The NAD(P)H oxidase homolog Nox4 modulates insulin-stimulated generation of H\u3csub\u3e2\u3c/sub\u3e0\u3csub\u3e2\u3c/sub\u3e and plays an integral role in insulin signal transduction

Insulin stimulation of target cells elicits a burst of H2O2 that enhances tyrosine phosphorylation of the insulin receptor and its cellular substrate proteins as well as distal signaling events in the insulin action cascade. The molecular mechanism coupling the insulin receptor with the cellular oxidant-generating apparatus has not been elucidated. Using reverse transcription-PCR and Northern blot analyses, we found that Nox4, a homolog of gp91phox, the phagocytic NAD(P)H oxidase catalytic subunit, is prominently expressed in insulin-sensitive adipose cells. Adenovirus-mediated expression of Nox4 deletion constructs lacking NAD(P)H or FAD/NAD(P)H cofactor binding domains acted in a dominant-negative fashion in differentiated 3T3-L1 adipocytes and attenuated insulin-stimulated H2O2 generation, insulin receptor (IR) and IRS-1 tyrosine phosphorylation, activation of downstream serine kinases, and glucose uptake. Transfection of specific small interfering RNA oligonucleotides reduced Nox4 protein abundance and also inhibited the insulin signaling cascade. Overexpression of Nox4 also significantly reversed the inhibition of insulin-stimulated IR tyrosine phosphorylation induced by coexpression of PTP1B by inhibiting PTP1B catalytic activity. These data suggest that Nox4 provides a novel link between the IR and the generation of cellular reactive oxygen species that enhance insulin signal transduction, at least in part via the oxidative inhibition of cellular protein-tyrosine phosphatases (PTPases), including PTP1B, a PTPase that has been previously implicated in the regulation of insulin action

Reactive uptake coefficients for multiphase reactions determined by a dynamic chamber system

Dynamic flow-through chambers are frequently used to measure gas exchange rates between the atmosphere and biosphere on the Earth's surface such as vegetation and soils. Here, we explore the performance of a dynamic chamber system in determining the uptake coefficient γ of exemplary gases (O3 and SO2) on bulk solid-phase samples. After characterization of the dynamic chamber system, the derived γ is compared with that determined from a coated-wall flow tube system. Our results show that the dynamic chamber system and the flow tube method show a good agreement for γin the range of 10−8 to 10−3. The dynamic chamber technique can be used for liquid samples and real atmospheric aerosol samples without complicated coating procedures, which complements the existing techniques in atmospheric kinetic studies.</p

Long-term trends and drivers of aerosol pH in eastern China

Aerosol acidity plays a key role in regulating the chemistry and toxicity of atmospheric aerosol particles. The trend of aerosol pH and its drivers is crucial in understanding the multiphase formation pathways of aerosols. Here, we reported the first trend analysis of aerosol pH from 2011 to 2019 in eastern China, calculated with the ISORROPIA model based on observed gas and aerosol compositions. The implementation of the Air Pollution Prevention and Control Action Plan led to −35.8 %, −37.6 %, −9.6 %, −81.0 % and 1.2 % changes of PM2.5, SO42-, NHx, non-volatile cations (NVCs) and NO3- in the Yangtze River Delta (YRD) region during this period. Different from the drastic changes of aerosol compositions due to the implementation of the Air Pollution Prevention and Control Action Plan, aerosol pH showed a minor change of −0.24 over the 9 years. Besides the multiphase buffer effect, the opposite effects from the changes of SO42- and non-volatile cations played key roles in determining this minor pH trend, contributing to a change of +0.38 and −0.35, respectively. Seasonal variations in aerosol pH were mainly driven by the temperature, while the diurnal variations were driven by both temperature and relative humidity. In the future, SO2, NOx and NH3 emissions are expected to be further reduced by 86.9 %, 74.9 % and 41.7 % in 2050 according to the best health effect pollution control scenario (SSP1-26-BHE). The corresponding aerosol pH in eastern China is estimated to increase by ∼0.19, resulting in 0.04 less NO3- and 0.12 less NH4+ partitioning ratios, which suggests that NH3 and NOx emission controls are effective in mitigating haze pollution in eastern China.</p

Tyrosine cross-linking of extracellular matrix is catalyzed by Duox, a multidomain oxidase/peroxidase with homology to the phagocyte oxidase subunit gp91phox

High molecular weight homologues of gp91phox, the superoxide-generating subunit of phagocyte nicotinamide adenine dinucleotide phosphate (NADPH)-oxidase, have been identified in human (h) and Caenorhabditis elegans (Ce), and are termed Duox for “dual oxidase” because they have both a peroxidase homology domain and a gp91phox domain. A topology model predicts that the enzyme will utilize cytosolic NADPH to generate reactive oxygen, but the function of the ecto peroxidase domain was unknown. Ce-Duox1 is expressed in hypodermal cells underlying the cuticle of larval animals. To investigate function, RNA interference (RNAi) was carried out in C. elegans. RNAi animals showed complex phenotypes similar to those described previously in mutations in collagen biosynthesis that are known to affect the cuticle, an extracellular matrix. Electron micrographs showed gross abnormalities in the cuticle of RNAi animals. In cuticle, collagen and other proteins are cross-linked via di- and trityrosine linkages, and these linkages were absent in RNAi animals. The expressed peroxidase domains of both Ce-Duox1 and h-Duox showed peroxidase activity and catalyzed cross-linking of free tyrosine ethyl ester. Thus, Ce-Duox catalyzes the cross-linking of tyrosine residues involved in the stabilization of cuticular extracellular matrix

Localization Algorithms of Underwater Wireless Sensor Networks: A Survey

In Underwater Wireless Sensor Networks (UWSNs), localization is one of most important technologies since it plays a critical role in many applications. Motivated by widespread adoption of localization, in this paper, we present a comprehensive survey of localization algorithms. First, we classify localization algorithms into three categories based on sensor nodes’ mobility: stationary localization algorithms, mobile localization algorithms and hybrid localization algorithms. Moreover, we compare the localization algorithms in detail and analyze future research directions of localization algorithms in UWSNs

Chemokines and Chemokine Receptors in Multiple Sclerosis

Multiple sclerosis is an autoimmune disease with classical traits of demyelination, axonal damage, and neurodegeneration. The migration of autoimmune T cells and macrophages from blood to central nervous system as well as the destruction of blood brain barrier are thought to be the major processes in the development of this disease. Chemokines, which are small peptide mediators, can attract pathogenic cells to the sites of inflammation. Each helper T cell subset expresses different chemokine receptors so as to exert their different functions in the pathogenesis of MS. Recently published results have shown that the levels of some chemokines and chemokine receptors are increased in blood and cerebrospinal fluid of MS patients. This review describes the advanced researches on the role of chemokines and chemokine receptors in the development of MS and discusses the potential therapy of this disease targeting the chemokine network

Advances in the Welding of Aluminum Matrix Composites: A New Open Special Issue in Materials

&ldquo;Advances in the Welding of Aluminum Matrix Composites&rdquo; is a new open Special Issue of Materials that aims to publish original research and review papers on new scientific and applied research and to make great contributions to advances in the field of welding aluminum matrix composites as well as to the related synthesis, fundamentals, characterization, and application of these materials [...

Grain Knowledge Graph Representation Learning: A New Paradigm for Microstructure-Property Prediction

The mesoscopic structure significantly affects the properties of polycrystalline materials. Current artificial-based microstructure-performance analyses are expensive and require rich expert knowledge. Recently, some machine learning models have been used to predict the properties of polycrystalline materials. However, they cannot capture the complex interactive relationship between the grains in the microstructure, which is a crucial factor affecting the material&rsquo;s macroscopic properties. Here, we propose a grain knowledge graph representation learning method. First, based on the polycrystalline structure, an advanced digital representation of the knowledge graph is constructed, embedding ingenious knowledge while completely restoring the polycrystalline structure. Then, a heterogeneous grain graph attention model (HGGAT) is proposed to realize the effective high-order feature embedding of the microstructure and to mine the relationship between the structure and the material properties. Through benchmarking with other machine learning methods on magnesium alloy datasets, HGGAT consistently demonstrates superior accuracy on different performance labels. The experiment shows the rationality and validity of the grain knowledge graph representation and the feasibility of this work to predict the material&rsquo;s structural characteristics