Low Serum Magnesium Level Is Associated with Microalbuminuria in Chinese Diabetic Patients

Whether serum magnesium deficiency is independently associated with the prevalence of microalbuminuria is still unclear. The objective of the present study was to elucidate the association between serum magnesium and microalbuminuria in diabetic patients. A cross-sectional study was conducted in 1829 diabetic subjects (aged ≥ 40 years) from Shanghai, China. Subjects were divided into three groups according to serum magnesium tertiles. A first-voided early-morning spot urine sample was obtained for urinary albumin-creatinine ratio (UACR) measurement. Microalbuminuria was defined as 30 mg/g ≤ UACR < 300 mg/g. Overall, 208 (11.37%) of the study population had microalbuminuria, with similar proportions in both genders (). The prevalence of microalbuminuria in tertile 1 of serum magnesium was higher than the prevalence in tertile 2 and tertile 3 (15.98%, 9.72%, and 8.46%, resp.; for trend <0.0001). After adjustment for age, sex, BMI, blood pressure, lipidaemic profile, HbA1c, eGFR, history of cardiovascular disease, HOMA-IR, antihypertensive and antidiabetic medication, and diabetes duration, we found that, compared with the subjects in tertile 3 of serum magnesium, those in tertile 1 had 1.85 times more likeliness to have microalbuminuria. We concluded that low serum magnesium level was significantly associated with the prevalence of microalbuminuria in middle-aged and elderly Chinese

Fungus Pichia kudriavzevii XTY1 and heterotrophic nitrifying bacterium Enterobacter asburiae GS2 cannot efficiently transform organic nitrogen via hydroxylamine and nitrite

Heterotrophic nitrification is a process of organic nitrogen degradation completed by the participation of heterotrophic nitrifying microorganisms, which can accelerate the nitrogen transformation process. However, the current research mainly focuses on heterotrophic nitrifying bacteria and their ammonium degradation capacities. And there is little accumulation of research on fungi, the main force of heterotrophic nitrification, and their capacities to transform organic nitrogen. In this study, novel heterotrophic nitrifying fungus (XTY1) and bacterium (GS2) were screened and isolated from upland soil, and the strains were identified and registered through GenBank comparison. After 24 h single nitrogen source tests and 15N labeling tests, we compared and preliminarily determined the heterotrophic nitrification capacities and pathways of the two strains. The results showed that XTY1 and GS2 had different transformation capacities to different nitrogen substrates and could efficiently transform organic nitrogen. However, the transformation capacity of XTY1 to ammonium was much lower than that of GS2. The two strains did not pass through NH2OH and NO2− during the heterotrophic nitrification of organic nitrogen, and mainly generated intracellular nitrogen and low N2O. Other novel organic nitrogen metabolism pathways may be existed, but they remain to be further validated

Intensive Cytokine induction in Pandemic H1N1 Influenza Virus Infection Accompanied by Robust Production of IL-10 and IL-6

BACKGROUND: The innate immune system is the first line of defense against viruses by inducing expression of cytokines and chemokines. Many pandemic influenza H1N1 virus [P(H1N1)] infected severe cases occur in young adults under 18 years old who were rarely seriously affected by seasonal influenza. Results regarding host cytokine profiles of P(H1N1) are ambivalent. In the present study we investigated host cytokine profiles in P(H1N1) patients and identified cytokines related to disease severity. METHODS AND PRINCIPAL FINDINGS: We retrieved 77, 59, 26 and 26 sera samples from P(H1N1) and non-flu influenza like illness (non-ILIs) cases with mild symptoms (mild patients), P(H1N1) vaccinees and healthy individuals, respectively. Nine and 16 sera were from hospitalized P(H1N1) and non-ILIs patients with severe symptoms (severe patients). Cytokines of IL-1, IL-2, IL-4, IL-5, IL-6, IL-8, IL-10, IL-12, IFN-γ and TNF-α were assayed by cytokine bead array, IL-17 and IL-23 measured with ELISA. Mild P(H1N1) patients produced significantly elevated IL-2, IL-12, IFN-γ, IL-6, TNF-α, IL-5, IL-10, IL-17 and IL-23 versus to healthy controls. While an overwhelming IL-6 and IL-10 production were observed in severe P(H1N1) patients. Higher IL-10 secretion in P(H1N1) vaccinees confirmed our observation that highly increased level of sera IL-6 and IL-10 in P(H1N1) patients may lead to disease progression. CONCLUSION AND SIGNIFICANCE: A comprehensive innate immune response was activated at the early stage of P(H1N1) infection with a combine Th1/Th2/Th3 cytokines production. As disease progression, a systemic production of IL-6 and IL-10 were observed in severe P(H1N1) patients. Further analysis found a strong correlation between IL-6 and IL-10 production in the severe P(H1N1) patients. IL-6 may be served as a mediator to induce IL-10 production. Highly elevated level of sera IL-6 and IL-10 in P(H1N1) patients may lead to disease progression, but the underlying mechanism awaits further detailed investigations

Simulation and Experimental Research on a Gas Liquid Separator with Rotary Impeller

Gas-liquid separation technology under microgravity is the basis for various gas and liquid treatments on a manned spacecraft, which has a wide range of applications in Environmental Control and Life Support System. Dynamic gas-liquid separator is commonly used for the separation of gas-liquid two-phase flow, which has two essential performance parameters called liquid outlet pressure and separating efficiency. Predicting these two parameters accurately under a specific structure has guiding significance for design and application of the dynamic gas-liquid separator. In this study, CFD simulations were conducted using the Volume of Fluid (VOF) model at steady state conditions. In addition, experiments were designed to verify the accuracy of numerical results. Finally, the performance of the separator under microgravity was predicted. It is showed that the simulation method can be utilized to determine the transport performance of dynamic gas-liquid separator, which has significant value in design and optimization

Simulation and Experimental Research on a Gas Liquid Separator with Rotary Impeller

Gas-liquid separation technology under microgravity is the basis for various gas and liquid treatments on a manned spacecraft, which has a wide range of applications in Environmental Control and Life Support System. Dynamic gas-liquid separator is commonly used for the separation of gas-liquid two-phase flow, which has two essential performance parameters called liquid outlet pressure and separating efficiency. Predicting these two parameters accurately under a specific structure has guiding significance for design and application of the dynamic gas-liquid separator. In this study, CFD simulations were conducted using the Volume of Fluid (VOF) model at steady state conditions. In addition, experiments were designed to verify the accuracy of numerical results. Finally, the performance of the separator under microgravity was predicted. It is showed that the simulation method can be utilized to determine the transport performance of dynamic gas-liquid separator, which has significant value in design and optimization

Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach

Pipeline transportation is widely used in industrial production and daily life. In order to reduce the waste of resources and economic losses caused by pipeline leakage, effective pipeline leakage detection and localization technology is particularly important. Among the many leakage detection methods, the model-based method for pipeline leakage detection and localization is widely used. However, the key to the method is how to obtain an accurate and reliable pipeline model to ensure and improve the detection accuracy. This paper proposes a novel method to obtain a reliable pipeline-mechanism model that fused data and mechanism models based on Bayesian theory. Moreover, in the process of Bayesian fusion, the complexity and calculations in the mechanism models were greatly reduced by establishing a surrogate model. After that, the multidimensional posterior distribution was sampled by the Markov chain Monte Carlo-differential evolution adaptive metropolis (ZS) (MCMC-DREAM (ZS)) algorithm, and the uncertainty in the model was updated to obtain a reliable pipeline-mechanism model. Subsequently, the pipeline resistance coefficient, which could be calculated based on the reliable pipeline-mechanism model, was proposed as an indicator for detecting whether the pipeline leaked or not. Finally, the pipeline leak model was used to determine the location of the leak. The reliable pipeline-mechanism model was applied in an experimental device to validate its performance. The results showed that the proposed method improved the accuracy and reliability of the mechanism model, and, in addition, the leakage could be accurately located

Low-Grade Albuminuria Is Associated with Metabolic Syndrome and Its Components in Middle-Aged and Elderly Chinese Population.

Micro-albuminuria has been well established as one of the risk factors of metabolic syndrome (MetS). However, the association of MetS and its components with low-grade albuminuria among those with normal urinary albumin excretion has not been clearly elucidated in Chinese population.A cross-sectional study was conducted among 9,579 participants with normal urinary albumin excretion, who were recruited from Jia Ding District, Shanghai, China. The single-void first morning urine sample was collected for urinary albumin and creatinine measurements, and urinary albumin-to-creatinine ratio (UACR) was calculated as urinary albumin divided by creatinine. Low-grade albuminuria was classified as sex-specific upper UACR quartile in this population. MetS was defined according to the National Cholesterol Education Program Adult Treatment Panel III criteria. The prevalence of MetS and its components increased across the UACR quartiles (all P trend <0.01). A multivariable adjusted logistic regression analysis revealed that the prevalence of MetS was gradually elevated according to the UACR quartiles (adjusted odds ratios [ORs] were 1.14, 1.24 and 1.59 for UACR quartiles 2, 3 and 4, compared with the lowest quartile; P trend<0.0001). In the further stratified logistic regression analyses, the associations between low-grade albuminuria and MetS were significant in both sex strata (male and female), both age strata (<60 and ≥60 years), both body mass index strata (<24 and ≥24 kg/m(2)), and both diabetes strata (yes and no). Compared to the lowest UACR quartile, the participants in the highest quartile of UACR had the highest prevalence of central obesity (OR = 1.43; 95%CI = 1.25-1.63), high blood pressure (OR = 1.64; 95%CI = 1.43-1.87), hyperglycemia (OR = 1.52; 95%CI = 1.30-1.78) and high triglycerides (OR = 1.19; 95%CI = 1.04-1.37).Low-grade albuminuria was significantly associated with the increasing prevalence of MetS and its components in the middle-aged and elderly Chinese population with normal urinary albumin excretion

Pipeline Leakage Detection and Localization Using a Reliable Pipeline-Mechanism Model Incorporating a Bayesian Model Updating Approach

Pipeline transportation is widely used in industrial production and daily life. In order to reduce the waste of resources and economic losses caused by pipeline leakage, effective pipeline leakage detection and localization technology is particularly important. Among the many leakage detection methods, the model-based method for pipeline leakage detection and localization is widely used. However, the key to the method is how to obtain an accurate and reliable pipeline model to ensure and improve the detection accuracy. This paper proposes a novel method to obtain a reliable pipeline-mechanism model that fused data and mechanism models based on Bayesian theory. Moreover, in the process of Bayesian fusion, the complexity and calculations in the mechanism models were greatly reduced by establishing a surrogate model. After that, the multidimensional posterior distribution was sampled by the Markov chain Monte Carlo-differential evolution adaptive metropolis (ZS) (MCMC-DREAM (ZS)) algorithm, and the uncertainty in the model was updated to obtain a reliable pipeline-mechanism model. Subsequently, the pipeline resistance coefficient, which could be calculated based on the reliable pipeline-mechanism model, was proposed as an indicator for detecting whether the pipeline leaked or not. Finally, the pipeline leak model was used to determine the location of the leak. The reliable pipeline-mechanism model was applied in an experimental device to validate its performance. The results showed that the proposed method improved the accuracy and reliability of the mechanism model, and, in addition, the leakage could be accurately located

Eosinophil inversely associates with type 2 diabetes and insulin resistance in Chinese adults.

CONTEXT: Limited population-based study focused on relationship between eosinophil and type 2 diabetes (T2D). OBJECTIVES: We aimed to evaluate the relationship between peripheral eosinophil percentage and glucose metabolism and insulin resistance in a large sample size of Chinese population aged 40 and older. DESIGN AND METHODS: A cross-sectional study was performed among 9,111 Chinese adults including 3,561 men and 5,550 women. The glucose metabolism status was confirmed by 75-g oral glucose tolerance test. Homeostasis model assessment of insulin resistance index and serum insulin levels were used to evaluate insulin resistance. Homeostasis model assessment-B was used to evaluate β cell function. RESULTS: The average age of participants was 58.5 years. The prevalence of T2D decreased across the tertiles of eosinophil percentage (21.3%, 18.2% and 16.9%, P<0.0001). Each one tertile increase of eosinophil percentage inversely associated with risk of T2D when referred not only to normal glucose tolerance (NGT) (odds ratio (OR) 0.81, 95% CI 0.76-0.87, P< 0.0001), but also to impaired glucose regulation (OR 0.89, 95% CI 0.83-0.97, P = 0.006), respectively, after adjustment for the confounding factors. Compared with the first tertile, the third tertile of eosinophil percentage associated with a 23% decrease of insulin resistance in NGT participants after full adjustments (P = 0.005). Each 1-standard deviation of increment of eosinophil percentage associated with a 37% decrease of insulin resistance (P = 0.005). CONCLUSIONS: Higher peripheral eosinophil percentage was associated with decreased risk of T2D. The inverse relation to insulin resistance was detected in NGT participants