SARS-CoV-2 NSP13 interacts with host IRF3, blocking antiviral immune responses.

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), poses an unprecedented threat to human health since late 2019. Notably, the progression of the disease is associated with impaired antiviral interferon (IFN) responses. Although multiple viral proteins were identified as potential IFN antagonists, the underlying molecular mechanisms remain to be fully elucidated. In this study, we firstly demonstrate that SARS-CoV-2 NSP13 protein robustly antagonizes IFN response induced by the constitutively active form of transcription factor IRF3 (IRF3/5D). This induction of IFN response by IRF3/5D is independent of the upstream kinase, TBK1, a previously reported NSP13 target, thus indicating that NSP13 can act at the level of IRF3 to antagonize IFN production. Consistently, NSP13 exhibits a specific, TBK1-independent interaction with IRF3, which, moreover, is much stronger than that of NSP13 with TBK1. Furthermore, the NSP13-IRF3 interaction was shown to occur between the NSP13 1B domain and IRF3 IRF association domain (IAD). In agreement with the strong targeting of IRF3 by NSP13, we then found that NSP13 blocks IRF3-directed signal transduction and antiviral gene expression, counteracting IRF3-driven anti-SARS-CoV-2 activity. These data suggest that IRF3 is likely to be a major target of NSP13 in antagonizing antiviral IFN responses and provide new insights into the SARS-CoV-2-host interactions that lead to viral immune evasion.

What We Ask about When We Ask about Quarantine? Content and Sentiment Analysis on Online Help-Seeking Posts during COVID-19 on a Q&A Platform in China.

The COVID-19 outbreak, a recent major public health emergency, was the first national health crisis since China entered the era of mobile social media. In this context, the public posted many quarantine-related posts for help on social media. Most previous studies of social media during the pandemic focused only on people's emotional needs, with less analysis of quarantine help-seeking content. Based on this situation, this study analyzed the relationship between the number of quarantine help-seeking posts and the number of new diagnoses at different time points in the pandemic using Zhihu, the most comprehensive topic discussion platform in China. It showed a positive correlation between the number of help-seeking posts and the pandemic's severity. Given the diversity of people's help-seeking content, this study used topic model analysis and sentiment analysis to explore the key content of people's quarantine help-seeking posts during the pandemic. In light of the framework of uses and gratifications, we found that people posted the most questions in relation to help with information related to pandemic information and quarantine information. Interestingly, the study also found that the content of people's quarantine posts during the pandemic was primarily negative in sentiment. This study can thus help the community understand the changes in people's perceptions, attitudes, and concerns through their reactions to emergencies and then formulate relevant countermeasures to address pandemic control and information regulation, which will have implications for future responses to public health emergencies. Moreover, in terms of psychological aspects, it will help implement future mental health intervention strategies and better address the public's psychological problems.

Broadly effective ACE2 decoy proteins protect mice from lethal SARS-CoV-2 infection (preprint)

As SARS-CoV-2 variants have been causing increasingly serious drug resistance problem, development of broadly effective and hard-to-escape anti-SARS-CoV-2 agents is in urgent need. Here we describe further development and characterization of two SARS-CoV-2 receptor decoy proteins, ACE2-Ig-95 and ACE2-Ig-105/106. We found that both proteins had potent and robust in vitro neutralization activities against diverse SARS-CoV-2 variants including Omicron, with an average IC50 of up to 37 pM. In a stringent lethal SARS-CoV-2 infection mouse model, both proteins lowered lung viral load by up to ~1000 fold, prevented the emergence of clinical signs in >75% animals, and increased animal survival rate from 0% (untreated) to >87.5% (treated). These results demonstrate that both proteins are good drug candidates for protecting animals from severe COVID-19. In a head-to-head comparison of these two proteins with five previously-described ACE2-Ig constructs, we found that two of these constructs, each carrying five surface mutations in the ACE2 region, had partial loss of neutralization potency against three SARS-CoV-2 variants. These data suggest that extensively mutating ACE2 residues near the RBD-binding interface should be avoided or performed with extra caution. Further, we found that both ACE2-Ig-95 and ACE2-Ig-105/106 could be produced to gram/liter level, demonstrating the developability of them as biologic drug candidates. Stress-condition stability test of them further suggests that more studies are required in the future to improve the stability of these proteins. These studies provide useful insight into critical factors for engineering and preclinical development of ACE2 decoys as broadly effective therapeutics against diverse ACE2-utilizing coronaviruses.

Dynamic Analysis of a VSEIR Model with Vaccination Efficacy and Immune Decline

Vaccination is an effective way to prevent the spread of infectious diseases. In this study, we formulate a VSEIR mathematical model to explore the effects of vaccination rate, vaccine efficacy, and immune decline on the COVID-19 transmission. The existence and stability criteria of equilibrium states were determined by analyzing the model. Model analysis was performed. One of the interesting phenomena involved in this issue is that diseases may or may not die out when the basic reproduction number falls below unity (i.e., a backward bifurcation may exist and cause multistability). The disease eventually becomes endemic in the population when the basic reproduction number exceeds one. By comparing different vaccination rates, vaccine efficacy, and infection rate factors, the diseases can be eliminated, not only by vaccines but also by strict protective measures. In addition, we used the COVID-19 number of reported cases in Xiamen in September 2021 to fit the model, and the model and the reported data were well matched.

Internet-based cognitive therapy for women with antenatal depressive symptoms during the COVID-19 pandemic: protocol for a multi-center randomized controlled trial across China.

BACKGROUND: Depression and anxiety are common among pregnant women. Internet-delivered psychological therapies such as cognitive behavioral therapy (iCBT) have been developed to increase accessibility and address common help-seeking barriers, especially during pandemic period. The objective of this trial is to evaluate the short-term and long-term effects of iCBT on reducing depressive symptoms among pregnant women during the COVID-19 pandemic with the overall goal of preventing depression recurrence in the first 12 months postpartum. METHODS: A multi-site randomized controlled trial will be conducted where 300 pregnant women early in their third trimester will be screened for depression symptoms using the Edinburgh Postnatal Depression Scale (EPDS) during a routine obstetrical visit. Eligible and consenting women with a score greater than 9 will be randomly allocated (1:1) to either intervention group or control group. ICBT involving the completion of 7 weekly online modules will be delivered via a well-designed perinatal mental healthcare app. The primary objective is to evaluate the effect of iCBT on reducing depression symptoms among pregnant Chinese women starting from their third trimester. The secondary objectives are to examine the effect of iCBT on anxiety, sleep quality, social support, parenting stress, co-parenting relationship, and infant development. DISCUSSION: This multi-center randomized controlled trial has been planned in accordance with best practices in behavioral trial design. The internet-based intervention addressed the needs of pregnant women during a major pandemic where face-to-face therapy is not preferable. The trial has a relatively large sample size with sufficient power to evaluate the efficacy of iCBT intervention for the primary and secondary outcomes. One year follow-up evaluation in the study is designed to determine the longer-term effect of the intervention on both maternal and infant outcomes. Although a limitation is the assessment of depression and anxiety using self-report measures, these easily incorporated and maternal-preferred assessments allow for real-life scalability if the intervention is proven to be effective. ETHICS AND DISSEMINATION: Ethics was approved by the institutional review board of International Peace Maternity and Child Health Hospital (GKLW2020-25). Dissemination of results will be published in peer-reviewed academic journals and presented at scientific conferences. TRIAL STATUS: The first patient was enrolled on 19 August 2020. To date, 203 participants have met eligibility requirements and been randomized to either the intervention group or control group. Data collection aims to be complete in September 2022. Date and version identifier: 2020715-version1.0. TRIAL REGISTRATION: ChiCTR2000033433. Registered 31 May 2020, http://www.chictr.org.cn/showproj.aspx?proj=54482 .

A differential diagnosis model for patients with COVID-19 and non-COVID-19 pneumonia based on laboratory indicators

OBJECTIVE: To retrospectively analyze the clinical characteristics, imaging features and laboratory indexes of the patients with COVID-19 and non-COVID-19 so as to seek for differential diagnosis indexes. METHODS: A total of 66 patients with COVID-19 and 40 non-COVID-19 patients were recruited as study subjects who were treated in the hospital from Jan 2020 to Apr 2020. The demographic data, clinical symptoms, underlying diseases, imaging features, length of hospital stay and laboratory test indexes at the admission were statistically analyzed. RESULTS: The white blood cell(WBC),albumin(ALB) and prealbumin(PALB) of the COVID-19 patients were remarkably lower than those of the non-COVID-19 patients;while the length of hospital stay, aspartate aminotransferase(AST), international normalized ratio(INR), fibrinogen(Fbg), lactate dehydrogenase(LDH), tumor specific growth factor(TSGF) and ferritin(Ferritin) of the COVID-19 group were remarkably higher than those of the non-COVID-19 group. The COVID-19 patients had a higher frequency of air bronchogram, reticular pattern, number of affected lobes and number of affected segments, but a lower frequency of centrilobular nodules than did the non-COVID-19 patients. The length of hospital stay of the COVID-19 patients was positively correlated with the age but was negatively correlated with LYM and ALB, and the length of hospital stay of the patients complicated with diabetes mellitus and hypertension was longer than the patients with other complications. Receiver operating characteristic(ROC) curve analysis showed that the areas under curves of WBC, TSGF, LDH and Ferritin were more than 75% in distinguishing between COVID-19 and non-COVID-19. Multivariate logistic regression analysis showed that TSGF, LDH and Ferritin were the independent factors for distinguishing between COVID-19 and non-COVID-19, and the area under curve of the joint detection of the three indexes was 0.9181. CONCLUSION: The ordinary COVID-19 patients and non-COVID-19 patients vary in some clinical characteristic, imaging features and clinical laboratory indexes. The joint diagnosis model of TSGF, LDH and Ferritin may be used as an effective indicator for distinguishing between ordinary COVID-19 and non-COVID-19.

Occupational Health and Wellness of Adult Women With Autism Spectrum Disorder During the COVID-19 Pandemic

Date Presented 03/31/2022 This quantitative survey study measured stress, engagement in meaningful activities, self-efficacy, quality of life, and coping among women with and without autism spectrum disorder (ASD) during the time of coronavirus disease 2019 (COVID-19). Statistical analysis revealed significant differences on all measures except engagement. These findings suggest a potential need for specialized OT support for women with ASD that may be especially desired when adapting to changes during and after COVID-19. Primary Author and Speaker: Yan-hua Huang Additional Authors and Speakers: Annika Lin, Teresa Lam, Alexandra Krizek, Jaclyn Ingram

Vertical Structure of Air Pollutant Transport Flux as Determined by Ground-Based Remote Sensing Observations in Fen-Wei Plain, China

Air pollutant transport plays an important role in local air quality, but field observations of transport fluxes, especially their vertical distributions, are very limited. We characterized the vertical structures of transport fluxes in central Luoyang, Fen-Wei Plain, China, in winter based on observations of vertical air pollutant and wind profiles using multi-axis differential optical absorption spectroscopy (MAX-DOAS) and Doppler wind lidar, respectively. The northwest and the northeast are the two privileged wind directions. The wind direction and total transport scenarios were dominantly the northwest during clear days, turning to the northeast during the polluted days. Increased transport flux intensities of aerosol were found at altitudes below 400 m on heavily polluted days from the northeast to the southwest over the city. Considering pollution dependence on wind directions and speeds, surface-dominated northeast transport may contribute to local haze events. Northwest winds transporting clean air masses were dominant during clean periods and flux profiles characterized by high altitudes between 200 and 600 m in Luoyang. During the COVID-19 lockdown period in late January and February, clear reductions in transport flux were found for NO2 from the northeast and for HCHO from the northwest, while the corresponding main transport altitude remained unchanged. Our findings provide better understandings of regional transport characteristics, especially at different altitudes.

Impact of Angiotensin-Converting Enzyme Inhibitors and Angiotensin Receptor Blockers on the Inflammatory Response and Viral Clearance in COVID-19 Patients.

Objectives: To evaluate the impact of angiotensin-converting enzyme inhibitors (ACEIs) or angiotensin receptor blockers (ARBs) on the inflammatory response and viral clearance in coronavirus disease 2019 (COVID-19) patients. Methods: We included 229 patients with confirmed COVID-19 in a multicenter, retrospective cohort study. Propensity score matching at a ratio of 1:3 was introduced to eliminate potential confounders. Patients were assigned to the ACEI/ARB group (n = 38) or control group (n = 114) according to whether they were current users of medication. Results: Compared to the control group, patients in the ACEI/ARB group had lower levels of plasma IL-1ß [(6.20 ± 0.38) vs. (9.30 ± 0.31) pg/ml, P = 0.020], IL-6 [(31.86 ± 4.07) vs. (48.47 ± 3.11) pg/ml, P = 0.041], IL-8 [(34.66 ± 1.90) vs. (47.93 ± 1.21) pg/ml, P = 0.027], and TNF-α [(6.11 ± 0.88) vs. (12.73 ± 0.26) pg/ml, P < 0.01]. Current users of ACEIs/ARBs seemed to have a higher rate of vasoconstrictive agents (20 vs. 6%, P < 0.01) than the control group. Decreased lymphocyte counts [(0.76 ± 0.31) vs. (1.01 ± 0.45)*109/L, P = 0.027] and elevated plasma levels of IL-10 [(9.91 ± 0.42) vs. (5.26 ± 0.21) pg/ml, P = 0.012] were also important discoveries in the ACEI/ARB group. Patients in the ACEI/ARB group had a prolonged duration of viral shedding [(24 ± 5) vs. (18 ± 5) days, P = 0.034] and increased length of hospitalization [(24 ± 11) vs. (15 ± 7) days, P < 0.01]. These trends were similar in patients with hypertension. Conclusions: Our findings did not provide evidence for a significant association between ACEI/ARB treatment and COVID-19 mortality. ACEIs/ARBs might decrease proinflammatory cytokines, but antiviral treatment should be enforced, and hemodynamics should be monitored closely. Since the limited influence on the ACEI/ARB treatment, they should not be withdrawn if there was no formal contraindication.

Nursing students' attitudes, knowledge, and willingness to receive the COVID-19 vaccine: A cross-sectional study (preprint)

Aim: To investigate nursing students' konwledge, attitudes and willingness to receive the COVID-19 vaccine, and the influencing factors. Background: Vaccination is one of the effective measures to prevent COVID-19, but the vaccination acceptance varies across countries and populations. As reserve nurses, nursing students have both the professionalism of medical personnel and the special characteristics of school students, their attitudes, knowledge, and willingness to receive the COVID-19 vaccine may greatly affect the vaccine acceptance of the population now and in the future. But little research has been done on vaccine acceptance among nursing students. Design: A cross-sectional survey of nursing students was conducted via online questionnaires in March 2021. Methods: Descriptive statistics, independent sample t tests/one-way ANOVA (normal distribution), Mann-Whitney U tests/Kruskal-Wallis H tests (skewness distribution) and multivariate linear regression were performed. Results: The score rate of attitude, knowledge and vaccination willingness were 70.07%, 80.70% and 84.38% respectively. Attitude was significantly influenced by family economic conditions and whether a family member had been vaccinated. The main factors influencing knowledge were gender, grade and academic background. In terms of willingness, gender, academic background, visits to risk areas, whether family members were vaccinated, and whether they had side effects were significant influencing factors. Conclusions: The vaccine acceptance of nursing students was fair. Greater focus needed to be placed on the males, those of younger age, with a science background, and having low grades, as well as on students whose family members had not received the COVID-19 vaccine or had side effects from the vaccine. Targeted intervention strategies were recommended to improve vaccination rates.

Spike mutations decrease SARS-CoV-2 sensitivity to neutralizing antibodies but not ACE2-Ig in vitro (preprint)

Spontaneous and selection-pressure-driven evolution of SARS-CoV-2 has started to pose more challenges to controlling the pandemic. Here, we first investigated cross-species receptor usage of an early SARS-CoV-2 isolate and multiple SARS-CoV-2 variants that emerged during the pandemic. We found that, in contrast to the early isolate, the circulating variants B.1.1.7/501Y.V1, B.1.351/501Y.V2, and P.1/501Y.V3 were able to use rat and mouse Ace2 orthologs as entry receptors, suggesting that rats and mice might be able to harbor and spread these variants. We then evaluated sensitivity of these variants to three therapeutic antibodies in clinics (CB6, casirivimab, and imdevimab) and an ACE2-Ig variant we developed recently. We found that all the tested variants developed resistance to at least one of the tested antibodies, but none of the variants showed resistance to ACE2-Ig. These data demonstrate that ACE2-Ig is a good drug candidate against SARS-CoV-2 variants that emerge over the course of the pandemic.

Qualitative and Quantitative Analysis of Ukrainian Iris Species: A Fresh Look on Their Antioxidant Content and Biological Activities

The major groups of antioxidant compounds (isoflavonoids, xanthones, hydroxycinnamic acids) in the rhizome methanol extracts of four Ukrainian Iris sp. (Iris pallida, Iris hungarica, Iris sibirica, and Iris variegata) were qualitatively and quantitatively analyzed using HPLC-DAD and UPLC-MS/MS. Gallic acid, caffeic acid, mangiferin, tectoridin, irigenin, iristectorigenin B, irisolidone, 5,6-dihydroxy-7,8,3′,5′-tetramethoxyisoflavone, irisolidone-7-O-β-d-glucopyranoside, germanaism B, and nigricin were recognized by comparing their UV/MS spectra, chromatographic retention time (tR) with those of standard reference compounds. I. hungarica and I. variegata showed the highest total amount of phenolic compounds. Germanaism B was the most abundant component in the rhizomes of I. variegata (7.089 ±0.032 mg/g) and I. hungarica (6.285 ±0.030 mg/g). The compound analyses showed good calibration curve linearity (r2 >0.999) and low detection and quantifications limit. These results validated the method for its use in the simultaneous quantitative evaluation of phenolic compounds in the studied Iris sp. I. hungarica and I. variegata rhizomes exhibited antioxidant activity, as demonstrated by the HPLC-ABTS system and NRF2 expression assay and anti-inflammatory activity on respiratory burst in human neutrophils. Moreover, the extracts showed anti-allergic and cytotoxic effects against cancer cells. Anti-coronavirus 229E and lipid formation activities were also evaluated. In summary, potent antioxidant marker compounds were identified in the examined Iris sp.

Novel serological biomarkers for inflammation in predicting disease severity in patients with COVID-19.

BACKGROUND: Patients with severe coronavirus disease 2019 (COVID-19) develop acute respiratory distress and multi-system organ failure and are associated with poor prognosis and high mortality. Thus, there is an urgent need to identify early diagnostic and prognostic biomarkers to determine the risk of developing serious illness. METHODS: We retrospectively analyzed 114 patients with COVID-19 at the Jinyintan Hospital, Wuhan based on their clinical and laboratory data. Patients were categorized into severe and mild to moderate disease groups. We analyzed the potential of serological inflammation indicators in predicting the severity of COVID-19 in patients using univariate and multivariate logistic regression, receiver operating characteristic curves, and nomogram analysis. The Spearman method was used to understand the correlation between the serological biomarkers and duration of hospital stay. RESULTS: Patients with severe disease had reduced neutrophils and lymphocytes; severe coagulation dysfunction; altered content of biochemical factors (such as urea, lactate dehydrogenase); elevated high sensitivity C-reactive protein levels, neutrophil-lymphocyte, platelet-lymphocyte, and derived neutrophil-lymphocyte ratios, high sensitivity C-reactive protein-prealbumin ratio (HsCPAR), systemic immune-inflammation index, and high sensitivity C-reactive protein-albumin ratio (HsCAR); and low lymphocyte-monocyte ratio, prognostic nutritional index (PNI), and albumin-to-fibrinogen ratio. PNI, HsCAR, and HsCPAR correlated with the risk of severe disease. The nomogram combining the three parameters showed good discrimination with a C-index of 0.873 and reliable calibration. Moreover, HsCAR and HsCPAR correlated with duration of hospital stay. CONCLUSION: Taken together, PNI, HsCAR, and HsCPAR may serve as accurate biomarkers for the prediction of disease severity in patients with COVID-19 upon admission/hospitalization.

Evaluation and improvement of the emergency capacity of medical staff for COVID-19: A cross-sectional study in China (preprint)

Background: Coronavirus disease 2019 (COVID-19) has spread to 216 countries and territories around the world. Most studies on response to public health emergencies, focus on health systems, local governments or medical organizations, but fewer studies focus on individuals. However, medical staff are the core strength for responding to public health emergencies. The aims of this study are to investigate the status of medical staff’s emergency capacity during the pandemic and to provide intellectual support to further enhance medical staff's ability to ensure the smooth operation of medical rescue. Methods: This study conducted a cross-sectional survey of four hospitals designated to treat patients with COVID-19 in China. Based on the emergency capacity system of medical staff for infectious diseases, an improved Emergency Preparedness Information Questionnaire was used to evaluate the emergency capacity of medical staff. Linear regression and one-way analysis of variance were used to test the differences in the emergency capacity of medical staff. Spearman correlation analysis was used to study the correlation between the self-efficacy and emergency capacity of medical staff. Results: The overall emergency capacity of the surveyed medical staff was at a medium level. There was a correlation between emergency capacity and age, working years, position, educational background and the area where medical staff worked. Emergency capacity was not related to the hospital grade. Emergency capacity was significantly related to whether medical staff had participated in frontline pandemic prevention work. There was also a positive correlation between emergency capacity and the self-efficacy of medical staff. Conclusions: The results highlight the importance of the training mechanism for emergency personnel. The emergency input for public health emergencies should be increased to improve the emergency capacity of medical staff. In addition, it is necessary to pay attention to the mental health of medical staff.

Controlling urban traffic-one of the useful methods to ensure safety in Wuhan based on COVID-19 outbreak.

Coronavirus disease 2019 (COVID-19) broke out in Wuhan, China. As of March 9, 2020, this epidemic has occurred in 102 countries and caused 3584 deaths with global serious concern. To cope with the outbreak, Chinese governments have strictly controlled urban traffic at all levels, especially in Wuhan. This article firstly reviews the urban traffic situation from January 23, 2020 to March 8, 2020, including safety problems of urban public transportation, traffic control methods, and emergency public transportation planning. Based on this, we present some emergency traffic control measures that are very urgent in the early stage of epidemic. Between cities, we strongly recommend blocking and controlling the flow of traffic in the early stage of epidemic. Inside a city, it is imperative to suspend the public transports, block all roads, restrict private cars, and close bridges and tunnels. Material isolation transfer stations are suggested to be established. A number of public transports should be organized to ensure transport of medical workers, patients, and daily necessities. We also give suggestions about the long-term planning and improvement methods. Considering the great success China has achieved in fighting COVID-19, we believe that this article offers a valuable reference of urban traffic control.

State-by-State prediction of likely COVID-19 scenarios in the United States and assessment of the role of testing and control measures (preprint)

Due to the heterogeneity among the States in the US, predicting COVID-19 trends and quantitatively assessing the effects of government testing capability and control measures need to be done via a State-by-State approach. We develop a comprehensive model for COVID-19 incorporating time delays and population movements. With key parameter values determined by empirical data, the model enables the most likely epidemic scenarios to be predicted for each State, which are indicative of whether testing services and control measures are vigorous enough to contain the disease. We find that government control measures play a more important role than testing in suppressing the epidemic. The vast disparities in the epidemic trends among the States imply the need for long-term placement of control measures to fully contain COVID-19.

Quantitative assessment of the role of undocumented infection in the 2019 novel coronavirus (COVID-19) pandemic (preprint)

An urgent problem in controlling COVID-19 spreading is to understand the role of undocumented infection. We develop a five-state model for COVID-19, taking into account the unique features of the novel coronavirus, with key parameters determined by the government reports and mathematical optimization. Tests using data from China, South Korea, Italy, and Iran indicate that the model is capable of generating accurate prediction of the daily accumulated number of confirmed cases and is entirely suitable for real-time prediction. The drastically disparate testing and diagnostic standards/policies among different countries lead to large variations in the estimated parameter values such as the duration of the outbreak, but such uncertainties have little effect on the occurrence time of the inflection point as predicted by the model, indicating its reliability and robustness. Model prediction for Italy suggests that insufficient government action leading to a large fraction of undocumented infection plays an important role in the abnormally high mortality in that country. With the data currently available from United Kingdom, our model predicts catastrophic epidemic scenarios in the country if the government did not impose strict travel and social distancing restrictions. A key finding is that, if the percentage of undocumented infection exceeds a threshold, a non-negligible hidden population can exist even after the the epidemic has been deemed over, implying the likelihood of future outbreaks should the currently imposed strict government actions be relaxed. This could make COVID-19 evolving into a long-term epidemic or a community disease a real possibility, suggesting the necessity to conduct universal testing and monitoring to identify the hidden individuals.