Lipoxin A4 attenuates MSU-crystal-induced NLRP3 inflammasome activation through suppressing Nrf2 thereby increasing TXNRD2

Gout is a common inflammatory disease. The activation of NLRP3 inflammasome induced by monosodium urate (MSU) crystals has a critical role in gout, and its prevention is beneficial for patients. Lipoxin A4 (LXA4) is an endogenous lipoxygenase-derived eicosanoid mediator with powerful anti-inflammatory properties. However, whether LXA4 can suppress NLRP3 inflammasome activation induced by MSU crystals remains unclear. This study aimed to investigate the protective effect of LXA4 on MSU-crystal-induced NLRP3 inflammasome activation and its underlying molecular mechanisms. We found that LXA4 inhibited MSU-crystal-induced NLRP3 inflammasome activation, interleukin (IL)-1β maturation, and pyroptosis. More specifically, LXA4 suppressed the assembly of the NLRP3 inflammasome, including oligomerization and speck formation of ASC, and ASC-NLRP3 interaction. Furthermore, LXA4 suppressed oxidative stress, the upstream events for NLRP3 inflammasome activation, as evidenced by the fact that LXA4 eliminated total reactive oxygen species (ROS) generation and alleviated nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activation and mitochondrial dysfunction. However, LXA4 also depressed the Nrf2 activation, a critical molecule in the antioxidant pathway, and then exerted an inhibitory impact on Klf9 expression and promotional impact on TXNRD2 expression, two molecules located downstream of Nrf2 in sequence. Knockdown of TXNRD2 reversed the LXA4-induced depression of ROS and NLRP3 inflammasome. Moreover, LXA4 alleviated joint inflammation and decreased the production of cleaved caspase-1 and matured IL-1β in gouty arthritis rats. Taken together, our findings demonstrate that LXA4 can attenuate MSU-crystal-induced NLRP3 inflammasome activation, probably through suppressing Nrf2 activation to increase TXNRD2 expression. The present study highlights the potential of LXA4 as an attractive new gout treatment candidate

Experimental Study on Single Corner Cold Bending Mechanical Response of Laminated of PVB Interlayer Tempered Glass Panes and the Coupling Effect with Load

The cold bending method is a type of curved glass curtain wall construction method that has been used in practical engineering for a short time. It has the advantages of simple operation, high efficiency and low cost. However, the mechanical response and properties of glass panes caused by cold bending have not been solved effectively. To study the mechanical response and the properties of cold formed laminated tempered glass panes after applying with a wind load, cold bending and load tests of 9 laminated tempered glass panes were conducted by the orthogonal experimental design method. The effects of cold bending curvature, glass pane thickness and interlayer thickness were considered. In this paper, the response law of cold bending stress to the curvature and the relationship among the influencing factors were analyzed. The variation process of stress, the deflection of cold-formed glass panes under uniform load and the characteristics affected by cold-formed stress and deformation were studied. The results show that the cold bending stress is distributed in a saddle shape, and the curvature has the greatest influence on the cold bending stress, followed by the thickness of the glass panes. The influence of the interlayer thickness is small. The maximum stress appears near the corner of the short side direction adjacent to the cold bending corner. The cold bending stress increases linearly with increasing cold bending curvature. The cold bending stress and deformation have little effect on the change process of the later stage load effect

An Improved Weighting Method of Time-Lag-Ensemble Averaging for Hourly Precipitation Forecasts and Its Application in a Typhoon-Induced Heavy Rainfall Event

Heavy rainfall events often cause great societal and economic impacts. The prediction ability of traditional extrapolation techniques decreases rapidly with the increase in the lead time. Moreover, deficiencies of high-resolution numerical models and high-frequency data assimilation will increase the prediction uncertainty. To address these shortcomings, based on the hourly precipitation prediction of Global/Regional Assimilation and Prediction System-Cycle of Hourly Assimilation and Forecast (GRAPES-CHAF) and Shanghai Meteorological Service-WRF ADAS Rapid Refresh System (SMS-WARR), we present an improved weighting method of time-lag-ensemble averaging for hourly precipitation forecast which gives more weight to heavy rainfall and can quickly select the optimal ensemble members for forecasting. In addition, by using the cross-magnitude weight (CMW) method, mean absolute error (MAE), root mean square error (RMSE) and correlation coefficient (CC), the verification results of hourly precipitation forecast for next six hours in Hunan Province during the 2019 typhoon Bailu case and heavy rainfall events from April to September in 2020 show that the revised forecast method can more accurately capture the characteristics of the hourly short-range precipitation forecast and improve the forecast accuracy and the probability of detection of heavy rainfall

GhKT2: a novel K⁺ transporter gene in cotton (Gossypium hirsutum)

Potassium is an essential nutrient for plant growth and productivity of crops. K+ transporters are important for K+ uptake and transport in plants. However, information on the function of K+ transporters and K+ channels in cotton is limited. The KT/KUP/HAK protein family is essential for a variety of physiological processes in plants, including nutrient acquisition and regulation of development. This study, identified a K+ transporter gene, GhKT2, expressed in the roots of cotton (Gossypium hirsutum) cv. Liaomian17. The deduced transcript of GhKT2 is highly homologous to Cluster II of KUP/HAK/KT K+ transporters and is predicted to contain 11 transmembrane domains. GhKT2 has been localized to the plasma membrane, and its transcripts were detected in roots, stems, leaves and shoot apices of cotton seedlings. Consistently, b-glucuronidase (GUS) expression driven by the GhKT2 promoter could be detected in roots, mesophyll cells, and leaf veins in transgenic Arabidopsis. In addition, the expression of GhKT2 was induced by low K+ stress in cotton roots and pGhKT2::GUS-transgenic Arabidopsis seedlings. The GhKT2-overexpression Arabidopsis lines plants were larger and showed greater K+ accumulation than the wild type (WT) regardless of K+ concentration supplied. The net K+ influx rate, measured by the noninvasive micro-test technique, in root meristem zone of GhKT2-transgenic Arabidopsis lines was significantly greater than that of WT. Taken together, this evidence indicates that GhKT2 may participate in K+ acquisition from low or high external K+, as well as K+ transport and distribution in plants

Two Wrongs Don’t Make a Right: Combating Confirmation Bias in Learning with Label Noise

Noisy labels damage the performance of deep networks. For robust learning, a prominent two-stage pipeline alternates between eliminating possible incorrect labels and semi-supervised training. However, discarding part of noisy labels could result in a loss of information, especially when the corruption has a dependency on data, e.g., class-dependent or instance-dependent. Moreover, from the training dynamics of a representative two-stage method DivideMix, we identify the domination of confirmation bias: pseudo-labels fail to correct a considerable amount of noisy labels, and consequently, the errors accumulate. To sufficiently exploit information from noisy labels and mitigate wrong corrections, we propose Robust Label Refurbishment (Robust LR)—a new hybrid method that integrates pseudo-labeling and confidence estimation techniques to refurbish noisy labels. We show that our method successfully alleviates the damage of both label noise and confirmation bias. As a result, it achieves state-of-the-art performance across datasets and noise types, namely CIFAR under different levels of synthetic noise and mini-WebVision and ANIMAL-10N with real-world noise

Towards Activity Recognition through Multidimensional Mobile Data Fusion with a Smartphone and Deep Learning

The field of activity recognition has evolved relatively early and has attracted countless researchers. With the continuous development of science and technology, people’s research on human activity recognition is also deepening and becoming richer. Nowadays, whether it is medicine, education, sports, or smart home, various fields have developed a strong interest in activity recognition, and a series of research results have also been put into people’s real production and life. Nowadays, smart phones have become quite popular, and the technology is becoming more and more mature, and various sensors have emerged at the historic moment, so the related research on activity recognition based on mobile phone sensors has its necessity and possibility. This article will use an Android smartphone to collect the data of six basic behaviors of human, which are walking, running, standing, sitting, going upstairs, and going downstairs, through its acceleration sensor, and use the classic model of deep learning CNN (convolutional neural network) to fuse those multidimensional mobile data, using TensorFlow for model training and test evaluation. The generated model is finally transplanted to an Android phone to complete the mobile-end activity recognition system

A novel silsesquioxanes modified electrospun composite fibrous separator by in-situ crosslinking method for lithium-ion batteries

Microporous electrospun PVDF-HFP nonwoven separators have advantages of higher porosities and better wettabilities compared with conventional polyolefin, but suffer from low mechanical strength and excessive swelling in electrolyte. To enhance the mechanical properties, thermal and dimensional stabilities as well as electrochemical performance of electrospun separators, cross-linked membranes covalently integrated with hybrid silsesquioxane components were fabricated by in-situ crosslinking method, obtaining armor-like shell structure coated on PVDF-HFP fibers. The silsesquioxanes crosslinked PVDF-HFP fibers separator (SQ-PFF) exhibits excellent tensile and puncture strength, superior thermal and dimensional stabilities. Besides, the SQ-PFF prepared cells revealed remarkable discharge capacity and excellent cycling performance ascribing to the high lithium-ion conductivity and the enhanced cross-linked structure. (C) 2019 Elsevier B.V. All rights reserved

Fluid Properties and Genesis of Dolomites in the Devonian Guanwushan Formation of Upper Yangtze Platform, SW China

The Guanwushan Formation (GWSF) of Devonian dolomite are extensively developed in the northwest of Sichuan Basin in the Upper Yangtze region, but the properties of dolomitization fluid and the geneses are still unclear. Three types of dolomites can be divided by petrological characteristics: the fine-microcrystalline dolomites (FMD), the fine crystalline dolomites (FCD) and the medium crystalline dolomites (MCD). The order degree of these three types of dolomites increased in turn, and they all showed dark cathodoluminescence (CL) luminescence. The total amount of Rare Earth Elements (∑REE) of the dolomite was low, while the dolomite enriched with light REE and lacking heavy REE presented a distribution pattern consistent with that of limestone. The weak negative anomalies of the Ce and Eu indicated that the dolomites were formed in a weak redox environment with relatively low temperature. The dolomitization fluids were inherited from the original seawater. The respective δ13CPDB values of the three types of dolomites varied a little, indicating that they were not affected by the biological effects. Specifically, the δ18OPDB values of the FMD and FCD dolomites were higher than that of the limestone, indicating that the dolomitization fluid was influenced by evaporation at the penecontemporaneous stage. The interpretations were also supported by the 87Sr/86Sr ratios, as the 87Sr/86Sr ratios of FMD comparable to the Middle Devonian seawater. The δ18OPDB value of the MCD dolomite was lower than that of the limestone. It also showed poor automorphic extent, which clarified that the dolomite experienced more intense dolomitization in greater burial depth and at higher temperatures

The Carbonate Platform Model and Reservoirs’ Origins of the Callovian-Oxfordian Stage in the Amu Darya Basin, Turkmenistan

The Calloviane-Oxfordian carbonates in the northeastern Amu Darya Basin of southeastern Turkmenistan are composed of medium- to thick-bedded, mostly grainy limestones with various skeletal (bivalves, brachiopods, echinoderms, foraminifera, corals, and sponge) and non-skeletal grains (intraclasts, ooids and peloids). Two facies zones, six standard facies belts and some microfacies types were recognized, and sedimentary model “carbonate ramp-rimmed platform” was proposed and established that can be compared with the classical carbonate sedimentary models. In this model, favorable reservoirs not only developed in the intraplatform shoal of open platform, or reef and shoal on the platform margin, but also in the patch reefs, shoal and mound facies on the upper slope. The reservoir’s pore space is dominated by intergranular and intragranular pores and fissure-pore reservoirs exist with medium porosity and medium to low permeability. Sedimentary facies and diagenetic dissolution are the key controlling factors for the development of high-quality reservoirs

Hydrodynamic delivery of IL-28B (IFN-λ3) gene ameliorates lung inflammation induced by cigarette smoke exposure in mice

Cigarette smoke (CS) is the principal cause of pulmonary inflammatory response. IL-28 (IFN-λ) is a novel group of class II cytokines targeting the epithelial cells and IL-28 responses prominent in lungs can exert important immunomodulatory effects. We tested the hypothesis that IL-28B may modulate the lung inflammation induced by CS. Groups of mice were exposed to CS two times per day for 11 consecutive days. CS exposure induced lymphocyte, neutrophil and macrophage infiltration and inflammatory cytokine (IL-1β, tumor necrosis factor-α (TNF)-α, IL-17, and IL-4) in the airways. More importantly, all these CS-induced pathogenic changes were significantly inhibited by hydrodynamic delivery of plasmid DNA encoding mouse IL-28B. Thus, our results suggest that IL-28 cytokines are beneficial for the suppression of CS-mediated airway inflammation and may be a therapeutic target in CS-related diseases