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The main purpose of this study is to analyze the relationship between urban public infrastructure, CO2 emissions and economic growth in China for the period 1990–2019 using the Dynamic Conditional Correlation Multivariate GARCH model (DCC-MGARCH) and Autoregressive Distributed Lagged Model (ARDL). According to the estimated results of the DCC-MGARCH, there is a positive influential effect among the economic growth, urban public infrastructure and CO2 emissions, while there is a negative influential effect between the urban public infrastructure and CO2 emissions, but the duration of volatility between the urban public infrastructure and CO2 emissions is relatively weak. Among such relationships, the conditional correlation also shows there is an effect in S-shape between the urban public infrastructure and economic growth, but the trend variation between the urban public infrastructure and CO2 emissions shows an inverted "U-shape" of Environmental Kuznets Curve Theory. The results of the ARDL-Bounds test show that there are long-term co-integration relationships and short-term dynamic correlation among all models. Also, the results of error correction terms show that the speed deviating economic growth and CO2 emissions from the long-term equilibrium and CO2 emissions deviating from the long-term equilibrium is larger than that of the urban public infrastructure, which indicates that the relationship between the economic growth and CO2 emissions is relatively strong. [ABSTRACT FROM AUTHOR]

Nurses have a relatively higher rate of depressive symptoms compared to other people. Previous studies have reported that gratitude is correlated with depressive symptoms among healthcare workers. The purpose of this study was to explore the causal relationship between gratitude and depressive symptoms among Chinese nurses. We collected data over 4 months, with 393 nurses at Time 1 and 241 at Time 2. All participants completed online questionnaires. We employed the structural equation models to test the hypotheses. The results revealed that gratitude at Time 1 could predict depressive symptoms at Time 2, and depressive symptoms at Time 1 could predict gratitude at Time 2. These results remained significant after controlling for gender, age, education, marital status, professional title, general positive affect, and negative affect. The findings provide initial evidence about the causal relationship between gratitude and depressive symptoms among Chinese nurses. Hospital administrators can intervene in depressive symptoms of nurses by developing gratitude interventions. Furthermore, nurses with lower levels of depressive symptoms feel more grateful. [ABSTRACT FROM AUTHOR]

The specific cytotoxic effects of nanoparticles on tumor cells may be used in future antitumor clinical applications. Gold nanoparticles (AuNPs) have been reported to produce potent cytotoxic effects; however, the precise mechanism is unclear. In this study, AuNPs were synthesized; the average size of the particles was 62.2 ± 6 nm with smooth surface and multiple shapes, which were determined using transmission electron microscopy and field emission scanning electron microscopy. The selected area electron diffraction patterns suggested that the synthesized AuNPs were crystalline. The X‐ray photoelectron spectroscopy (XPS) spectrum of the synthesized AuNPs has presented an intense peak at 100 eV, signifying the entire composition of Au in the developed AuNPs. This synthesized AuNPs showed the most potent efficacy in prostate cancer cells, regardless of whether or not they were androgen dependent. Secretome determinations using two‐dimensional difference in‐gel electrophoresis (2D‐DIGE), followed by enzyme‐linked immunosorbent assay and quantitative reverse transcriptase–polymerase chain reaction validations, have identified a series of secretory proteins that were dysregulated by AuNP treatment in prostate cancer cells, many of which are highly involved in cytokine–chemokine functions, including CXCL3, interleukin‐10, CCL2, and matrix metalloproteinase 9 (MMP9). Further research on molecular mechanism has indicated that AuNPs can trigger the secretion of anticancer factors and myeloid cell‐polarizing factors from tumor cells through MMP9 inhibition. These results have clearly signified the cytotoxic potential of AuNPs for treating prostate cancer and may provide a novel direction for prostate cancer therapy in the future. We have synthesized new gold nanoparticles (AuNPs) and identified their shape, properties, and components. This type of AuNPs has demonstrated significant cytotoxicity on prostate cancer cells, and they can regulate the polarization of myeloid cells in the tumor microenvironment. A series of secretory proteins regulated by AuNPs were screened using a proteomic method; and a secretory protein, matrix metalloproteinase 9, was proven to mediate the function of AuNPs on prostate cancer cells. [ABSTRACT FROM AUTHOR]

Summary: Thioredoxins (TRXs) occur in plant chloroplasts as complex disulphide oxidoreductases. Although many biological processes are regulated by thioredoxins, the regulatory mechanism of chloroplast TRXs are largely unknown.Here we report a rice white panicle2 mutant caused by a mutation in the thioredoxin z gene, an orthologue of AtTRX z in Arabidopsis. white panicle2 (wp2) seedlings exhibited a high‐temperature‐sensitive albinic phenotype.We found that plastid multiple organellar RNA editing factors (MORFs) were the regulatory targets of thioredoxin z. We showed that OsTRX z protein physically interacts with OsMORFs in a redox‐dependent manner and that the redox state of a conserved cysteine in the MORF box is essential for MORF–MORF interactions. wp2 and OsTRX z knockout lines show reduced editing efficiencies in many plastidial‐encoded genes especially under high‐temperature conditions. An Arabidopsis trx z mutant also exhibited significantly reduced chloroplast RNA editing.Our combined results suggest that thioredoxin z regulates chloroplast RNA editing in plants by controlling the redox state of MORFs. [ABSTRACT FROM AUTHOR]

Coronavirus disease 2019 (COVID-19) is a novel infectious viral disease caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Two consecutively negative SARS-CoV-2 viral RNA test (interval ≥ 24 hours), improved respiratory symptoms and obvious absorption of inflammation in pulmonary imaging are the discharge criteria for COVID-19 patients. The clearance profile of viral RNA in the upper respiratory tract specimens, including nasopharyngeal swab and/or oropharyngeal swabs, is related to innate immune cells such as Natural Killer cells. A total of 168 patients were included for the study. In this cohort, non-severe and severe groups showed significant differences in white blood cells, neutrophils, lymphocytes, basophils and platelets counts, as well as in infection related parameters such as CRP and serum cytokine IL-6. For lymphocyte subsets tests at admission, the severe group displayed significantly lower cell counts than the non-severe group. Higher counts of total T cells, CD4 + T cells, CD8 + T cells, and NK cells in peripheral blood showed a significant correlation with the shorter time taken to obtain the first negative viral RNA test and first positive IgM/ IgG antibody test. The number of B cells was only correlated with time to achieve the first positive IgM/IgG test. The count of NK cells was also correlated with a higher level of IgG antibody (p = 0.025). The lymphocytopenia group had a significantly worse survival rate (p = 0.022) and a longer duration (p = 0.023) of viral shedding than the normal lymphocyte count group. A lower NK cell count correlates the most with the worse survival rate (p<0.001) and a longer duration (p<0.001) of viral shedding. This study suggests the potential value of allo-Natural Killer cell therapy as an universal COVID-19 treatment strategy. [ABSTRACT FROM AUTHOR]

The clinical features of EBV-positive diffuse large B cell lymphoma (DLBCL) indicate a poorer prognosis than EBV-negative DLBCL. Currently, there is no efficacious drug for EBV-positive DLBCL. The cytokine interleukin-21 (IL-21) has been reported to be pro-apoptotic in DLBCL cell lines and is being explored as a new therapeutic strategy for this type of lymphomas. However, our previous studies showed that IL-21 stimulation of EBV-positive DLBCL cell lines leads to increased proliferation. Here, analysis of a rare clinical sample of EBV-positive DLBCL, in combination with a NOD/SCID mouse xenograft model, confirmed the effect of IL-21 on the proliferation of EBV-positive DLBCL cells. Using RNA-sequencing, we identified the pattern of differentially-expressed genes following IL-21 treatment and verified the expression of key genes at the protein level using western blotting. We found that IL-21 upregulates expression of the host MYC and AP-1 (composed of related Jun and Fos family proteins) and STAT3 phosphorylation, as well as expression of the viral LMP-1 protein. These proteins are known to promote the G1/S phase transition to accelerate cell cycle progression. Furthermore, in NOD/SCID mouse xenograft model experiments, we found that IL-21 treatment increases glucose uptake and angiogenesis in EBV-positive DLBCL tumours. Although more samples are needed to validate these observations, our study reconfirms the adverse effects of IL-21 on EBV-positive DLBCL, which has implications for the drug development of DLBCL. [ABSTRACT FROM AUTHOR]

The multi-objective directed acyclic graph scheduling problem (MDAGSP) is prevalent in cloud scheduling systems, involving the selection, assignment, and execution of multiple tasks/jobs with complex coupling interdependencies. High-quality solutions can yield substantial economic benefits. However, prevailing methods face challenges in obtaining a set of superior solutions for MDAGSP, due to the multifaceted nature of its variables, objectives, constraints, and heterogeneity. Firstly, this paper formulates a three-objective MDAGSP that includes makespan, energy costs and revenue, to model cloud scheduling systems. Subsequently, we propose a composite algorithm consisting of a selection phase and an assignment phase to automatically generate an efficient scheduling policy for this model. During the selection phase, a graph convolutional neural network learns high-level features to extract complex dependencies between tasks. During the assignment phase, an adaptive evolutionary algorithm assigns tasks to the appropriate executors. Finally, a series of experiments are conducted to validate the model's accuracy and assess the algorithm's efficiency. Compared to heuristic approaches, the algorithm achieves at least a 20.1% makespan reduction and 3.17% revenue increase. Remarkably, the algorithm obtains at least an 8.86% reduction in energy costs over the eleven baselines. In conclusion, the proposed algorithm provides decision-makers with a global view of scheduling plan. [ABSTRACT FROM AUTHOR]

Byline: Lijuan Wu, Yuanyuan Hao, Chen Sun, Ronghou Liu The anaerobic fermentation experiments were carried out on a self-manufactured bench scale anaerobic digester with pig dung as feed material. Under mesophilic digestion condition, effects of different solid concentration of feed on characteristics of biogas production were investigated. Results showed that daily average biogas production rate and total biogas yield were increased with the increases in the solid concentration of feed. The highest daily average biogas production rate of 1114.84 ml l−1 days−1 and total biogas yield of 17,057 ml were obtained at solid concentration of 12%, respectively. However, the highest TS biogas production rate of 174.86 ml g−1was obtained at solid concentration of 9%. Methane contents at solid concentration of 6, 9 and 12% were 60.8, 68.1 and 68.8%, respectively, after 15 days digestion.