Cardiovascular risk factors in relatives of type 2 diabetics with normal glucose tolerance test and elevated one-hour plasma glucose

Introduction: To investigate the effect of elevated one hour post-load plasma glucose on cardiovascular risk factors, in normal glucose tolerance (NGT) people, who are first degree relatives of type 2 diabetics. Material and methods: A cross-sectional study on 1475 NGT subjects (Arian ethnicity), who had one hour post-load plasma glucose was carried out. We compared the mean of age, sex, body mass index, waist circumference, blood pressure, lipid profile, and area under the curve of glucose (AUC-G) of 1190 out of 1475 NGT subjects with one hour plasma glucose (1hpG) &#8805; 155 mg/dL, and 285 NGT subjects with 1hpG < 155 mg/dL. Results: The mean age, body mass index, waist circumference, blood pressure, lipid profile (but not low HDL-cholesterol), and area under the curve of glucose (AUC-G) was significantly higher in NGT subjects with 1hpG &#8805; 155 mg/dL (P < 0.05). Normal glucose tolerance people (first degree relatives of type 2 diabetic patients) with 1hpG &#8805; 155 mg/dL were older and heavier than those with 1hpG < 155 mg/dL. Cardiovascular risk factors (but not low HDL and hypertension) were more prevalent in those with elevated one hour post-load group (P < 0.05). Conclusions: NGT subjects with elevated one hour post-load plasma glucose (1hpG &#8805; 155 mg/dL) had higher prevalence of most cardiovascular risk factors in comparison with those with 1hpG < 155 mg/dL. (Pol J Endocrinol 2010; 61 (4): 359-363)Wstęp: Celem badania była ocena wpływu podwyższonej glikemii w pierwszej godzinie po obciążeniu glukozą na czynniki ryzyka sercowo- naczyniowego u osób z prawidłową tolerancją glukozy (NGT, normal glucose tolerance) będących krewnymi pierwszego stopnia chorych na cukrzycę typu 2. Materiał i metody: Badanie wieloośrodkowe objęło 1475 osób z prawidłową tolerancją glikemii (etniczni Arianie), u których oznaczono stężenie glukozy w osoczu w godzinę po doustnym obciążeniu glukozą. Wszystkich chorych podzielono na dwie grupy w zależności od wartości glikemii: 1190, u których glikemia 1 godzinę po obciążeniu glukozą wynosiła &#8805; 155 mg/dl i 285 osób < 155 mg/dl. W obu grupach porównano średnie wartości następujących parametrów: wieku, płci, wskaźnika masy ciała, obwodu talii, ciśnienia tętniczego, profilu lipidowego i pola pod krzywą stężenia glukozy. Wyniki: U osób z prawidłową tolerancją glikemii (będących krewnymi pierwszego stopnia chorych na cukrzycę typu 2), u których glikemia na czczo w godzinę po doustnym obciążeniu glukozą wynosiła &#8805; 155 mg/dl (p < 0,05) stwierdzono istotnie wyższe wartości następujących parametrów: średni wiek, wskaźnik masy ciała, obwód talii, ciśnienie tętnicze, stężenia lipidów (z wyjątkiem cholesterolu frakcji HDL) i pola pod krzywą stężenia glukozy. Osoby, u których glikemia w godzinę po obciążeniu glukozą wynosiła &#8805; 155 mg/dl były starsze i cięższe niż osoby z niższym poposiłkowym stężeniem glukozy (< 155 mg/dl). Czynniki ryzyka sercowo-naczyniowego (z wyjątkiem niskiego stężenia cholesterolu frakcji HDL i nadciśnienia tętniczego) występowały częściej u osób z wyższymi wartościami glikemii w godzinę po obciążeniu glukozą (p < 0,05). Wnioski: U osób z prawidłową tolerancją glukozy i wyższymi wartościami glikemii w godzinę po obciążeniu glukozą (&#8805; 155 mg/dl) stwierdzono częstsze występowanie czynników ryzyka chorób sercowo-naczyniowego niż u osób, u których glikemia w godzinę po obciążeniu glukozą wynosiła < 155 mg/dl. (Endokrynol Pol 2010; 61 (4): 359-363

Experimental and numerical investigation of an innovative method for strengthening cold-formed steel profiles in bending throughout finite element modeling and application of neural network based on feature selection method

This study evaluates an innovative reinforcement method for cold-formed steel (CFS) upright sections through finite element assessment as well as prediction of the normalized ultimate load and deflection of the profiles by artificial intelligence (AI) and machine learning (ML) tech-niques. Following the previous experimental studies, several CFS upright profiles with different lengths, thicknesses and reinforcement spacings are modeled and analyzed under flexural loading. The finite element method (FEM) is employed to evaluate the proposed reinforcement method in different upright sections and to provide a valid database for the analytical study. To detect the most influential factor on flexural strength, the “feature selection” method is performed on the FEM results. Then, by using the feature selection method, a hybrid neural network (a combination of multi-layer perceptron algorithm and particle swarm optimization method) is developed for the prediction of normalized ultimate load. The correlation coefficient (R), root mean square error (RMSE), Nash–Sutcliffe efficiency (NSE), mean absolute error (MAE) and Wilmot’s index of agree-ment (WI) are used as the measure of precision. The results show that the geometrical parameters have almost the same contribution in the flexural capacity and deflection of the specimens. According to the performance evaluation indexes, the best model is detected and optimized by tuning other algorithm parameters. The results indicate that the hybrid neural network can successfully predict the normalized ultimate load and deflection

Experimental and numerical investigation of a method for strengthening cold-formed steel profiles in bending

Perforated cold-formed steel (CFS) beams subjected to different bending scenarios should be able to deal with different buckling modes. There is almost no simple way to address this significant concern. This paper investigates the bending capacity and flexural behavior of a novel-designed system using bolt and nut reinforcing system through both experimental and numerical approaches. For the experiential program, a total of eighteen specimens of three types were manufactured: a non-reinforced section, and two sections reinforced along the upright length at 200 mm and 300 mm pitches. Then, monotonic loading was applied to both the minor and major axes of the specimens. The finite element models were also generated and proved the accuracy of the test results. Using the proposed reinforcing system the flexural capacity of the upright sections was improved around either the major axis or minor axis. The 200 mm reinforcement type provided the best performance of the three types. The proposed reinforcing pattern enhanced flexural behavior and constrained irregular buckling and deformation. Thus, the proposed reinforcements can be a very useful and cost-effective method for strengthening all open CFS sections under flexural loading, considering the trade-off between flexural performance and the cost of using the method

Investigation of a method for strengthening perforated cold-formed steel profiles under compression loads

Cold-formed steel (CFS) storage rack structures are extensively used in various industries to store products in safe and secure warehouses before distribution to the market. Thin-walled open profiles that are typically used in storage rack structures are prone to loss of stability due to different buckling modes such as local, distortional, torsional and flexural, or any interaction between these modes. In this paper, an efficient way of increasing ultimate capacity of upright frames under compression load is proposed using bolts and spacers which are added externally to the section with certain pitches along the height. Hereinto, experimental tests on 81 upright frames with different thicknesses and different heights were conducted, and the effect of employing reinforcement strategies was examined through the failure mode and ultimate load results. Non-linear finite element analyses were also performed to investigate the effect of different reinforcement spacing on the upright performance. The results showed that the reinforcement method could restrain upright flange and consequently increase the distortional strength of the upright profiles. This method can also be effective for any other light gauged steel open section with perforation. It was also observed that the reinforcement approach is much more useful for short length upright frames compared to the taller frames

Electron flow of biological H2 production by sludge under simple thermal treatment: Kinetic study

Mixed culture sludge has been widely used as a microbial consortium for biohydrogen production. Simple thermal treatment of sludge is usually required in order to eliminate any H2-consuming bacteria that would reduce H2 production. In this study, thermal treatment of sludge was carried out at various temperatures. Electron flow model was then applied in order to assess community structure in the sludge upon thermal treatment for biohydrogen production. Results show that the dominant electron sink was acetate (150–217 eˉ meq/mol glucose). The electron equivalent (eˉ eq) balances were within 0.8–18% for all experiments. Treatment at 100 °C attained the highest H2 yield of 3.44 mol H2/mol glucose from the stoichiometric reaction. As the treatment temperature increased from 80 to 100 °C, the computed acetyl-CoA and reduced form of ferredoxin (Fdred) concentrations increased from 13.01 to 17.34 eˉ eq (1.63–2.17 mol) and 1.34 to 4.18 eˉ eq (0.67–2.09 mol), respectively. The NADH2 balance error varied from 3 to 10% and the term eˉ(Fd↔NADH2) (m) in the NADH2 balance was NADH2 consumption (m = −1). The H2 production was mainly via the Fd:hydrogenase system and this is supported with a good NADH2 balance. Using the modified Gompertz model, the highest maximum H2 production potential was 1194 mL whereas the maximum rate of H2 production was 357 mL/h recorded at 100 °C of treatment

Experimental and numerical investigation of a method for strengthening cold-formed steel profiles in bending

© 2020 by the authors. Perforated cold-formed steel (CFS) beams subjected to different bending scenarios should be able to deal with different buckling modes. There is almost no simple way to address this significant concern. This paper investigates the bending capacity and flexural behavior of a noveldesigned system using bolt and nut reinforcing system through both experimental and numerical approaches. For the experiential program, a total of eighteen specimens of three types were manufactured: a non-reinforced section, and two sections reinforced along the upright length at 200 mm and 300 mm pitches. Then, monotonic loading was applied to both the minor and major axes of the specimens. The finite element models were also generated and proved the accuracy of the test results. Using the proposed reinforcing system the flexural capacity of the upright sections was improved around either the major axis or minor axis. The 200 mm reinforcement type provided the best performance of the three types. The proposed reinforcing pattern enhanced flexural behavior and constrained irregular buckling and deformation. Thus, the proposed reinforcements can be a very useful and cost-effective method for strengthening all open CFS sections under flexural loading, considering the trade-off between flexural performance and the cost of using the method

Numerical Evaluation of the Upright Columns with Partial Reinforcement along with the Utilisation of Neural Networks with Combining Feature-Selection Method to Predict the Load and Displacement

This study evaluated the axial capacity of cold-formed racking upright sections strengthened with an innovative reinforcement method by finite element modelling and artificial intelligence techniques. At the first stage, several specimens with different lengths, thicknesses and reinforcement spacings were modelled in ABAQUS. The finite element method (FEM) was employed to increase the available datasets and evaluate the proposed reinforcement method in different geometrical types of sections. The most influential factors on the axial strength were investigated using a feature-selection (FS) method within a multi-layer perceptron (MLP) algorithm. The MLP algorithm was developed by particle swarm optimization (PSO) and FEM results as input. In terms of accuracy evaluation, some of the rolling criteria including results showed that geometrical parameters have almost the same contribution in compression capacity and displacement of the specimens. According to the performance evaluation indexes, the best model was detected and specified in the paper and optimised by tuning other parameters of the algorithm. As a result, the normalised ultimate load and displacement were predicted successfully

Should the first degree relatives of type 2 diabetic patients with isolated impaired fasting glucose be considered for a diabetes primary prevention program?

Background: The aim of this study is to investigate the need for diabetes primary prevention program in isolated impaired fasting glucose (i-IFG) of the first degree relatives of type 2 diabetics. Methods: In a cross sectional study, 793 individuals with prediabetes [543 with i-IFG and 250 with isolated impaired glucose tolerance (i-IGT)] who were the first degree relatives of type 2 diabetic patients, were enrolled. Isolated IFG was considered as fasting plasma glucose between 100-125 mg/dl and 2 hour plasma glucose < 140 mg/dl and isolated IGT as FPG < 100 mg/dl and 2 hour plasma glucose between 140-199 mg/dl during an overnight fasting 75 g oral glucose tolerance test. Mean of the age, weight, waist circumference, body mass index, systolic and diastolic blood pressure, plasma glucose, HbA1C, and lipid profile were compared between two groups (i-IFG and i-IGT). The prevalence of cardiometabolic risk factors (BMI ≥ 25 kg/m2, hypertension, cholesterol ≥ 200 mg/dl, LDL-C ≥ 100 mg/dl, HDL-C ≤ 40 mg/dl, and triglyceride ≥ 150 mg/dl) adjusted by age, sex and BMI were compared. Results: The prevalence of cardiometabolic risk factors is higher in i-IFG group than i-IGT. The mean level of LDL-C is significantly higher in i-IFG than i-IGT group. Conclusions: First degree relatives of T2DM with isolated impaired fasting glucose should probably be included in the primary preventive program for diabetes. However, longitudinal cohort study is required to show high progression of i-IFG to T2DM