Modeling particulate nitrate in China: Current findings and future directions.

Particulate nitrate (pNO3) is now becoming the principal component of PM2.5 during severe winter haze episodes in many cities of China. To gain a comprehensive understanding of the key factors controlling pNO3 formation and driving its trends, we reviewed the recent pNO3 modeling studies which mainly focused on the formation mechanism and recent trends of pNO3 as well as its responses to emission controls in China. The results indicate that although recent chemical transport models (CTMs) can reasonably capture the spatial-temporal variations of pNO3, model-observation biases still exist due to large uncertainties in the parameterization of dinitrogen pentoxide (N2O5) uptake and ammonia (NH3) emissions, insufficient heterogeneous reaction mechanism, and the predicted low sulfate concentrations in current CTMs. The heterogeneous hydrolysis of N2O5 dominates nocturnal pNO3 formation, however, the contribution to total pNO3 varies among studies, ranging from 21.0% to 51.6%. Moreover, the continuously increasing PM2.5 pNO3 fraction in recent years is mainly due to the decreased sulfur dioxide emissions, the enhanced atmospheric oxidation capacity (AOC), and the weakened nitrate deposition. Reducing NH3 emissions is found to be the most effective control strategy for mitigating pNO3 pollution in China. This review suggests that more field measurements are needed to constrain the parameterization of heterogeneous N2O5 and nitrogen dioxide (NO2) uptake. Future studies are also needed to quantify the relationships of pNO3 to AOC, O3, NOx, and volatile organic compounds (VOCs) in different regions of China under different meteorological conditions. Research on multiple-pollutant control strategies involving NH3, NOX, and VOCs is required to mitigate pNO3 pollution, especially during severe winter haze events.

Discussion on the mechanism of Xiyanping injection in the treatment of human coronavirus infection based on network pharmacology and molecular docking

Objective: To explore the mechanism of Xiyanping injection in the treatment of human coronavirus infection based on network pharmacology and molecular docking method. Methods: The active components and targets of Xiyanping injection were screened by CNKI, SwissTarget Prediction and Targetnet. The Human Gene Database (Genecards), Online Human Mendelian Inheritance Database (OMIM) and Therapeutic Target Database (TTD) were searched to predict disease targets. Venny 2.1.0, Cytoscape 3.8.2 and STRING11.5 were used to construct "drug target-disease target Venn diagram", "drug-active ingredient-target-disease network" and "protein interaction network". The Database for Annotation, Visualization and Integrated Discovery (DAVID) and Bioinformatics, Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) were used for the enrichment analysis and visualization. Finally, molecular docking was performed by AutoDock Vina and PyMOL. Results: The active ingredient of Xiyanping injection was andrographolide, andrographolide had 140 targets, 1 812 potential targets of human coronavirus infection, and 35 common targets of Xiyanping and human coronavirus infection;PPI network analysis and molecular docking showed that MAPK9, MAPK8, TYK2, CDKI and interleukin (IL)-6 among the 35 common targets might be the key targets of Xiyanping injection in the treatment of human coronavirus infection. Lactone was tightly bound;enrichment analysis showed that key targets were closely related to protein phosphorylation, cell signal transduction, and gene expression regulation, and key targets were NOD-like receptor signaling pathway, Toll-like receptor signaling pathway, FOXO signaling pathway, there was also an important link in the TNF signaling pathway. Conclusion: The active ingredient of Xiyanping injection was andmgrapholide, and its treatment of human coronavirus infection might affect NOD-like receptor signaling pathway, Toll-like receptor signaling pathway and FOXO signaling by inhibiting the activities of MAPK9, MAPK8, TYK2, CDK1 and IL-6. The activation of the pathway and the TNF signaling pathway regulates protein phosphorylation, cell signal transduction and gene expression, thereby exerting anti-inflammatory effects.

Weighted gene co-expression network analysis revealed T cell differentiation associated with the age-related phenotypes in COVID-19 patients.

The risk of severe condition caused by Corona Virus Disease 2019 (COVID-19) increases with age. However, the underlying mechanisms have not been clearly understood. The dataset GSE157103 was used to perform weighted gene co-expression network analysis on 100 COVID-19 patients in our analysis. Through weighted gene co-expression network analysis, we identified a key module which was significantly related with age. This age-related module could predict Intensive Care Unit status and mechanical-ventilation usage, and enriched with positive regulation of T cell receptor signaling pathway biological progress. Moreover, 10 hub genes were identified as crucial gene of the age-related module. Protein-protein interaction network and transcription factors-gene interactions were established. Lastly, independent data sets and RT-qPCR were used to validate the key module and hub genes. Our conclusion revealed that key genes were associated with the age-related phenotypes in COVID-19 patients, and it would be beneficial for clinical doctors to develop reasonable therapeutic strategies in elderly COVID-19 patients.

Explore the Approaches to Corporate Social Responsibility Implemented by E-Commerce Platforms in China During the Early Stage of COVID-19: A Mixed-Methods Content Analysis.

OBJECTIVES: The aim of this study was to explore (a) the approaches to corporate social responsibility (CSR) implemented by e-commerce platforms in China during the early stage of coronavirus disease 2019 (ESCOVID-19) and (b) the factors associated with the platforms' choice of these approaches. METHODS: We collected the CSR data from the Internet during ESCOVID-19. Conventional content analysis was used to develop the targeted approaches. Finally, based on the frequency analysis of each approach, rank-based nonparametric testing was conducted to answer objective (b). RESULTS: Three main approaches (ie, donative CSR actions, responsive CSR actions, and strategic CSR actions) and 8 subapproaches were implemented. The strategic approach was the most frequently used approach. The platforms with higher market size implemented more donative and strategic CSR actions than did the platforms with lower market size. Donative CSR actions were significantly implemented in the earlier period, while strategic CSR actions were significantly implemented in the later period. CONCLUSIONS: Our research highlights the importance of e-commerce platforms to help the public survive and identifies that market size and time were associated with the platforms' CSR choice. The design of prevention and control policies should incorporate and support e-commerce platforms and evaluate the factors when confronting future public health crises.

CASA: a comprehensive database resource for the COVID-19 Alternative Splicing Atlas.

BACKGROUND: As a key process in transcriptional regulatory mechanisms, alternative splicing (AS) plays a crucial role in maintaining the diversity of RNA and protein expression, and mediates the immune response in infectious diseases, especially for the COVID-19. Therefore, urgent data gathering and more research of AS profiles in microbe-infected human cells are needed to improve understanding of COVID-19 and related infectious diseases. Herein, we have created CASA, the COVID-19 Alternative Splicing Atlas to provide a convenient computing platform for studies of AS in COVID-19 and COVID-19-related infectious diseases. METHODS: In CASA, we reanalyzed thousands of RNA-seq datasets generated from 65 different tissues, organoids and cell lines to systematically obtain quantitative data on AS events under different conditions. A total of 262,994 AS events from various infectious diseases with differing severity were detected and visualized in this database. In order to explore the potential function of dynamics AS events, we performed analysis of functional annotations and drug-target interactions affected by AS in each dataset. RNA-binding proteins (RBPs), which may regulate these dynamic AS events are also provided for users in this database. RESULTS: CASA displays microbe-induced alterations of the host cell splicing landscape across different virus families and helps users identify condition-specific splicing patterns, as well as their potential regulators. CASA may greatly facilitate the exploration of AS profiles and novel mechanisms of host cell splicing by viral manipulation. CASA is freely available at http://www.splicedb.net/casa/ .

The Network of Interactions between the Porcine Epidemic Diarrhea Virus Nucleocapsid and Host Cellular Proteins.

Host-virus protein interactions are critical for intracellular viral propagation. Understanding the interactions between cellular and viral proteins may help us develop new antiviral strategies. Porcine epidemic diarrhea virus (PEDV) is a highly contagious coronavirus that causes severe damage to the global swine industry. Here, we employed co-immunoprecipitation and liquid chromatography-mass spectrometry to characterize 426 unique PEDV nucleocapsid (N) protein-binding proteins in infected Vero cells. A protein-protein interaction network (PPI) was created, and gene ontology (GO) annotation and Kyoto Encyclopedia of Genes and Genomes (KEGG) database analyses revealed that the PEDV N-bound proteins belong to different cellular pathways, such as nucleic acid binding, ribonucleoprotein complex binding, RNA methyltransferase, and polymerase activities. Interactions of the PEDV N protein with 11 putative proteins: tripartite motif containing 21, DEAD-box RNA helicase 24, G3BP stress granule assembly factor 1, heat shock protein family A member 8, heat shock protein 90 alpha family class B member 1, YTH domain containing 1, nucleolin, Y-box binding protein 1, vimentin, heterogeneous nuclear ribonucleoprotein A2/B1, and karyopherin subunit alpha 1, were further confirmed by in vitro co-immunoprecipitation assay. In summary, studying an interaction network can facilitate the identification of antiviral therapeutic strategies and novel targets for PEDV infection.

Current status and capacity of pathogen laboratories in centers for disease control and prevention in China during the COVID-19 pandemic: A nationwide cross-sectional survey.

The pathogen laboratory (p-lab) is the core and primary department of centers for disease control and prevention (CDCs) in China to respond to infectious disease outbreaks such as COVID-19. To understand the current status and capacity of p-labs in Chinese CDCs during the COVID-19 pandemic, we conducted a nationwide cross-sectional survey among 399 respondents from 239 CDCs. Differences in the current status of p-labs in CDCs of provinces, cities, and counties mainly comprised laboratory equipment, IEIs, mastery of personal occupational skills, and maximum detection capacity. Most CDCs reported a lack of staff and funds for personnel, which should be a priority in China's upcoming public health reform. The development of sequencing technologies has received considerable attention in CDCs. These are mainly used to study respiratory viruses such as influenza and SARS-CoV-2. The COVID-19 pandemic has driven development of the CDCs in China, and personnel and funds are considered key factors in improving the detection capacity of CDC p-labs.

Scarcity Mindset Neuro Network Decoding With Reward: A Tree-Based Model and Functional Near-Infrared Spectroscopy Study.

Resource scarcity imposes challenging demands on the human cognitive system. Insufficient resources cause the scarcity mindset to affect cognitive performance, while reward enhances cognitive function. Here, we examined how reward and scarcity simultaneously contribute to cognitive performance. Experimental manipulation to induce a polar scarcity mindset and reward conditions within participants under functional near-infrared spectroscopy (fNIRS) recording was implemented to explore the mechanism underlying the scarcity mindset and reward in terms of behavior and neurocognition. Participants showed decreased functional connectivity from the dorsolateral prefrontal cortex (DLPFC) to the ventrolateral prefrontal cortex (VLPFC) with a scarcity mindset, a region often implicated in cognitive control. Moreover, under reward conditions, the brain activation of the maximum total Hb bold signal was mainly located in the left hemisphere [channels 1, 3, and 4, left ventrolateral prefrontal cortex (L-VLPFC) and channel 6, left dorsolateral prefrontal cortex (L-DLPFC)], and there was also significant brain activation of the right dorsolateral prefrontal cortex (R-DLPFC) in the right hemisphere (channel 17). Furthermore, these data indicate the underlying neural changes of the scarcity mentality and demonstrate that brain activities may underlie reward processing. Additionally, the base-tree machine learning model was trained to detect the mechanism of reward function in the prefrontal cortex (PFC). According to SHapley Additive exPlanations (SHAP), channel 8 contributed the most important effect, as well as demonstrating a high-level interrelationship with other channels.

Genome-Wide Profiling Reveals Alternative Polyadenylation of Innate Immune-Related mRNA in Patients With COVID-19.

The coronavirus disease 2019 (COVID-19) pandemic has caused many deaths worldwide. To date, the mechanism of viral immune escape remains unclear, which is a great obstacle to developing effective clinical treatment. RNA processing mechanisms, including alternative polyadenylation (APA) and alternative splicing (AS), are crucial in the regulation of most human genes in many types of infectious diseases. Because the role of APA and AS in response to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection remains unknown, we performed de novo identification of dynamic APA sites using a public dataset of human peripheral blood mononuclear cell (PBMC) RNA-Seq data in COVID-19 patients. We found that genes with APA were enriched in innate immunity -related gene ontology categories such as neutrophil activation, regulation of the MAPK cascade and cytokine production, response to interferon-gamma and the innate immune response. We also reported genome-wide AS events and enriched viral transcription-related categories upon SARS-CoV-2 infection. Interestingly, we found that APA events may give better predictions than AS in COVID-19 patients, suggesting that APA could act as a potential therapeutic target and novel biomarker in those patients. Our study is the first to annotate genes with APA and AS in COVID-19 patients and highlights the roles of APA variation in SARS-CoV-2 infection.

Field Validation of a Rapid Recombinase Aided Amplification Assay for SARS-CoV-2 RNA at Customs - Zhejiang Province, China, January 2021.

INTRODUCTION: The best approach to preventing the importation of coronavirus disease 2019 (COVID-19) is enhancing the detection capacity at customs. The rapid detection is of utmost importance and therefore highly demanded. METHODS: We conducted a field validation study of a duplex real-time reverse transcription recombinase-aided amplification (RT-RAA) assay in Zhoushan and Hangzhou customs, in Zhejiang Province, China. The reverse transcriptase polymerase chain reaction (RT-PCR) assay kit routinely used at customs was used in parallel, and the duration the two methods took to complete a specific number of samples was compared. RESULTS: Among 506 samples collected, RT-RAA results were consistent with the RT-PCR results. The sensitivity and specificity were 100%, the total coincidence rate was 100%, and the Kappa value was 1 (P<0.05) for both methods. The RT-RAA kit took a significantly shorter time in testing the 20-200 samples than the RT-PCR kit. DISCUSSION: The RT-RAA detection method is more efficient and suitable for use at customs than RT-PCR assay to realize rapid customs clearance of 200 or fewer samples.

RNA-dependent RNA polymerase (RdRp) inhibitors: The current landscape and repurposing for the COVID-19 pandemic.

The widespread nature of several viruses is greatly credited to their rapidly altering RNA genomes that enable the infection to persist despite challenges presented by host cells. Within the RNA genome of infections is RNA-dependent RNA polymerase (RdRp), which is an essential enzyme that helps in RNA synthesis by catalysing the RNA template-dependent development of phosphodiester bonds. Therefore, RdRp is an important therapeutic target in RNA virus-caused diseases, including SARS-CoV-2. In this review, we describe the promising RdRp inhibitors that have been launched or are currently in clinical studies for the treatment of RNA virus infections. Structurally, nucleoside inhibitors (NIs) bind to the RdRp protein at the enzyme active site, and nonnucleoside inhibitors (NNIs) bind to the RdRp protein at allosteric sites. By reviewing these inhibitors, more precise guidelines for the development of more promising anti-RNA virus drugs should be set, and due to the current health emergency, they will eventually be used for COVID-19 treatment.