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Due to the COVID-19 outbreak, the Chinese government implemented nationwide traffic restrictions and self-quarantine measures from January 23 to April 8 (in Wuhan), 2020. We estimated how these measures impacted ambient air pollution and the subsequent consequences on health and the health-related economy in 367 Chinese cities. A random forests modeling was used to predict the business-as-usual air pollution concentrations in 2020, after adjusting for the impact of long-term trend and weather conditions. We calculated changes in mortality attributable to reductions in air pollution in early 2020 and health-related economic benefits based on the value of statistical life (VSL). Compared with the business-as-usual scenario, we estimated 1239 (95% CI 844-1578) PM2.5-related deaths were avoided, as were 2777 (95% CI 1565-3995) PM10-related deaths, 1587 (95% CI 98-3104) CO-related deaths, 4711 (95% CI 3649-5781) NO2-related deaths, 215 (95% CI 116-314) O3-related deaths, and 1088 (95% CI 774-1421) SO2-related deaths. Based on the reduction in deaths, economic benefits for in PM2.5, PM10, CO, NO2, O3, and SO2 were 1.22, 2.60, 1.36, 4.05, 0.20, and 0.95 billion USD, respectively. Our findings demonstrate the substantial benefits in human health and health-related costs due to improved urban air quality during the COVID lockdown period in China in early 2020.Ammonia is one of major pollutants in aquatic environment that induces severe stress and toxicity to organisms in aquatic system. The intestine acts a major defense line that protects living organisms from biotic and abiotic stresses. In the current study, we examined the effects of ammonia on intestinal histomorphology, transcriptional levels of intestinal barrier functioning genes and intestinal microbiota of Chinese striped-neck turtle (Mauremys sinensis). Thus, the turtles were placed in water with addition of ammonia at 0 (control), 100, 200 mg L-1 for 30 days. Our findings showed that ammonia reduced the villus length and induced the inflammatory cells appearance. In addition, the epithelial tight junction genes, claudin and zonola occludin significantly downregulated in ammonia exposed groups as compared to control group (P less then 0.05). Similarly, the mRNA expression levels of MUC-2 gene also significantly decreased in ammonia treated groups (P less then 0.05). However, the expression levels of intestinal immune related genes such as IL-10, IL-12, TGF-β1, TNF-α and IFN-γ significantly increased (P less then 0.05). Furthermore, ammonia changed gut microbial diversity variedly. At the phylum levels, Firmicutes increased, whereas Bacteroidota, Desulfobacterota and Synergistota decreased significantly. Likewise, Lachnospiraceae, Bacteroides, Eubacteriaceae, Desulfovibrio, Muribaculaceae, Bilophila, Cloacibacillus, Christensenellaceae, Ruminococcus and Parabacteroides decreased while, Romboutsia and Turicibacter increased in ammonia exposed groups. In conclusion, ammonia at 100 and 200 mg L-1 could alter the intestinal barrier function and change the composition of intestinal microbiota, leading to bad health status in M. sinensis.Cigarette seriously affects human health, and electronic cigarette (e-cigarette), considered as cigarette substitutes, become popular as its contribution to quit smoking. But scientific evidence about the absolute safety of e-cigarette is insufficient. Previous studies also have indicated that different dosages of cigarette can lead to different biological effects. Thus, the impact of cigarette at toxicological dose such as IC50 compared with that of e-cigarette are highly needed. In this study, we investigated the effects of cigarette smoke condensate (CSC) at toxicological dose compared with e-cigarette smoke condensate (ECSC) in equivalent nicotine level. Nicotine content of CSC and ECSC were determined by UPLC. Human lung epithelial cells (BEAS-2B) were exposed to 0-32 μg/ml of CSC and ECSC for 24 h to determine IC50 of cell viability and morphological assessment. Inflammation, apoptosis, cell cycle analysis and RNA-Seq transcriptome analysis were performed to characterize the differences between CSC and ECSC. We found that acute exposure of BEAS-2B cells to CSC at IC50 leaded to morphological change, inflammatory cytokines production and cell apoptosis, while ECSC did not exert such cell effects in equivalent nicotine level. The transcriptome analysis showed that differentially expressed genes in CSC were far more than that in ECSC, and mainly enriched in the category of cell cycle, DNA repair, cancer, and metabolic related pathways. Such cell cycle arrest was further experimentally confirmed. These results suggested that toxicological dose of ECSC might be much higher than that of CSC. Based on equivalent nicotine content, an acute exposure to CSC had significant impacts on cell effects and gene expression profile compared to ECSC. Our results provided a reference for the safety studies of conventional cigarette and e-cigarette.Anti-doping substances listed by the World Anti-Doping Agency (WADA) include hundreds of compounds of very different physico-chemical properties. Anti-doping control laboratories need to screen all these substances in the so-called Initial Testing Procedures (ITPs) what is very challenging from an analytical point of view. ITPs are mostly based on reversed-phase (RP) liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) using C18 columns, which feature poor retention and peak tailing for polar and basic compounds, respectively. While studies on this field dealing with the comparison of stationary phases are focused on certain chemical classes, this research provides a wide multi-target approach. For this purpose, a representative group of 93 anti-doping agents (log P from -2.4 to 9.2) included in ten different classes of prohibited substances was selected. A comprehensive study on the performance of six columns and four eluents on different separation parameters (retention factors, asymmetry faFP. Possible retention mechanisms underlying separation in the different stationary phases were discussed. This research provides valuable information to anti-doping control labs for improving LC-MS/MS-based ITPs and it proposes PFP as a suitable alternative to the already established C18.γ-Aminobutyric acid (GABA), a signal molecule, is regarded as the intersection node of carbon and nitrogen metabolism, and its contributions to flavonoid metabolism in tea plant growth and development remain unclear. The correlation between the GABA shunt and flavonoid metabolism in tea plants is worth to explore. Secondary metabolites and their correlations with the taste of tea soup made from tea plants (Camellia sinensis) during different seasons were investigated. Related secondary metabolites and transcript profiles of genes encoding enzymes in the GABA shunt, flavonoid pathway and polyamine biosynthesis were measured throughout the tea plant growth seasons and after exogenous GABA applications. In addition, the abundance of differentially expressed proteins was quantified after treatments with or without exogenous GABA. The tea leaves showed the highest metabolite concentrations in spring season. CsGAD, CsGABAT, CsSPMS, CsODC, CsF3H and CsCHS were found to be important genes in the GABA and anthocyanin biosynthesis pathways. GABA and anthocyanin concentrations showed a positive correlation, to some extent, CsF3H and CsCHS played important roles in the GABA and anthocyanin biosynthesis.Understanding the uncertainty in the parameterization of the two photosynthetic capacity parameters, leaf maximum carboxylation rate (Vcmax), and maximum electron transport rate (Jmax), is crucial for modeling and predicting carbon fluxes in terrestrial ecosystems. In gas exchange models, to date, Jmax is typically estimated from Vcmax based on a linear regression. However, recent studies have revealed that this relationship varies, dependent upon species, leaf groups, and time, so it is doubtful that the regression applies universally. Furthermore, far less is known regarding how other leaf traits affect the regression. In this study we analyzed the two key photosynthetic parameters and popularly measurable leaf traits, leaf chlorophyll concentration and leaf mass per area (LMA), of cool-temperate forest stands in Japan, aiming to construct a simple regression applicable to temperate deciduous forests, at least. The analysis was based on a long-term field dataset covering years of data for both sunlit and shaded leaves at different altitudes. Results showed that the best-fitted slope of the regression differed markedly from those previously reported, which were typically acquired from sunlit leaves. LMA had a significant effect on the regression, producing the lowest root mean square errors and the highest ratio of performance to deviation values (RPD = 2.017). 6Aminonicotinamide Although more data are needed to validate in other ecosystems, our approach at least provides a promising way to substantially improve photosynthesis model predictions, by introducing leaf traits into the popular empirical regression of Jmax against Vcmax, and ultimately to better understand the functioning of the photosynthetic machinery.Find the global optimal solution of the model is one promising research topic in computational intelligent community. Dependent on analogies to natural processes, the evolutionary swarm intelligent algorithms are widely used for solving global optimization problems which directed by the fitness values. In this paper, we propose one efficient fractional global learning machine (Fragmachine) which includes two stages (descending and ascending) to determine the optimal search path. The neural network model is used to approach the given fitness value. Specifically, for the descending stage, the integer gradient of the network output with respect the current location is employed to find the next descending point, while for the ascending stage, the fractional gradient is implemented to climb and escape from the local optimal point. We further propose one adaptive learning rate during training which relies on both the current gradient (integer or fractional) information and the fitness value. Finally, a series of numerical experiments verify the effectiveness of the proposed algorithm, Fragmachine.The assembly of amyloidogenic peptides and proteins, such as the β-amyloid peptide, α-synuclein, huntingtin, tau, and islet amyloid polypeptide, into amyloid fibrils and oligomers is directly linked to amyloid diseases, such as Alzheimer's, Parkinson's, and Huntington's diseases, frontotemporal dementias, and type II diabetes. Although amyloid oligomers have emerged as especially important in amyloid diseases, high-resolution structures of the oligomers formed by full-length amyloidogenic peptides and proteins have remained elusive. Investigations of oligomers assembled from fragments or stabilized β-hairpin segments of amyloidogenic peptides and proteins have allowed investigators to illuminate some of the structural, biophysical, and biological properties of amyloid oligomers. Here, we summarize recent advances in the application of these peptide model systems to investigate and understand the structures, biological properties, and biophysical properties of amyloid oligomers.
Website: https://www.selleckchem.com/products/6-aminonicotinamide.html
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