The effect of strict lockdown on Omicron SARS-CoV-2 variant transmission in Shanghai (preprint)

Background Omicron, the current SARS-CoV-2 variant of concern, is much more contagious than other previous variants. Whether strict lockdown could effectively curb the transmission of Omicron is largely unknown. Methods In this retrospective study, we compared the strictness of government lockdown policies in Shanghai and some countries. Based on the daily Omicron case number from March 1st 2022 to April 30th 2022, the effective reproductive numbers in this Shanghai Omicron wave were calculated to confirm the impact of strict lockdown on Omicron transmission. Pearson correlation was conducted to illustrate the determining factor of strict lockdown outcomes in the 16 different districts of Shanghai. Results After very strict citywide lockdown since April 1st, the average daily effective reproductive number reduced significantly, indicating that strict lockdown could slow down the spreading of Omicron. Omicron control is more challenging in districts with higher population mobility and lockdown is more likely to decrease the number of asymptomatic carrier than the symptomatic cases. Conclusions The strict lockdown could curb the transmission of Omicron effectively, especially for the asymptomatic spread. And urban city with extensive personnel movement is suggested to adopt this lockdown strategy at early stage to maximally control the virus transmission.

CT-Based Quantitative Assessment of Coronavirus Disease 2019 Using a Deep Learning-Based Segmentation System: A Longitudinal Study (preprint)

BackgroundCoronavirus disease 2019 (COVID-19) is a global catastrophic disease that has severely affected more than 185 countries. The key steps in fighting against COVID-19 involve early detection and tracking of the treatment effects. A large number of studies highlighted computed tomography (CT) as a reliable method for early diagnosis and follow-up monitoring of the disease. However, there are limited data on quantitative analysis of the follow-up images. In this study, we used a deep learning model using a neural network with high accuracy in automatic segmentation and quantification to analyze the infected lesions on chest CT images.MethodsWe used a deep learning model using a neural network with high accuracy in automatic segmentation and quantification to analyze the infected lesions on chest CT images. A total of 14 patients (mean age, 53±14 years; age range, 23–74 years; 42.9% men and 57.1% women) with confirmed mild-type COVID-19 from January 1 to May 7, 2020, were retrospectively reviewed. Initial and follow-up original CT images were collected, and CT quantitative parameters, including percentage of infection (POI) and density variation of pneumonia, were determined.ResultsThe median initial POI was 3.4% (interquartile range, IQR 0.5%–8.4%) for the whole lung, 0.8% (IQR 0.2%–6.7%) for the left lung, and 5.8% (IQR 0.5%–9.7%) for the right lung. The infection was more serious in the right than in the left lung. The infected region mainly involved bilateral lower lobes, more pronounced on the right side. Quantitative CT showed that POI significantly decreased throughout the follow-up period in all 14 patients (p < 0.001). Among them, 50% of the patients had a more significant decrease in POI (51.3%) after a negative nucleic acid test. Moreover, there was a significant decrease in the CT number range of ground-glass opacities (GGO) and consolidation (p < 0.001).ConclusionsThis study demonstrated the quantitative analysis of follow-up CT scans plays an important role in the monitoring of COVID-19 treatment, which could help in treatment planning and standardizing the assessment for discharge.

Therapeutic application of alpha-1-antitrypsin in COVID-19 (preprint)

Rationale: The treatment options for COVID-19 patients are sparse and do not show sufficient efficacy. Alpha-1-antitrypsin (AAT) is a multi-functional host-defense protein with anti-proteolytic and anti-inflammatory activities. Objectives: The aim of the present study was to evaluate whether AAT is a suitable candidate for treatment of COVID-19. Methods: AAT and inflammatory markers were measured in the serum of COVID-19 patients. Human cell cultures were employed to determine the cell-based anti-protease activity of AAT and to test whether AAT inhibits the host cell entry of vesicular stomatitis virus (VSV) particles bearing the spike (S) protein of SARS-CoV-2 and the replication of authentic SARS-CoV-2. Inhaled and / or intravenous AAT was applied to nine patients with mild-to-moderate COVID-19. Measurements and Main Results: The serum AAT concentration in COVID-19 patients was increased as compared to control patients. The relative AAT concentrations were decreased in severe COVID-19 or in non-survivors in ratio to inflammatory blood biomarkers. AAT inhibited serine protease activity in human cell cultures, the uptake of VSV-S into airway cell lines and the replication of SARS-CoV-2 in human lung organoids. All patients, who received AAT, survived and showed decreasing respiratory distress, inflammatory markers, and viral load. Conclusion: AAT has anti-SARS-CoV-2 activity in human cell models, is well tolerated in patients with COVID-19 and together with its anti-inflammatory properties might be a good candidate for treatment of COVID-19.

Single-cell analysis reveals the function of lung progenitor cells in COVID-19 patients (preprint)

The high mortality of severe 2019 novel coronavirus disease (COVID-19) cases is mainly caused by acute respiratory distress syndrome (ARDS), which is characterized by increased permeability of the alveolar epithelial barriers, pulmonary edema and consequently inflammatory tissue damage. Some but not all patients showed full functional recovery after the devastating lung damage, and so far there is little knowledge about the lung repair process1. Here by analyzing the bronchoalveolar lavage fluid (BALF) of COVID-19 patients through single cell RNA-sequencing (scRNA-Seq), we found that in severe (or critical) cases, there is remarkable expansion of TM4SF1+ and KRT5+ lung progenitor cells. The two distinct populations of progenitor cells could play crucial roles in alveolar cell regeneration and epithelial barrier re-establishment, respectively. In order to understand the function of KRT5+ progenitors in vivo, we transplanted a single KRT5+ cell-derived cell population into damaged mouse lung. Time-course single-cell transcriptomic analysis showed that the transplanted KRT5+ progenitors could long-term engrafted into host lung and differentiate into HOPX+ OCLN+ alveolar barrier cell which restored the epithelial barrier and efficiently prevented inflammatory cell infiltration. Similar barrier cells were also identified in some COVID-19 patients with massive leukocyte infiltration. Altogether this work uncovered the mechanism that how various lung progenitor cells work in concert to prevent and replenish alveoli loss post severe SARS-CoV-2 infection.

Diagnostic classification of coronavirus disease 2019 (COVID-19) and other pneumonias using radiomics features in CT chest images (preprint)

We propose a classification method using the radiomics features of CT chest images to identify patients with coronavirus disease 2019 (COVID-19) and other pneumonias. The chest CT images of two groups of participants (90 COVID-19 patients and 90 other pneumonias patients) were collected, and the two groups of data were manually drawn to outline the region of interest (ROI) of pneumonias. The radiomics method was used to extract textural features and histogram features of the ROI and obtain a radiomics features vector from each sample. Finally, using the radiomics features as an input, a support vector machine (SVM) model was constructed to classify patients with COVID-19 and patients with other pneumonias. This model used 20 rounds of 10-fold cross-validation for training and testing. In the COVID-19 patients, correlation analysis (multiple comparison correction—Bonferroni correction, p<0.05/7) was also conducted to determine whether the textural and histogram features were correlated with the laboratory test index of blood, i.e., blood oxygen, white blood cell, lymphocytes, neutrophils, C-reactive protein, hypersensitive C-reactive protein, and erythrocyte sedimentation rate. The results showed that the proposed method had a classification accuracy as high as 88.33%, sensitivity of 83.56%, specificity of 93.11%, and an area under the curve of 0.947. This proved that the radiomics features were highly distinguishable, and this SVM model can effectively identify and diagnose patients with COVID-19 and other pneumonias. The correlation analysis results showed that some texture features were positively correlated with WBC, NE, and CRP and also negatively related to SPO2H and NE.

Clinical symptoms and psychological changes of patients with COVID-19 in Jiangxi Province (preprint)

Objective The purpose of this study was to determine the prevalence and differences in etiology, clinical manifestations, and psychological activity of coronavirus disease-19 (COVID-19) among patients. Results We recruited 90 subjects, 30 were healthy controls, 30 were patients with moderate infection, and 30 were patients with severe/critical infections. No significant differences were noted in the sex ratio, mean age, body mass index, or blood type; however, the history of exposure of the patients with COVID-19 compared with healthy controls was noteworthy. The erythrocyte sedimentation rate, as well as the levels of C-reactive protein and serum amyloid A (SAA) were all increased. In terms of mental health, there were significant differences in the worry scores between severely and moderately infected patients and healthy controls. There was a significant difference in depression scores between patients with moderate infection and healthy hypertension, and there was also a significant difference in dream worry scores. Analysis of the Mini-Mental State Examination scores showed that for patients with moderate infection, the depression score was moderately and positively correlated with the dream anxiety score. For patients with severe infection, the anxiety score was positively correlated with the dream anxiety score, and the depression score was moderately and positively correlated with the dream anxiety score. Conclusion Patients with severe infection showed increased pain and sputum in the pharyngeal area compared with patients with moderate infection. Patients with blood type A may be more susceptible to COVID-19, and lymphopenia may indicate worsening of COVID-19.

Changes in the clinical characteristics of severe Corona Virus Disease 2019 in Jiangxi Province (preprint)

Backgrounds: To determine the differences in clinical manifestations and biomarker levels of Corona Virus Disease 2019 (COVID-19) patients, including common patients and severe (serious and critical) patients.Methods: A total of 89 COVID-19 patients were diagnosed and treated at the First Affiliated Hospital of Nanchang University. We clinically classified the patients and collected data. Findings: There was a higher proportion of confirmed cases in patients with type A blood (44.8%). There were no obvious differences in number of lung lobes involved in the lesion between the patients with or without a positive nucleic acid test (p>0.05).There were obvious differences in contact history (p<0.001), duration of symptoms (p=0.004), and respiratory rate (p=0.029) between the patients with or without a positive nucleic acid test. According to the results of the nucleic acid diagnosis test, there were no obvious differences in the number of lung lobes involved in the lesion and all items of routine blood, liver, and kidney function tests between the patients with or without positive nucleic acid tests (all p>0.05). Between the common patients and severe patients, there were obvious differences in age (p=0.006), duration of symptoms (p=0.001), diastolic blood pressure (p=0.046), lymphocyte count (p＜0.0001), neutrophil count (p=0.019), albumin (p=0.002), lactate dehydrogenase (p=0.007), calcium (p＜0.0001), C-reactive protein (CRP) (p=0.004), erythrocyte sedimentation rate (p=0.021), international standard ratio (p=0.020), and CD3 (p=0.001), CD3+CD4 (p=0.006), and CD3+CD8 (p=0.001) levels. In patients infected with SARS-COV-2, the number of lung lobes involved in the lesion were positively correlated with lymphocytes (R=0.261, p=0.044); the body mass index (BMI) values were positively correlated with the number of lung lobes involved in the lesion (R=0.320, P=0.034); the age (R=0.391, p<0.001) and respiratory rate (R=0.352, p=0.001) were positively correlated with neutrophil count; and the age (R=0.349, p=0.001) and the number of lung lobes involved in the lesion (R=0.422, p=0.001) were positively correlated with CRP.Conclusion: Patients with blood type A may be more susceptible to SARS-COV-2. The decrease in lymphocytes may indicate the aggravation of COVID-19, whereas the number of lung lobes involved in the lesion may not be a valid criterion for COVID-19 diagnosis.

Single-cell RNA expression profiling of ACE2, the putative receptor of Wuhan 2019-nCov (preprint)

A novel coronavirus SARS-CoV-2 was identified in Wuhan, Hubei Province, China in December of 2019. According to WHO report, this new coronavirus has resulted in 76,392 confirmed infections and 2,348 deaths in China by 22 February, 2020, with additional patients being identified in a rapidly growing number internationally. SARS-CoV-2 was reported to share the same receptor, Angiotensin-converting enzyme 2 (ACE2), with SARS-CoV. Here based on the public database and the state-of-the-art single-cell RNA-Seq technique, we analyzed the ACE2 RNA expression profile in the normal human lungs. The result indicates that the ACE2 virus receptor expression is concentrated in a small population of type II alveolar cells (AT2). Surprisingly, we found that this population of ACE2-expressing AT2 also highly expressed many other genes that positively regulating viral entry, reproduction and transmission. This study provides a biological background for the epidemic investigation of the COVID-19, and could be informative for future anti-ACE2 therapeutic strategy development.