Hexokinase-2-Linked Glycolytic Overload and Unscheduled Glycolysis—Driver of Insulin Resistance and Development of Vascular Complications of Diabetes

The recent discovery of the glucose-induced stabilization of hexokinase-2 (HK2) to proteolysis in cell dysfunction in model hyperglycemia has revealed a likely key initiating factor contributing to the development of insulin resistance and vascular complications in diabetes. Consequently, the increased flux of glucose metabolism without a change in the expression and activity of glycolytic enzymes produces a wave of increased glycolytic intermediates driving mitochondrial dysfunction and increased reactive oxygen species (ROS) formation, the activation of hexosamine and protein kinase C pathways, the increased formation of methylglyoxal-producing dicarbonyl stress, and the activation of the unfolded protein response. This is called HK2-linked glycolytic overload and unscheduled glycolysis. The conditions required to sustain this are GLUT1 and/or GLUT3 glucose uptake and the expression of HK2. A metabolic biomarker of its occurrence is the abnormally increased deposition of glycogen, which is produced by metabolic channeling when HK2 becomes detached from mitochondria. These conditions and metabolic consequences are found in the vasculature, kidneys, retina, peripheral nerves, and early-stage embryo development in diabetes and likely sustain the development of diabetic vascular complications and embryopathy. In insulin resistance, HK2-linked unscheduled glycolysis may also be established in skeletal muscle and adipose tissue. This may explain the increased glucose disposal by skeletal uptake in the fasting phase in patients with type 2 diabetes mellitus, compared to healthy controls, and the presence of insulin resistance in patients with type 1 diabetes mellitus. Importantly, glyoxalase 1 inducer—trans-resveratrol and hesperetin in combination (tRES-HESP)—corrected HK2-linked glycolytic overload and unscheduled glycolysis and reversed insulin resistance and improved vascular inflammation in overweight and obese subjects in clinical trial. Further studies are now required to evaluate tRES-HESP for the prevention and reversal of early-stage type 2 diabetes and for the treatment of the vascular complications of diabetes.     

Enhanced Boiling of Methanol on Copper Coated Surface

This paper presents an experimental investigation on nucleate pool boiling of saturated methanol on uncoated as well as copper‐coated mild steel heating tubes of various thicknesses at atmospheric and subatmospheric pressures. It also includes the effect of heat flux, pressure and coating thickness on the boiling heat transfer coefficient of coated tube surfaces. Heat flux was progressively increased from 15,670.20 to 43,151.57 W/m² in six steps and pressure from 23.02 to 98.68 kN/m² in five steps. Boiling characteristics on such surfaces are compared with those on uncoated ones. Also, a criterion for enhanced boiling of methanol on copper‐coated tubes is described.     

Growth and characterization of Ni:DLC composite films using pulsed laser deposition technique

The structure and surface morphology of Ni-incorporated diamond like carbon (Ni:DLC) films have been investigated. These films were deposited on Si substrates using pulsed laser deposition (PLD) technique. A KrF Excimer laser (λ = 248 nm) was used for co-ablation from multi component Ni–graphite target. The concentration of Ni was varied by ablating the Ni part of the target with various numbers of laser pulses. The SEM and AFM analysis reveals that the surface is composed of segregates of Ni which increases with the increase in Ni content during the growth process. The structural investigations by XRD and Raman spectroscopy provided information about the orientation of the incorporated constituent and the ordering of the carbon species. Maximum height of the nano structures which were observed on the surface was ∼50 nm. The G-peak of the graphite was shifted towards higher wave number due to enhancement in SP² sites which have been increased due to the increase in the Ni concentration. A small change in the surface roughness ranging from 7.78 nm to 13.1 nm due to increased Ni concentration was also observed.     

An onsite demonstration and validation of LiDAR technology for wind energy resource assessment

The investigation of wind resource at higher heights is very crucial in planning wind power project. Normally, this involves the installation of a high and costly meteorological mast with a cup anemometer and wind vanes. This investigation uses the new ground-based remote-sensing technique Light Detection and Ranging (LiDAR) to investigate the wind resource at higher heights. This paper describes the LiDAR technology principle and examines the potential of LiDAR measurement to estimate the wind resource at higher heights by conducting a measurement campaign at Tamil Nadu, India. The wind statistics were determined using the 10?min average time-series wind data monitored by ZephIR LiDAR. These include the Weibull parameters, daily mean wind speed, wind power density, wind energy density, vertical wind speed profile and capacity factor. The investigation reveals that the vertical wind speed profile measured from the LiDAR system has approximate closer values to the standard meteorological measurement.     

Anemia prevalence and risk factors in pregnant women in an urban area of Pakistan

BACKGROUND: Anemia affects almost two-thirds of pregnant women in developing countries and contributes to maternal morbidity and mortality and to low birthweight. OBJECTIVE: To determine the prevalence of anemia and the dietary and socioeconomic factors associated with anemia in pregnant women living in an urban community setting in Hyderabad, Pakistan. METHODS: This was a prospective, observational study of 1,369 pregnant women enrolled at 20 to 26 weeks of gestation and followed to 6 weeks postpartum. A blood sample was obtained at enrollment to determine hemoglobin levels. Information on nutritional knowledge, attitudes, and practice and dietary history regarding usual food intake before and during pregnancy were obtained by trained interviewers within 1 week of enrollment. RESULTS: The prevalence of anemia (defined by the World Health Organization as hemoglobin < 11.0 g/dL) in these subjects was 90.5%; of these, 75.0% had mild anemia (hemoglobin from 9.0 to 10.9 g/dL) and 14.8% had moderate anemia (hemoglobin from 7.0 to 8.9 g/dL). Only 0.7% were severely anemic (hemoglobin < 7.0 g/ dL). Nonanemic women were significantly taller, weighed more, and had a higher body mass index. Multivariate analysis after adjustment for education, pregnancy history, iron supplementation, and height showed that drinking more than three cups of tea per day before pregnancy (adjusted prevalence odds ratio [aPOR], 3.2; 95% confidence interval [CI], 1.3 to 8.0), consumption of clay or dirt during pregnancy (aPOR, 3.7; 95% CI, 1.1 to 12.3), and never consuming eggs or consuming eggs less than twice a week during pregnancy (aPOR, 1.7; 95% CI, 1.1 to 2.5) were significantly associated with anemia. Consumption of red meat less than twice a week prior to pregnancy was marginally associated with anemia (aPOR, 1.2; 95% CI, 0.8 to 1.8) but was significantly associated with lower mean hemoglobin concentrations (9.9 vs. 10.0 g/dL, p = .05) during the study period. A subanalysis excluding women with mild anemia found similar associations to those of the main model, albeit even stronger. CONCLUSIONS: A high percentage of women at 20 to 26 weeks of pregnancy had mild to moderate anemia. Pica, tea consumption, and low intake of eggs and red meat were associated with anemia. Women of childbearing age should be provided nutritional education regarding food sources of iron, especially prior to becoming pregnant, and taught how food choices can either enhance or interfere with iron absorption.     

Hydrolytic degradation of poly(l‐lactic acid)/poly(methyl methacrylate) blends

The hydrolytic degradation of poly(l ‐lactic acid)/poly(methyl methacrylate) (PLLA/PMMA) blends was carried out by the immersion of thin films in buffer solutions (pH = 7.24) in a shaking water bath at 60 °C for 38 days. The PLA/PMMA blends (0/100; 30/70; 50/50; 70/30; 100/0) were obtained by melt blending using a Brabender internal mixer and shaped into thin films of about 150 µm in thickness. Considering that PMMA does not undergo hydrolytic degradation, that of PLLA was followed via evolution of PLA molecular weight (recorded by size exclusion chromatography), thermal parameters (differential scanning calorimetry (DSC)) and morphology of the films (scanning transmission electron microscopy). The results reveal a completely different degradation pathway of the blends depending on the polymethacrylate/polyester weight ratio. DSC data suggest that, during hydrolysis at higher PMMA content, the polyester amorphous chains, more sensitive to water, are degraded before being able to crystallize, while at higher PLLA content, the crystallization is favoured leading to a sample more resistant to hydrolysis. In other words, and quite unexpectedly, increasing the content of water‐sensitive PLLA in the PLLA/PMMA blends does not mean de facto faster hydrolytic degradation of the resulting materials. © 2018 Society of Chemical Industry     

NS-2 based simulation framework for cognitive radio sensor networks

In this paper, we propose a simulation model for cognitive radio sensor networks (CRSNs) which is an attempt to combine the useful properties of wireless sensor networks and cognitive radio networks. The existing simulation models for cognitive radios cannot be extended for this purpose as they do not consider the strict energy constraint in wireless sensor networks. Our proposed model considers the limited energy available for wireless sensor nodes that constrain the spectrum sensing process—an unavoidable operation in cognitive radios. Our model has been thoroughly tested by performing experiments in different scenarios of CRSNs. The results generated by the model have been found accurate which can be considered for realization of CRSNs.     

Traffic Queuing Management in the Internet of Things: An Optimized RED Algorithm Based Approach

Congestion control is one of the main obstacles in cyberspace traffic. Overcrowding in internet traffic may cause several problems; such as high packet hold-up, high packet dropping, and low packet output. In the course of data transmission for various applications in the Internet of things, such problems are usually generated relative to the input. To tackle such problems, this paper presents an analytical model using an optimized Random Early Detection (RED) algorithm-based approach for internet traffic management. The validity of the proposed model is checked through extensive simulation-based experiments. An analysis is observed for different functions on internet traffic. Four performance metrics are taken into consideration, namely, the possibility of packet loss, throughput, mean queue length and mean queue delay. Three sets of experiments are observed with varying simulation results. The experiments are thoroughly analyzed and the best packet dropping operation with minimum packet loss is identified using the proposed model.