Identification of differentially expressed genes and pathways in kidney of ANCA-associated vasculitis by integrated bioinformatics analysis.

The antineutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is a systematic of relatively rare autoimmune diseases with unknown cause. Kidney involvement is one of the most common clinical manifestations, and the degree of renal damage is closely associated with the development and prognosis of AAV. In this study, we utilized the Robust Rank Aggreg (RRA) method in R to integrate GSE104948, GSE104954, GSE108109, GSE108112, and GSE108113 profile datasets loaded from Gene Expression Omnibus (GEO) database and identified a set of differentially expressed genes (DEGs) in kidney between AAV patients and living donors. Then, the results of gene ontology (GO) functional annotation showed that immunity and metabolism involved process of AAV both in glomerulus and tubulointerstitial. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis revealed that following pathways, such as complement and coagulation cascades pathway; Staphylococcus aureus infection; disease-COVID-19; and systemic lupus erythematosus (SLE) pathway play a crucial role in AAV. Next, the results analyzed by protein-protein interaction (PPI) network and Cytoscape software exhibited the hub genes ALB, TYROBP, and CYBB existed in both glomerular and tubulointerstitial compartments datasets. Finally, KEGG analysis using genes of two most important modules also further validated complement and coagulation cascades pathway and S. aureus infection existed both in glomerulus and tubulointerstitial compartments datasets. In conclusion, this study identified key genes and pathways involved in kidney of AAV, which was benefit to further uncover the mechanisms underlying the development and progress of AAV, biomarkers, and potential therapeutic targets as well.

An integrated dual-layer microfluidic platform for multiple respiratory viruses screening.

Currently, the coronavirus disease 2019 (COVID-19) caused by the outbreak of a novel coronavirus (SARS-CoV-2) is spreading rapidly worldwide. Due to the high incidence of influenza coinciding with SARS-CoV-2, rapid detection is crucial to prevent spreading. Here, we present an integrated dual-layer microfluidic platform for specific and highly sensitive SARS-CoV-2, influenza viruses A (FluA) H1N1, H3N2, and influenza virus B (FluB) simultaneous detection. The platform includes a dual microchip (Dµchip) and a portable detection device for real-time fluorescence detection, temperature control and online communication. The Reverse Transcription Loop-mediated Isothermal Amplification (RT-LAMP) and Cas12a cleavage were performed on the Dµchip. The limit of detection (LoD) of the Dµchip assay was 10 copies for SARS-CoV-2, FluA H1N1, H3N2, and FluB RNAs. The Dµchip assay yielded no cross-reactivity against other coronaviruses, so it was suitable for the screening of multiple viruses. Moreover, the positive percentage agreement (PPA) and negative percentage agreement (NPA) of the assay were 97.9% and 100%, respectively, in 75 clinical samples compared to data from RT-PCR-based assays. Furthermore, the assay allowed the detection SARS-CoV-2 and influenza viruses in spiked samples. Overall, the present platform would provide a rapid method for the screening of multiple viruses in hospital emergency, community and primary care settings and facilitate the remote diagnosis and outbreak control of the COVID-19.

IFITM3 Inhibits SARS-CoV-2 Infection and Is Associated with COVID-19 Susceptibility.

SARS-CoV-2 has become a global threat to public health. Infected individuals can be asymptomatic or develop mild to severe symptoms, including pneumonia, respiratory distress, and death. This wide spectrum of clinical presentations of SARS-CoV-2 infection is believed in part due to the polymorphisms of key genetic factors in the population. In this study, we report that the interferon-induced antiviral factor IFITM3 inhibits SARS-CoV-2 infection by preventing SARS-CoV-2 spike-protein-mediated virus entry and cell-to-cell fusion. Analysis of a Chinese COVID-19 patient cohort demonstrates that the rs12252 CC genotype of IFITM3 is associated with SARS-CoV-2 infection risk in the studied cohort. These data suggest that individuals carrying the rs12252 C allele in the IFITM3 gene may be vulnerable to SARS-CoV-2 infection and thus may benefit from early medical intervention.

Immunogenicity of a vaccinia virus-based severe acute respiratory syndrome coronavirus 2 vaccine candidate

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines provide essential tools for the control of the COVID-19 pandemic. A number of technologies have been employed to develop SARS-CoV-2 vaccines, including the inactivated SARS-CoV-2 particles, mRNA to express viral spike protein, recombinant spike proteins, and viral vectors. Here, we report the use of the vaccinia virus Tiantan strain as a vector to express the SARS-CoV-2 spike protein. When it was used to inoculate mice, robust SARS-CoV-2 spike protein-specific antibody response and T-cell response were detected. Sera from the vaccinated mice showed strong neutralizing activity against the ancestral Wuhan SARS-CoV-2, the variants of concern (VOCs) B.1.351, B.1.617.2, and the emerging B.1.1.529 (omicron). This finding supports the possibility of developing a new type of SARS-CoV-2 vaccine using the vaccinia virus vector.

Exploring the Antecedents to the Reputation of Chinese Public Sector Organizations During COVID-19: An Extension of Situational Crisis Communication Theory

The study is intended to examine the impact of crisis responsibility on the reputation of the Chinese public sector organization during the COVID-19 crisis. In addition to that, the study has also examined the mediating role of crisis response strategy in the relationship between crisis responsibility and the reputation of the Chinese public sector organization during the COVID-19 crisis. Lastly, the study has also examined the moderating role of internal crisis communication in the relationship between the crisis responsibility and crisis response strategy of the Chinese public sector organization during COVID-19. This study bases on a quantitative research approach along with a cross-sectional research design. The population of the study is the Chinese public sector organization companies. Data is collected from the employees working in Chinese public sector organizations. The current study used 500 sample sizes;205 valid responses are received which were used in data analysis. The SEM-PLS is used for the data analysis. The result of the study indicates that all the direct hypotheses are accepted significantly, which indicates that the crisis responsibility and crisis response strategy are significant determinants of organizational reputation during the COVID-19. In a similar vein, the crisis responsibility has placed a significant impact on the crisis response strategy of Chinese organizations during COVID-19. The study is among the pioneer studies on crisis responsibility in the Chinese public sector organization during COVID-19. The study has employed an extended framework encircling the literature on crisis responsibility, crisis response strategy, internal crisis communication, and organizational reputation. Theoretically, the study has extended the situational crisis communication theory framework by incorporating internal crisis communication in the framework.

Spatiotemporal neural network for estimating surface NO2 concentrations over north China and their human health impact.

Atmospheric nitrogen dioxide (NO2) is an important reactive gas pollutant harmful to human health. The spatiotemporal coverage provided by traditional NO2 monitoring methods is insufficient, especially in the suburban and rural areas of north China, which have a high population density and experience severe air pollution. In this study, we implemented a spatiotemporal neural network (STNN) model to estimate surface NO2 from multiple sources of information, which included satellite and in situ measurements as well as meteorological and geographical data. The STNN predicted NO2 with high accuracy, with a coefficient of determination (R2) of 0.89 and a root mean squared error of 5.8 µg/m3 for sample-based 10-fold cross-validation. Based on the surface NO2 concentration determined by the STNN, we analyzed the spatial distribution and temporal trends of NO2 pollution in north China. We found substantial drops in surface NO2 concentrations ranging between 9.1% and 33.2% for large cities during the 2020 COVID-19 lockdown when compared to those in 2019. Moreover, we estimated the all-cause deaths attributed to NO2 exposure at a high spatial resolution of about 1 km, with totals of 6082, 4200, and 18,210 for Beijing, Tianjin, and Hebei Provinces in 2020, respectively. We observed remarkable regional differences in the health impacts due to NO2 among urban, suburban, and rural areas. Generally, the STNN model could incorporate spatiotemporal neighboring information and infer surface NO2 concentration with full coverage and high accuracy. Compared with machine learning regression techniques, STNN can effectively avoid model overfitting and simultaneously consider both spatial and temporal correlations of input variables using deep convolutional networks with residual blocks. The use of the proposed STNN model, as well as the surface NO2 dataset, can benefit air quality monitoring, forecasting, and health burden assessments.

Illuminated border: Spatiotemporal analysis of COVID-19 pressure in the Sino-Burma border from the perspective of nighttime light.

The emergence of mutant strains such as Omicron has increased the uncertainty of COVID-19, and all countries have taken strict measures to prevent the spread of the disease. The spread of the disease between countries is of particular concern. However, most COVID-19 research focuses mainly on the country or community, and there is less research on the border areas between two countries. In this study, we analyzed changes in the total nighttime light intensity (TNLI) and total nighttime lit area (TNLA) along the Sino-Burma border and used the data to construct an epidemic pressure input index (PII) model in reference to the Shen potential model. The results show that, as the epidemic became more severe, TNLI on both sides of the border at the Ruili border port increased, while that in areas far from the port decreased. At the same time, increases and decreases in TNLA occurred in areas far from the port, and PII can indicate the areas where imported cases are likely to occur. Along the Sino-Burma border, the PII model showed low PII in the north and south and high PII in the central region. The areas between Dehong and Lincang, especially the Ruili, Wanding, Nansan, and Qingshuihe border ports, had high PII. The results of this study offer a reference for public health officials and decision makers when determining resource allocation and the implementation of stricter quarantine rules. With updated epidemic statistics, PII can be recalculated to support timely monitoring of COVID-19 in border areas.

SARS-CoV-2 spike protein-induced cell fusion activates the cGAS-STING pathway and the interferon response.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused the unprecedented coronavirus disease 2019 (COVID-19) pandemic. Critical cases of COVID-19 are characterized by the production of excessive amounts of cytokines and extensive lung damage, which is partially caused by the fusion of SARS-CoV-2-infected pneumocytes. Here, we found that cell fusion caused by the SARS-CoV-2 spike (S) protein induced a type I interferon (IFN) response. This function of the S protein required its cleavage by proteases at the S1/S2 and the S2' sites. We further showed that cell fusion damaged nuclei and resulted in the formation of micronuclei that were sensed by the cytosolic DNA sensor cGAS and led to the activation of its downstream effector STING. Phosphorylation of the transcriptional regulator IRF3 and the expression of IFNB, which encodes a type I IFN, were abrogated in cGAS-deficient fused cells. Moreover, infection with VSV-SARS-CoV-2 also induced cell fusion, DNA damage, and cGAS-STING-dependent expression of IFNB. Together, these results uncover a pathway underlying the IFN response to SARS-CoV-2 infection. Our data suggest a mechanism by which fused pneumocytes in the lungs of patients with COVID-19 may enhance the production of IFNs and other cytokines, thus exacerbating disease severity.

A Novel Strategy for the Detection of SARS-CoV-2 Variants Based on Multiplex PCR-Mass Spectrometry Minisequencing Technology.

The objective of this study was to construct a novel strategy for the detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants using multiplex PCR-mass spectrometry minisequencing technique (mPCR-MS minisequencing). Using the nucleic acid sequence of a SARS-CoV-2 nonvariant and a synthetic SARS-CoV-2 variant-carrying plasmid, a matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) method based on the single-base mass probe extension of multiplex PCR amplification products was established to detect 9 mutation types in 7 mutated sites (HV6970del, N501Y, K417N, P681H, D614G, E484K, L452R, E484Q, and P681R) in the receptor-binding domain of the spike protein of SARS-CoV-2 variants. Twenty-one respiratory tract pathogens (9 bacteria and 12 respiratory viruses) and nucleic acid samples from non-COVID-19 patients were selected for specific validation. Twenty samples from COVID-19 patients were used to verify the accuracy of this method. The 9 mutation types could be detected simultaneously by triple PCR amplification coupled with MALDI-TOF MS. SARS-CoV-2 and six variants, B.1.1.7 (Alpha), B.1.351 (Beta), B.1.429 (Epsilon), B.1.526 (Iota), P.1 (Gamma) and B.1.617.2 (Delta), could be identified. The detection limit for all 9 sites was 1.5 × 103 copies. The specificity of this method was 100%, and the accuracy of real-time PCR cycle threshold (CT) values less than 27 among positive samples was 100%. This method is open and extensible, and can be used in a high-throughput manner, easily allowing the addition of new mutation sites as needed to identify and track new SARS-CoV-2 variants as they emerge. mPCR-MS minisequencing provides a new detection option with practical application value for SARS-CoV-2 and its variant infection. IMPORTANCE The emergence of SARS-CoV-2 variants is the key factor in the second wave of the COVID-19 pandemic. An all-in-one SARS-CoV-2 variant identification method based on a multiplex PCR-mass spectrometry minisequencing system was developed in this study. Six SARS-CoV-2 variants (Alpha, Beta, Epsilon, Iota, Gamma, and Delta) can be identified simultaneously. This method can not only achieve the multisite simultaneous detection that cannot be realized by PCR coupled with first-generation sequencing technology and quantitative PCR (qPCR) technology but also avoid the shortcomings of time-consuming, high-cost, and high technical requirements of whole-genome sequencing technology. As a simple screening assay for monitoring the emergence and spread of SARS-CoV-2 and variants, mPCR-MS minisequencing is expected to play an important role in the detection and monitoring of SARS-CoV-2 infection as a supplementary technology.

Improved Anthropogenic SO2 Retrieval from High-Spatial-Resolution Satellite and its Application during the COVID-19 Pandemic.

Sulfur dioxide (SO2) measured by satellites is widely used to estimate anthropogenic emissions. The Sentinel-5 Precursor (S-5P) operational SO2 product is overestimated compared to the ground-based multiaxis differential optical absorption spectroscopy (MAX-DOAS) measurements in China and shows an opposite variation to the surface measurements, which limits the application of TROPOspheric monitoring instrument (TROPOMI) products in emissions research. Radiometric calibration, a priori profiles, and fitting windows might cause the overestimation of S-5P operational SO2 product. Here, we improve the optimal-estimation-based algorithm through several calibration methods. The improved retrieval agrees reasonably well with the ground-based measurements (R > 0.70, bias <13.7%) and has smaller biases (-28.9%) with surface measurements over China and India. It revealed that the SO2 column in March 2020 decreased by 51.6% compared to March 2019 due to the lockdown for curbing the spread of the COVID-19 pandemic, and there was a decrease of 50% during the lockdown than those after the lockdown, similar to the surface measurement trend, while S-5P operational SO2 product showed an unrealistic increase of 19%. In India, the improved retrieval identified obvious "hot spots" and observed a 30% decrease of SO2 columns during the lockdown.

Depression and Anxiety Among Quarantined People, Community Workers, Medical Staff, and General Population in the Early Stage of COVID-19 Epidemic.

Background: We described the prevalence of anxiety and depression related to COVID-19 pandemic among different types of population and examined their potential risk factors. Methods: A cross-sectional survey was conducted to collect demographic characteristics, exposure histories, and many other concerns about COVID-19. The Zung's self-rating anxiety scale (SAS) and self-rating depression scale (SDS), followed by a four-step multiple logistic regression analysis was performed to identify factors associated with mental health outcomes. Results: Out of 3,303 participants, the quarantined people (40.9%), community workstation staffs-policemen-volunteers (CPV) (36.4%) and general public (30.7%) reported higher percentages of depression than the general medical staff (18.4%). Moreover, the quarantined people (19.1%) also showed higher prevalence of anxiety than the general public (9.1%) and the general medical staff (7.8%). The quarantined people had the highest risk of anxiety and depression, whereas the self-rated health was negatively associated with the risks of anxiety and depression. Younger age group (18 to 30 years) showed higher risks of anxiety (OR = 6.22, 95% CI = 2.89-13.38, p < 0.001) and depression (OR = 3.69, 95% CI = 2.40-5.69, p < 0.001). People who had exposure history or contact from Hubei province after December 1, 2019 (OR = 1.57, 95% CI = 1.07-2.30, p < 0.001), had family or friends engaged in front-line health care work (OR = 1.47, 95% CI = 1.02-2.14, p < 0.001), had confirmed case nearby (OR = 2.44, 95% CI = 1.43-4.18, p < 0.001) were all more likely to suffer from anxiety. Moreover, the negligence (OR = 1.85, 95% CI = 1.37-2.51, p < 0.001) or overindulgence (OR = 1.45, 95% CI = 1.03-2.04, p < 0.001) toward the epidemic information was associated with a higher risk of depression and anxiety. Conclusions: Our findings show that the CPV and quarantined people were most at-risk population. We have identified that the young people, people with exposure histories and negligence or overindulgence toward epidemic information are in grave need of attention.

Case Report: Identification of SARS-CoV-2 in Cerebrospinal Fluid by Ultrahigh-Depth Sequencing in a Patient With Coronavirus Disease 2019 and Neurological Dysfunction.

We reported that the complete genome sequence of SARS-Coronavirus-2 (SARS-CoV-2) was obtained from a cerebrospinal fluid (CSF) sample by ultrahigh-depth sequencing. Fourteen days after onset, seizures, maxillofacial convulsions, intractable hiccups and a significant increase in intracranial pressure developed in an adult coronavirus disease 2019 patient. The complete genome sequence of SARS-CoV-2 obtained from the cerebrospinal fluid indicates that SARS-CoV-2 can invade the central nervous system. In future, along with nervous system assessment, the pathogen genome detection and other indicators are needed for studying possible nervous system infection of SARS-CoV-2.

Reduction and partitioning of viral and bacterial indicators in a UASB reactor followed by high rate algal ponds treating domestic sewage.

Human enteric pathogens are a major global concern, as they are responsible for thousands of preventable deaths every year. New pathogens in wastewater are constantly emerging. For example, SARS-CoV-2 has been recently detected in domestic sewage and primary sludge. Knowledge about the reduction of viruses in wastewater treatment and their partitioning between the treated liquid effluent versus the sludge or biosolids is still very scarce, especially in countries with emerging economies and tropical climates. Upflow anaerobic sludge blanket (UASB) reactors are among the top three most commonly used technologies for the treatment of sewage in Latin America and the Caribbean, and their use has become increasingly common in many other low- and middle-income countries. High-rate algal ponds (HRAP) are regarded as a sustainable technology for the post-treatment of UASB effluent. This study evaluated the overall reduction and the liquid-solid partitioning of somatic coliphages, F-specific coliphages, and E. coli in a pilot-scale system comprised of a UASB reactor followed by HRAPs treating real wastewater. Average log removal for somatic and F-specific coliphages were 0.40 and 0.56 for the UASB reactor, and 1.15 and 1.70 for HRAPs, respectively. The overall removal of both phages in the system was 2.06-log. Removal of E. coli was consistently higher. The number of viruses leaving the system in the UASB solids and algal biomass was less than 10% of the number leaving in the clarified liquid effluent. The number of E. coli leaving the system in solids residuals was estimated to be approximately one order of magnitude higher than the number of E. coli leaving in the liquid effluent. Results from this study demonstrate the suitability of UASB-HRAP systems to reduce viral and bacterial indicators from domestic sewage and the importance of adequately treating sludge for pathogen reduction before they are used as biosolids.

Ozone profile retrievals from TROPOMI: Implication for the variation of tropospheric ozone during the outbreak of COVID-19 in China.

During the outbreak of the coronavirus disease 2019 (COVID-19) in China in January and February 2020, production and living activities were drastically reduced to impede the spread of the virus, which also caused a strong reduction of the emission of primary pollutants. However, as a major species of secondary air pollutant, tropospheric ozone did not reduce synchronously, but instead rose in some region. Furthermore, higher concentrations of ozone may potentially promote the rates of COVID-19 infections, causing extra risk to human health. Thus, the variation of ozone should be evaluated widely. This paper presents ozone profiles and tropospheric ozone columns from ultraviolet radiances detected by TROPOospheric Monitoring Instrument (TROPOMI) onboard Sentinel 5 Precursor (S5P) satellite based on the principle of optimal estimation method. We compare our TROPOMI retrievals with global ozonesonde observations, Fourier Transform Spectrometry (FTS) observation at Hefei (117.17°E, 31.7°N) and Global Positioning System (GPS) ozonesonde sensor (GPSO3) ozonesonde profiles at Beijing (116.46°E, 39.80°N). The integrated Tropospheric Ozone Column (TOC) and Stratospheric Ozone Column (SOC) show excellent agreement with validation data. We use the retrieved TOC combining with tropospheric vertical column density (TVCD) of NO2 and HCHO from TROPOMI to assess the changes of tropospheric ozone during the outbreak of COVID-19 in China. Although NO2 TVCD decreased by 63%, the retrieved TOC over east China increase by 10% from the 20-day averaged before the lockdown on January 23, 2020 to 20-day averaged after it. Because the production of ozone in winter is controlled by volatile organic compounds (VOCs) indicated by monitored HCHO, which did not present evident change during the lockdown, the production of ozone did not decrease significantly. Besides, the decrease of NOx emission weakened the titration of ozone, causing an increase of ozone.