Integrated histopathology, spatial and single cell transcriptomics resolve cellular drivers of early and late alveolar damage in COVID-19 (preprint)

The most common cause of death due to COVID-19 remains respiratory failure. Yet, our understanding of the precise cellular and molecular changes underlying lung alveolar damage is limited. Here, we integrate single cell transcriptomic data of COVID-19 donor lungs with spatial transcriptomic data stratifying histopathological stages of diffuse alveolar damage (DAD). We identify changes in cellular composition across progressive DAD, including waves of molecularly distinct macrophages and depleted epithelial and endothelial populations throughout different types of tissue damage. Predicted markers of pathological states identify immunoregulatory signatures, including IFN-alpha and metallothionein signatures in early DAD, and fibrosis-related collagens in organised DAD. Furthermore, we predict a fibrinolytic shutdown via endothelial upregulation of SERPINE1/PAI-1. Cell-cell interaction analysis revealed macrophage-derived SPP1/osteopontin signalling as a key regulator during early DAD. These results provide the first comprehensive, spatially resolved atlas of DAD stages, highlighting the cellular mechanisms underlying pro-inflammatory and pro-fibrotic pathways across alveolar damage progression.

The Relationship Between Mindfulness, Fatigue, and Perceived Symptoms Among Frontline Nurses Who Performed Nucleic Acid Sample Collection During the COVID-19 in China: A Cross-Sectional Study.

Objective: Given the immense stress faced by medical staff during the COVID-19 pandemic, this study aimed to evaluate the relationship between mindful attention awareness, fatigue, and perceived symptoms among frontline nurses who performed nucleic acid sample collection during the COVID-19 pandemic, to reduce their fatigue and help them cope with perceived uncomfortable symptoms. Methods: A convenience sampling method was used to survey nurses who travelled to Hainan for nucleic acid sampling in August 2022 using an online (WeChat) questionnaire. A total of 514 frontline nurses who performed nucleic acid tests completed the questionnaire. The questionnaire covered basic demographic information, Mindful Attention Awareness Scale (MAAS) ratings, and Fatigue Severity Scale (FSS) ratings. Spearman correlation analysis was used to separate the relationship between MASS and FSS, and univariate and multivariate factor analyses were used to explore the relevant influences contributing to the occurrence of fatigue. Results: A total of 514 individuals completed the survey,93.97% (n=483) were female, mean age was 31.15 ± 5.7, MASS score was 69.01 ± 13.53, and 296 (57.59%) nurses experienced symptoms of fatigue during the auxiliary period. Spearman correlation analysis showed that FSS was associated with MASS. Multifactorial analysis showed that sex, age, marital status, fertility status, years of work, adaptation to dietary habits, hidrorrhea, and MAAS scores affected the presence of fatigue symptoms among the medical staff in Hainan (P<0.05). Conclusion: The psychological status of frontline nurses undergoing nucleic acid testing during the pandemic was poor, and the appearance of fatigue symptoms could be effectively reduced by increasing levels of positive thinking among medical staff to help them cope with public health emergencies.

Results of the Adult COVID-19 Lifestyle Matching Study.

Objective: The aim of our case-control study was to find the influence of lifestyle and comorbidities on COVID-19 susceptibility, identify risk factors and protective factors, and identify ways to encourage people to adopt a healthy lifestyle. Methods: Patients with COVID-19 were matched with non-COVID-19 participants in a ratio of 1:2. Univariate analysis was performed using the chi-square test, and multivariate analysis was performed using conditional logistic regression. Results: Multivariate analysis using conditional logistic regression found that alcohol consumption (AC) and a bland diet increased the risk of COVID-19, while college degrees and above, smoking, drinking tea, and exercise, especially walking, significantly reduced the risk of COVID-19. Conclusion: After removing the effects of demographic factors, the study demonstrated that AC significantly reduced the ability of the body to resist COVID-19 infection. Moreover, following a bland diet increased the susceptibility to COVID-19. Notably, people who drank tea and performed regular exercises, especially walking, were significantly less likely to be infected with COVID-19. College degree or above relative illiteracy is COVID-19 protective factors of infection.

A case report of laryngeal edema caused by COVID-19 (preprint)

Background Laryngeal edema is caused by the exudation of submucosal tissue fluid from the laxity of the pharynx and can lead to obstruction of the upper airway. It is commonly caused by post-extubation, drug allergy, and bacterial infection. During the current COVID-19 pandemic situation, laryngeal edema is a relatively rare but fatal complication of COVID-19. Taking measures to prevent laryngeal edema can reduce the incidence of sudden life-threatening events in the course of treatment.Case presentation: Here, we report a case in a Chinese male with COVID-19 complicated with laryngeal edema. The initial diagnosis of COVID-19 was followed by a sudden onset of inspiratory dyspnea during hospitalization. At the time of tracheal intubation, laryngeal edema was seen, and a positive bacterial culture suggested a secondary bacterial infection.Conclusion We report a rare case of laryngeal edema complicated by COVID-19. The patient recovered after prompt intubation and treatment. Close monitoring of patients' inflammation indicators and auxiliary bacterial monitoring can effectively prevent the occurrence of laryngeal edema caused by COVID-19.

The Collateral Impact of the COVID-19 Pandemic on HPV-positive Oropharyngeal Cancer Diagnosis

Purpose We aim to assess the potential impact of the COVID-19 pandemic on diagnostic delays in HPV-positive oropharyngeal cancer (OPC), and to describe their underlying reasons. Methods All HPV+ OPC referred to a tertiary cancer centre and diagnosed between June-December 2019 (Pre-Pandemic cohort) vs June-December 2020 (Pandemic cohort) were reviewed. TNM classification, gross-tumor-volumes (GTV) and intervals between sign/symptom onset and treatment initiation were compared between the cohorts. Reasons for delay (>6 months from onset of signs/symptoms to a positive biopsy of the primary tumor, or a delay specifically mentioned in the patient chart) in establishing the diagnosis were recorded per clinician's documentation, and categorized as COVID-related or non-COVID-related. Results A total of 157 consecutive HPV+ OPC patients were identified (Pre-Pandemic: 92;Pandemic: 65). Compared to the Pre-Pandemic cohort, Pandemic cohort patients had a higher proportion of N2-N3 (32% vs 15%, p=0.019) and stage III (38% vs 23%, p=0.034) disease at presentation. The differences in proportions with >6 months delay from symptom onset to establishing the diagnosis (29% vs 20%, p=0.16) or to first treatment (49% vs 38%, p=0.22) were not statistically different. 47% of diagnostic delays in the Pandemic cohort were potentially attributable to COVID-19. Conclusion We observed a collateral impact of the COVID-19 pandemic on HPV+ OPC care through more advanced stage at presentation and a non-significant but numerically longer interval to diagnosis. This could adversely impact patient outcomes and future resource allocation. Both COVID-19-related or unrelated factors contribute to diagnostic delay. Tailored interventions to reduce delays are warranted.

Explainable Artificial Intelligence Methods in Combating Pandemics: A Systematic Review.

Despite the myriad peer-reviewed papers demonstrating novel Artificial Intelligence (AI)-based solutions to COVID-19 challenges during the pandemic, few have made a significant clinical impact, especially in diagnosis and disease precision staging. One major cause for such low impact is the lack of model transparency, significantly limiting the AI adoption in real clinical practice. To solve this problem, AI models need to be explained to users. Thus, we have conducted a comprehensive study of Explainable Artificial Intelligence (XAI) using PRISMA technology. Our findings suggest that XAI can improve model performance, instill trust in the users, and assist users in decision-making. In this systematic review, we introduce common XAI techniques and their utility with specific examples of their application. We discuss the evaluation of XAI results because it is an important step for maximizing the value of AI-based clinical decision support systems. Additionally, we present the traditional, modern, and advanced XAI models to demonstrate the evolution of novel techniques. Finally, we provide a best practice guideline that developers can refer to during the model experimentation. We also offer potential solutions with specific examples for common challenges in AI model experimentation. This comprehensive review, hopefully, can promote AI adoption in biomedicine and healthcare.

The collateral impact of the COVID-19 pandemic on HPV-positive oropharyngeal cancer diagnosis.

PURPOSE: We aim to assess the potential impact of the COVID-19 pandemic on diagnostic delays in HPV-positive oropharyngeal cancer (OPC), and to describe their underlying reasons. METHODS: All HPV + OPC referred to a tertiary cancer centre and diagnosed between June-December 2019 (Pre-Pandemic cohort) vs June-December 2020 (Pandemic cohort) were reviewed. TNM classification, gross-tumor-volumes (GTV) and intervals between sign/symptom onset and treatment initiation were compared between the cohorts. Reasons for delay (>6 months from onset of signs/symptoms to a positive biopsy of the primary tumor, or a delay specifically mentioned in the patient chart) in establishing the diagnosis were recorded per clinician's documentation, and categorized as COVID-related or non-COVID-related. RESULTS: A total of 157 consecutive HPV + OPC patients were identified (Pre-Pandemic: 92; Pandemic: 65). Compared to the Pre-Pandemic cohort, Pandemic cohort patients had a higher proportion of N2-N3 (32 % vs 15 %, p = 0.019) and stage III (38 % vs 23 %, p = 0.034) disease at presentation. The differences in proportions with > 6 months delay from symptom onset to establishing the diagnosis (29 % vs 20 %, p = 0.16) or to first treatment (49 % vs 38 %, p = 0.22) were not statistically different. 47 % of diagnostic delays in the Pandemic cohort were potentially attributable to COVID-19. CONCLUSION: We observed a collateral impact of the COVID-19 pandemic on HPV + OPC care through more advanced stage at presentation and a non-significant but numerically longer interval to diagnosis. This could adversely impact patient outcomes and future resource allocation. Both COVID-19-related and unrelated factors contribute to diagnostic delays. Tailored interventions to reduce delays are warranted.

Lymphocyte–C-reactive protein ratio can differentiate disease severity of COVID-19 patients and serve as an assistant screening tool for hospital and ICU admission

In this study, we aimed to explore whether lymphocyte–C-reactive protein ratio (LCR) can differentiate disease severity of coronavirus disease 2019 (COVID-19) patients and its value as an assistant screening tool for admission to hospital and intensive care unit (ICU). A total of 184 adult COVID-19 patients from the COVID-19 Treatment Center in Heilongjiang Province at the First Affiliated Hospital of Harbin Medical University between January 2020 and March 2021 were included in this study. Patients were divided into asymptomatic infection group, mild group, moderate group, severe group, and critical group according to the Diagnosis and Treatment of New Coronavirus Pneumonia (ninth edition). Demographic and clinical data including gender, age, comorbidities, severity of COVID-19, white blood cell count (WBC), neutrophil proportion (NEUT%), lymphocyte count (LYMPH), lymphocyte percentage (LYM%), red blood cell distribution width (RDW), platelet (PLT), C-reactive protein (CRP), alanine aminotransferase (ALT), aspartate aminotransferase (AST), serum creatinine (SCr), albumin (ALB), total bilirubin (TB), direct bilirubin (DBIL), indirect bilirubin (IBIL), and D-dimer were obtained and collated from medical records at admission, from which sequential organ failure assessment (SOFA) score and LCR were calculated, and all the above indicators were compared among the groups. Multiple clinical parameters, including LYMPH, CRP, and LCR, showed significant differences among the groups. The related factors to classify COVID-19 patients into moderate, severe, and critical groups included age, number of comorbidities, WBC, LCR, and AST. Among these factors, the number of comorbidities showed the greatest effect, and only WBC and LCR were protective factors. The area under the receiver operating characteristic (ROC) curve of LCR to classify COVID-19 patients into moderate, severe, and critical groups was 0.176. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 1,780.7050 and 84.6% and 66.2%, respectively. The related factors to classify COVID-19 patients into severe and critical groups included the number of comorbidities, PLT, LCR, and SOFA score. Among these factors, SOFA score showed the greatest effect, and LCR was the only protective factor. The area under the ROC curve of LCR to classify COVID-19 patients into severe and critical groups was 0.106. The cutoff value of LCR and the sensitivity and specificity of the ROC curve were 571.2200 and 81.3% and 90.0%, respectively. In summary, LCR can differentiate disease severity of COVID-19 patients and serve as a simple and objective assistant screening tool for hospital and ICU admission.

A duplex nested RT-PCR method for monitoring porcine epidemic diarrhea virus and porcine delta-coronavirus (preprint)

·          Background: Porcine epidemic diarrhea virus (PEDV) and porcine delta-coronavirus (PDCoV) are economically important pathogens that cause diarrhea in sows and acute death of newborn piglets. Moreover, the emerging porcine delta-coronavirus was reported to infect children. The current situation is that vaccine prevention has not met expectations, and emergency containment strategies following outbreaks cannot prevent the damages and losses already incurred. Therefore, a more sensitive detection method, that is both convenient and enables accurate and effective sequencing, that will provide early warning of PEDV and PDCoV is necessary. This will enable active, effective, and comprehensive prevention and control, which will possibly reduce disease occurrences.·          Results: Duplex nested RT-PCR (dnRT-PCR) is an ideal method to achieve early warning and monitoring of PEDV and PDCoV diseases, and to additionally identify any molecular epidemiological characteristics. In this study, two pairs of primers were designed for each virus based upon the highly conserved N protein sequences of both PEDV and PDCoV retrieved from the NCBI Genbank PEDV and PDCoV entries. After optimization of the reaction conditions, the dnRT-PCR assay amplified a 749-bp fragment specific to PEDV and a 344-bp fragment specific to PDCoV. Meanwhile, the specificity and sensitivity of the primers and clinical samples were tested to verify and establish this dnRT-PCR method. The limit of detection (LoD)for both PEDV and PDCoV was 10 copies/ml. The results showed that among 251 samples, 1 sample contained PEDV infection only, 19 samples contained a PDCoV infection, and 8 samples were infected with both viruses, following the use of dnRT-PCR. Thereafter, the positive samples were sent for sequencing, and the sequencing results confirmed that they were all positive for the viruses detected using dnRT-PCR, and conventional RT-PCR detection was conducted again after the onset of disease. As these results were consistent with previous results, a detection method for PEDV and PDCoV using dnRT-PCR was successfully established. In conclusion, the dnRT-PCR method established in this study was able to detect both PEDV and PDCoV, concomitantly.·          Conclusions: The duplex nested RT-PCR method represents a convenient, reliable, specific, sensitive and anti-interference technique for detecting PEDV and PDCoV, and can additionally be used to simultaneously determine the molecular epidemiological background.

Capo: Calibrating Device-to-Device Positioning in Heterogeneous Systems (preprint)

Device-to-device relative positioning systems such as COVID-19 contact tracing, seamless access systems, mobile interactive gaming, directional interaction, etc. have been promoted recently. The legacy absolute object positioning technologies are not suitable for device-to-device positioning because of the mobility and heterogeneity of devices. In this paper, we focus on the heterogeneity problem and propose Capo, the first calibration algorithm that enables the interaction among devices with different communication modes for relative positioning in heterogeneous systems. In particular, Capo optimizes the ranging results of low-precision devices in a collaborative network based on the ranging data collected from high-precision devices. Evaluation results show that Capo can significantly improve up to 26.56% of the positioning accuracy of the heterogeneous systems. Real use case study on COVID-19 contact tracing further shows that Capo significantly improves the accuracy of exposure notifications.

The Impacts of Reducing the Infection Rate and Infection Source on the Transmission of Emerging Infectious Diseases

There are many prevention and control measures for emerging infectious diseases. This paper divides the effects of these measures into two categories. One is to reduce the infection rate. The other is to use diagnosis rate to reflect the decreases of the infection source. The impacts of measures intensity, diagnosis rate, and the start time of taking measures on emerging infectious diseases with infectious capacity during the incubation period are considered comprehensively by using a differential equation model. Results show that for each diagnosis rate, the number of infections and deaths has a phase change structure with respect to the measures intensity. If the measures intensity is less than the value of the phase change point, the epidemic will break out whenever measures are taken. If the measures intensity is greater than the value of the phase change point, the epidemic can be controlled when the measures are taken timely. But if measures are not taken in time, epidemic will also break out. The location of the phase change point is related to the diagnosis rate. For the different measures intensity and the diagnosis rate, this paper gives a method to judge whether the spread of the corresponding epidemic can be controlled.

The relationship between adolescent risk perception and emotions during the COVID-19: a short-term longitudinal study

This study explores the relationship between adolescents’ perceptions of epidemic risk and their emotions through three follow-up surveys during the early stages of the COVID-19 pandemic on February 11th (T1), 18th (T2), and 25th (T3), 2020. Three hundred and four adolescents in different academic stages (junior high middle school, senior high middle school, and university) participated in the online survey, and cross-lag analysis was used to examine the causal relationship between epidemic risk perceptions and positive and negative emotions. The results found that the individual’s positive emotions were significantly higher than the negative emotions in T1, T2 and T3. Cross-lag analysis found that for positive emotions, T2 positive emotions could negatively predict T3 epidemic risk perceptions, and T2 epidemic risk perceptions could negatively predict the individual’s T3 positive emotions. For negative emotions, risk perceptions at T1 could positively predict negative emotions at T2, and at the same time, negative emotions at T1 could also positively predict epidemic risk perceptions at T2. This indicates that during the early stages of the COVID-19 pandemic, there was a causal relationship between the perceptions of epidemic risk and the emotions of adolescents, and this relationship had high stability among groups of different genders and academic stages.

Sleep Quality and the Depression-Anxiety-Stress State of Frontline Nurses Who Perform Nucleic Acid Sample Collection During COVID-19: A Cross-Sectional Study.

OBJECTIVE: To explore the sleep quality and depression-anxiety-stress state of frontline nurses in high-risk areas who conduct nucleic acid sampling testing for COVID-19 to provide a basis for formulating intervention programs in crisis management. METHODS: From August 22 to 30, 2021, a convenient sampling method was used in Zhangjiajie City, Hunan Province, China. A total of 248 frontline nurses who performed nucleic acid sample collection were selected. The following tests were used: the general information questionnaire, Pittsburgh Sleep Quality Questionnaire (PSQI), and Depression-Anxiety Stress Scale (DASS-21). RESULTS: A total of 236 nurses completed the survey; 88.14% (n = 208) were women, the average age was 33.02±6.81, the PSQI score was 15 (13-17), and 231 (97.88%) nurses had sleep disorders during the period in Zhangjiajie, 219 nurses (81.36%) had anxiety, 135 nurses (45.76%) had depression, and 112 nurses (42.59%) felt stressed. Spearman correlation analysis was used to associate the PSQI with the DASS-21. The results showed that the use of hypnotic drugs was negatively correlated with DASS-21 (P<0.05), while the rest were positively correlated. The results of the multivariate analysis of sleep disorders showed that depression, anxiety, and stress were related to sleep quality (P<0.05), and there was no statistical difference in the other variables. CONCLUSION: During the COVID-19 pandemic, the sleep quality and depression-anxiety-stress state of the frontline nurses performing nucleic acid testing were adversely affected. Sleep disturbance is a serious problem among nurses testing for the delta strain during the pandemic. Anxiety, stress, and depression are associated with sleep disorders. It is necessary to take corresponding measures and conduct crisis management interventions to improve sleep quality and mental health adjustment during public health emergencies.

Inhibition of SAR S-CoV-2 infection and replication by lactoferrin, MUC1 and α-lactalbumin identified in human breastmilk (preprint)

The global pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection confers great threat to the public health. Human breastmilk is an extremely complex with nutritional composition to nourish infants and protect them from different kinds of infection diseases and also SARS-CoV-2 infection. Previous studies have found that breastmilk exhibited potent antiviral activity against SARS-CoV-2 infection. However, it is still unknown which component(s) in the breastmilk is responsible for its antiviral activity. Here, we identified Lactoferrin (LF), MUC1 and α-Lactalbumin (α-LA) from human breastmilk by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and in vitro confirmation that inhibited SARS-CoV-2 infection and analyzed their antiviral activity using the SARS-CoV-2 pseudovirus system and transcription and replication-competent SARS-CoV-2 virus-like-particles (trVLP) in the Huh7.5, Vero E6 and Caco-2-N cell lines. Additionally, we found that LF and MUC1 could inhibit viral attachment, entry and post-entry replication, while α-LA just inhibit viral attachment and entry. Importantly, LF, MUC1 and α-LA possess potent antiviral activities towards not only wild-type but also variants such as B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma) and B.1.617.1 (kappa). Moreover, LF from other species (e.g., bovine and goat) is still capable of blocking viral attachment to cellular heparan sulfate. Taken together, our study provided the first line of evidence that human breastmilk components (LF, MUC1 and α-LA) are promising therapeutic candidates warranting further development or treatingVID-19 given their exceedingly safety levels.

COVID-19 Automatic Diagnosis With Radiographic Imaging: Explainable Attention Transfer Deep Neural Networks.

Researchers seek help from deep learning methods to alleviate the enormous burden of reading radiological images by clinicians during the COVID-19 pandemic. However, clinicians are often reluctant to trust deep models due to their black-box characteristics. To automatically differentiate COVID-19 and community-acquired pneumonia from healthy lungs in radiographic imaging, we propose an explainable attention-transfer classification model based on the knowledge distillation network structure. The attention transfer direction always goes from the teacher network to the student network. Firstly, the teacher network extracts global features and concentrates on the infection regions to generate attention maps. It uses a deformable attention module to strengthen the response of infection regions and to suppress noise in irrelevant regions with an expanded reception field. Secondly, an image fusion module combines attention knowledge transferred from teacher network to student network with the essential information in original input. While the teacher network focuses on global features, the student branch focuses on irregularly shaped lesion regions to learn discriminative features. Lastly, we conduct extensive experiments on public chest X-ray and CT datasets to demonstrate the explainability of the proposed architecture in diagnosing COVID-19.

Policy Evaluation during a Pandemic (preprint)

National and local governments have implemented a large number of policies in response to the Covid-19 pandemic. Evaluating the effects of these policies, both on the number of Covid-19 cases as well as on other economic outcomes is a key ingredient for policymakers to be able to determine which policies are most effective as well as the relative costs and benefits of particular policies. In this paper, we consider the relative merits of common identification strategies that exploit variation in the timing of policies across different locations by checking whether the identification strategies are compatible with leading epidemic models in the epidemiology literature. We argue that unconfoundedness type approaches, that condition on the pre-treatment "state" of the pandemic, are likely to be more useful for evaluating policies than difference-in-differences type approaches due to the highly nonlinear spread of cases during a pandemic. For difference-in-differences, we further show that a version of this problem continues to exist even when one is interested in understanding the effect of a policy on other economic outcomes when those outcomes also depend on the number of Covid-19 cases. We propose alternative approaches that are able to circumvent these issues. We apply our proposed approach to study the effect of state level shelter-in-place orders early in the pandemic.

Did COVID-19 Affect Time to Presentation in the Setting of Pediatric Testicular Torsion?

OBJECTIVES: To determine if boys with acute testicular torsion, a surgical emergency requiring prompt diagnosis and treatment to optimize salvage of the testicle, delayed presentation to a medical facility and experienced an extended duration of symptoms (DoS), and secondarily, a higher rate of orchiectomy, during the coronavirus disease 2019 (COVID-19) pandemic. METHODS: Single-center, descriptive retrospective chart review of boys presenting with acute testicular torsion from March 15, to May 4, 2020 ("during COVID-19" or group 2), as well as for the same time window in the 5-year period from 2015 to 2019 ("pre-COVID-19" or group 1). RESULTS: A total of 78 boys met inclusion criteria, group 1 (n = 57) and group 2 (n = 21). The mean age was 12.86 ± 2.63 (group 1) and 12.86 ± 2.13 (group 2). Mean DoS before presentation at a medical facility was 23.2 ± 35.0 hours in group 1 compared with 21.3 ± 29.7 hours in group 2 (P < 0.37). When DoS was broken down into acute (<24 hours) versus delayed (≥24 hours), 41 (71.9%) of 57 boys in group 1 and 16 (76.2%) of 21 boys in group 2 presented within less than 24 hours of symptom onset (P < 0.78). There was no difference in rate of orchiectomy between group 1 and group 2 (44.7% vs 25%, P < 0.17), respectively. CONCLUSIONS: Boys with acute testicular torsion in our catchment area did not delay presentation to a medical facility from March 15, to May 4, 2020, and did not subsequently undergo a higher rate of orchiectomy.

SARS-CoV-2 and Malayan pangolin coronavirus infect human endoderm, ectoderm and induced lung progenitor cells (preprint)

Since the infection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in several somatic cells, little is known about the infection of SASRS-CoV-2 and its related pangolin coronavirus (GX_P2V). Here we present for the first time that SARS-CoV-2 pseudovirus and GX_P2V could infect lung progenitor and even anterior foregut endoderm cells causing these cells death, which differentiated from human embryonic stem cells (hESCs). The infection and replication of SARS-CoV-2 and GX_P2V were inhibited when treated with whey protein of breastmilk and Remdesivir, confirming that these two viruses could infect lung progenitor and even anterior foregut endoderm. Moreover, we found that SARS-CoV-2 pseudovirus could infect endoderm and ectoderm. We found that whey protein blocked SARS-CoV-2 infecting these cells. In line with the SARS-CoV-2 results, GX_P2V could also infected endoderm and ectoderm, and also was inhibited by Remdesivir treatment. Although expressing coronavirus related receptor such as ACE2 and TMPRSS2, mesoderm cells are not permissive for SARS-CoV-2 and GX_P2V infection, which needed further to study the mechanisms. Interestingly, we also found that hESCs, which also express ACE2 and TMPRSS2 markers, are permissive for GX_P2V but not SARS-CoV-2 pseudovirus infection and replication, indicating the widespread cell types for GX_P2V infection. Heparin treatment blocked efficiently viral infection. These results provided insight that these stem cells maybe provided a stable repository of coronavirus function or genome. The potential consequence of SARS-CoV-2 and animal coronavirus such as GX_P2V infection in hESCs, germ layer and induced progenitors should be closely monitored.

Using simulation Technology to Analyze the COVID-19 Epidemic in Changsha, Hunan Province, China (preprint)

This study mainly uses simulation technology to simulate the COVID-19 epidemic in Changsha, Hunan Province, China, and analyze the impact of different prevention and control measures on the epidemic. we Collect the information of all COVID-19 patients in Changsha from January 21, 2020 to March 14, 2020 and relevant policies during the COVID-19 epidemic in Changsha. Established the SEIAR infectious disease dynamics model under natural conditions, and added isolation measures on this basis. Using Anylogic8.5, the COVID-19 epidemic in Changsha City was simulated under various conditions based on the established model.In this study we find that There were 242 COVID-19 patients in Changsha. including 121 males (50%) and 121 females (50%).Most cases occurred between February 6 and February 16. Through the calculation of the Rt during the epidemic in Changsha, it is found that it is reasonable to resume work on February 8, because the Rt value of Changsha dropped below 1 at this time.The simulation results show that reducing the contact rate of residents and reducing the success rate of virus transmission (wearing masks, disinfection, etc.) can effectively prevent the spread of COVID-19 and significantly reduce the number of peak patients.We believe that the disease is mainly spread by the respiratory tract. Therefore, the simulation results show that whether in the early or mid-stage of the epidemic, quarantining the names of residents or reducing the contact rate of residents is very effective in controlling the COVID-19 epidemic.