUSIONS: This study is the first to identify immune cell infiltration with microarray data of glomeruli in LN by using CIBERSORT analysis and provides novel evidence and clues for further research of the molecular mechanisms of LN.

Bioinformatic analysis reveals novel hub genes and pathways associated with hypertensive nephropathy.

AIM: Hypertensive nephropathy (HTN) is one of the leading causes of end-stage renal disease and is closely associated with inflammation and tubule-interstitial fibrosis. The molecular mechanism underlying HTN remains unclear. This study used bioinformatic analysis to identify the novel gene targets for HTN. METHODS: We downloaded the microarray data of GSE99325 and GSE32591 from Gene Expression Omnibus. The dataset comprised 20 HTN and 15 normal samples. The differentially expressed genes (DEG) were identified, and then gene ontology (GO) enrichment was performed, and a GO tree was constructed by using clusterProfiler and ClueGO. In addition, a protein-protein interaction network was established using the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape. The novel hub genes were validated in in vitro experiments. RESULTS: A total of 267 genes (117 up-regulated and 150 down-regulated genes) were identified as DEG. GO analysis and the GO tree indicated that the DEG were mainly associated with steroid hormone response and the extracellular matrix. Based on the protein-protein interaction network, we screened out several novel hub genes. Considering the findings and the literature review, we focused on and validated the dual specificity phosphatase 1, tissue inhibitor of matrix metalloproteinases 1, fos proto-oncogene and jun proto-oncogenes, which may play significant roles in the pathogenesis of HTN. These findings were consistent with the bioinformatic results for the in vitro validation. CONCLUSION: This study identified for the first time novel hub genes with microarray data in HTN by using bioinformatic analysis and provided novel evidence and clues for future works.

Internal Calibration Potentiometric Aptasensors for Simultaneous Detection of Hg2+, Cd2+, and As3+ Based on a Screen-Printed Carbon Electrodes Array.

An all-solid-state potentiometric aptasensor array based on a multichannel disposable screen-printed carbon electrode (SPCE) was demonstrated for the simultaneous detection of Hg2+, Cd2+, and As3+ by open circuit potential (OCP) technology. The potential of the channel with an internal calibration DNA sequence (IC-DNA) was employed as the internal calibration potential (ICP) to subtract the background signal generated by the detection system, providing a built-in correction methodology. As a result, the developed aptasensor array showed high sensitivity and accuracy for detecting Hg2+, Cd2+, and As3+ without mutual interference or interference from other ions. The linear response ranged from 2.5 pM to 2.5 µM, and the detection limits for Hg2+, Cd2+, and As3+ were 2.0, 0.62, and 0.17 pM, respectively. Furthermore, the potentiometric aptasensor array was successfully applied for the simultaneous detection of three ions in real samples. The results obtained from the developed approach agreed well with the results obtained from inductively coupled plasma mass spectrometry.

PYCARD Gene Plays a Key Role in Rapidly Progressive Glomerulonephritis: Results of a Weighted Gene Co-Expression Network Analysis.

BACKGROUND: Rapidly progressive glomerulonephritis (RPGN) is caused by various diseases process, thereby resulting in extensive crescent formation, which could lead to a rapid loss of kidney function. The molecular pathogenesis of RPGN remains largely unknown and requires clarification. The weighted gene co-expression network analysis (WGCNA) is a powerful bioinformatics tool to identify meaningful molecules in diseases. METHODS: The dataset of GSE104948, which contains 22 RPGN and 18 normal samples, was obtained from Gene Expression Omnibus database. After data pre-processing, the WGCNA was performed to successfully cluster several significant modules. The most significant module was selected for further Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis. Visualization of network and screening of hub genes were performed by using Cytoscape software. RESULTS: A total of 11 modules were clustered by WGCNA, and the most significant module-turquoise module was selected. As discovered via GO enrichment and KEGG pathway analysis, the turquoise module was mainly associated with neutrophil activation and degranulation. After visualization and calculation for the network, the PYCARD gene has higher relationship score in 2 clusters, namely, neutrophil activation and degranulation. In accordance with the literature review, the hub gene could be closely related to the inflammation response and could act as the potential therapeutic targets in RPGN. CONCLUSIONS: WGCNA in RPGN expression profiling was used for the first time in this paper. A novel hub gene closely associated with RPGN was screened out, thereby providing the brand-new molecular candidate for RPGN.

Multiple network algorithm for epigenetic modules via the integration of genome-wide DNA methylation and gene expression data.

BACKGROUND: With the increase in the amount of DNA methylation and gene expression data, the epigenetic mechanisms of cancers can be extensively investigate. Available methods integrate the DNA methylation and gene expression data into a network by specifying the anti-correlation between them. However, the correlation between methylation and expression is usually unknown and difficult to determine. RESULTS: To address this issue, we present a novel multiple network framework for epigenetic modules, namely, Epigenetic Module based on Differential Networks (EMDN) algorithm, by simultaneously analyzing DNA methylation and gene expression data. The EMDN algorithm prevents the specification of the correlation between methylation and expression. The accuracy of EMDN algorithm is more efficient than that of modern approaches. On the basis of The Cancer Genome Atlas (TCGA) breast cancer data, we observe that the EMDN algorithm can recognize positively and negatively correlated modules and these modules are significantly more enriched in the known pathways than those obtained by other algorithms. These modules can serve as bio-markers to predict breast cancer subtypes by using methylation profiles, where positively and negatively correlated modules are of equal importance in the classification of cancer subtypes. Epigenetic modules also estimate the survival time of patients, and this factor is critical for cancer therapy. CONCLUSIONS: The proposed model and algorithm provide an effective method for the integrative analysis of DNA methylation and gene expression. The algorithm is freely available as an R-package at https://github.com/william0701/EMDN .

Downregulation of uncoupling protein-2 by genipin exacerbates diabetes-induced kidney proximal tubular cells apoptosis.

Renal tubular epithelial cell injury is a major pathological event that contributes to the development of diabetic kidney disease (DKD). Uncoupling protein-2 (UCP2), a mitochondrial membrane protein, has been reported to participate in the regulation of reactive oxygen species (ROS) generation, which contributes to tubular cell apoptosis induced by hyperglycemia. In this study, we found that genipin, a UCP2 inhibitor, dramatically boosted oxidative stress, attenuated antioxidative capacity, and exacerbated cell apoptosis accompanied with caspase-3 activation in rat renal proximal tubular cells (NRK-52E) incubated with high glucose. The present study results suggest that manipulation of UCP2 could be important in the prevention of oxidative stress damage in renal tubular epithelial cells induced by hyperglycemia in vitro.

Mendelian randomization study of sodium-glucose cotransporter 2 inhibitors in cardiac and renal diseases.

OBJECTIVE: Sodium-glucose cotransporter 2 inhibitors (SGLT2i) target the reabsorption of sodium and glucose in the kidney proximal tubules to reduce blood sugar levels. However, clinical randomized controlled trials on SGLT2i have yielded inconsistent results, necessitating further research into their efficacy and safety for specific cardiac and renal diseases. METHODS: "Sodium in urine" was selected as a downstream biomarker of SGLT2i. Single nucleotide polymorphisms were extracted from genome-wide association study data as instrumental variables. Mendelian randomization analysis was then conducted for cardiac and renal diseases and potential adverse events. The causal effects of SGLT2i on these diseases were determined based on inverse variance weighted results, followed by sensitivity and pleiotropy tests. RESULTS: SGLT2i had a significant protective effect against nephrotic syndrome (odds ratio [OR] 0.0011, 95% confidence interval [CI] 0.000-0.237), chronic glomerulonephritis (OR 0.0002, 95% CI 0.000-0.21), and hypertensive nephropathy (OR 0.0003, 95% CI 0.000-0.785). No causal effects were observed between SGLT2i and cardiac diseases or potential adverse events. CONCLUSIONS: SGLT2i can act as protective factors against nephrotic syndrome, chronic glomerulonephritis, and hypertensive nephropathy.

Renal protective effects of early continuous venovenous hemofiltration in rhabdomyolysis: improved renal mitochondrial dysfunction and inhibited apoptosis.

Rhabdomyolysis (RM) and subsequent myoglobin (Mb) deposition can lead to acute kidney injury. Continuous venovenous hemofiltration (CVVH) can remove Mb, but direct renal protection is unclear. We hypothesized that CVVH can improve renal mitochondrial dysfunction in its early stage. Twenty-four mongrel dogs were randomly divided into four groups: (A) control; (B) model; (C) model + CVVH (50 mL/kg/h); and (D) model + CVVH (30 mL/kg/h). RM was induced by glycerol via intramuscular injection. The dogs were closely monitored for urine flow and renal function. Mb, plasma tumor necrosis factor-α (TNF-α), and interleukin (IL)-6 were measured by enzyme-linked immunosorbent assay. After 8 h of CVVH, the morphological changes of renal mitochondria were observed and mitochondrial function indicators (reactive oxygen species, malondialdehyde, and respiratory control index) were detected. Western blot analysis was used to detect the expression of Mb, TNF-α, and IL-6 in renal tubules. The terminal deoxynucleotidyl transferase-mediated dUTP-biotin nick end labeling assay method and Western blot analysis were used to detect apoptosis and apoptosis-related proteins. In group B, the dog urine output gradually decreased with increased blood creatinine. In groups C and D, the urine output was normal and stable. CVVH effectively eliminated Mb. High-dose CVVH was significantly better for removal efficiency than low-dose CVVH. CVVH significantly reduced the deposition of circulating Mb in the kidney in a dose-dependent manner. The impact of CVVH on TNF-α and IL-6 were not observed. The morphological changes of mitochondria and function indicators were significantly improved in group C compared with groups D and B. Compared with group B, renal apoptosis and apoptosis-related protein expression were inhibited in groups C and D. Group C was significantly better for mitochondrial improvement and apoptosis inhibition than group D. At the cellular and molecular level, CVVH can improve renal mitochondrial function and inhibit cell apoptosis. Early CVVH can protect from RM-caused renal injuries in a dose-dependent manner.

Machine learning model to estimate probability of remission in patients with idiopathic membranous nephropathy.

BACKGROUND: Idiopathic membranous nephropathy (IMN) is a type of nephrotic syndrome and the leading cause of chronic kidney disease. As far as we know, no predictive model for assessing the prognosis of IMN is currently available. This study aims to establish a nomogram to predict remission probability in patients with IMN and assists clinicians to make treatment decisions. METHODS: A total of 266 patients with histopathology-proven IMN were included in this study. Least absolute shrinkage and selection operator regression was utilized to identify the most important variables. Subsequently, multivariate Cox regression analysis was conducted to construct a nomogram, and bootstrap resampling was employed for internal validation. Receiver operating characteristic and calibration curves and decision curve analysis (DCA) were utilized to assess the performance and clinical utility of the developed model. RESULTS: A prognostic nomogram was established, which incorporated creatinine, glomerular_basement_membrane_thickening, gender, IgG_deposition, low-density lipoprotein cholesterol, and fibrinogen. The areas under the curves of the 3-, 12-, 24-month were 0.751, 0.725, and 0.830 in the training set, and 0.729, 0.730, and 0.948 in the validation set respectively. These results and calibration curves demonstrated the good discrimination and calibration of the nomogram in the training and validation sets. Additionally, DCA indicated that the nomogram was useful for remission prediction in clinical settings. CONCLUSION: The nomogram was useful for clinicians to evaluate the prognosis of patients with IMN in early stage.

Effect of plasma exchange on hepatocyte oxidative stress, mitochondria function, and apoptosis in patients with acute fatty liver of pregnancy.

Acute fatty liver of pregnancy (AFLP) is an uncommon but clinically severe hepatopathy, and reactive oxygen species (ROS)-mediated mitochondrial apoptosis may be its key pathogenesis. Traditional therapy is inadequate for patients with severe conditions so the application of plasma exchange (PE) has been attempted. The present study aims to determine whether or not PE can lessen injuries to hepatocytes by ameliorating ROS and mitochondrial functions. Thirteen patients with AFLP were included in the experimental group, while fifteen patients made up the case-control group. PE was applied to patients in the PE group once a day for 1-3 days. Cultured hepatocytes were treated with serum or replacement fluid from patients and controls, respectively. Malondialdehyde, superoxide dismutase (SOD), mitochondrial membrane potential (MMP), caspase-3, caspase-9, and apoptosis of hepatocytes were measured. The clinical details and prognoses were also assessed. Patients in the experimental group had shorter durations of hepatic function recovery, intensive care unit (ICU) stay, and hospitalization than those in the case-control group, although both groups showed the same mortality. PE could induce the production of SOD, inhibit the production of malondialdehyde, and recover MMP. The upregulation of caspase-3 and caspase-9 expression, as well as increase in apoptosis rate in the AFLP group, could be inhibited by PE. Moreover, PE also appeared to have a dose-dependent effect. PE protects hepatocytes by reducing damage to the mitochondria caused by oxidative stress; thus, it could be beneficial in the treatment of patients with severe AFLP and induce liver function recovery.

[Relation between bone matrix proteins and monocyte chemoattractant protein-1 in renal small artery in diabetic nephropathy rats].

OBJECTIVE: To observe the expressions of bone matrix proteins and monocyte chemoattractant protein-1 ((MCP-1) in the renal arteriole of diabetic nephropathy (DN) rats and analyze their correlations and roles in diabetic nephropathy. METHODS: Adult Sprague-Dawley male rats were used to establish the animal model of diabetic nephropathy induced by peritoneal injection of 55 mg/kg of streptozocin. Calcium deposit around the renal arteriole was observed by alizarin red staining. The protein and mRNA levels of core-bind factor alpha 1 (cbfalpha1), bone morphogenetic protein 2 (BMP-2) and matrix Gla protein (MGP) in renal arteriole of DN rats were detected by immunohistochemistry, in-situ hybridization and real-time PCR. The biochemical indices were detected by routine test. RESULTS: 1. Blood glucose and Urine protein of 24 h were significantly increased in the renal arteriole of DN rats versus the control rats (P < 0.05), serum creatinine (SCr) and phosphorus were significantly increased from 12 weeks. 2. Little deposit of calcium salt was observed in the renal arteriole of DN rats at the 4th week and a large amount of deposit was observed at 24th week, but no calcium deposit was observed in control rats. 3. Cbfalpha1 and BMP-2 expressions were significantly increased in the renal arteriole of DN rats from 4 to 24 weeks vs. the control rats. MGP mRNA expression in the renal arteriole of DN rats was significantly decreased from 4 to 24 weeks. MCP-1 expression was obviously upregulated in the renal arteriole of DN rats at 24th week versus that at 4th and 12th week. No MCP-1 expression was observed in the renal arterioles of control rats. MCP-1 were positively correlated with the expression of cbfalpha1 and BMP-2. CONCLUSION: Bone matrix proteins has already expressed in renal arteriole before the formation of vascular calcification. MCP-1 can affect the expression of cbfalpha1, BMP-2; cbfalpha1, BMP-2, MGP and MCP-1 may be involved in the formation of vascular lesions of DN.

[Association of diabetes and early failure of arteriovenous fistula in the end stage of renal diseases].

OBJECTIVE: To determine the association of diabetes and glycemic control with early failure of native arteriovenous fistula(AVF). METHODS: 266 patients with end stage renal diseases(ESRD) were recruited and divided into non-diabetic group (165), HbA1C < 7% group (51) and HbA1C > or = 7% group (50). Clinical indicators and early failure of AVF were examined. RESULTS: In total, 63 (23.7%) patients had AVF early failure. The AVF early failure occurred in 18. 1% of patients in the non-diabetic group and 21.6% of patients in the HbA1C < 7% group, significantly less than that in the HbA1C > or = 7% group (44%). The COX regression model showed that increased HbA1C, total cholesterol (TC) and decreased high-density lipoprotein (HDL)increased the risk of AVF failure. CONCLUSION: The levels of glycemic and serum lipid subfractions are associated with AVF early failure in ESRD patients. Good control of glycemic and lipid can lower the rates of AVF early failure.

Application of weighted gene co-expression network analysis to identify novel key genes in diabetic nephropathy.

AIMS/INTRODUCTION: Diabetic nephropathy (DN) is among the leading causes of end-stage renal disease worldwide. DN pathogenesis remains largely unknown. Weighted gene co-expression network analysis is a powerful bioinformatic tool for identifying key genes in diseases. MATERIALS AND METHODS: The datasets GSE30122, GSE104948, GSE37463 and GSE47185 containing 23 DN and 23 normal glomeruli samples were obtained from the National Center for Biotechnology Information Gene Expression Omnibus database. After data pre-processing, weighted gene co-expression network analysis was carried out to cluster significant modules. Then, Gene Set Enrichment Analysis-based Gene Ontology analysis and visualization of network were carried out to screen the key genes in the most significant modules. The connectivity map analysis was carried out to find the significant chemical compounds. Finally, some key genes were validated in in vivo and in vitro experiments. RESULTS: A total of 454 upregulated and 392 downregulated genes were identified. A total of 16 modules were clustered, and the most significant modules (green, red and yellow modules) were determined. The green module was associated with extracellular matrix organization, the red module was associated with immunity reaction and the yellow module was associated with kidney development. We found several key genes in these three modules separately, and part of them were validated in vivo and in vitro successfully. We found the top 15 chemical compounds that could perturb the overall expression of key genes in DN. CONCLUSION: Weighted gene co-expression network analysis was applied to DN expression profiling in combination with connectivity map analysis. Several novel key genes and chemical compounds were screened out, providing new molecular targets for DN.

Clinical predictive model to estimate probability of remission in patients with lupus nephritis.

BACKGROUND: Lupus nephritis (LN) is a major organ complication and cause of morbidity and mortality in patients with systemic lupus erythematosus. This study aims to provide the clinician with a quantitative tool for the prediction of the individual remission probability of LN and obtain new insights for improved clinical management in LN treatment. METHODS: A total of 301 patients with renal biopsy-proven LN were recruited and randomly divided into model construction and validation group. The least absolute shrinkage and selection operator regression analysis was conducted to select significant variables, and a multivariate Cox regression predictive model was established. The performance of the model was verified and tested with 1000-bootstrap validation in the validation group. Finally, the nomogram was constructed, and the performance was evaluated. The predictive accuracy and efficiency were verified through receiver operation characteristic and calibration curves. RESULTS: A total of 210 and 91 patients who all received renal biopsy were included in the training and validation group, respectively. A final prognostic model was established, which included the course of LN, gender, 24h-proteinuria, creatinine, triglycerides, FIB, Complement C3, anti-dsDNA antibody, tubular atrophy and classification of kidney biopsy. Moreover, an easy-to-use nomogram was built based on the predictive model. The areas under the curve (AUC) of the 1, 2, 5-year prediction were 77.12, 77.98 and 87.01 in the training group, respectively. In the validation group, the AUC of the 1, 2, 5-year prediction were 81.42, 87.20 and 92.81 respectively, which indicated good performance in predicting the remission probability of LN. CONCLUSION: This novel model was constructed to predict the remission probability of patients with LN for the first time. This model displayed good predictive performance and was easy to use for clinical practice.

[Influence of high glucose and mannose binding lectin complement pathway activation to IL-6 and TNF-alpha's expression by human renal glomerular endothelial cells].

OBJECTIVE: To investigate the effect of high glucose and mannose binding lectin (MBL) complement pathway activation's effect on expression of Interleukin-6 (IL-6) and Tumor necrosis factor-alpha (TNF-alpha) from human renal glomerular endothelial cells (HRGEC), to explore unknown pathogenesy of diabetic nephropathy. METHODS: Normal HRGEC was divided randomly into normal glucose group(5 mmol/L D-glucose), manicol group (5 mmol/L D-glucose+25 mmol/L manicol) and high glucose group (30 mmol/L D-glucose). Real-time PCR was used to detect IL-6 and TNF-alpha mRNA expression in each group, Euzymelinked Immunosorbent Assay (ELISA) was performed to examine the protein expression of IL-6 and TNF-alpha in supernatant after 24 hours' culture. HRGEC was then randomly divided into two groups: single high glucose group and high glucose + MBL group. After 24 hours' culture with 30 mmol/L D-glucose, 30% MBL deficiency human serum was added into two groups, 1 microg/mL MBL was only added into high glucose + MBL group, continued the culturation for another 4 hours. Flow cytometry and immunofluorescence technique were applied to evaluate MBL, C3 and membrane attacks complex (MAC) deposition on cell surface respectively. Real-time PCR and ELISA were performed to examine mRNA and protein expression of both IL-6 and TNF-alpha in each group. RESULTS: Compared with normal glucose group and manicol group, the mRNA and protein expression of IL-6 and TNF-alpha in high glucose group were increased (P < 0.05). Flow cytometry confirmed obvious MBL and C3 co-deposition and Immunofluorescence confirmed obvious MAC deposition on cell surface in high glucose+ MBL group. Compared with single high glucose group, the mRNA and protein expression of IL-6 and TNF-alpha in high glucose+ MBL group were significantly higher (P < 0.05). CONCLUSION: High glucose can bring inflammatory factors' overexpression from cultured HRGEC; high glucose together with MBL can bring MBL complement pathway activation and inflammatory factors' overexpression, this indicates that the activation of MBL complement pathway may be a potential unknown pathogenesy of diabetic nephropathy and its proinflammatory status.

[Influence of mannose binding lectin to expression of TGF-beta1 and NF-kappaB in high concentration of glucose cultured human renal glomerular endothelial cells].

OBJECTIVE: To investigate the effect of mannose binding lectin (MBL) complement pathway on expression of transforming growth factor-beta1 (TGF-beta1) and NF-kappaB in cultured human renal glomerular endothelial cells (HRGECs) stimulated by high concentration of glucose. METHODS: Human glomerular endothelial cells in culture were randomly divided into 5 groups according to different managements: normal concentration of glucose as controlled group, MBL + normal concentration of glucose group, high concentration of glucose, MBL + high glucose and MBL + high glucose + MBL blocker respectively. Flow cytometry was used to detect the depositions of MBL and C3 on the surfaces of HRGECs. Real-time PCR method was used to detect the mRNA levels of TGF-beta1. Human TGF-beta1 ELISA kit was used to detect the concentration of TGF-beta1 in supernatant fluid. ESMA was used to detect the activity of NF-kappaB in HRGECs. RESULTS: Compared with the normal glucose group and high glucose group, the depositions of MBL, C3 were apparently increased in MBL + high glucose group (P < 0.05). Expression of TGF-beta1 were significantly higher (P < 0.05) in MBL + high concentration of glucose groups than the normal glucose group and the high concentration of glucose group. Compared with the high glucose group, the activity of NF-kappaB in HRGECs was apparently increased in MBL + high glucose group, which could be significantly downregulated by MBL blocking antibody. CONCLUSION: High concentration of glucose can increase the expression of TGF-beta1 of cultured human glomerular endothelial cells. At the same time, high glucose together with MBL can up regulate the expression of TGF-beta1 and the activity of NF-kappaB in HRGECs.