No increase in body mass index in a healthy Chinese population during the COVID-19 outbreak (preprint)

Background The Coronavirus Disease 2019 (COVID-19) epidemic continues to spread worldwide. This study aimed to investigate (1) the change in body mass index (BMI) before and after the COVID-19 outbreak and (2) the impact of behaviours on BMI during the quarantine period. Methods We recruited 197 healthy adults who underwent a physical examination within two months after the Spring Festival holidays of 2018, 2019 and 2020 in Taizhou, China. Of them, 138 respondents answered a questionnaire on lifestyle behaviours during the quarantine period. Univariate analysis and multiple logistic regression models were used to analyse the impact of behaviours during the quarantine period on changes in BMI. Results The average BMI of the population increased from 2018 to 2019 (P<0.05) and then decreased from 2019 to 2020 (P>0.05). The proportion of BMI increase after the COVID-19 outbreak was significantly lower than that in the previous year (41.6% vs. 59.4%, paired χ2=8.151, P=0.002). Young age and living in an urban area were risk factors for a BMI increase in men from 2019 to 2020 (P<0.05), while the habit of eating late-night snacks increased the risk of higher BMI in women (OR=6.11, 95% CI: 1.87–19.98, P<0.05). Conclusions The results of this study demonstrated that there was no significant increase in BMI among the healthy population during the COVID-19 outbreak. Late-night snacking should be discouraged to prevent BMI increases, especially in at-risk women. Level of Evidence: Level III，well-designed cohort

Satellite-based estimates of daily NO2 exposure in urban agglomerations of China and application to spatio-temporal characteristics of hotspots

The analysis of the daily spatial patterns of near-surface Nitrogen dioxide (NO2) concentrations can assist decision makers mitigate this common air pollutant in urban areas. However, comparative analysis of NO2 estimates in different urban agglomerations of China is limited. In this study, a new linear mixed effect model (LME) with multi-source spatiotemporal data is proposed to estimate daily NO2 concentrations at high accuracy based on the land-use regression (LUR) model and Ozone Monitoring Instrument (OMI) and TROPOspheric Monitoring Instrument (TROPOMI) products. In addition, three models for NO2 concentration estimation were evaluated and compared in four Chinese urban agglomerations from 2018 to 2020, including the COVID-19 closed management period. Each model included a unique combination of methods and satellite NO2 products: ModelⅠ: LUR model with OMI products;Model Ⅱ: LUR model with TropOMI products;Model Ⅱ: LME model with TropOMI products. The results show that the LME model outperformed the LUR model in all four urban agglomerations as the average RMSE decreased by 16.09% due to the consideration of atmospheric dispersion random effects, and using TropOMI instead of OMI products can improve the accuracy. Based on our NO2 estimations, pollution hotspots were identified, and pollution anomalies during the COVID-19 period were explored for two periods;the lockdown and revenge pollution periods. The largest NO2 pollution difference between the hotspot and non-hotspot areas occurred in the second period, especially in the heavy industrial urban agglomerations.

WeChat users’ debunking strategies in response to COVID-19 conspiracy theories: A mixed-methods study

The current study adopted a mixed-methods approach to examine both qualitative and quantitative data of Chinese WeChat users? strategies in response to COVID-19 conspiracy theories disseminated in WeChat. Thematic analysis based on 30 interviewees suggested interesting patterns about how such conspiracy theories were disseminated based on relationship types within WeChat groups and how different types of debunking strategies were used to counter conspiracy theories based on the relational outcomes and contexts. Quantitative data based on 588 participants suggested COVID-19 information exposures from different sources, conspiracy beliefs, exposures of conspiracy beliefs and face concerns influence WeChat users? responses to address COVID-19-related information in WeChat platform.

Feasibility analysis and mechanism exploration of Rhei Radix et Rhizome-Schisandrae Sphenantherae Fructus (RS) against COVID-19.

Introduction. As a novel global epidemic, corona virus disease 2019 (COVID-19) caused by SARS-CoV-2 brought great suffering and disaster to mankind. Recently, although significant progress has been made in vaccines against SARS-CoV-2, there are still no drugs for treating COVID-19. It is well known that traditional Chinese medicine (TCM) has achieved excellent efficacy in the treatment of COVID-19 in China. As a treasure-house of natural drugs, Chinese herbs offer a promising prospect for discovering anti-COVID-19 drugs.Hypothesis/Gap Statement. We proposed that Rhei Radix et Rhizome-Schisandrae Sphenantherae Fructus (RS) may have potential value in the treatment of COVID-19 patients by regulating immune response, protecting the cardiovascular system, inhibiting the production of inflammatory factors, and blocking virus invasion and replication processes.Aim. We aimed to explore the feasibility and molecular mechanisms of RS against COVID-19, to provide a reference for basic research and clinical applications.Methodology. Through literature mining, it is found that a Chinese herbal pair, RS, has potential anti-COVID-19 activity. In this study, we analysed the feasibility of RS against COVID-19 by high-throughput molecular docking and molecular dynamics simulations. Furthermore, we predicted the molecular mechanisms of RS against COVID-19 based on network pharmacology.Results. We proved the feasibility of RS anti-COVID-19 by literature mining, virtual docking and molecular dynamics simulations, and found that angiotensin converting enzyme 2 (ACE2) and 3C-like protease (3 CL pro) were also two critical targets for RS against COVID-19. In addition, we predicted the molecular mechanisms of RS in the treatment of COVID-19, and identified 29 main ingredients, 21 potential targets and 16 signalling pathways. Rhein, eupatin, (-)-catechin, aloe-emodin may be important active ingredients in RS. ALB, ESR1, EGFR, HMOX1, CTSL, and RHOA may be important targets against COVID-19. Platelet activation, renin secretion, ras signalling pathway, chemokine signalling pathway, and human cytomegalovirus infection may be important signalling pathways against COVID-19.Conclusion. RS plays a key role in the treatment of COVID-19, which may be closely related to immune regulation, cardiovascular protection, anti-inflammation, virus invasion and replication processes.

Genetic characteristics and nucleic acid detection results of SARS-CoV-2 in 2297 clinical samples

Objective To analyze the genomics characteristics and nucleic acid detection results of the severe Acute respiratory syndrome coronavirus 2（SARS-CoV-2） in 2 297 clinical samples collected in January and February, 2020 in Laboratory of Microbiology of Changsha Municipal Center for Disease Control and Prevention. Methods Viral RNA of throat swabs or respiratory tract specimens of coronavirus disease 2019（COVID-19） suspected cases from January 19, 2020 to February 29, 2020 was extracted and SARS-CoV-2 nucleic acid was detected by real-time reverse transcription polymerase chain reaction.The full length genome of SARS-CoV-2 in positive samples was enriched by using viral genome capture kit and sequenced on Illumina MiSeq platform.The raw reads were mapped and aligned with SPAdes software v 3.13.0.Reference SARS-CoV-2 sequences were obtained from GISAID（https://www.gisaid.org） andviral genetic evolution and antigen variation were analyzed. Results A total of 215 SARS-Co V2-nucleic acid positive samples were identified from 2 297 clinical samples.Among the SARS-Co V2-positive samples, 110 were males and 105 were from females.The male to female ratio was 1.05∶1.The highest positive rate was among 40-<60 years old people（11.35%） and the lowest positive rate was in children under 6 years old（5.49%）.The peak of newly confirmed cases was in the 5 th week（January 26 to February 1, 2020） and then decreased.There was no newly positive case after February 25, 2020.Five SARS-Co V2-whole genome sequences were obtained and there were 4 to 6 nucleotide mutations compared to the Wuhan reference strain, and the homology was more than 99.90%.Most mutations occurred only once except C8782 T and T28144 C, indicating random mutations.Phylogenetic analysis revealed that the 5 sequences belonged to the L/B or S/A lineages and were highly homologous with strains prevalent in other provinces of China at the same time. Conclusions With the quick nucleic acid tests and quarantine measures, the SARS-Co V2-positive cases in Changsha began to decline after a 2-week increasing period, and there was no new confirmed cases 6 weeks later.The genomes of SARS-Co V-2 prevalent in Changsha are highly homology with the Wuhan strains in the early 2020 and no obvious mutation is found in the local pandemic period. Reset

Long-term stability and protection efficacy of the RBD-targeting COVID-19 mRNA vaccine in nonhuman primates.

Messenger RNA (mRNA) vaccine technology has shown its power in preventing the ongoing COVID-19 pandemic. Two mRNA vaccines targeting the full-length S protein of SARS-CoV-2 have been authorized for emergency use. Recently, we have developed a lipid nanoparticle-encapsulated mRNA (mRNA-LNP) encoding the receptor-binding domain (RBD) of SARS-CoV-2 (termed ARCoV), which confers complete protection in mouse model. Herein, we further characterized the protection efficacy of ARCoV in nonhuman primates and the long-term stability under normal refrigerator temperature. Intramuscular immunization of two doses of ARCoV elicited robust neutralizing antibodies as well as cellular response against SARS-CoV-2 in cynomolgus macaques. More importantly, ARCoV vaccination in macaques significantly protected animals from acute lung lesions caused by SARS-CoV-2, and viral replication in lungs and secretion in nasal swabs were completely cleared in all animals immunized with low or high doses of ARCoV. No evidence of antibody-dependent enhancement of infection was observed throughout the study. Finally, extensive stability assays showed that ARCoV can be stored at 2-8 °C for at least 6 months without decrease of immunogenicity. All these promising results strongly support the ongoing clinical trial.

Mucosal Cytokine Profiles in Children with COVID-19

Background The mechanisms associated with COVID-19 in children are not well understood. We sought to define the differences in nasopharyngeal (NP) cytokine profiles according to clinical presentation in children with COVID-19. Methods Single-center, prospective study in 137 children and adolescents < 21 years of age hospitalized with COVID-19, and 35 age, sex and race matched pre-pandemic (2016-2019) healthy controls. Children with COVID-19 were categorized according to their clinical presentation in: COVID-19-symptomatic;COVID-19-screening, and multisystem inflammatory syndrome (MIS-C). NP swabs were obtained within 24 hours of admission to measure SARS-CoV-2 loads by rt-PCR, and a 92-cytokine panel. Unsupervised and supervised analysis adjusted for multiple comparisons were performed. Results From 3/2020 to 1/2021, we enrolled 76 COVID-19-symptomatic children (3.5 [0.2-15.75] years);45 COVID-19-screening (11.1 [4.2-16.1] years), and 16 MIS-C (11.2 [5.9-14.6] years). Median NP SARS-CoV-2 loads were higher in COVID-19-symptomatic versus screening and MIS-C (6.8 vs 3.5 vs 2.82 log10 copies/mL;p< 0.001). Statistical group comparisons identified 15 cytokines that consistently differed between groups and were clustered in three functional categories: (1) antiviral/regulatory, (2) pro-inflammatory/chemotactic, and (3) a combination of (1) and (2);(Fig 1). All 15 cytokines were higher in COVID-19-symptomatic versus controls (p< 0.05). Similarly, and except for TNF, CCL3, CCL4 and CCL23, which were comparable in COVID-19-symptomatic and screening patients, the remaining cytokines were higher in symptomatic children (p< 0.05). PDL-1 (p=0.01) and CCL3 (p=0.03) were the only cytokines significantly decreased in children with MIS-C versus symptomatic COVID-19 children. The 15 cytokines identified by multiple comparisons were correlated using Person’s in R software. Red reflects a positive correlation and blue a negative correlation with the intensity of the color indicating the strength of the association. Conclusion Children with symptomatic COVID-19 demonstrated higher viral loads and greater mucosal cytokines concentrations than those identified via screening, whereas in MIS-C concentrations of regulatory cytokines were decreased. Simultaneous evaluation of viral loads and mucosal immune responses using non-invasive sampling could aid with the stratification of children and adolescents with COVID-19 in the clinical setting. Disclosures Octavio Ramilo, MD, Adagio (Consultant)Bill & Melinda Gates Foundation (Grant/Research Support)Janssen (Grant/Research Support)Lilly (Consultant)Merck (Consultant, Grant/Research Support)NIH (Grant/Research Support)Pfizer (Consultant)SANOFI (Board Member) Asuncion Mejias, MD, PhD, MsCS, Janssen (Grant/Research Support, Advisor or Review Panel member)Merck (Grant/Research Support, Advisor or Review Panel member)Roche (Advisor or Review Panel member)Sanofi (Advisor or Review Panel member).

Generalized additive mixed model to evaluate the association between total pulmonary infection volume and volume ratio, and clinical types, in patients with COVID-19 pneumonia: a propensity score analysis.

OBJECTIVES: To investigate the association between longitudinal total pulmonary infection volume and volume ratio over time and clinical types in COVID-19 pneumonia patients. METHODS: This retrospective review included 367 patients with COVID-19 pneumonia. All patients underwent CT examination at baseline and/or one or more follow-up CT. Patients were categorized into two clinical types (moderate and severe groups). The severe patients were matched to the moderate patients via propensity scores (PS). The association between total pulmonary infection volume and volume ratio and clinical types was analyzed using a generalized additive mixed model (GAMM). RESULTS: Two hundred and seven moderate patients and 160 severe patients were enrolled. The baseline clinical and imaging variables were balanced using PS analysis to avoid patient selection bias. After PS analysis, 172 pairs of moderate patients were allocated to the groups; there was no difference in the clinical and CT characteristics between the two groups (p > 0.05). A total of 332 patients, including 396 CT scans, were assessed. The impact of total pulmonary infection volume and volume ratio with time was significantly affected by clinical types (p for interaction = 0.01 and 0.01, respectively) using GAMM. Total pulmonary infection volume and volume ratio of the severe group increased by 14.66 cm3 (95% confidence interval [CI]: 3.92 to 25.40) and 0.45% (95% CI: 0.13 to 0.77) every day, respectively, compared to that of the moderate group. CONCLUSIONS: Longitudinal total pulmonary infection volume and volume ratio are independently associated with the clinical types of COVID-19 pneumonia. KEY POINTS: • The impact of total pulmonary infection volume and volume ratio over time was significantly affected by the clinical types (p for interaction = 0.01 and 0.01, respectively) using the GAMM. • Total pulmonary infection volume and volume ratio of the severe group increased by 14.66 cm3 (95% CI: 3.92 to 25.40) and 0.45% (95% CI: 0.13 to 0.77) every day, respectively, compared to that of the moderate group.

Perioperative Mortality and Complications in Patients with COVID-19 Undergoing Surgery: A Meta-Regression and Meta-Analysis of 8 Cohort Studies (preprint)

Objectives: The novel coronavirus pneumonia (COVID-19)，spread rapidly world wide, was first reported in December 2019. Meanwhile, there are still a large number of patients who need to undergo various surgical treatments. However, the consensus on whether patients with COVID-19 receive emergency or elective surgery will influence their perioperative mortality and complications still cannot be reached. Therefore, we used meta-analysis to explore the impact of patients with COVID-19 perioperative mortality and complications, aiming to provide evidence for clinical decision-making.Methods: We searched PubMed, Embase, Web of Science, Wan Fang database, date from December 2019 to July 2020 for collecting clinical trail on the impact of patients with COVID-19 perioperative mortality and complications. According to the Cochrane system evaluation method, the data is meta-analyzed with RevMan5.3 software.Results: Eight studies involving 2037 patients, 261 (12.81%) patients with COVID-19 and 1776(87.19%) without COVID-19, were included. The results of meta-analysis showed: the COVID-19 group vs Non-COVID-19 group , perioperative mortality and postoperative pneumonia syndrome increased in COVID-19 group（OR:3.84，95%CI：2.10-7.02，I2 =46%， P <0.0001）, (OR: 33.42，95%CI：15.49-72.07，I 2 =0%， P <0.00001), The number of postoperative fever were significantly higher in COVID-19 , There were no significant difference in postoperative complications and ICU admission between the two groups.Conclusions: In our study, The risk of perioperative death and postoperative pulmonary is significantly increased in patients with COVID-19. These data suggested that consideration should be taken for postponing non-critical procedures and promoting nonoperative treatment to delay or avoid the need for surgery during the pandemic of COVID-19.Funding Statement: Natural Science Foundation of China, Grant number: 31760327/ 81760191Declaration of Interests: The authors declare no competing interests.

Risk factors for illness severity in patients with COVID-19 pneumonia: a prospective cohort study (preprint)

Background Although COVID-19 pneumonia is spreading internationally, knowledge regarding the factors associated with the illness severity of patients remains limited. We aimed to identify the factors associated with the disease severity of patients with COVID-19 pneumonia induced by a novel coronavirus, severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Methods We prospectively enrolled a single-center case series of adult patients with COVID-19 admitted to the Infectious Disease Hospital of Jining, Jining City, Shandong Province, China, from January 24 to March 1, 2020. Demographics, clinical characteristics, and laboratory findings were compared to investigate the risk factors related with the disease severity of COVID-19 pneumonia patients. Results We included a total of 78 patients with COVID-19 pneumonia, of whom 6 had the severe type. As compared to a moderately ill cohort, our analysis showed that shortness of breath, fatigue, neutrophil percentages > 70%, neutrophil counts > 6.3 × 10 9 /L, lymphocyte percentages < 20%, lymphocyte counts < 1.0 × 10 9 /L, platelet < 100 × 10 9 /L, C-reactive protein (CRP) > 10 mg/L, neutrophil to platelet ratio (NPR) > 2.3, neutrophil to lymphocyte ratio (NLR) > 3.9, aspartate aminotransferase (AST) > 40 U/L, albumin < 40 g/L, lactate dehydrogenase (LDH) > 245 U/L, and glucose > 6.1 mmol/L were predictors of disease severity in COVID-19 pneumonia. In the sex-, age-, and comorbid illness-matched case-control study, neutrophil percentages > 70%, neutrophil counts > 6.3 × 10 9 /L, lymphocyte percentages < 20%, NPR > 2.3, NLR > 3.9, albumin < 40 g/L, and LDH > 245 U/L remained associated with the early detection and identification of severe patients. Conclusion We demonstrated that neutrophil percentages > 70%, neutrophil counts > 6.3×10 9 /L, lymphocyte percentages < 20%, NPR > 2.3, NLR > 3.9, albumin < 40 g/L, and LDH > 245 U/L might predict the severity of illness in patients with COVID-19 pneumonia.

Radiomics nomogram for the prediction of 2019 novel coronavirus pneumonia caused by SARS-CoV-2.

OBJECTIVES: To develop and validate a radiomics model for predicting 2019 novel coronavirus (COVID-19) pneumonia. METHODS: For this retrospective study, a radiomics model was developed on the basis of a training set consisting of 136 patients with COVID-19 pneumonia and 103 patients with other types of viral pneumonia. Radiomics features were extracted from the lung parenchyma window. A radiomics signature was built on the basis of reproducible features, using the least absolute shrinkage and selection operator method (LASSO). Multivariable logistic regression model was adopted to establish a radiomics nomogram. Nomogram performance was determined by its discrimination, calibration, and clinical usefulness. The model was validated in 90 consecutive patients, of which 56 patients had COVID-19 pneumonia and 34 patients had other types of viral pneumonia. RESULTS: The radiomics signature, consisting of 3 selected features, was significantly associated with COVID-19 pneumonia (p < 0.05) in both training and validation sets. The multivariable logistic regression model included the radiomics signature and distribution; maximum lesion, hilar, and mediastinal lymph node enlargement; and pleural effusion. The individualized prediction nomogram showed good discrimination in the training sample (area under the receiver operating characteristic curve [AUC], 0.959; 95% confidence interval [CI], 0.933-0.985) and in the validation sample (AUC, 0.955; 95% CI, 0.899-0.995) and good calibration. The mixed model achieved better predictive efficacy than the clinical model. Decision curve analysis demonstrated that the radiomics nomogram was clinically useful. CONCLUSIONS: The radiomics model derived has good performance for predicting COVID-19 pneumonia and may help in clinical decision-making. KEY POINTS: • A radiomics model showed good performance for prediction 2019 novel coronavirus pneumonia and favorable discrimination for other types of pneumonia on CT images. • A central or peripheral distribution, a maximum lesion range > 10 cm, the involvement of all five lobes, hilar and mediastinal lymph node enlargement, and no pleural effusion is associated with an increased risk of 2019 novel coronavirus pneumonia. • A radiomics model was superior to a clinical model in predicting 2019 novel coronavirus pneumonia.

Relationship between clinical types and radiological subgroups defined by latent class analysis in 2019 novel coronavirus pneumonia caused by SARS-CoV-2.

OBJECTIVES: To investigate whether meaningful subgroups sharing the CT features of patients with COVID-19 pneumonia could be identified using latent class analysis (LCA) and explore the relationship between the LCA-derived subgroups and clinical types. METHODS: This retrospective review included 499 patients with confirmed COVID-19 pneumonia between February 11 and March 8, 2020. Subgroups sharing the CT features were identified using LCA. Univariate and multivariate logistic regression models were utilized to analyze the association between clinical types and the LCA-derived subgroups. RESULTS: Two radiological subgroups were identified using LCA. There were 228 subjects (45.69%) in class 1 and 271 subjects (54.31%) in class 2. The CT findings of class 1 were smaller pulmonary infection volume, more peripheral distribution, more GGO, more maximum lesion range ≤ 5 cm, a smaller number of lesions, less involvement of lobes, less air bronchogram, less dilatation of vessels, less hilar and mediastinal lymph node enlargement, and less pleural effusion than the CT findings of class 2. Univariate analysis demonstrated that older age, therapy, presence of fever, presence of hypertension, decreased lymphocyte count, and increased CRP levels were significant parameters associated with an increased risk for class 2. Multivariate analyses revealed that the patients with clinically severe type disease had a 1.97-fold risk of class 2 than the patients with clinically moderate-type disease. CONCLUSIONS: The demographic and clinical differences between the two radiological subgroups based on the LCA were significantly different. Two radiological subgroups were significantly associated with clinical moderate and severe types. KEY POINTS: • Two radiological subgroups were identified using LCA. • Older age, therapy, presence of fever, presence of hypertension, decreased lymphocyte count, and increased CRP levels were significant parameters with an increased risk for class 2 defined by LCA. • Patients with clinically severe type had a 1.97-fold higher risk of class 2 defined by LCA in comparison with patients showing clinically moderate-type disease.

Comparison of chest CT findings between COVID-19 pneumonia and other types of viral pneumonia: a two-center retrospective study.

OBJECTIVES: To compare the pulmonary chest CT findings of patients with COVID-19 pneumonia with those with other types of viral pneumonia. METHODS: This retrospective review includes 154 patients with RT-PCR-confirmed COVID-19 pneumonia diagnosed between February 11 and 20, 2020, and 100 patients with other types of viral pneumonia diagnosed between April 2011 and December 2020 from two hospitals. High-resolution CT (HRCT) of the chest was performed. Data on location, distribution, attenuation, maximum lesion range, lobe involvement, number of lesions, air bronchogram signs, Hilar and mediastinal lymph node enlargement, and pleural effusion were collected. Associations between imaging characteristics and COVID-19 pneumonia were analyzed with univariate and multivariate logistic regression models. RESULTS: A peripheral distribution was associated with a 13.04-fold risk of COVID-19 pneumonia, compared with a diffuse distribution. A maximum lesion range > 10 cm was associated with a 9.75-fold risk of COVID-19 pneumonia, compared with a maximum lesion range ≤ 5 cm, and the involvement of 5 lobes was associated with an 8.45-fold risk of COVID-19 pneumonia, compared with a maximum lesion range ≤ 2. No pleural effusion was associated with a 3.58-fold risk of COVID-19 pneumonia compared with the presence of pleural effusion. Hilar and mediastinal lymph node enlargement was associated with a 2.79-fold risk of COVID-19 pneumonia. CONCLUSION: A peripheral distribution, a lesion range > 10 cm, involvement of 5 lobes, presence of hilar and mediastinal lymph node enlargement, and no pleural effusion were significantly associated with 2019-novel coronavirus pneumonia. KEY POINTS: • A peripheral distribution, a lesion range > 10 cm, involvement of 5 lobes, presence of hilar and mediastinal lymph node enlargement, and no pleural effusion were significantly associated with COVID-19 compared with other types of viral pneumonia.