Mid-upper arm circumference predicts the risk of gestational diabetes in early pregnancy.

BACKGROUND: The present work aimed to assess the value of mid-upper arm circumference (MUAC) at 8 to 12 weeks in predicting the occurrence of gestational diabetes mellitus (GDM). METHODS: According to eligibility criteria, 328 women with singleton pregnancies who underwent routine antenatal check-ups at Qinhuangdao Maternal and Child Health Hospital from September 2017 to September 2020 were included. The patients were divided into the gestational diabetes mellitus (GDM) and non-GDM groups according to oral glucose tolerance test (OGTT) data from gestation weeks 24 to 28. Clinical data were compared between the two groups. Logistic regression analysis was performed to determine factors independently predicting GDM. Receiver operating characteristic (ROC) curve analysis was employed to analyze the value of MUAC in predicting the occurrence of GDM. The optimal cut-off points were calculated. RESULTS: In logistic regression analysis, pre-pregnancy weight, waist circumference, MUAC, UA, TG, and HDL-C independently predicted the occurrence of GDM (P < 0.05). MUAC retained statistical significance upon adjustment for various confounders (OR = 8.851, 95%CI: 3.907-20.048; P < 0.001). ROC curve analysis revealed good diagnostic potential for MUAC in GDM (AUC = 0.742, 95%CI: 0.684-0.800, P < 0.001), with a cut-off of 28.5 cm, sensitivity and specificity were 61% and 77%, respectively. CONCLUSION: Pregnant women with MUAC >28.5 cm are prone to develop GDM during pregnancy, indicating that MUAC as an important predictive factor of GDM in early pregnancy.

The impact of inflammatory biomarkers on amputation rates in patients with diabetic foot ulcers.

Diabetic Foot Ulcers (DFUs) are a major complication of diabetes, often leading to amputation. Understanding the relationship between haematological inflammatory markers and the incidence of amputation in DFU patients with infectious complications is crucial for improving management and outcomes. This retrospective study, conducted from May 2020 to October 2022, involved 109 patients with DFUs, categorised into amputation (AM) and non-amputation (NAM) groups. Patients were evaluated for various factors, including demographic data, DFU duration, and blood parameters such as haemoglobin A1c (HbA1c), haemoglobin (Hb), albumin (ALB), white blood cell count (WBC), erythrocyte sedimentation rate (ESR), procalcitonin (PCT), C-reactive protein (CRP), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), and lymphocyte-to-monocyte ratio (LMR). Statistical analyses were performed using independent sample t-tests, Mann-Whitney U test and logistic regression. The univariate analysis showed no significant difference in BMI, DM duration or DFU duration between groups. However, significant differences were noted in PCT, Hb, ESR, ALB, HbA1c and WBC levels, and in inflammatory ratios (NLR, PLR and LMR). Multivariate logistic regression identified CRP, NLR and PLR as independent risk factors for amputation. The study highlights CRP, PLR and NLR as key independent risk factors for amputation in patients with DFUs. These easily obtainable markers from routine blood tests can effectively aid in predicting the risk of osteomyelitis and amputation, enhancing clinical decision making and patient care strategies.

A polyaniline functionalized NiFeP nanosheet array-based electrochemical immunosensor using Au/Cu2O nanocubes as a signal amplifier for the detection of SARS-CoV-2 nucleocapsid protein.

Coronavirus disease 2019 (COVID-19) is an infectious disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which emerged as a novel pathogen in 2019. The virus is responsible for a severe acute respiratory syndrome outbreak, affecting the respiratory system of infected individuals. COVID-19 is a super amplifier of basic diseases, and the disease with basic diseases is often more serious. Controlling the spread of the COVID-19 pandemic relies heavily on the timely and accurate detection of the virus. To resolve the problem, a polyaniline functionalized NiFeP nanosheet array-based electrochemical immunosensor using Au/Cu2O nanocubes as a signal amplifier is fabricated for the detection of SARS-CoV-2 nucleocapsid protein (SARS-CoV-2 NP). Polyaniline (PANI) functionalized NiFeP nanosheet arrays are synthesized as an ideal sensing platform for the first time. PANI is coated on the surface of NiFeP by electropolymerization to enhance biocompatibility, beneficial for the efficient loading of the capture antibody (Ab1). Significantly, Au/Cu2O nanocubes possess excellent peroxidase-like activity and exhibit outstanding catalytic activity for the reduction of H2O2. Therefore, Au/Cu2O nanocubes combine with a labeled antibody (Ab2) through the Au-N bond to form labeled probes, which can effectively amplify current signals. Under optimal conditions, the immunosensor for the detection of SARS-CoV-2 NP shows a wide linear range of 10 fg mL-1-20 ng mL-1 and a low detection limit of 1.12 fg mL-1 (S/N = 3). It also exhibits desirable selectivity, repeatability, and stability. Meanwhile, the excellent analytical performance in human serum samples confirms the practicality of the PANI functionalized NiFeP nanosheet array-based immunosensor. The electrochemical immunosensor based on the Au/Cu2O nanocubes as a signal amplifier demonstrates great potential for application in the personalized point-of-care (POC) clinical diagnosis.

Analysis of the association between serum levels of 25(OH)D, retinol binding protein, and Cyclooxygenase-2 and the disease severity in patients with diabetic foot ulcers.

Diabetic foot ulcers (DFUs) pose significant clinical challenges, representing severe complications in diabetes mellitus patients and contributing to non-traumatic amputations. Identifying reliable biomarkers can optimize early diagnosis and improve therapeutic outcomes. This study focused on evaluating the association between serum levels of 25-hydroxyvitamin D [25-(OH)D], Serum Retinol Binding Protein (RBP), and Cyclooxygenase-2 (COX-2) in elderly DFU patients. A retrospective study involving 240 participants, from March 2020 to March 2023. The participants were segmented into three cohorts: 80 with DFUs, 80 diabetic patients without DFUs, and 80 healthy controls. Serum concentrations of the three biomarkers were assayed using methods like enzyme-linked immunosorbent assay (ELISA), chemiluminescence immunoassay, and an automated biochemistry analyser. Comparisons were made both between groups and within the DFU group based on disease severity. Statistical analysis revealed significant differences in biomarker levels across the groups (p < 0.05). COX-2 and RBP concentrations were highest in the DFU group, followed by the non-DFU diabetic group, and lowest in the control group. Conversely, 25(OH)D levels were highest in the control group, followed by the non-DFU diabetic group, and lowest in the DFU group. Within the DFU group, RBP and COX-2 levels increased with disease severity, while 25(OH)D levels decreased. These variations were especially pronounced in patients with the most severe Wagner grading. A significant positive correlation was observed between disease severity and levels of RBP (r = 0.651, p < 0.05) and COX-2 (r = 0.356, p < 0.05). Conversely, a significant negative correlation was identified between disease severity and 25(OH)D levels (r = -0.658, p < 0.05). Assessing 25(OH)D, RBP, and COX-2 serum levels offers a promising tool for evaluating the severity and progression of DFUs. Monitoring these biomarkers can enrich our understanding of the metabolic and inflammatory pathways of the disease and potentially refine therapeutic strategies.

The relationship between hypertriglyceridemic waist circumference phenotype and gestational diabetes mellitus.

AIMS: To investigate the correlation between hypertriglyceridemic waist circumference (HTWC) phenotype and gestational diabetes mellitus (GDM). METHODS: A total of 1083 patients with gestational age ≤8 weeks were divided into four groups: normal triglyceride and waist circumference group (group A, n = 575), simple abdominal obesity group (group B, n = 317), simple high triglyceride group (group C, n = 125), and HTWC group (group D, n = 66). General information and serum biochemical indicators were measured and recorded. Analysis of variance (ANOVA) and logistic regression analysis were used to evaluate the relationship between HTWC with GDM. RESULTS: The prevalence of GDM in the HTWC group was significantly greater than in the other three groups. After adjustment by multivariate logistic regression analysis, the proportion of GDM in the HTWC group was 1.753 times higher than in group A. CONCLUSION: These findings suggest that there is a significant correlation between HTWC phenotype and GDM, indicating that the HTWC phenotype could be applied as a simple marker for identifying GDM risk factors.

Use of magnetic resonance imaging combined with gene analysis for the diagnosis of fetal congenital heart disease.

BACKGROUND: Fetal deformity is a disease caused by abnormal chromosome structure, which may be influenced by genetic factors as well as the maternal and external environment. Magnetic resonance imaging (MRI) may be used to effectively diagnose fetus deformities. However it has been reported that gene analysis is a more accurate diagnostic method. The aim of the present study was to investigate the effectiveness of MRI in combination with gene analysis for the diagnosis of fetal congenital heart disease, a form of fetus deformity. METHODS: MRI, array comparative genome hybridization analysis and fluorescence in situ hybridization were used to analyze the effectiveness of the two methods in a total of 78 pregnant women with suspected fetal congenital heart disease. RESULTS: Our findings demonstrated that the combination of MRI and gene analysis resulted in significantly improved diagnostic accuracy, sensitivity and specificity for fetal congenital heart disease compared with either method alone. MRI combined with gene analysis confirmed 42 fetuses with pulmonary stenosis, 24 with aortic stenosis and 12 healthy fetuses, which was significantly improved compared with MRI or gene analysis alone. It was also observed that gene analysis was a more efficient method of diagnosis compared with MRI; however, the combination of the two methods was the most effective. CONCLUSION: In conclusion, the results of the present study suggest that MRI combined with gene analysis may be a more effective diagnostic method for fetal congenital heart disease compared with the current protocol.

Identification of urinary biomarkers for the prediction of gestational diabetes mellitus in early second trimester of young gravidae based on iTRAQ quantitative proteomics.

Gestational Diabetes Mellitus (GDM) has brought great harm to maternal and fetus. Up to now, only a few plasma biomarkers for its early diagnosis have been reported; nevertheless, there is no report about identification of urinary biomarkers for prediction of GDM. Thus, it is necessary to correct this deficiency. In our study, urine samples were collected from 889 healthy young gravidae at the early second trimester (15 to 20 weeks), 69 of whom were subsequently diagnosed with GDM at 24 to 28 weeks. iTRAQ (the isobaric tags for relative and absolute quantification) quantitative proteomics was conducted on sixteen GDM (trial group) and an equal number of matched healthy young gravidae (control group). Validation was performed in 40 cases of each group by ELISA. A total of 1,901 proteins were identified in this study, including 119 significantly differential proteins (fold change ≧1.2 or ≦0.83 and p < 0.05). Compared with control group, 83 differential proteins were increased and 36 proteins were decreased in GDM group. The validation for expression of CD59 and IL1RA showed significant difference and the area under the receiver operating characteristic curve was 0.729 and 0.899, respectively (p < 0.05). The two candidate protein biomarkers (CD59 and IL1RA) in urine could be an early, noninvasive diagnostic predictors of young pravidae with GDM, and IL1RA is stronger diagnostic power than CD59.

First-Trimester Triglyceride-Glucose Index and Triglyceride/High-Density Lipoprotein Cholesterol are Predictors of Gestational Diabetes Mellitus Among the Four Surrogate Biomarkers of Insulin Resistance.

Purpose: This study seeks to assess the potential of early pregnancy Triglyceride Glucose Index (TyG), triglyceride to High-Density Lipoprotein Cholesterol ratio (TG/HDL-c), Low-Density Lipoprotein Cholesterol to High-Density Lipoprotein Cholesterol ratio (LDL-C/HDL-C), and Total Cholesterol to High-Density Lipoprotein Cholesterol ratio (TC/HDL-C) in predicting Gestational Diabetes Mellitus (GDM). Patients and Methods: A total of 1073 adults singleton pregnant women were enrolled from June 2017 to September 2019. Complete anthropometric data and lipid profiles were measured in the first trimester (before 12 weeks gestation) and a 75g oral glucose tolerance test (OGTT) at 24-28 weeks was performed. Based on OGTT results, participants were categorised into Normal Glucose Tolerance (NGT) group (n=872) and GDM group (n=201). General data, laboratory test results, and surrogate insulin resistance indicators such as TyG index, TG/HDL-C, LDL-C/HDL-C, and TC/HDL-C were documented and compared. To compare differences between the two groups, t-test was used, Spearman correlation analysis and linear regression analysis were performed to establish associations between these indicators and insulin resistance in GDM. Receiver Operating Characteristic (ROC) curves were generated to compare the thresholds of these indicators for predicting GDM during pregnancy and to quantify overall diagnostic accuracy. Results: Individuals with GDM had higher TyG, TG/HDL-C, and LDL-C/HDL-C levels (P < 0.001), but with no significant difference observed in TC/HDL-C. All four ratios were positively correlated with Homeostatic Model Assessment of Insulin Resistance (HOMA-IR), yet only TyG emerged as an independent risk factor for HOMA-IR. The Area under the Curve (AUC) of TyG index (0.692) was comparable to that of HOMA-IR (0.703). The cut-off points for TyG index, TG/HDL-C, and HOMA-IR in predicting GDM were 7.088, 0.831, and 1.8, respectively. HOMA-IR exhibited the highest sensitivity (79.1%), while TyG index (64.3%) and TG/HDL-C ratio (64.3%) demonstrated better specificity compared to HOMA-IR (56.3%). LDL-C/HDL-C and TC/HDL-C offered no discernible predictive advantage. Conclusion: Early pregnancy TyG index and TG/HDL-C can aid in identifying pregnant women at risk for GDM, potentially facilitating early and effective intervention to improve prognosis. TyG index exhibited superior predictive capability compared to TG/HDL-C.

New perspective on first-trimester serum uric acid level in predicting the risk of gestational diabetes mellitus.

This study aimed to investigate the correlation between serum uric acid (UA) and gestational diabetes mellitus (GDM) during the first trimester and provide a new perspective for the prevention and treatment of GDM. Based on the diagnostic criteria of gestational diabetes of the International Association of Diabetes and Pregnancy Study Groups, 1744 and 4256 patients were enrolled in the GDM and normal glucose tolerance (NGT) groups. Four groups were constituted based on the quartile of first-trimester serum UA (UA) level, and the differences in each indicator between groups were compared. Logistic regression was used to analyze the effects of UA level on GDM risk. The rate of GDM in the UA quartile changed from low to high. Significant differences were also observed in fasting plasma glucose level, 1 h post glucose and 2 h post glucose levels, in all the groups (P < 0.05), which increased with the UA level. UA level were independent risk factors for GDM. The best threshold of GDM predicted by the first-trimester UA level was 226.55 µmol/L. The first-trimester UA level in patients with GDM was relatively higher and was an independent risk factor for GDM.

Correlation Between Neck Circumference and Gestational Diabetes.

Purpose: The objective of this study was to explore whether neck circumference can serve as an early predictor of the risk of Gestational Diabetes (GDM). Patients and Methods: A total of 318 singleton pregnant women who underwent routine prenatal examinations at Qinhuangdao Maternal and Child Health Hospital from September 2017 to September 2020 were selected and categorized into the GDM group and the normal glucose tolerance group (NGT) based on the results of the oral glucose tolerance test (OGTT) conducted during the second trimester. The general information and laboratory test results were compared and analyzed. Inter-group comparison was conducted using the t-test, and multivariate logistic regression analysis was employed to analyze the independent risk factors of GDM. The predictive threshold of various indicators for GDM occurrence during pregnancy was determined using the subject's work curve. Results: The GDM group exhibited significantly higher levels of pre-pregnancy weight, pre-pregnancy BMI, neck circumference, waist circumference, hip circumference, triglycerides (TG), uric acid (UA), TG/HDL-C ratio, and waist-hip ratio compared to the NGT group. Additionally, HDL cholesterol (HDL-C) levels were significantly lower in the GDM group, and blood glucose levels at each point of the OGTT were markedly higher compared to the NGT group (P<0.05). Multivariate logistic regression analysis revealed that neck circumference (OR=1.239, P<0.001) and early pregnancy TG (OR=1.842, P<0.001) were independent risk factors for GDM. The receiver operating characteristic analysis demonstrated that the optimal critical value of neck circumference for predicting GDM was 32.6 cm, with a sensitivity of 50% and specificity of 74.3%. Conclusion: The neck circumference during early pregnancy was found to be related to GDM, and the predictive cutoff point of 32.6 cm for neck circumference could be employed as a simple index to predict GDM in early pregnancy.

The relationship between serum adipokine fibroblast growth factor-21 and gestational diabetes mellitus.

AIMS/INTRODUCTION: To explore the differences of serum fibroblast growth factor-21 (FGF-21) levels in pregnant women with normal glucose tolerance and gestational diabetes mellitus (GDM), and to analyze the relationship between FGF-21 and glucose and lipid metabolic indicators, leptin, retinol binding protein 4 (RBP-4) and adiponectin in GDM, in order to provide basis for the prevention and treatment of GDM. MATERIALS AND METHODS: Total of 120 women were included, and divided into normal glucose tolerance group (58 cases) and GDM group (62 cases) according to the 75 g oral glucose tolerance test results. General information were recorded; height, weight and blood pressure, blood glucose, lipids, insulin, FGF-21, leptin, RMP-4, and adiponectin were measured, and body mass index (BMI), homeostasis model assessment-IR, homeostasis model assessment-ß and area under glucose curve were calculated. The t-test, Pearson analysis and multiple linear regression analysis were used to evaluate the differences and related factors of FGF-21 in GDM. RESULTS: The pre-pregnancy BMI, pregnancy BMI, weight gain during pregnancy and FGF-21 levels were higher in GDM group, whereas there were no statistically significant differences in leptin, RBP-4 and adiponectin. Correlation analysis suggested that FGF-21 level was correlated with age, pre-pregnancy BMI, weight gain during pregnancy, high-density lipoprotein cholesterol, leptin, RBP-4 and adiponectin, and the results of multiple linear regression showed that serum FGF-21 was related to pre-pregnancy BMI, weight gain during pregnancy, leptin, RBP-4 and adiponectin in GDM. CONCLUSIONS: There were higher serum FGF-21 levels in GDM, which might be related to pre-pregnancy BMI, weight gain during pregnancy, leptin, RBP-4 and adiponectin.

Rapid determination of SARS-CoV-2 nucleocapsid proteins based on 2D/2D MXene/P-BiOCl/Ru(bpy)32+ heterojunction composites to enhance electrochemiluminescence performance.

At the end of 2019, the novel coronavirus disease 2019 (COVID-19), a cluster of atypical pneumonia caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has been known as a highly contagious disease. Herein, we report the MXene/P-BiOCl/Ru(bpy)32+ heterojunction composite to construct an electrochemiluminescence (ECL) immunosensor for SARS-CoV-2 nucleocapsid protein (CoVNP) determination. Two-dimensional (2D) material ultrathin phosphorus-doped bismuth oxychloride (P-BiOCl) is exploited and first applied in ECL. 2D architectures MXene not only act as "soft substrate" to improve the properties of P-BiOCl, but also synergistically work with P-BiOCl. Owing to the inimitable set of bulk and interfacial properties, intrinsic high electrochemical conductivity, hydrophilicity and good biocompatible of 2D/2D MXene/P-BiOCl/Ru(bpy)32+, this as-exploited heterojunction composite is an efficient signal amplifier and co-reaction accelerator in the presence of tri-n-propylamine (TPA) as a coreactant. The proposed MXene/P-BiOCl/Ru(bpy)32+-TPA system exhibits a high and stable ECL signal and achieves ECL emission quenching for "signal on-off" recognition of CoVNP. Fascinatingly, the constructed ECL biosensor towards CoVNP allows a wide linear concentration range from 1 fg/mL to 10 ng/mL and a low limit of detection (LOD) of 0.49 fg/mL (S/N = 3). Furthermore, this presented strategy sheds light on designing a highly efficient ECL nanostructure through the combination of 2D MXene architectures with 2D semiconductor materials in the field of nanomedicine. This ECL biosensor can successfully detect CoVNP in human serum, which can promote the prosperity and development of diagnostic methods of SARS-CoV-2.

A two-dimensional G-CoP/N,P-co-doped carbon nanowire electrode for the simultaneous determination of hydroquinone and catechol in domestic wastewater.

Hydroquinone (HQ) and catechol (CC) are important chemical raw materials in the modern industry, unfortunately, which are also high toxic phenolic pollutants. So how to achieve highly sensitive and selective determination HQ and CC is the challenge we face. In the present work, we report a facile strategy to obtain nitrogen and phosphorous co-doped glucose-derived carbon coated CoP nanowires (G-CoP/N,P-C NWs), in which nitrilotriacetic acid (NTA) was as the chelating reagent, glucose was as carbon source, and the precursors were subsequently experienced carbonization and phosphorization process. G-CoP/N,P-C NWs can shorten the distance of the electron transport and expand the reaction area, showing the intriguing electronic conductivity and electrocatalytic abilities. An electrochemical phenolic sensor based on G-CoP/N,P-C NWs is fabricated. The as-prepared sensor showcases the good sensing performance for HQ and CC with comparative linearity ranges of 0.8-900 µM (HQ) and 0.6-800 µM (CC), low limits of detections (LODs) of 0.18 µM (S/N = 3) and 0.12 µM (S/N = 3) for HQ and CC, respectively. Notably, it also displays excellent practical application for the recognition of HQ and CC in the rain water, the tap water, the domestic wastewater and the lake water, which may be a promising candidate in environmental water monitoring and drinking water safety.

Long Non-coding RNA XIST Attenuates Diabetic Peripheral Neuropathy by Inducing Autophagy Through MicroRNA-30d-5p/sirtuin1 Axis.

Diabetic peripheral neuropathy (DPN) is a prevalent diabetes mellitus (Feldman et al., 2017) complication and the primary reason for amputation. Meanwhile, long non-coding RNAs (lncRNAs) are a type of regulatory non-coding RNAs (ncRNAs) that broadly participate in DPN development. However, the correlation of lncRNA X-inactive specific transcript (XIST) with DPN remains unclear. In this study, we were interested in the role of XIST in the modulation of DPN progression. Significantly, our data showed that the expression of XIST and sirtuin1 (SIRT1) was inhibited, and the expression of microRNA-30d-5p (miR-30d-5p) was enhanced in the trigeminal sensory neurons of the diabetic mice compared with the normal mice. The levels of LC3II and Beclin-1 were inhibited in the diabetic mice. The treatment of high glucose (HG) reduced the XIST expression in Schwann cells. The apoptosis of Schwann cells was enhanced in the HG-treated cells, but the overexpression of XIST could block the effect in the cells. Moreover, the levels of LC3II and Beclin-1 were reduced in the HG-treated Schwann cells, while the overexpression of XIST was able to reverse this effect. The HG treatment promoted the production of oxidative stress, while the XIST overexpression could attenuate this result in the Schwann cells. Mechanically, XIST was able to sponge miR-30d-5p and miR-30d-5p-targeted SIRT1 in the Schwann cells. MiR-30d-5p inhibited autophagy and promoted oxidative stress in the HG-treated Schwann cells, and SIRT1 presented a reversed effect. MiR-30d-5p mimic or SIRT1 depletion could reverse XIST overexpression-mediated apoptosis and autophagy of the Schwann cells. Thus, we concluded that XIST attenuated DPN by inducing autophagy through miR-30d-5p/SIRT1 axis. XIST and miR-30d-5p may be applied as the potential targets for DPN therapy.

[Effect of dapagliflozin on gene expression of glucose transporter 2 and glucose transporter 4 in kidney of type 2 diabetic rats].

Objective: To investigate the effects of dapagliflozin on the gene expressions of glucose transporter 2 (GLUT2) and glucose transporter 4 (GLUT4) in type 2 diabetic rats. Methods: High fat diet and 40 mg/kg streptozotocin (STZ) were used to establish the rat model of type 2 diabetes mellitus. When the fasting blood glucose (FBG) content was more than or equal to 16.7 mmol/L, the model was established successfully. After successful modeling, the rats were randomly divided into model group (group B, normal saline), dapagliflozin low-dose group (Group C, 0.75 mg/kg), dapagliflozin middle dose group (Group D, 1.5 mg/kg) and dapagliflozin high-dose group (Group E, 3.0 mg/kg), with 6 rats in each group. Six healthy SD rats were selected as normal control group (group A, normal saline). Each group was administrated by gavage once a day for 7 weeks. The body weight, serum FBG, hemoglobin A1c (HbA1c), blood urea nitrogen (BUN) and serum creatinine (Scr) were measured after 7 weeks. The levels of malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione peroxidase (GSH-PX) in serum and kidney were measured by enzyme-linked immunosorbent assay (ELISA). HE staining was used to observe the pathological changes of kidney. The protein expressions of GLUT2 and GLUT4 were detected by Western blot. RT-qPCR was used to detect the relative expressions of GLUT2 and GLUT4 mRNA in kidney tissue. Results: Compared with group A, the body weight, SOD, GSH-Px levels of rats in each group were significantly decreased (P＜0.05), while the levels of FBG, HbA1c, BUN, SCR and MDA were significantly increased (P＜0.05), renal pathological damage was serious, the relative expressions of GLUT2, GLUT4 mRNA and protein in renal tissue were significantly decreased (P＜0.05). Compared with group B, the body weight, SOD, GSH-Px levels and the mRNA relative expressions of GLUT2 and GLUT4 in group C, group D and group E were significantly increased (P＜0.05), while the levels of FBG, HbA1c, BUN, SCR and MDA were significantly decreased (P＜0.05). The renal pathological damage in group D and group E was significantly alleviated, and the expressions of GLUT2 and GLUT4 protein in renal tissue were significantly increased (all P＜0.05). Conclusion: Dapagliflozin can alleviate the condition of type 2 diabetic rats and up regulate the expression of GLUT2 and GLUT4 genes in kidney.

6-Shogaol ameliorates diabetic nephropathy through anti-inflammatory, hyperlipidemic, anti-oxidative activity in db/db mice.

The prevalence of type 2 diabetes mellitus has been increasing worldwide and more than two thirds of the patients may develop diabetic nephropathy (DN). However, the efficiency of existing approaches on DN progression is limited. 6-Shogaol (6-SG), a major dehydrated derivative of gingerols, possesses various biological properties. The present study was designed to evaluate the possible effects of 6-SG on DN in db/db mice and to investigate the mechanisms. We revealed that 6-SG reduced the levels of fasting blood glucose, serum insulin, C-peptide, glycosylated hemoglobin A1c, and systolic blood pressure. 6-SG decreased the levels of blood urea nitrogen (BUN), serum creatinine, urinary albumin content and albumin/creatinine ratio (ACR), ameliorated the pathological injuries of kidneys, reduced the surface area of Bowman's capsule, Bowman's space, glomerular tuft, and decreased the expression of collagen IV and fibronectin in kidneys of db/db mice. The high levels of systemic and renal triglyceride and cholesterol were decreased by 6-SG. Moreover, 6-SG exhibited anti-inflammatory effects, as reflected by reduction of tumor necrosis factor ɑ (TNFɑ), monocyte chemotactic protein-1 (MCP-1), and IL-6 levels in circulation and kidneys, and decrease of NF-κB expression. Furthermore, 6-SG also inhibited oxidative stress and restored the expression of NF-E2-related factor 2 (Nrf2) in kidneys of db/db mice. In conclusion, we have demonstrated that 6-SG exhibits anti-diabetic and renal protective effects against DN, in which effect the anti-inflammatory, hyperlipidemic, anti-oxidative activities may be involved. Overall, 6-SG could be a promising therapeutic treatment to ameliorate diabetes and the development of DN.