Salt stress can significantly affect plant growth and agricultural productivity. Receptor-like kinases (RLKs) are believed to play essential roles in plant growth, development, and responses to ...abiotic stresses. Here, we identify a receptor-like cytoplasmic kinase, salt tolerance receptor-like cytoplasmic kinase 1 (STRK1), from rice (Oryza sativa) that positively regulates salt and oxidative stress tolerance. Our results show that STRK1 anchors and interacts with CatC at the plasma membrane via palmitoylation. CatC is phosphorylated mainly at Tyr-210 and is activated by STRK1. The phosphorylation mimic form CatCY210D exhibits higher catalase activity both in vitro and in planta, and salt stress enhances STRK1-mediated tyrosine phosphorylation on CatC. Compared with wild-type plants, STRK1-overexpressing plants exhibited higher catalase activity and lower accumulation of H2O2 as well as higher tolerance to salt and oxidative stress. Our findings demonstrate that STRK1 improves salt and oxidative tolerance by phosphorylating and activating CatC and thereby regulating H2O2 homeostasis. Moreover, overexpression of STRK1 in rice not only improved growth at the seedling stage but also markedly limited the grain yield loss under salt stress conditions. Together, these results offer an opportunity to improve rice grain yield under salt stress.
Abstract
Immune checkpoint genes (ICGs) play critical roles in circumventing self-reactivity and represent a novel target to develop treatments for cancers. However, a comprehensive analysis for the ...expression profile of ICGs at a pan-cancer level and their correlation with patient response to immune checkpoint blockade (ICB) based therapy is still lacking. In this study, we defined three expression patterns of ICGs using a comprehensive survey of RNA-seq data of tumor and immune cells from the functional annotation of the mammalian genome (FANTOM5) project. The correlation between the expression patterns of ICGs and patients survival and response to ICB therapy was investigated. The expression patterns of ICGs were robust across cancers, and upregulation of ICGs was positively correlated with high lymphocyte infiltration and good prognosis. Furthermore, we built a model (ICGe) to predict the response of patients to ICB therapy using five features of ICG expression. A validation scenario of six independent datasets containing data of 261 patients with CTLA-4 and PD-1 blockade immunotherapies demonstrated that ICGe achieved area under the curves of 0.64–0.82 and showed a robust performance and outperformed other mRNA-based predictors. In conclusion, this work revealed expression patterns of ICGs and underlying correlations between ICGs and response to ICB, which helps to understand the mechanisms of ICGs in ICB signal pathways and other anticancer treatments.
The impacts of urbanization on carbon emissions have attracted widespread attention for a long time. Quantitative research on the impacts is of great significance for formulating carbon reduction ...policy. Based on the dynamic panel autoregressive distribution lag (ARDL) model, we systematically study the general and heterogeneous long-run equilibrium relationships, short-run dynamic relationships, impact mechanism and lag effect between urbanization and three carbon emission dimensions in OECD high-income countries during long period. The main empirical results indicate that developed countries tend to have the same negative impacts of urbanization on carbon emissions, although there are differences in the endowments of different countries. The impact is relatively weak, for each percentage point increase in urbanization rate, CO2 emissions per capita decrease by 0.015%, total CO2 emissions decrease by 0.012%, and CO2 emission intensity decrease by 0.009%. All member countries have achieved the decoupling of urbanization and carbon emissions. Urbanization affects carbon emissions by affecting economic growth, energy efficiency, and final energy consumption structure. This paper further reveals the multi-level impacts of urbanization on carbon emissions and provides policy implications of achieving carbon reduction through urbanization's agglomeration effect for government decision makers.
•Estimate the impact of urbanization on carbon emissions based on panel ARDL model.•Analyze general & heterogeneous long-, short-run relationship and impact mechanism.•Urbanization decreases carbon emissions but the impact is weak in OECD countries.•Developed economies have achieved the decoupling of urbanization and CO2 emissions.•Promote urbanization process and exert its scale effect to reduce carbon emissions.
This paper explores the interaction mechanism between urbanization and the ecological environment based on the unique correlation between urbanization and the ecological environment. BISE and ...Savizky-Golay algorithms are combined to establish the time series data, and for the characteristic curves of the EVI time response of the land cover, the spectral angle mapping method is combined with the minimum distance method to form the spectral angle-minimum distance classification method. The application of time series data involves calculating the time and spatial change of urban land cover and analyzing the evolution of urban ecological environment elements. Based on the temporal and spatial consistency test and land cover analysis of urban ecological environment construction, as well as the development of urbanization construction, relevant development paths are proposed. The comprehensive score of new urbanization in the four districts and one city of Hengyang City is concentrated towards 1.6, indicating that the level of economic development and the construction of new urbanization have reached coupling at different levels, respectively.
Objective
To explore the experiences of front‐line nurses combating the coronavirus disease‐2019 epidemic.
Design and Sample
Fifteen front‐line nurses caring for COVID‐19 patients were recruited from ...two hospitals in Wuhan, China from January 26 to February 5, 2020. Data were collected through semi‐structured individual interviews and analyzed using standard qualitative methods.
Results
Four theme categories emerged from the data analysis: (a) “Facing tremendous new challenges and danger”; (b) “Strong pressure because of fear of infection, exhaustion by heavy workloads and stress of nursing seriously ill COVID‐19 patients”; (c) “Strong sense of duty and identity as a healthcare provider”; (d) “Rational understanding of the epidemic—the nurses believed that the epidemic would soon be overcome and would like to receive disaster rescue training.”
Conclusions
Although the intensive rescue work drained front‐line nurses, both physically and emotionally, they showed a spirit of dedication and felt a responsibility to overcome this epidemic. Their experiences provide useful insights into implementing a safer public health emergency rescue system in preparation for future outbreaks of infectious diseases. Specifically, psychological support and humanistic care should be provided to front‐line nurses to maintain their well‐being, and nationwide emergency rescue training and disaster education should be implemented.
Abstract
Electrorefining process has been widely used to separate and purify metals, but it is limited by deposition potential of the metal itself. Here we report in-situ anodic precipitation (IAP), ...a modified electrorefining process, to purify aluminium from contaminants that are more reactive. During IAP, the target metals that are more cathodic than aluminium are oxidized at the anode and forced to precipitate out in a low oxidation state. This strategy is fundamentally based on different solubilities of target metal chlorides in the NaAlCl
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molten salt rather than deposition potential of metals. The results suggest that IAP is able to efficiently and simply separate components of aluminum alloys with fast kinetics and high recovery yields, and it is also a valuable synthetic approach for metal chlorides in low oxidation states.
This study was aimed to estimate the prevalences of chlamydia (CT) and gonococcal (NG) infections and explore risk factors associated with the CT infection among women in Shenzhen, China. We ...collected socio-demographic and clinical data from women (aged 20-60) and determined positivity of CT or NG by nucleic acid amplification test (NAAT) with self-collected urine specimens. We estimated prevalence of CT and NG and determined risk factors associated with CT infection. Among 9,207 participants, 4.12% (95% confidence interval CI, 3.71%-4.53%) tested positive for CT and 0.17% (95% CIs, 0.09%-0.25%) for NG. Factors significantly associated with CT infection included being an ethnic minority (ethnicity other than Han China) (Adjusted odds ratio AOR, 1.9; 95% CI, 1.2-3.0), using methods other than condom for contraception (AOR, 1.5; 95% CI, 1.2-1.8), having a history of adverse pregnancy outcomes (AOR, 1.4; 95% CI, 1.1-1.8), and experiencing reproductive tract symptoms in the past three months (AOR, 1.3; 95% CI, 1.0-1.7). we found that CT infection is prevalent among women in Shenzhen, China and associated with both demographic and behavioral factors. A comprehensive CT screening, surveillance and treatment programme targeting this population is warranted.
Heart failure creates a leading public health burden worldwide and cardiac fibrosis is a hallmark of pathological cardiac remodeling which was found in HF patients. In this study, we detected the ...expression of 9 candidate miRNAs in the plasma exosome samples from 31 HF patients, and found the level of miR-21, miR-425 and miR-744 was altered. The downregulation of miR-425 and miR-744 was also found in angiotensin II treated cardiac fibroblasts. Through functional study, we identified that the reduction of miR-425 and miR-744 relates to overexpression of collagen 1 and α-SMA, which result in fibrogenesis of cardiac fibroblasts. Conversely, overexpression of miR-425 or miR-744 in cultured cardiac fibroblasts significantly abrogates angiotensin induced collagen formation and fibrogenesis. Finally, we confirmed that TGFβ1 is a direct target of miR-425 and miR-744 by dual luciferase assay and immunoblotting. Our data demonstrate that miR-425 and miR-744 function as negative regulators of cardiac fibrosis by suppression TGFβ1 expression, and miR-425 and miR-744 level in the plasma exosomes has the potential to be a biomarker to predict cardiac fibrosis and heart failure.
In imbalanced network traffic, malicious cyber-attacks can often hide in large amounts of normal data. It exhibits a high degree of stealth and obfuscation in cyberspace, making it difficult for ...Network Intrusion Detection System(NIDS) to ensure the accuracy and timeliness of detection. This paper researches machine learning and deep learning for intrusion detection in imbalanced network traffic. It proposes a novel Difficult Set Sampling Technique(DSSTE) algorithm to tackle the class imbalance problem. First, use the Edited Nearest Neighbor(ENN) algorithm to divide the imbalanced training set into the difficult set and the easy set. Next, use the KMeans algorithm to compress the majority samples in the difficult set to reduce the majority. Zoom in and out the minority samples' continuous attributes in the difficult set synthesize new samples to increase the minority number. Finally, the easy set, the compressed set of majority in the difficult, and the minority in the difficult set are combined with its augmentation samples to make up a new training set. The algorithm reduces the imbalance of the original training set and provides targeted data augment for the minority class that needs to learn. It enables the classifier to learn the differences in the training stage better and improve classification performance. To verify the proposed method, we conduct experiments on the classic intrusion dataset NSL-KDD and the newer and comprehensive intrusion dataset CSE-CIC-IDS2018. We use classical classification models: random forest(RF), Support Vector Machine(SVM), XGBoost, Long and Short-term Memory(LSTM), AlexNet, Mini-VGGNet. We compare the other 24 methods; the experimental results demonstrate that our proposed DSSTE algorithm outperforms the other methods.
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