Identification of Age-Related Characteristic Genes Involved in Severe COVID-19 Infection Among Elderly Patients using Machine Learning and Immune Cell Infiltration Analysis (preprint)

Background Elderly patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) are at higher risk of severe clinical manifestation, extended hospitalization, and increased mortality. Those patients are more likely to experience persistent symptoms and exacerbate the condition of basic diseases with long COVID-19 syndrome. However, the molecular mechanisms underlying severe COVID-19 in the elderly patients remain unclear. Our study aims to investigate the function of the interaction between disease-characteristic genes and immune cell infiltration in patients with severe COVID-19 infection.Methods COVID-19 datasets (GSE164805 and GSE180594) and aging dataset (GSE69832) were obtained from the Gene Expression Omnibus (GEO) database. The combined different expression genes (DEGs) were subjected to Gene Ontology (GO) functional enrichment analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Diseases Ontology (DO) functional enrichment analysis, Gene Set Enrichment Analysis (GSEA), machine learning, and immune cell infiltration analysis.Results GO and KEGG enrichment analysis revealed that the eight DEGs (IL23A, PTGER4, PLCB1, IL1B, CXCR1, C1QB, MX2, ALOX12) were mainly involved in inflammatory mediator regulation of TRP channels, coronavirus disease-COVID-19, and cytokine activity signaling pathways. Two-degree algorithm (LASSO and SVM-RFE) and correlation analysis showed that the seven DEGs upregulated the immune cells of macrophages M0/M1, memory B cells, gramma delta T cell, dendritic cell resting and master cell resisting.Conclusion Our study identified seven hallmark genes that can serve as disease-characteristic genes and target immune cells infiltrated in severe COVID-19 patients among the elderly population, which may contribute to the study of pathogenesis and the evaluation of diagnosis and prognosis in aging patients infected with severe COVID-19.

Hematologic health services and practical characteristics: report of a nationwide survey among Chinese hematologists (preprint)

Background: In the past 40 years, China has experienced tremendous economic development, but the current situation of hematologists has rarely been reported. A landscape survey of human resources is essential for healthcare development and policy formulation in the future. Methods: The Chinese Society of Hematology initiated a survey of Chinese hematologists in mainland China for evaluating demographic and practice characteristics. Respondents were anonymous, and there were no limitations regarding their age, sex, etc. Results: Totally 2032 hematologists responded, with a median age bracket of 36-45 years. Respondents were well engaged into subspecialties, and 28.1% acquired doctorates of philosophy. Hematopoietic cell transplantation (HCT) centers have been established all over China. Higher-GDP regions reported more advantages, including bigger scale of transplant centers (P < 0.001), younger age structure (P = 0.039), better education qualifications (P = 0.001) and less turnover intentions (P = 0.004), despite of increased risk of medical disputes (P = 0.028). Although females accounted for 65.5% of hematologists, males were older (P < 0.001), and had more senior professional titles (P < 0.001), academic positions (P < 0.001), opportunities for continuing education (P < 0.001), and paper publishing in the recent two years (P = 0.001). For turnover intention, the higher GDP regions led to an independently reduced risk (HR = 0.673, 95%CI [0.482-0.940], P = 0.020), whereas medical disputes resulted in an increased the risk (HR = 2.037, 95%CI [1.513-2.743], P < 0.001). Considering the impact of the COVID-19 pandemic, majority of respondents believed that the decline in patient visits and delay in treatment was within 30%. 67.9% of respondents reported a decrease of the use of bone marrow as grafts but 18.8% reported an increase of cord blood units. 35.0% of the respondents switched their daily work to support the anti-epidemic medical activities. Conclusions: We concluded the discipline of hematology in China has flourished in recent years with a young workforce, while regional economic and gender disparities warrant further continuous optimization. Joint efforts against the impact of COVID-19 are needed in the post-pandemic era.

Immune Repertoire Sequencing Reveals an Abnormal Adaptive Immune System in COVID-19 Survivors.

Accumulating evidence suggests that SARS-CoV-2 impairs the adaptive immune system during acute infection. Still, it remains largely unclear whether the frequency and functions of T and B cells return to normal after the recovery of COVID-19. Here, we analyzed immune repertoires and SARS-CoV-2-specific neutralization antibodies in a prospective cohort of 40 COVID-19 survivors with a six-month follow-up after hospital discharge. Immune repertoire sequencing revealed abnormal T- and B-cell expression and function with large TCR/BCR clones, decreased diversity, abnormal class switch recombination and somatic hypermutation. A decreased number of B cells but an increased proportion of CD19+ CD138+ B cells were found in COVID-19 survivors. The proportion of CD4+ T cells, especially circulating follicular helper T (cTfh) cells, was increased, whereas the frequency of CD3+ CD4- T cells was decreased. SARS-CoV-2-specific neutralization IgG and IgM antibodies were identified in all survivors, especially those recorded with severe COVID-19 who showed a higher inhibition rate of neutralization antibodies. All severe cases complained of more than one COVID-19 sequelae after 6 months of recovery. Overall, our findings indicate that SARS-CoV-2-specific antibodies remain detectable even after 6 months of recovery. Because of their abnormal adaptive immune system with a low number of CD3+ CD4- T cells and high susceptibility to infections, COVID-19 patients might need more time and medical care to fully recover from immune abnormalities and tissue damage. This article is protected by copyright. All rights reserved.

Research on the Influence of Socially Regulated Learning on Online Collaborative Knowledge Building in the Post COVID-19 Period

Online teaching has become an important initiative to maintain normal educational order in the post COVID-19 period. However, learners face multiple challenges in the online learning process, which cannot be successfully carried out without the support of socially regulated learning (SoRL). This study designed SoRL intervention strategies from the perspective of shared metacognitive scripts. A total of 77 undergraduate students participated in this study and were randomly assigned into experimental and control groups. The students in the experimental group received an SoRL intervention, and the students in the control group learned with the traditional online collaborative learning approach. The results showed that there was variability in the supply of SoRL intervention scripts and the actual selection status of the learners. The regulation foci activated in this study were time management, content monitoring, and atmosphere activation. Atmosphere activation drove collaborative learning activities to continue. Time management and content monitoring drove collaborative knowledge building (CKB) to a deeper level. This study is of great significance in revealing the impact mechanism of SoRL on CKB.

Data Forecasts of the Epidemic COVID-19 by Deterministic and Stochastic Time-Dependent Models (preprint)

We propose a deterministic SAIVRD model and a stochastic SARV model of the epidemic COVID-19 involving asymptomatic infections and vaccinations to conduct data forecasts using time-dependent parameters. The forecast by our deterministic model conducts 10-day predictions to see whether the epidemic will ease or become more severe in the short term. The forecast by our stochastic model predicts the probability distributions of the final size and the maximum size to see how large the epidemic will be in the long run. The first forecast using the data set from the USA gives the relative errors within 3% in 5 days and 7% in 10 days for the prediction of isolated infectious cases and smaller ones for the predictions of recoveries and deaths. The distributions in the second forecast using the time-varying parameters from the first forecast are also bimodal in our model with time-independent parameters in our simulations of smaller populations. For the model with time-dependent model, what are different are that there is another peak in the final size distribution, that the the probability of minor outbreak is higher and that the maximum size distribution is oscillating with time-dependent parameters. The final size distributions are similar between different populations and so are the maximum size distributions, which means that we can expect that with the same parameters and in a large population, the ratio of the final size and the maximum size are distributed similarly (only different by the value of the second peak). The result shows that under recent transmissibility of this disease in the USA, when an initial infection is introduced into all-susceptible (large) population, major outbreak occurs with around 95% of the population and with high probability the epidemic is maximized to around 30% of the population.

Improving the Behavioral Intention of Continuous Online Learning Among Learners in Higher Education During COVID-19.

The COVID-19 pandemic caused colleges and universities to rely heavily on online learning to continue knowledge dissemination to learners. This study used the second-generation model of unified theory of acceptance and use of technology (UTAUT2) to comprehensively analyze the mediating effects of self-efficacy, which affects learners' effective use of online tools for learning, and capability of metacognition and self-regulation, which can independently adjust learning progress into the UTAUT2 model, on the learner's willingness to continue online learning [i.e., their behavioral intention (BI)] by constructing a UTAUT2-based e-learning model. This study administered questionnaires to undergraduates in universities in East China to collect data. The effects of performance expectancy, effort expectancy (EE), social influence (SI), and facilitating conditions (FCs), hedonic motivation (HM), price value (PV), and habits on BI (directly or through mediators) were analyzed through data analysis and structural equation modeling, and the UTAUT2-based e-learning model was accordingly modified. The results indicated that the self-efficacy enhanced the effects of EE, SI, FCs, HM, and PV on learners' BI; that metacognition and self-regulation (MS) capabilities enhanced the effects of EE on learners' BI; and that habits had a direct and strong effect on BI. This study also provided some suggestions to enhance higher education learners' willingness to continue online learning, such as improving social recognition and support, careful design of teaching content, easy-to-use technology, financial support. These results and suggestions may guide colleges and universities in conducting, continuing, or enhancing online education, particularly as the pandemic continues.

Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study

ObjectiveTo delineate the clinical characteristics of patients with coronavirus disease 2019 (covid-19) who died.DesignRetrospective case series.SettingTongji Hospital in Wuhan, China.ParticipantsAmong a cohort of 799 patients, 113 who died and 161 who recovered with a diagnosis of covid-19 were analysed. Data were collected until 28 February 2020.Main outcome measuresClinical characteristics and laboratory findings were obtained from electronic medical records with data collection forms.ResultsThe median age of deceased patients (68 years) was significantly older than recovered patients (51 years). Male sex was more predominant in deceased patients (83;73%) than in recovered patients (88;55%). Chronic hypertension and other cardiovascular comorbidities were more frequent among deceased patients (54 (48%) and 16 (14%)) than recovered patients (39 (24%) and 7 (4%)). Dyspnoea, chest tightness, and disorder of consciousness were more common in deceased patients (70 (62%), 55 (49%), and 25 (22%)) than in recovered patients (50 (31%), 48 (30%), and 1 (1%)). The median time from disease onset to death in deceased patients was 16 (interquartile range 12.0-20.0) days. Leukocytosis was present in 56 (50%) patients who died and 6 (4%) who recovered, and lymphopenia was present in 103 (91%) and 76 (47%) respectively. Concentrations of alanine aminotransferase, aspartate aminotransferase, creatinine, creatine kinase, lactate dehydrogenase, cardiac troponin I, N-terminal pro-brain natriuretic peptide, and D-dimer were markedly higher in deceased patients than in recovered patients. Common complications observed more frequently in deceased patients included acute respiratory distress syndrome (113;100%), type I respiratory failure (18/35;51%), sepsis (113;100%), acute cardiac injury (72/94;77%), heart failure (41/83;49%), alkalosis (14/35;40%), hyperkalaemia (42;37%), acute kidney injury (28;25%), and hypoxic encephalopathy (23;20%). Patients with cardiovascular comorbidity were more likely to develop cardiac complications. Regardless of history of cardiovascular disease, acute cardiac injury and heart failure were more common in deceased patients.ConclusionSevere acute respiratory syndrome coronavirus 2 infection can cause both pulmonary and systemic inflammation, leading to multi-organ dysfunction in patients at high risk. Acute respiratory distress syndrome and respiratory failure, sepsis, acute cardiac injury, and heart failure were the most common critical complications during exacerbation of covid-19.

Hanshiyi Formula treatment in patients with COVID-19: study protocol and statistical analysis plan (SAP) of an open-label randomized controlled clinical trial (preprint)

Background As COVID-19 continues to spread rapidly in 2019, the risks to human health cannot be underestimated. There is still lack of antiviral drugs for COVID-19, and the development of effective treatments is urgent. Traditional Chinese Medicine (TCM) has been widely used in the treatment of epidemic infectious diseases, The purpose of this randomized controlled clinical trial will to evaluate the clinical efficacy and safety of Hanshiyi Formula (HSYF) in patients with COVID-19.Methods We will conduct this randomized, controlled, open, non-inferiority test clinical study in 240 COVID-19 subjects. Eligible patients will be divided into a control group ( LH granule ) or a treatment group ( HSYF ) in a 1:1 ratio. The intervention duration will be 14 days, and the medication could be stopped in advance if the discharge standard was reached. Clinical efficacy measures will be analyzed at baseline and on day 1–14 of enrollment, The occurrence of adverse events will be monitored throughout the trial. The statistical analysis plan included the treatment of missing data, the analysis of outcome measures, and the method of safety endpoints.Discussion To investigate the efficacy and safety of HSYF in the treatment of COVID-19, provide more sufficient high-quality evidence-based medical basis for TCM intervention in the diagnosis and treatment of COVID-19. To avoid selective reporting bias and data-driven analysis, the statistical analysis plan will standardize the statistical analysis of clinical trials.Trial registration: Chinese Clinical Trial Registry, ChiCTR2200058384. Version V1.2, created on April 11, 2022.https://www.chictr.org.cn/com/25/hvshowproject.aspx?id=159938.

Gestational SARS-CoV-2 infection is associated with placental expression of immune and trophoblast genes (preprint)

Introduction: Maternal SARS-CoV-2 infection during pregnancy is associated with adverse pregnancy outcomes and can have effects on the placenta, even in the absence of severe disease or vertical transmission to the fetus. This study aimed to evaluate histopathologic and molecular effects in the placenta after SARS-CoV-2 infection during pregnancy. Methods: We performed a study of 45 pregnant participants from the Generation C prospective cohort study at the Mount Sinai Health System in New York City. We compared histologic features and the expression of 48 immune and trophoblast genes in placentas delivered from 15 SARS-CoV-2 IgG antibody positive and 30 IgG SARS-CoV-2 antibody negative mothers. Statistical analyses were performed using Fisher exact tests, Spearman correlations and linear regression models. Results: The median gestational age at the time of SARS-CoV-2 IgG serology test was 35 weeks. Two of the IgG positive participants also had a positive RT-PCR nasal swab at delivery. 82.2% of the infants were delivered at term ([≥]37 weeks), and gestational age at delivery did not differ between the SARS-CoV-2 antibody positive and negative groups. No significant differences were detected between the groups in placental histopathology features. Differential expression analyses revealed decreased expression of two trophoblast genes (PSG3 and CGB3) and increased expression of three immune genes (CXCL10, TLR3 and DDX58) in placentas delivered from SARS-CoV-2 IgG positive participants. Discussion: SARS-CoV-2 infection during pregnancy is associated with gene expression changes of immune and trophoblast genes in the placenta at birth which could potentially contribute to long-term health effects in the offspring.

Network-Based Approach to Repurpose Approved Drugs for COVID-19 by Integrating GWAS and Text Mining Data

The coronavirus disease 19 (COVID-19) is a global pandemic caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which has a rapidly increasing prevalence and has caused significant morbidity/mortality. Despite the availability of many vaccines that can offer widespread immunization, it is also important to reach effective treatment for COVID-19 patients. However, the development of novel drug therapeutics is usually a time-consuming and costly process, and therefore, repositioning drugs that were previously approved for other purposes could have a major impact on the fight against COVID-19. Here, we first identified lung-specific gene regulatory/interaction subnetworks (COVID-19-related genes modules) enriched for COVID-19-associated genes obtained from GWAS and text mining. We then screened the targets of 220 approved drugs from DrugBank, obtained their drug-induced gene expression profiles in the LINCS database, and constructed lung-specific drug-related gene modules. By applying an integrated network-based approach to quantify the interactions of the COVID-19-related gene modules and drug-related gene modules, we prioritized 13 approved drugs (e.g., alitretinoin, clocortolone, terazosin, doconexent, and pergolide) that could potentially be repurposed for the treatment of COVID-19. These findings provide important and timely insights into alternative therapeutic options that should be further explored as COVID-19 continues to spread.

Maternal cytokine response after SARS-CoV-2 infection during pregnancy (preprint)

Objective: Dysregulation of the immune system during pregnancy is associated with adverse pregnancy outcomes. Recent studies report cytokine changes during the acute phase of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. We examine whether there is a lasting association between SARS-CoV-2 infection during pregnancy and peripheral blood cytokine levels. Study design: We conducted a case-control study at the Mount Sinai health system in NYC including 100 SARS-CoV-2 IgG antibody positive people matched to 100 SARS-CoV-2 IgG antibody negative people on age, race/ethnicity, parity, and insurance status. Blood samples were collected at a median gestational age of 34 weeks. Levels of 14 cytokines were measured. Results: Individual cytokine levels and cytokine cluster Eigenvalues did not differ significantly between groups, indicating no persisting maternal cytokine changes after SARS-CoV-2 infection during pregnancy. Conclusion: Our findings suggest that the acute inflammatory response after SARS-CoV-2 infection may be restored to normal values during pregnancy.

Neurological manifestations in COVID-19 patients and their application in predicting fatal disease: A retrospective cohort study.

BACKGROUND: To explore the development of central nervous system (CNS) symptoms and clinical application in predicting the clinical outcomes of SARS-COV-2 patients. METHODS: A retrospective cohort study was performed on the hospitalized patients with SARS-COV-2 recruited from four hospitals in Hubei Province, China from 18 January to 10 March 2020. The patients with CNS symptoms were determined. Data regarding clinical symptoms and laboratory tests were collected from medical records. RESULTS: Of 1268 patients studied, 162 (12.8%) had CNS symptoms, manifested as unconsciousness (71, 5.6%), coma (69, 5.4%), dysphoria (50, 3.9%), somnolence (34, 2.7%) and convulsion (3, 0.2%), which were observed at median of 14 (interquartile range 9-18) days after symptom onset and significantly associated with older age (OR = 5.71, 95% confidence interval [CI] 2.78-11.73), male (OR = 1.73, 95% CI 1.22-2.47) and preexisting hypertension (OR = 1.78, 95% CI 1.23-2.57). The presence of CNS symptoms could be predicted by abnormal laboratory tests across various clinical stages, including by lymphocyte counts of <0.93 × 109/L, LDH≥435 U/L and IL-6≥28.83 pg/L at 0-10 days post disease; by lymphocyte count<0.86 × 109/L, IL-2R ≥ 949 U/L, LDH≥382 U/L and WBC≥8.06 × 109/L at 11-20 days post disease. More patients with CNS symptoms developed fatal outcome compared with patients without CNS symptoms (HR = 33.96, 95% CI 20.87-55.16). CONCLUSION: Neurological symptoms of COVID-19 were related to increased odds of developing poor prognosis and even fatal infection.

Rumor, Chinese Diets, and COVID-19: Questions and Answers about Chinese Food and Eating Habits

As the coronavirus emerged as a global pandemic during early 2020, "ground zero" of the disease was initially named in the press as the Huanan Seafood Wholesale Market in the city of Wuhan, Hubei, in central China. With a population of over 11 million residents, and as a major transportation hub situated on the Yangtze River, Wuhan was placed under strict lockdown at the end of January by Chinese authorities, with severe restrictions on travel and movement. These efforts at containment proved too late to prevent the eventual spread of the virus around the world. The dramatic global impact of the virus has been all too painfully clear, yet the exact origins and zoonotic transmission pathway of the virus remain uncertain. Scientists suggest that SARS-CoV-2 probably jumped from horseshoe bats to an unknown intermediate animal vector, from which it spread to humans, but exactly how, where, and when this happened is still unknown..

A systematic meta-analysis of immune signatures in patients with COVID-19.

Currently severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission has been on the rise worldwide. Predicting outcome in COVID-19 remains challenging, and the search for more robust predictors continues. We made a systematic meta-analysis on the current literature from 1 January 2020 to 15 August 2020 that independently evaluated 32 circulatory immunological signatures that were compared between patients with different disease severity was made. Their roles as predictors of disease severity were determined as well. A total of 149 distinct studies that evaluated ten cytokines, four antibodies, four T cells, B cells, NK cells, neutrophils, monocytes, eosinophils and basophils were included. Compared with the non-severe patients of COVID-19, serum levels of Interleukins (IL)-2, IL-2R, IL-4, IL-6, IL-8, IL-10 and tumor necrosis factor α were significantly up-regulated in severe patients, with the largest inter-group differences observed for IL-6 and IL-10. In contrast, IL-5, IL-1ß and Interferon (IFN)-γ did not show significant inter-group difference. Four mediators of T cells count, including CD3+ T, CD4+ T, CD8+ T, CD4+ CD25+ CD127- Treg, together with CD19+ B cells count and CD16+ CD56+ NK cells were all consistently and significantly depressed in severe group than in non-severe group. SARS-CoV-2 specific IgA and IgG antibodies were significantly higher in severe group than in non-severe group, while IgM antibody in the severe patients was slightly lower than those in the non-severe patients, and IgE antibody showed no significant inter-group differences. The combination of cytokines, especially IL-6 and IL-10, and T cell related immune signatures can be used as robust biomarkers to predict disease severity following SARS-CoV-2 infection.

Tracking Reproductivity of COVID-19 Epidemic in China with Varying Coefficient SIR Model

We propose a varying coefficient Susceptible-Infected-Removal (vSIR) model that allows changing infection and removal rates for the latest corona virus (COVID-19) outbreak in China. The vSIR model together with proposed estimation procedures allow one to track the reproductivity of the COVID-19 through time and to assess the effectiveness of the control measures implemented since Jan 23 2020 when the city of Wuhan was lockdown followed by an extremely high level of self-isolation in the population. Our study finds that the reproductivity of COVID-19 had been significantly slowed down in the three weeks from January 27th to February 17th with 96.3% and 95.1% reductions in the effective reproduction numbers R among the 30 provinces and 15 Hubei cities, respectively. Predictions to the ending times and the total numbers of infected are made under three scenarios of the removal rates. The paper provides a timely model and associated estimation and prediction methods which may be applied in other countries to track, assess and predict the epidemic of the COVID-19 or other infectious diseases.

The Data Forecast in COVID-19 Model with Applications to US, South Korea, Brazil, India, Russia and Italy (preprint)

In this paper, we firstly propose SQIARD and SIARD models to investigate the transmission of COVID-19 with quarantine, infected and asymptomatic infected, and discuss the relation between the respective basic reproduction number $R_0, R_Q$ and the stability of the equilibrium points of model. Secondly, after training the related data parameters, in our numerical simulations, we respectively conduct the forecast of the data of US, South Korea, Brazil, India, Russia and Italy, and the effect of prediction of the epidemic situation in each country. Furthermore, we apply US data to compare SQIARD with SIARD, and display the effects of predictions.

Epidemiological parameters of COVID-19 and its implication for infectivity among patients in China, 1 January to 11 February 2020.

BackgroundThe natural history of disease in patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remained obscure during the early pandemic.AimOur objective was to estimate epidemiological parameters of coronavirus disease (COVID-19) and assess the relative infectivity of the incubation period.MethodsWe estimated the distributions of four epidemiological parameters of SARS-CoV-2 transmission using a large database of COVID-19 cases and potential transmission pairs of cases, and assessed their heterogeneity by demographics, epidemic phase and geographical region. We further calculated the time of peak infectivity and quantified the proportion of secondary infections during the incubation period.ResultsThe median incubation period was 7.2 (95% confidence interval (CI): 6.9‒7.5) days. The median serial and generation intervals were similar, 4.7 (95% CI: 4.2‒5.3) and 4.6 (95% CI: 4.2‒5.1) days, respectively. Paediatric cases < 18 years had a longer incubation period than adult age groups (p = 0.007). The median incubation period increased from 4.4 days before 25 January to 11.5 days after 31 January (p < 0.001), whereas the median serial (generation) interval contracted from 5.9 (4.8) days before 25 January to 3.4 (3.7) days after. The median time from symptom onset to discharge was also shortened from 18.3 before 22 January to 14.1 days after. Peak infectivity occurred 1 day before symptom onset on average, and the incubation period accounted for 70% of transmission.ConclusionThe high infectivity during the incubation period led to short generation and serial intervals, necessitating aggressive control measures such as early case finding and quarantine of close contacts.