Notes

ORF3a of SARS-CoV-2 stimulates lysosomal exocytosis-mediated popular evacuation.
It is indicated by ratio of iron ions contributions in B sites (octahedral) and A sites (tetrahedral) in magnetite spinel structure, which is much lower than 2.0 (theoretical value for stoichiometric magnetite). The characteristic feature of TMPs collected from the vicinity of old metallurgical plants (>180 years) was the high contribution of surface components probably related to the surface oxidation/maghemitization. We found that, TMPs can be easily differentiated from geogenic magnetite based on their magnetic parameters. The TMP produced by the iron and steel metallurgy had relatively narrow ranges of magnetic parameters (saturation ratio Mrs/Ms, less then 0.15, coercivity ratio Bcr/Bc 2.5-6.0 and saturation to susceptibility ratio Mrs/χ 3.5-15). These magnetic parameters may be indicative for TMPs emitted by these pollution sources and helpful in the study of historical pollution sources in topsoil in urban and post-industrial areas.Ureolytic microorganisms, a kind of microorganism which can secrete urease and decompose urea, have great potential in remediation of soil heavy metals based on microbial induced carbonate precipitation. However, the horizontal and vertical distribution of ureolytic microbial community in heavy metals contaminated soils is poorly understood. In this study, urease genes in agricultural soils surrounding tailings were first investigated using metagenomic in two dimensions heavy metal pollution (Low-L, Middle-M, High-H) and soil depth (0-20 cm, 20-40 cm, 40-60 cm, 60-80 cm, 80-100 cm). Results showed that the effect of heavy metal concentration on ureolytic microorganisms was indeed significant, while the changes of ureolytic microorganisms with increasing soil depth varied in the vertical direction at the same level of heavy metal contamination. H site had the highest diversity of ureolytic microorganisms except for the topsoil. And at the same heavy metal contamination level, the ureolytic microbial diversity was lower in deeper soils. Proteobacteria, Actinobacteria and Thaumarchaeota (Archaea) were the dominant phyla of ureolytic microorganisms in all three sites, accounting for more than 80% of the total. However, the respond to the heavy metal concentrations of three phyla were different, which were increasing, decreasing and essentially unchanged, respectively. https://www.selleckchem.com/products/ON-01910.html Besides, other environmental factors such as SOM and pH had different effects on ureolytic microorganisms, with Proteobacteria being positively correlated and Actinobacteria being the opposite. Another phenomenon was that Actinobacteria and Verrucomicrobia were biomarkers of group L, which could significantly explain the difference with the other two sites. These results provided valuable information for further research on the response mechanism and remediation of heavy metal pollution by ureolytic microbial system.Coastal soil is an important land reserve that may be used to alleviate the shortage of cultivated land; however, this soil is stressed by saline conditions and nutrient deficiency. Biochar offers the potential to reclaim coastal soil, but the response of plant growth to biochar addition in salt-affected soil is species-dependent. In this study, the response of ice plant (Mesembryanthemum crystallinum L.), an economically valuable halophyte that grows in the coastal soil of the Yellow River Delta, to wood chip biochar (WBC) either alone or in combination with chemical fertilizer was investigated using a 90-day pot experiment. The WBC enhanced the growth of ice plants in the coastal soil, but combining it with chemical fertilizer did not increase its effect. The nutritional quality of the plants was improved by the addition of WBC, regardless of whether chemical fertilizer was applied; moreover, WBC amendment enhanced photosynthesis and reduced the oxidative stress of the plants. The ameliorated soil properties (e.g., soil organic matter and water holding capacity) and increased contents of available macronutrients (e.g., P and K) and micronutrients (e.g., Mg, Mn, B and Zn) resulting from soil amendment with WBC may have contributed to the enhanced growth and quality of the ice plants. Additionally, in soil modified with WBC, an increased abundance of beneficial taxa (e.g., Erythrobacter, Sphingomonas and Lysobacter) and a shift in the microbial community may also have helped to improve the growth and quality of the ice plants. The results of our study provide useful information for developing a biochar-based technology to use in combination with valuable halophytes to reclaim degraded coastal soil and enhance food security.Soil salinization is an extremely serious land degradation problem in arid and semi-arid regions that hinders the sustainable development of agriculture and food security. Information and research on soil salinity using remote sensing (RS) technology provide a quick and accurate assessment and solutions to address this problem. This study aims to compare the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction and exploration of the potential application of derivatives to RS prediction of salinized soils. It explores the ability of derivatives to be used in the Landsat-8 OLI and Sentinel-2A MSI multispectral data, and it was used as a data source as well as to address the adaptability of salinity prediction on a regional scale. The two-dimensional (2D) and three-dimensional (3D) optimal spectral indices are used to screen the bands that are most sensitive to soil salinity (0-10 cm), and RS data and topographic factors are combined with machine learning to construct a comprehensive soil salinity estimation model based on gray correlation analysis. The results are as follows (1) The optimal spectral index (2D, 3D) can effectively consider possible combinations of the bands between the interaction effects and responding to sensitive bands of soil properties to circumvent the problem of applicability of spectral indices in different regions; (2) Both the Landsat-8 OLI and Sentinel-2A MSI multispectral RS data sources, after the first-order derivative techniques are all processed, show improvements in the prediction accuracy of the model; (3) The best performance/accuracy of the predictive model is for sentinel data under first-order derivatives. This study compared the capabilities of Landsat-8 OLI and Sentinel-2A MSI in RS prediction in finding the potential application of derivatives to RS prediction of salinized soils, with the results providing some theoretical basis and technical guidance for salinized soil prediction and environmental management planning.
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