Novel insight into the underlying dysregulation mechanisms of immune cell-to-cell communication by analyzing multitissue single-cell atlas of two COVID-19 patients.

How does SARS-CoV-2 cause lung microenvironment disturbance and inflammatory storm is still obscure. We here performed the single-cell transcriptome sequencing from lung, blood, and bone marrow of two dead COVID-19 patients and detected the cellular communication among them. Our results demonstrated that SARS-CoV-2 infection increase the frequency of cellular communication between alveolar type I cells (AT1) or alveolar type II cells (AT2) and myeloid cells triggering immune activation and inflammation microenvironment and then induce the disorder of fibroblasts, club, and ciliated cells, which may cause increased pulmonary fibrosis and mucus accumulation. Further study showed that the increase of T cells in the lungs may be mainly recruited by myeloid cells through ligands/receptors (e.g., ANXA1/FPR1, C5AR1/RPS19, and CCL5/CCR1). Interestingly, we also found that certain ligands/receptors (e.g., ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1) are significantly activated and shared among lungs, blood and bone marrow of COVID-19 patients, implying that the dysregulation of ligands/receptors may lead to immune cell's activation, migration, and the inflammatory storm in different tissues of COVID-19 patients. Collectively, our study revealed a possible mechanism by which the disorder of cell communication caused by SARS-CoV-2 infection results in the lung inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

3044 Cases reveal important prognosis signatures of COVID-19 patients.

Critical patients and intensive care unit (ICU) patients are the main population of COVID-19 deaths. Therefore, establishing a reliable method is necessary for COVID-19 patients to distinguish patients who may have critical symptoms from other patients. In this retrospective study, we firstly evaluated the effects of 54 laboratory indicators on critical illness and death in 3044 COVID-19 patients from the Huoshenshan hospital in Wuhan, China. Secondly, we identify the eight most important prognostic indicators (neutrophil percentage, procalcitonin, neutrophil absolute value, C-reactive protein, albumin, interleukin-6, lymphocyte absolute value and myoglobin) by using the random forest algorithm, and find that dynamic changes of the eight prognostic indicators present significantly distinct within differently clinical severities. Thirdly, our study reveals that a model containing age and these eight prognostic indicators can accurately predict which patients may develop serious illness or death. Fourthly, our results demonstrate that different genders have different critical illness rates compared with different ages, in particular the mortality is more likely to be attributed to some key genes (e.g. ACE2, TMPRSS2 and FURIN) by combining the analysis of public lung single cells and bulk transcriptome data. Taken together, we urge that the prognostic model and first-hand clinical trial data generated in this study have important clinical practical significance for predicting and exploring the disease progression of COVID-19 patients.

Characteristics of lymphocyte subset alterations in COVID-19 patients with different levels of disease severity.

BACKGROUND: Coronavirus disease 2019 (COVID-19) is a respiratory disorder caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which had rapidly spread all over the world and caused public health emergencies in the past two years. Although the diagnosis and treatment for COVID-19 have been well defined, the immune cell characteristics and the key lymphocytes subset alterations in COVID-19 patients have not been thoroughly investigated. METHODS: The levels of immune cells including T cells, B cells, and natural killer (NK) cells in 548 hospitalized COVID-19 patients, and 30 types of lymphocyte subsets in 125 hospitalized COVID-19 patients admitted to Wuhan Huoshenshan Hospital of China were measured using flow cytometry. The relationship between lymphocytes subsets with the cytokine interleukin-6 (IL-6) and the characteristics of lymphocyte subsets in single-cell RNA sequencing (scRNA-seq) data obtained from peripheral blood mononuclear cells (PBMCs) were also analysed in COVID-19 patients. RESULTS: In this study, we found that patients with critical COVID-19 infection exhibited an overall decline in lymphocytes including CD4+ T cells, CD8+ T cells, total T cells, B cells, and NK cells compared to mild and severe patients. However, the number of lymphocyte subsets, such as CD21low CD38low B cells, effector T4 cells, and PD1+ depleted T8 cells, was moderately increased in critical COVID-19 patients compared to mild cases. Notably, except for effector memory T4 cells, plasma blasts and Tregs, the number of all lymphocyte subsets was markedly decreased in COVID-19 patients with IL-6 levels over 30-fold higher than those in healthy cases. Moreover, scRNA-seq data showed obvious differences in the distribution and numbers of lymphocyte subsets between COVID-19 patients and healthy persons, and subsets-specific marker genes of lymphocyte subsets including CD4, CD19, CCR7, and IL7R, were markedly decreased in COVID-19 patients compared with those in healthy cases. CONCLUSION: A comprehensive decrease in immune cell and lymphocyte subsets in critical COVID-19 patients, and peripheral lymphocyte subset alterations showed a clear association with clinical characteristics.

Environmental contamination with SARS-CoV-2 in COVID-19 hospitals in Wuhan, China, 2020.

Coronavirus disease 2019 (COVID-19) pandemic has caused high number of infections and deaths of healthcare workers globally. Distribution and possible transmission route of SARS-CoV-2 in hospital environment should be clarified. We herein collected 431 environmental (391 surface and 40 air) samples in the intensive care unit (ICU) and general wards (GWs) of three hospitals in Wuhan, China from February 21 to March 4, 2020, and detected SARS-CoV-2 RNA by real-time quantitative PCR. The viral positive rate in the contaminated areas was 17.8% (28/157), whereas there was no virus detected in the clean areas. Higher positive rate (22/59, 37.3%) was found in ICU than that in GWs (3/63, 4.8%). The surfaces of computer keyboards and mouse in the ICU were the most contaminated (8/10, 80.0%), followed by the ground (6/9, 66.7%) and outer glove (2/5, 40.0%). From 17 air samples in the contaminated areas, only one sample collected at a distance of around 30 cm from the patient was positive. Enhanced surface disinfection and hand hygiene effectively decontaminated the virus from the environment. This finding might help understand the transmission route and contamination risk of SARS-CoV-2 and evaluate the effectiveness of infection prevention and control measures in healthcare facilities.

Can We Cryopreserve the Sperm of COVID-19 Patients During the Pandemic?

An extreme strain has been placed on healthcare facilities in the COVID-19 era. Initial stage of the pandemic, national and international societies for reproductive medicine suggested the suspension of new IVF treatments and non-essential cryopreservation of gametes. Accordingly, the demands of cryopreservation of semen with COVID-19 patients also was suspended by some of cryobanks to protect staff and patients from unnecessary viral exposure at the acute stage. However, the pandemic may stay with us longer than expected. In addition, there will be some male COVID-19 patients with cancer or critically illness who needs to cryopreserve their semen before medical treatments, otherwise they might loss the chance of getting their own offspring. In this document, we summarize available evidence to deepen and expand awareness of feasibility of sperm cryopreservation and propose some suggestions to help cryobanks carry out sperm preservation procedure for COVID-19 male patients.

Ligand/Receptor-mediated Cell Communication Alteration Causes the Lung Inflammation Microenvironment and the Redistribution of Inter-tissue Immune Cells in COVID-19 Patients (preprint)

How SARS-CoV-2 causes disturbances of the lung microenvironment and systemic immune response remains a mystery. Here, we first analyze detailedly paired single-cell transcriptome data of the lungs, blood and bone marrow of two patients who died of COVID-19. Second, our results demonstrate that SARS-CoV-2 infection significantly increases the cellular communication frequency between AT1/AT2 cells and highly inflammatory myeloid cells, and induces the pulmonary inflammation microenvironment, and drives the disorder of fibroblasts, club and ciliated cells, thereby causing the increase of pulmonary fibrosis and mucus accumulation. Third, our works reveal that the increase of the lung T cell infiltration is mainly recruited by myeloid cells through certain ligands/receptors (ANXA1/FPR1, C5AR1/RPS19 and CCL5/CCR1), rather than AT1/AT2. Fourth, we find that some ligands and receptors such as ANXA1/FPR1, CD74/COPA, CXCLs/CXCRs, ALOX5/ALOX5AP, CCL5/CCR1, are significantly activated and shared among patients’ lungs, blood and bone marrow, implying that dysregulated ligands and receptors may cause the migration, redistribution and the inflammatory storm of immune cells in different tissues. Overall, our study reveals a latent mechanism by which the disorders of ligands and receptors caused by SARS-CoV-2 infection drive cell communication alteration, the pulmonary inflammatory microenvironment and systemic immune responses across tissues in COVID-19 patients.

Rapid SARS-CoV-2 diagnosis using disposable strips and a metal-oxide-semiconductor field-effect transistor platform.

The SARS-CoV-2 pandemic has had a significant impact worldwide. Currently, the most common detection methods for the virus are polymerase chain reaction (PCR) and lateral flow tests. PCR takes more than an hour to obtain the results and lateral flow tests have difficulty with detecting the virus at low concentrations. In this study, 60 clinical human saliva samples, which included 30 positive and 30 negative samples confirmed with RT-PCR, were screened for COVID-19 using disposable glucose biosensor strips and a reusable printed circuit board. The disposable strips were gold plated and functionalized to immobilize antibodies on the gold film. After functionalization, the strips were connected to the gate electrode of a metal-oxide-semiconductor field-effect transistor on the printed circuit board to amplify the test signals. A synchronous double-pulsed bias voltage was applied to the drain of the transistor and strips. The resulting change in drain waveforms was converted to digital readings. The RT-PCR-confirmed saliva samples were tested again using quantitative PCR (RT-qPCR) to determine cycling threshold (Ct) values. Ct values up to 45 refer to the number of amplification cycles needed to detect the presence of the virus. These PCR results were compared with digital readings from the sensor to better evaluate the sensor technology. The results indicate that the samples with a range of Ct values from 17.8 to 35 can be differentiated, which highlights the increased sensitivity of this sensor technology. This research exhibits the potential of this biosensor technology to be further developed into a cost-effective, point-of-care, and portable rapid detection method for SARS-CoV-2.

Characterization and evaluation of the leachability of bottom ash from a mobile emergency incinerator of COVID-19 medical waste: A case study in Huoshenshan Hospital, Wuhan, China.

To dispose of the medical waste generated during the COVID-19 pandemic, a new type of mobile emergency incinerator (MEI) was used in Huoshenshan Hospital, Wuhan, China, and consequently, it produced a number of medical bottom ashs (MBAs). In this study, the characterization and environmental risk evaluation of these MBAs were conducted to evaluate the disposal effect of this MEI used during the pandemic. Three types of leaching tests, EN 12457-2, TCLP 1311, and HJ/T 299-2007, were compared to investigate the release behaviors of major and trace elements from these MBAs. Lack of detection of COVID-19 in MBAs showed that this mobile emergency incinerator could thoroughly eliminate the COVID-19 virus in medical wastes to avoid secondary transmission. The results indicated that the increasing usage of chlorinated disinfectants and physiological saline solutions resulted in high Cl contents in MBAs. In addition, the increasing usage of polypropylene (PP) products changed the chemical properties and compositions of MBAs, with Ca as the main element. The leachability investigation revealed that the main metals in leachates were Ca, Na and K, and the toxic heavy metals such as Zn, Pb, Cu, and Cr in MBAs were difficult to extract because of the high pH (>12) of these MBAs. This study could provide consultation for the treatment and management of MBAs produced from MEIs dealing with emergent infectious diseases such as COVID-19.

Association of blood glucose level and prognosis of inpatients with coexistent diabetes and COVID-19.

Type 2 diabetes (T2D) increases the risk of coronavirus disease (COVID-19). This study investigates the association between glucose control of COVID-19 patients with T2D in first 7 days after hospital admission and prognosis. A total of 252 infected inpatients with T2D in China were included. Well-controlled blood glucose was defined as stable fasting blood glucose (FBG) levels in the range of 3.9-7.8 mmol/L during first 7 days using indicators of average (FBGA), maximum (FBGM) or first-time (FBG1) FBG levels. The primary endpoint was admission to intensive care unit or death. Hazard ratio (HR) of poorly controlled glucose level group compared with well-controlled group were 4.96 (P = 0.021) for FBGM and 5.55 (P = 0.014) for FBGA. Well-controlled blood glucose levels in first 7 days could improve the prognosis of COVID-19 inpatients with diabetes.

Different Profiles of Antibodies and Cytokines Were Found Between Severe and Moderate COVID-19 Patients.

Objectives: Our objective was to determine the antibody and cytokine profiles in different COVID-19 patients. Methods: COVID-19 patients with different clinical classifications were enrolled in this study. The level of IgG antibodies, IgA, IgM, IgE, and IgG subclasses targeting N and S proteins were tested using ELISA. Neutralizing antibody titers were determined by using a toxin neutralization assay (TNA) with live SARS-CoV-2. The concentrations of 8 cytokines, including IL-2, IL-4, IL-6, IL-10, CCL2, CXCL10, IFN-γ, and TNF-α, were measured using the Protein Sample Ella-Simple ELISA system. The differences in antibodies and cytokines between severe and moderate patients were compared by t-tests or Mann-Whitney tests. Results: A total of 79 COVID-19 patients, including 49 moderate patients and 30 severe patients, were enrolled. Compared with those in moderate patients, neutralizing antibody and IgG-S antibody titers in severe patients were significantly higher. The concentration of IgG-N antibody was significantly higher than that of IgG-S antibody in COVID-19 patients. There was a significant difference in the distribution of IgG subclass antibodies between moderate patients and severe patients. The positive ratio of anti-S protein IgG3 is significantly more than anti-N protein IgG3, while the anti-S protein IgG4 positive rate is significantly less than the anti-N protein IgG4 positive rate. IL-2 was lower in COVID-19 patients than in healthy individuals, while IL-4, IL-6, CCL2, IFN-γ, and TNF-α were higher in COVID-19 patients than in healthy individuals. IL-6 was significantly higher in severe patients than in moderate patients. The antibody level of anti-S protein was positively correlated with the titer of neutralizing antibody, but there was no relationship between cytokines and neutralizing antibody. Conclusions: Our findings show the severe COVID-19 patients' antibody levels were stronger than those of moderate patients, and a cytokine storm is associated with COVID-19 severity. There was a difference in immunoglobulin type between anti-S protein antibodies and anti-N protein antibodies in COVID-19 patients. And clarified the value of the profile in critical prevention.

Laboratory Testing Implications of Risk-Stratification and Management of COVID-19 Patients.

Objective: To distinguish COVID-19 patients and non-COVID-19 viral pneumonia patients and classify COVID-19 patients into low-risk and high-risk at admission by laboratory indicators. Materials and methods: In this retrospective cohort, a total of 3,563 COVID-19 patients and 118 non-COVID-19 pneumonia patients were included. There are two cohorts of COVID-19 patients, including 548 patients in the training dataset, and 3,015 patients in the testing dataset. Laboratory indicators were measured during hospitalization for all patients. Based on laboratory indicators, we used the support vector machine and joint random sampling to risk stratification for COVID-19 patients at admission. Based on laboratory indicators detected within the 1st week after admission, we used logistic regression and joint random sampling to develop the survival mode. The laboratory indicators of COVID-10 and non-COVID-19 were also compared. Results: We first identified the significant laboratory indicators related to the severity of COVID-19 in the training dataset. Neutrophils percentage, lymphocytes percentage, creatinine, and blood urea nitrogen with AUC >0.7 were included in the model. These indicators were further used to build a support vector machine model to classify patients into low-risk and high-risk at admission in the testing dataset. Results showed that this model could stratify the patients in the testing dataset effectively (AUC = 0.89). Our model still has good performance at different times (Mean AUC: 0.71, 0.72, 0.72, respectively for 3, 5, and 7 days after admission). Moreover, laboratory indicators detected within the 1st week after admission were able to estimate the probability of death (AUC = 0.95). We identified six indicators with permutation p < 0.05, including eosinophil percentage (p = 0.007), white blood cell count (p = 0.045), albumin (p = 0.041), aspartate transaminase (p = 0.043), lactate dehydrogenase (p = 0.002), and hemoglobin (p = 0.031). We could diagnose COVID-19 and differentiate it from other kinds of viral pneumonia based on these laboratory indicators. Conclusions: Our risk-stratification model based on laboratory indicators could help to diagnose, monitor, and predict severity at an early stage of COVID-19. In addition, laboratory findings could be used to distinguish COVID-19 and non-COVID-19.

Genome-wide association study of COVID-19 severity among the Chinese population.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection causes a broad clinical spectrum of coronavirus disease 2019 (COVID-19). The development of COVID-19 may be the result of a complex interaction between the microbial, environmental, and host genetic components. To reveal genetic determinants of susceptibility to COVID-19 severity in the Chinese population, we performed a genome-wide association study on 885 severe or critical COVID-19 patients (cases) and 546 mild or moderate patients (controls) from two hospitals, Huoshenshan and Union hospitals at Wuhan city in China. We identified two loci on chromosome 11q23.3 and 11q14.2, which are significantly associated with the COVID-19 severity in the meta-analyses of the two cohorts (index rs1712779: odds ratio [OR] = 0.49; 95% confidence interval [CI], 0.38-0.63 for T allele; P = 1.38 × 10-8; and index rs10831496: OR = 1.66; 95% CI, 1.38-1.98 for A allele; P = 4.04 × 10-8, respectively). The results for rs1712779 were validated in other two small COVID-19 cohorts in the Asian populations (P = 0.029 and 0.031, respectively). Furthermore, we identified significant eQTL associations for REXO2, C11orf71, NNMT, and CADM1 at 11q23.3, and CTSC at 11q14.2, respectively. In conclusion, our findings highlight two loci at 11q23.3 and 11q14.2 conferring susceptibility to the severity of COVID-19, which might provide novel insights into the pathogenesis and clinical treatment of this disease.

Mechanistic insights into SARS-CoV-2 epidemic via revealing the features of SARS-CoV-2 coding proteins and host responses upon its infection.

SUMMARY: There are seven known coronaviruses that infect humans: four mild coronaviruses, including HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1, only cause mild respiratory diseases, and three severe coronaviruses, including SARS-CoV, MERS-CoV and SARS-CoV-2, can cause severe respiratory diseases even death of infected patients. Both infection and death caused by SARS-CoV-2 are still rapidly increasing worldwide. In this study, we demonstrate that viral coding proteins of SARS-CoV-2 have distinct features and are most, medium and least conserved with SARS-CoV, MERS-CoV and the rest four mild coronaviruses (HCoV-229E, HCoV-OC43, HCoV-NL63 and HCoV-HKU1), respectively. Moreover, expression of host responsive genes (HRG), HRG-enriched biological processes and HRG-enriched KEGG pathways upon infection of SARS-CoV-2 shows slightly overlapping with SARS-CoV and MERS-CoV but distinctive to the four mild coronaviruses. Interestingly, enrichment of overactivation of neutrophil by HRGs is only and commonly found in infections of severe SARS-CoV-2, SARS-CoV and MERS-CoV but not in the other four mild coronaviruses, and the related gene networks show different patterns. Clinical data support that overactivation of neutrophil for severe patients can be one major factor for the similar clinical symptoms observed in SARS-CoV-2 infection compared to infections of the other two severe coronavirus (SARS-CoV and MERS-CoV). Taken together, our study provides a mechanistic insight into SARS-CoV-2 epidemic via revealing the conserved and distinct features of SARS-CoV-2, raising the critical role of dysregulation of neutrophil for SARS-CoV-2 infection. AVAILABILITY AND IMPLEMENTATION: All data sources and analysis methods related to this manuscript are available in the methods, supplementary materials and GEO database (https://www.ncbi.nlm.nih.gov/geo/). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Sex-based clinical and immunological differences in COVID-19.

BACKGROUND: Males and females differ in their immunological responses to foreign pathogens. However, most of the current COVID-19 clinical practices and trials do not take the sex factor into consideration. METHODS: We performed a sex-based comparative analysis for the clinical outcomes, peripheral immune cells, and severe acute respiratory syndrome coronavirus (SARS-CoV-2) specific antibody levels of 1558 males and 1499 females COVID-19 patients from a single center. The lymphocyte subgroups were measured by Flow cytometry. The total antibody, Spike protein (S)-, receptor binding domain (RBD)-, and nucleoprotein (N)- specific IgM and IgG levels were measured by chemiluminescence. RESULTS: We found that male patients had approximately two-fold rates of ICU admission (4.7% vs. 2.7% in males and females, respectively, P = 0.005) and mortality (3% vs. 1.4%, in males and females, respectively, P = 0.004) than female patients. Survival analysis revealed that the male sex is an independent risk factor for death from COVID-19 (adjusted hazard ratio [HR] = 2.22, 95% confidence interval [CI]: 1.3-3.6, P = 0.003). The level of inflammatory cytokines in peripheral blood was higher in males during hospitalization. The renal (102/1588 [6.5%] vs. 63/1499 [4.2%], in males and females, respectively, P = 0.002) and hepatic abnormality (650/1588 [40.9%] vs. 475/1499 [31.7%], P = 0.003) were more common in male patients than in female patients. By analyzing dynamic changes of lymphocyte subsets after symptom onset, we found that the percentage of CD19+ B cells and CD4+ T cells was generally higher in female patients during the disease course of COVID-19. Notably, the protective RBD-specific IgG against SARS-CoV-2 sharply increased and reached a peak in the fourth week after symptom onset in female patients, while gradually increased and reached a peak in the seventh week after symptom onset in male patients. CONCLUSIONS: Males had an unfavorable prognosis, higher inflammation, a lower percentage of lymphocytes, and indolent antibody responses during SARS-CoV-2 infection and recovery. Early medical intervention and close monitoring are important, especially for male COVID-19 patients.

Comparative Characterization and Risk Stratification of Asymptomatic and Presymptomatic Patients With COVID-19.

The identification of asymptomatic, non-severe presymptomatic, and severe presymptomatic coronavirus disease 2019 (COVID-19) in patients may help optimize risk-stratified clinical management and improve prognosis. This single-center case series from Wuhan Huoshenshan Hospital, China, included 2,980 patients with COVID-19 who were hospitalized between February 4, 2020 and April 10, 2020. Patients were diagnosed as asymptomatic (n = 39), presymptomatic (n = 34), and symptomatic (n = 2,907) upon admission. This study provided an overview of asymptomatic, presymptomatic, and symptomatic COVID-19 patients, including detection, demographics, clinical characteristics, and outcomes. Upon admission, there was no significant difference in clinical symptoms and CT image between asymptomatic and presymptomatic patients for diagnosis reference. The mean area under the receiver operating characteristic curve (AUC) of the differential diagnosis model to discriminate presymptomatic patients from asymptomatic patients was 0.89 (95% CI, 0.81-0.98). Importantly, the severe and non-severe presymptomatic patients can be further stratified (AUC = 0.82). In conclusion, the two-step risk-stratification model based on 10 laboratory indicators can distinguish among asymptomatic, severe presymptomatic, and non-severe presymptomatic COVID-19 patients on admission. Moreover, single-cell data analyses revealed that the CD8+T cell exhaustion correlated to the progression of COVID-19.

Efficacy and Safety of Tocilizumab Treatment COVID-19 Patients: A Case-Control Study and Meta-Analysis.

INTRODUCTION: As the pandemic progresses, the pathophysiology of COVID-19 is becoming more apparent, and the potential for tocilizumab is increasing. However, the clinical efficacy and safety of tocilizumab in the treatment of COVID-19 patients remain unclear. METHODS: To assess the efficacy and safety of tocilizumab treatment in COVID-19 patients, we performed a retrospective case-control study. The study was conducted, including 95 patients treated with tocilizumab plus standard treatment and matched controls with 95 patients treated with standard treatment therapy by propensity score from February to April 2020. We searched some databases using the search terms for studies published from January 1, 2020, to June 1, 2021. RESULTS: Our case-control study found a lower mortality rate in the tocilizumab treatment group than in the standard treatment group (9.47% versus 16.84%, P = 0.134), but the results were not statistically significant. We also found that the mortality rate in tocilizumab treatment groups was significantly lower than in the standard treatment group in the stratified ICU analysis (OR 0.52, 95% CI 0.44-0.61, P = 0.048 and OR 0.31, 95% CI 0.10-0.99, P = 0.044). We selected 49 studies (including 6568 cases and 11,660 controls) that met the inclusion criteria in the meta-analysis. In the overall analysis, we performed a meta-analysis that showed significantly decreased mortality after patients received tocilizumab (OR 0.81, 95% CI 0.69-0.95, P = 0.008). We also revealed significant associations within some subgroups. The sequential trial analysis showed a true-positive result. No significant associations were observed between tocilizumab and elevated secondary infection risk, discharge, adverse events, and mechanical ventilation in the overall analysis. CONCLUSION: Tocilizumab significantly decreased mortality in COVID-19 patients with no increased discharge, secondary infection risk, adverse events, and mechanical ventilation in a meta-analysis. Our data suggest that clinicians should pay attention to tocilizumab therapy as an effective and safe treatment for COVID-19 patients.

A cohort autopsy study defines COVID-19 systemic pathogenesis.

Severe COVID-19 disease caused by SARS-CoV-2 is frequently accompanied by dysfunction of the lungs and extrapulmonary organs. However, the organotropism of SARS-CoV-2 and the port of virus entry for systemic dissemination remain largely unknown. We profiled 26 COVID-19 autopsy cases from four cohorts in Wuhan, China, and determined the systemic distribution of SARS-CoV-2. SARS-CoV-2 was detected in the lungs and multiple extrapulmonary organs of critically ill COVID-19 patients up to 67 days after symptom onset. Based on organotropism and pathological features of the patients, COVID-19 was divided into viral intrapulmonary and systemic subtypes. In patients with systemic viral distribution, SARS-CoV-2 was detected in monocytes, macrophages, and vascular endothelia at blood-air barrier, blood-testis barrier, and filtration barrier. Critically ill patients with long disease duration showed decreased pulmonary cell proliferation, reduced viral RNA, and marked fibrosis in the lungs. Permanent SARS-CoV-2 presence and tissue injuries in the lungs and extrapulmonary organs suggest direct viral invasion as a mechanism of pathogenicity in critically ill patients. SARS-CoV-2 may hijack monocytes, macrophages, and vascular endothelia at physiological barriers as the ports of entry for systemic dissemination. Our study thus delineates systemic pathological features of SARS-CoV-2 infection, which sheds light on the development of novel COVID-19 treatment.

High Expression of ACE2 and TMPRSS2 at the Resection Margin Makes Lung Cancer Survivors Susceptible to SARS-CoV-2 With Unfavorable Prognosis.

BACKGROUND: Coronavirus disease 2019 (COVID-19) has rapidly spread worldwide. Systematic analysis of lung cancer survivors at molecular and clinical levels is warranted to understand the disease course and clinical characteristics. METHODS: A single-center, retrospective cohort study was conducted in 65 patients with COVID-19 from Wuhan Huoshenshan Hospital, of which 13 patients were diagnosed with lung cancer. The study was conducted from February 4 to April 11, 2020. RESULTS: During the course of treatment, lung cancer survivors infected with severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) had shorter median time from symptom onset to hospitalization (P = 0.016) and longer clinical symptom remission time (P = 0.020) than non-cancer individuals. No differences were observed among indicators such as time from symptom onset to hospitalization and symptom remission time between medium-term and short-term survivors. The expression of ACE2 (P = 0.013) and TMPRSS2 (P <0.001) was elevated in lung cancer survivors as compared with that in non-cancer individuals. CONCLUSIONS: ACE2 and TMPRSS2 levels were higher at resection margins of lung cancer survivors than those in normal tissues of non-cancerous individuals and may serve as factors responsible for the high susceptibility to COVID-19 among lung cancer survivors. Lung cancer patients diagnosed with COVID-19, including medium-term survivors, have worse outcomes than the general population.

Fast SARS-CoV-2 virus detection using disposable cartridge strips and a semiconductor-based biosensor platform.

Detection of the SARS-CoV-2 spike protein and inactivated virus was achieved using disposable and biofunctionalized functional strips, which can be connected externally to a reusable printed circuit board for signal amplification with an embedded metal-oxide-semiconductor field-effect transistor (MOSFET). A series of chemical reactions was performed to immobilize both a monoclonal antibody and a polyclonal antibody onto the Au-plated electrode used as the sensing surface. An important step in the biofunctionalization, namely, the formation of Au-plated clusters on the sensor strips, was verified by scanning electron microscopy, as well as electrical measurements, to confirm successful binding of thiol groups on this Au surface. The functionalized sensor was externally connected to the gate electrode of the MOSFET, and synchronous pulses were applied to both the sensing strip and the drain contact of the MOSFET. The resulting changes in the dynamics of drain waveforms were converted into analog voltages and digital readouts, which correlate with the concentration of proteins and virus present in the tested solution. A broad range of protein concentrations from 1 fg/ml to 10 µg/ml and virus concentrations from 100 to 2500 PFU/ml were detectable for the sensor functionalized with both antibodies. The results show the potential of this approach for the development of a portable, low-cost, and disposable cartridge sensor system for point-of-care detection of viral diseases.