Auxin may have a positive effect on plants under drought stress. White clover is widely cultivated and often prone to water shortages. In the present study, we investigated the effects of exogenous ...indole - 3-acetic acid (IAA) on growth and physiological changes of white clover under drought stress condition. The contents of endogenous IAA and other hormones including ABA, CTK, JA, GA, IAA, and SA were assayed. Moreover, expressions of auxin-responsive genes, drought-responsive genes and leaf senescence-associated genes were detected in response to exogenous IAA.
Compared to control, drought stress alone significantly diminished stem dry weigh, relative water content (RWC) and total chlorophyll content (Chl). Exogenous IAA treatment significantly increased RWC and Chl, whereas L-AOPP treatment drastically decreased stem dry weight, RWC and Chl under drought stress condition. Additionally, exogenous IAA treatment significantly increased ABA content and JA content, up-regulated expression of auxin responsive genes (GH3.1, GH3.9, IAA8), drought stress responsive genes (bZIP11, DREB2, MYB14, MYB48, WRKY2, WRKY56, WRKY108715 and RD22), and down-regulated expressions of auxin-responding genes (GH3.3, GH3.6, IAA27) and leaf senescence genes (SAG101 and SAG102) in the presence of PEG. Contrarily, L-AOPP treatment significantly reduced contents of ABA, GA3 and JA, down-regulated expressions of GH3.1, GH3.9, IAA8, bZIP11, DREB2, MYB14, MYB48, WRKY2, WRKY56, WRKY108715, ERD and RD22, and up-regulated SAG101 and SAG102.
Exogenous IAA improved drought tolerance of white clover possibly due to endogenous plant hormone concentration changes and modulation of genes involving in drought stress response and leaf senescence. These results provided useful information to understand mechanisms of IAA improved drought tolerance in white clover.
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Protein hotspot residues are key sites that mediate protein-protein interactions. Accurate identification of these residues is essential for understanding the mechanism from protein to function and ...for designing drug targets. Current research has mostly focused on using machine learning methods to predict hot spots from known interface residues, which artificially extract the corresponding features of amino acid residues from sequence, structure, evolution, energy, and other information to train and test machine learning models. The process is cumbersome, time-consuming and laborious to some extent. This paper proposes a novel idea that develops a pre-trained protein sequence embedding model combined with a one-dimensional convolutional neural network, called Embed-1dCNN, to predict protein hotspot residues. In order to obtain large data samples, this work integrates and extracts data from the datasets of ASEdb, BID, SKEMPI and dbMPIKT to generate a new dataset, and adopts the SMOTE algorithm to expand positive samples to form the training set. The experimental results show that the method achieves an F1 score of 0.82 on the test set. Compared with other hot spot prediction methods, our model achieved better prediction performance.
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Smart city construction represents an advanced stage of China's urbanisation process and plays an important role in promoting green economic growth and sustainable development. Propensity score ...matching is combined with the difference-in-difference method to analyse the data of 221 prefecture-level cities in China from 2006 to 2020 to assess the impact of smart city construction on urban green development. We found that smart city construction can significantly contribute to urban green development; this contribution has long-term benefits. Further analysis shows that smart city construction promotes urban green development via industrial structure and green technology innovation and that smart city construction has a significant positive spatial spillover effect, i.e., it promotes urban green development locally while significantly contributing to urban green development in neighbouring regions.
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Recent studies indicate that endothelial Nlrp3 inflammasome is critically involved in the development of cardiovascular complications. However, it remains unknown whether endothelial inflammasome is ...involved in endothelial barrier dysfunction associated with smoking. This study aims to investigate the role of endothelial Nlrp3 inflammasome in nicotine-induced disruption of inter-endothelial tight junctions and consequent endothelial barrier dysfunction. The confocal microscopic analysis demonstrated that mice treated with nicotine exhibited disrupted inter-endothelial tight junctions as shown by decreased ZO-1 and ZO-2 expression in the coronary arterial endothelium, whereas the decreases in ZO-1/2 were prevented by Nlrp3 gene deficiency. In cultured endothelial cells, nicotine caused Nlrp3 inflammasome complex formation and enhances the inflammasome activity as shown by increased cleavage of pro-caspase-1, and interleukin-1β (IL-1β) production. Further, nicotine disrupted tight junction and increased permeability in an endothelial cell monolayer, and this nicotine-induced effect was prevented by silencing of Nlrp3 gene, inhibition of caspase-1, or blockade of high mobility group box 1 (HMGB1). Nicotine increased endothelial cell lysosomal membrane permeability and triggered the lysosomal release of cathepsin B, whereas these events were prevented by pretreating cells with a lysosome stabilizing agent, dexamethasone. Collectively, our data suggest that nicotine enhances cathepsin B-dependent Nlrp3 inflammasome activation and the consequent production of a novel permeability factor HMGB1, which causes disruption of inter-endothelial tight junctions leading to endothelial hyperpermeability. Instigation of endothelial inflammasomes may serve as an important pathogenic mechanism contributing to the early onset of vasculopathy associated with smoking.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Obesity is an important risk factor for exacerbating chronic diseases such as cardiovascular disease and cancer. High serum level of saturated free fatty acids such as palmitate is an important ...contributor for obesity-induced diseases. Here, we examined the contribution of inflammasome activation in vascular cells to free fatty acid-induced endothelial dysfunction and vascular injury in obesity. Our findings demonstrated that high fat diet-induced impairment of vascular integrity and enhanced vascular permeability in the myocardium in mice were significantly attenuated by Nlrp3 gene deletion. In microvascular endothelial cells (MVECs), palmitate markedly induces Nlrp3 inflammasome complex formation leading to caspase-1 activation and IL1β production. By fluorescence microscopy and flow cytometry, we observed that such palmitate-induced Nlrp3 inflammasome activated was accompanied by a reduction in inter-endothelial tight junction proteins ZO-1/ZO-2. Such palmitate-induced decrease of ZO-1/ZO-2 was also correlated with an increase in the permeability of endothelial monolayers treated with palmitates. Moreover, palmitate-induced alterations in ZO-1/ZO-2 or permeability were significantly reversed by an inflammasome activity inhibitor, YVAD, or a high mobility group box 1 (HMGB1) activity inhibitor glycyrrhizin. Lastly, blockade of cathepsin B with Ca-074Me significantly abolished palmitate-induced activation of Nlrp3 inflammasomes, down-regulation of ZO-1/ZO-2, and enhanced permeability in MVECs or their monolayers. Together, these data strongly suggest that activation of endothelial inflammasomes due to increased free fatty acids produces HMGB1, which disrupts inter-endothelial junctions and increases paracellular permeability of endothelium contributing to early onset of endothelial injury during obesity.
Accurate prediction of binding affinity between protein and ligand is a very important step in the field of drug discovery. Although there are many methods based on different assumptions and rules do ...exist, prediction performance of protein-ligand binding affinity is not satisfactory so far. This paper proposes a new cascade graph-based convolutional neural network architecture by dealing with non-Euclidean irregular data. We represent the molecule as a graph, and use a simple linear transformation to deal with the sparsity problem of the one-hot encoding of original data. The first stage adopts ARMA graph convolutional neural network to learn the characteristics of atomic space in the protein-ligand complex. In the second stage, one variant of the MPNN graph convolutional neural network is introduced with chemical bond information and interactive atomic features. Finally, the architecture passes through the global add pool and the fully connected layer, and outputs a constant value as the predicted binding affinity. Experiments on the PDBbind v2016 data set showed that our method is better than most of the current methods. Our method is also comparable to the state-of-the-art method on the data set, and is more intuitive and simple.
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Light Field (LF) imaging empowers many attractive applications by simultaneously recording spatial and angular information of light rays. In order to meet the challenges of LF storage and ...transmission, many view reconstruction-based LF compression methods are put forward. However, occlusion issue and under-exploitation of LF rich structure information limit the view reconstruction qualities, which further influence LF compression efficiency. In order to alleviate these problems, in this paper, we propose a geometry-aware view reconstruction network for LF compression. In our method, only sparsely-sampled LF views are encoded, which are further used as priors to reconstruct the un-sampled LF views at the decoder side. The proposed reconstruction process contains two stages including geometry-aware reconstruction and texture refinement. The geometry-aware reconstruction stage utilizes a multi-stream framework, which can fully explore LF spatial-angular, location and geometry information. The texture refinement stage can adequately fuse such rich LF information to further improve LF reconstruction quality. Comprehensive experimental results validate the superiority of the proposed method. The rate-distortion performance and the perceptual quality of reconstructed views further demonstrate that the proposed method can save more bitrate while increasing LF reconstruction quality.
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Capillary penetration is widely existed in stope leaching, both the rate of liquid wetting ore and flow out of ore are affected by it. Stope leaching is carried out in a high-temperature environment ...when mining minerals with large burial depth. The mechanism of intra-particle liquid capillary penetration mechanisms at high-temperature have not been revealed. In this paper, samples with a size of Φ50 mm × 100 mm were selected for quantitative analysis. The capillary rise behaviour inside samples with different porosity were detected at 30 °C, 40 °C and 50 °C by using magnetic resonance imaging (MRI). In most cases, capillary rise height is underestimated when the outside wetting line is used as an indicator, because the rise height inside the sample is greater. The liquid capillary rise height increased slightly with the temperature, whereas the wetting surface profile remained unchanged. The capillary rise rate increased significantly with porosity, mainly due to the increase of internal effective porosity. The results help to understand the liquid penetration behaviour under high-temperature stope leaching condition, and lay a theoretical foundation for improving the liquid permeability.
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Electronic skin is an important means through which robots can obtain external information. A novel flexible tactile sensor capable of simultaneously detecting the contact position and force was ...proposed in this paper. The tactile sensor had a three-layer structure. The upper layer was a specially designed conductive film based on indium-tin oxide polyethylene terephthalate (ITO-PET), which could be used for detecting contact position. The intermediate layer was a piezoresistive film used as the force-sensitive element. The lower layer was made of fully conductive material such as aluminum foil and was used only for signal output. In order to solve the inconsistencies and nonlinearity of the piezoresistive properties for large areas, a Radial Basis Function (RBF) neural network was used. This includes input, hidden, and output layers. The input layer has three nodes representing position coordinates,
,
, and resistor,
. The output layer has one node representing force,
. A sensor sample was fabricated and experiments of contact position and force detection were performed on the sample. The results showed that the principal function of the tactile sensor was feasible. The sensor sample exhibited good consistency and linearity. The tactile sensor has only five lead wires and can provide the information support necessary for safe human-computer interactions.
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Primary kidney neuroendocrine tumors (NETs) are rare renal malignancies. However, detecting and monitoring neuroendocrine neoplasms remains challenging because of their nonspecific nature. We herein ...present a case involving a 53-year-old woman who experienced episodes of intermittent abdominal pain, dizziness, and nausea for a period of 5 days. Computed tomography urography revealed a small (approximately 19- × 16-mm) nodular shadow in the left kidney. The nodular shadow exhibited slightly lower density than the surrounding tissue as well as enhancement, with a portion protruding into the renal sinus region. Histological and immunohistochemical analyses of the biopsy specimen from the mass indicated a well-differentiated NET. After analysis of this case, we performed a literature review and herein discuss various techniques for imaging and pathological diagnosis of renal NETs. Additionally, we provide insights into the treatment options and prognosis for affected patients. By combining this case study with the existing published literature, we aim to offer a valuable reference for clinicians treatment patients diagnosed with renal NETs.
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