Functions of double-negative B cells in autoimmune diseases, infections, and cancers.

Most mature B cells can be divided into four subtypes based on the expression of the surface markers IgD and CD27: IgD+ CD27- naïve B cells, IgD+ CD27+ unswitched memory B cells, IgD- CD27+ switched memory B cells, and IgD- CD27- double-negative (DN) B cells. Despite their small population size in normal peripheral blood, DN B cells play integral roles in various diseases. For example, they generate autoimmunity in autoimmune conditions, while these cells may generate both autoimmune and antipathogenic responses in COVID-19, or act in a purely antipathogenic capacity in malaria. Recently, DN B cells have been identified in nasopharyngeal carcinoma and non-small-cell lung cancers, where they may play an immunosuppressive role. The distinct functions that DN B cells play in different diseases suggest that they are a heterogeneous B-cell population. Therefore, further study of the mechanisms underlying the involvement of DN B cells in these diseases is essential for understanding their pathogenesis and the development of therapeutic strategies. Further research is thus warranted to characterize the DN B-cell population in detail.

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.

Corrigendum to "Clinical Characteristics of Asymptomatic Patients with SARS-CoV-2 in Zhejiang: An Imperceptible Source of Infection".

[This corrects the article DOI: 10.1155/2020/2045341.].

Medicinal chemistry perspective on cGAS-STING signaling pathway with small molecule inhibitors.

The cyclic GMP-AMP synthase (cGAS)-stimulator of interferon genes (STING) signaling pathway serves as a pivotal mediator of innate immunity by triggering the secretion of type I interferons and other proinflammatory cytokines. In view of the immune-related diseases caused by abnormal activity of the cGAS-STING signaling pathway, considerable progress in this field has encouraged the discovery of cGAS-STING inhibitors in the past five years. In this review, we will focus on the link between the cGAS-STING signaling pathway and autoimmune and inflammatory disorders, summarize the development and optimization of cGAS-STING signaling pathway inhibitors, discuss the therapeutic effects on inflammatory diseases and propose suggestions and insights for future exploitation.

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future.

As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) "Resolution Revolution" made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.

Deep learning identified genetic variants for COVID-19-related mortality among 28,097 affected cases in UK Biobank.

Analysis of host genetic components provides insights into the susceptibility and response to viral infection such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes coronavirus disease 2019 (COVID-19). To reveal genetic determinants of susceptibility to COVID-19 related mortality, we train a deep learning model to identify groups of genetic variants and their interactions that contribute to the COVID-19 related mortality risk using the UK Biobank data (28,097 affected cases and 1656 deaths). We refer to such groups of variants as super variants. We identify 15 super variants with various levels of significance as susceptibility loci for COVID-19 mortality. Specifically, we identify a super variant (odds ratio [OR] = 1.594, p = 5.47 × 10-9 ) on Chromosome 7 that consists of the minor allele of rs76398985, rs6943608, rs2052130, 7:150989011_CT_C, rs118033050, and rs12540488. We also discover a super variant (OR = 1.353, p = 2.87 × 10-8 ) on Chromosome 5 that contains rs12517344, rs72733036, rs190052994, rs34723029, rs72734818, 5:9305797_GTA_G, and rs180899355.

Electron microscopy holdings of the Protein Data Bank: the impact of the resolution revolution, new validation tools, and implications for the future

As a discipline, structural biology has been transformed by the three-dimensional electron microscopy (3DEM) “Resolution Revolution” made possible by convergence of robust cryo-preservation of vitrified biological materials, sample handling systems, and measurement stages operating a liquid nitrogen temperature, improvements in electron optics that preserve phase information at the atomic level, direct electron detectors (DEDs), high-speed computing with graphics processing units, and rapid advances in data acquisition and processing software. 3DEM structure information (atomic coordinates and related metadata) are archived in the open-access Protein Data Bank (PDB), which currently holds more than 11,000 3DEM structures of proteins and nucleic acids, and their complexes with one another and small-molecule ligands (~ 6% of the archive). Underlying experimental data (3DEM density maps and related metadata) are stored in the Electron Microscopy Data Bank (EMDB), which currently holds more than 21,000 3DEM density maps. After describing the history of the PDB and the Worldwide Protein Data Bank (wwPDB) partnership, which jointly manages both the PDB and EMDB archives, this review examines the origins of the resolution revolution and analyzes its impact on structural biology viewed through the lens of PDB holdings. Six areas of focus exemplifying the impact of 3DEM across the biosciences are discussed in detail (icosahedral viruses, ribosomes, integral membrane proteins, SARS-CoV-2 spike proteins, cryogenic electron tomography, and integrative structure determination combining 3DEM with complementary biophysical measurement techniques), followed by a review of 3DEM structure validation by the wwPDB that underscores the importance of community engagement.

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.

Identification and characterization of a novel cell binding and cross-reactive region on spike protein of SARS-CoV-2.

Given that COVID-19 continues to wreak havoc around the world, it is imperative to search for a conserved region involved in viral infection so that effective vaccines can be developed to prevent the virus from rapid mutations. We have established a twelve-fragment library of recombinant proteins covering the entire region of spike protein of both SARS-CoV-2 and SARS-CoV from Escherichia coli. IgGs from murine antisera specifically against 6 spike protein fragments of SARS-CoV-2 were produced, purified, and characterized. We found that one specific IgG against the fusion process region, named COVID19-SF5, serologically cross-reacted with all twelve S-protein fragments. COVID19-SF5, with amino acid sequences from 880 to 1084, specifically bound to VERO-E6 and BEAS-2B cells, with K_d values of 449.1 ± 21.41 and 381.9 ± 31.53 nM, and IC₅₀ values of 761.2 ± 28.2 nM and 862.4 ± 32.1 nM, respectively. In addition, COVID19-SF5 greatly enhanced binding of the full-length CHO cell-derived spike protein to the host cells in a concentration-dependent manner. Furthermore, COVID19-SF5 and its IgGs inhibited the infection of the host cells by pseudovirus. The combined data from our studies reveal that COVID19-SF5, a novel cell-binding fragment, may contain a common region(s) for mediating viral binding during infection. Our studies also provide valuable insights into how virus variants may evade host immune recognition. Significantly, the observation that the IgGs against COVID19-SF5 possesses cross reactivity to all other fragments of S protein, suggesting that it is possible to develop universal neutralizing monoclonal antibodies to curb rapid mutations of COVID-19.

Comparison of Use of Neoadjuvant Systemic Treatment for Breast Cancer and Short-term Outcomes Before vs During the COVID-19 Era in Ontario, Canada.

Importance: In response to an increase in COVID-19 infection rates in Ontario, several systemic treatment (ST) regimens delivered in the adjuvant setting for breast cancer were temporarily permitted for neoadjuvant-intent to defer nonurgent breast cancer surgical procedures. Objective: To examine the use and compare short-term outcomes of neoadjuvant-intent vs adjuvant ST in the COVID-19 era compared with the pre-COVID-19 era. Design, Setting, and Participants: This was a retrospective population-based cohort study in Ontario, Canada. Patients with cancer starting selected ST regimens in the COVID-19 era (March 11, 2020, to September 30, 2020) were compared to those in the pre-COVID-19 era (March 11, 2019, to March 10, 2020). Patients were diagnosed with breast cancer within 6 months of starting systemic therapy. Main Outcomes and Measures: Estimates were calculated for the use of neoadjuvant vs adjuvant ST, the likelihood of receiving a surgical procedure, the rate of emergency department visits, hospital admissions, COVID-19 infections, and all-cause mortality between treatment groups over time. Results: Among a total of 10 920 patients included, 7990 (73.2%) started treatment in the pre-COVID-19 era and 7344 (67.3%) received adjuvant ST; the mean (SD) age was 61.6 (13.1) years. Neoadjuvant-intent ST was more common in the COVID-19 era (1404 of 2930 patients [47.9%]) than the pre-COVID-19 era (2172 of 7990 patients [27.2%]), with an odds ratio of 2.46 (95% CI, 2.26-2.69; P < .001). This trend was consistent across a range of ST regimens, but differed according to patient age and geography. The likelihood of receiving surgery following neoadjuvant-intent chemotherapy was similar in the COVID-19 era compared with the pre-COVID-19 era (log-rank P = .06). However, patients with breast cancer receiving neoadjuvant-intent hormonal therapy were significantly more likely to receive surgery in the COVID-19 era (log-rank P < .001). After adjustment, there were no significant changes in the rate of emergency department visits over time between patients receiving neoadjuvant ST, adjuvant ST, or ST only during the ST treatment period or postoperative period. Hospital admissions decreased in the COVID-19 era for patients who received neoadjuvant ST compared with adjuvant ST or ST alone (P for interaction = .01 for both) in either setting. Conclusions and Relevance: In this cohort study, patients were more likely to start neoadjuvant ST in the COVID-19 era, which varied across the province and by indication. There was limited evidence to suggest any substantial impact on short-term outcomes.

Distribution, Progression, and Associated Factors of Refractive Status of Children in Lhasa, Tibet, after COVID-19 Quarantine.

INTRODUCTION: Uncorrected refractive error is one of the major causes of visual impairment in children and adolescents worldwide. During the COVID-19 epidemic, home isolation is considered a boost to the progression of children's myopia. Under geographical conditions of high altitude and strong sunshine, the Tibetan plateau is the main residence of the Tibetan population, where little information is available about the refractive status and developmental trajectory. Therefore, this article aimed to evaluate the distribution, progression, and associated factors of the refractive status in second-grade children in Lhasa after COVID-19 quarantine. MATERIALS AND METHODS: Students from 7 elementary schools completed comprehensive ocular examinations in the Lhasa Childhood Eye Study. Data regarding cycloplegic refraction and corneal biometry parameters, including axial length (AL), corneal power, anterior chamber depth (ACD), and other demographic factors, were analyzed. RESULTS: A total of 1,819 students were included, with a mean age of 7.9 ± 0.5 years, of which 961 were boys (52.8%), and 95.1% were Tibetan. The prevalence of myopia, emmetropia, mild hyperopia, and hyperopia was 10.94%, 24.02%, 60.80%, and 4.24%, respectively. Besides, the average cycloplegic spherical equivalent refraction (SER) was +1.07 ± 0.92 diopter (D) before the COVID-19 quarantine and +0.59 ± 1.08D after the quarantine (p < 0.05), with a growth rate of 7%. Moreover, the prevalence of hyperopia in girls was significantly higher than that of boys (p < 0.001). Nonetheless, the proportion of myopia and emmetropia was similar (p = 0.75). Meanwhile, children in suburban schools had a significantly lower proportion of myopia (p < 0.001). The average AL, ACD, lens power (LP), and AL-to-corneal radius (AL/CR) ratio were 22.79 ± 0.78 mm, 3.54 ± 0.21 mm, 25.12 ± 1.48D, and 2.93 ± 0.08, respectively. The results of AL, ACD, and AL/CR for girls were significantly lower than for boys, while the result of LP is the opposite (p < 0.001). Finally, multivariate regression analysis revealed that SER was negatively correlated with AL, LP, and AL/CR ratio, while positively correlated with CR and ACD (p < 0.001). CONCLUSION: This study found that after the COVID-19 confinement, myopia progressed faster in Lhasa children but was still significantly lower than that of plain cities in China. Compared to short-term confinement, this acceleration was more likely related to the growth and general trend of myopia in children. Collectively, these findings help to explore the differences in ocular growth and development among children of different ethnic groups.

Construction of Influenza Early Warning Model Based on Combinatorial Judgment Classifier: A Case Study of Seasonal Influenza in Hong Kong.

OBJECTIVE: The annual influenza epidemic is a heavy burden on the health care system, and has increasingly become a major public health problem in some areas, such as Hong Kong (China). Therefore, based on a variety of machine learning methods, and considering the seasonal influenza in Hong Kong, the study aims to establish a Combinatorial Judgment Classifier (CJC) model to classify the epidemic trend and improve the accuracy of influenza epidemic early warning. METHODS: The characteristic variables were selected using the single-factor statistical method to establish the influencing factor system of an influenza outbreak. On this basis, the CJC model was proposed to provide an early warning for an influenza outbreak. The characteristic variables in the final model included atmospheric pressure, absolute maximum temperature, mean temperature, absolute minimum temperature, mean dew point temperature, the number of positive detections of seasonal influenza viruses, the positive percentage among all respiratory specimens, and the admission rates in public hospitals with a principal diagnosis of influenza. RESULTS: The accuracy of the CJC model for the influenza outbreak trend reached 96.47%, the sensitivity and specificity change rates of this model were lower than those of other models. Hence, the CJC model has a more stable prediction performance. In the present study, the epidemic situation and meteorological data of Hong Kong in recent years were used as the research objects for the construction of the model index system, and a lag correlation was found between the influencing factors and influenza outbreak. However, some potential risk factors, such as geographical nature and human factors, were not incorporated, which ideally affected the prediction performance to some extent. CONCLUSION: In general, the CJC model exhibits a statistically better performance, when compared to some classical early warning algorithms, such as Support Vector Machine, Discriminant Analysis, and Ensemble Classfiers, which improves the performance of the early warning of seasonal influenza.

The impact of the COVID-19 preventive measures on influenza transmission: molecular and epidemiological evidence.

OBJECTIVE: We quantify the impact of COVID-19-related control measures on the spread of human influenza virus H1N1 and H3N2. METHODS: We analyzed case numbers to estimate the end of the 2019-2020 influenza season and compared it with the median of the previous 9 seasons. In addition, we used influenza molecular data to compare within-region and between-region genetic diversity and effective population size from 2019 to 2020. Finally, we analyzed personal behavior and policy stringency data for each region. RESULTS: The 2019-2020 influenza season ended earlier than the median of the previous 9 seasons in all regions. For H1N1 and H3N2, there was an increase in between-region genetic diversity in most pairs of regions between 2019 and 2020. There was a decrease in within-region genetic diversity for 12 of 14 regions for H1N1 and 9 of 12 regions for H3N2. There was a decrease in effective population size for 10 of 13 regions for H1N1 and 3 of 7 regions for H3N2. CONCLUSIONS: We found consistent evidence of a decrease in influenza incidence after the introduction of preventive measures due to COVID-19 emergence.

Environment uncertainty, accounting information quality and inefficient investment

The business environment of an enterprise is changing rapidly. Enterprises need to find suitable investment opportunities in the rapidly changing business environment to promote the long-term growth of enterprise value. Since the outbreak of 2019-nCoV, business environment has undergone major changes, which has a profound impact on the enterprise’s investment behavior. This paper selects A-share listed companies from 2014 to 2018. Based on the study of the impact of environment uncertainty on investment efficiency, the paper analyzes the mechanism of the impact of accounting information quality on this correlation. It is found that when the enterprise is facing uncertain environment, improving accounting information quality can effectively alleviate the inefficient investment of the enterprise.

Hesperidin Is a Potential Inhibitor against SARS-CoV-2 Infection.

Hesperidin (HD) is a common flavanone glycoside isolated from citrus fruits and possesses great potential for cardiovascular protection. Hesperetin (HT) is an aglycone metabolite of HD with high bioavailability. Through the docking simulation, HD and HT have shown their potential to bind to two cellular proteins: transmembrane serine protease 2 (TMPRSS2) and angiotensin-converting enzyme 2 (ACE2), which are required for the cellular entry of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Our results further found that HT and HD suppressed the infection of VeroE6 cells using lentiviral-based pseudo-particles with wild types and variants of SARS-CoV-2 with spike (S) proteins, by blocking the interaction between the S protein and cellular receptor ACE2 and reducing ACE2 and TMPRSS2 expression. In summary, hesperidin is a potential TMPRSS2 inhibitor for the reduction of the SARS-CoV-2 infection.

The impact of COVID-19 pandemic on influenza transmission: molecular and epidemiological evidence (preprint)

To quantify the impact of COVID-19-related control measures on the spread of human influenza virus, we analyzed case numbers, viral molecular sequences, personal behavior data, and policy stringency data from various countries, and found consistent evidence of decrease in influenza incidence after the emergence of COVID-19.

Analyzing master regulators and scRNA-seq of COVID-19 patients reveals an underlying anti-SARS-CoV-2 mechanism of ZNF proteins.

Studies have demonstrated that both mortality and severe illness rates exist significant difference in different gender COVID-19 patients, but the reasons are still very mysterious to date. Here, we firstly find that the survival outcome of female patients is better to male patients through analyzing the 3044 COVID-19 cases. Secondly, we identify many important master regulators [e.g. STAT1/STAT2 and zinc finger (ZNF) proteins], in particular female patients can express more ZNF proteins and stronger transcriptional activities than male patients in response to SARS-CoV-2 infection. Thirdly, we discover that ZNF protein activity is significantly negative correlation with the SARS-CoV-2 load of COVID-19 patients, and ZNF proteins as transcription factors can also activate their target genes to participate in anti-SARS-CoV-2 infection. Fourthly, we demonstrate that ZNF protein activity is positive correlation with the abundance of multiple immune cells of COVID-19 patients, implying that the highly ZNF protein activity might promote the abundance and the antiviral activity of multiple immune cells to effectively suppress SARS-CoV-2 infection. Taken together, our study proposes an underlying anti-SARS-COV-2 role of ZNF proteins, and differences in the amount and activity of ZNF proteins might be responsible for the distinct prognosis of different gender COVID-19 patients.

Upregulated IL-6 Indicates a Poor COVID-19 Prognosis: A Call for Tocilizumab and Convalescent Plasma Treatment.

A comprehensive understanding of the dynamic changes in interleukin-6 (IL-6) levels is essential for monitoring and treating patients infected with severe acute respiratory syndrome coronavirus 2 (SARS-Cov-2). By analyzing the correlations between IL-6 levels and health conditions, underlying diseases, several key laboratory detection indices, and the prognosis of 1,473 patients with the coronavirus disease 2019 (COVID-19), the role of IL-6 during SARS-CoV-2 infection was demonstrated. Our results indicated that IL-6 levels were closely related to age, sex, body temperature, oxygen saturation (SpO2) of blood, and underlying diseases. As a stable indicator, the changes in IL-6 levels could indicate the inflammatory conditions during a viral infection. Two specific treatments, namely, tocilizumab and convalescent plasma therapy (CPT), decreased the level of IL-6 and relieved inflammation. CPT has an important role in the therapy for patients with critical COVID-19. We also found that patients with IL-6 levels, which were 30-fold higher than the normal level, had a poor prognosis compared to patients with lower levels of IL-6.

Potential False-Positive and False-Negative Results for COVID-19 IgG/IgM Antibody Testing After Heat-Inactivation.

Objectives: With the worldwide spread of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), various antibody detection kits have been developed to test for SARS-CoV-2- specific IgG, IgM, and total antibody. However, the use of different testing methods under various heat-inactivation conditions might affect the COVID-19 detection results. Methods: Seven different antibody detection kits produced by four manufacturers for detection of SARS-CoV-2 IgG, IgM, and total antibody were tested at Wuhan Huoshenshan Hospital, China. Most of the kits used the indirect immunity, capture, and double-antigen sandwich methods. The effects of various heat-inactivation conditions on SARS-CoV-2-specific IgG, IgM, and total antibody detection were analyzed for the different test methods. Results: Using the indirect immunity method, values for SARS-CoV-2 IgG antibody significantly increased and those for IgM antibody decreased with increasing temperature of heat-inactivation using indirect immunity method. However, values for SARS-CoV-2 IgM and total antibody showed no change when the capture and double-antigen sandwich methods were used. The changes in IgG and IgM antibody values with the indirect immunity method indicated that heat-inactivation could affect COVID-19 detection results obtained using this method. In particular, 18 (22.2%) SARS-CoV-2 IgM positive samples were detected as negative with heat-inactivation at 65°C for 30 min, and one (25%) IgG negative sample was detected as positive after heat-inactivation at 56°C for 60 min and 60°C for 30 min. Conclusions: Heat-inactivation could increase SARS-CoV-2 IgG antibody values, and decrease IgM antibody values, causing potential false-positive or false-negative results for COVID-19 antibody detection using the indirect immunity method. Thus, before conducting antibody testing, the testing platforms should be evaluated in accordance with the relevant requirements to ensure accurate COVID-19 detection results.

The paradoxical problem with COVID-19 ocular infection: Moderate clinical manifestation and potential infection risk.

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which induced mainly the respiratory damage also caused ocular surface symptoms. However, the detailed description of ocular manifestations, severity fluctuations in confirmed COVID-19 adult patients still lacked. We analyzed onset clinical symptoms and duration, ocular symptoms, needs for medication, outcomes in 28 conjunctivitis patients who were extracted from 3198 COVID-19 patients hospitalized in Huoshenshan Hospital and Taikangtongji Hospital, Wuhan, China. The expression levels of ACE2, TMPRSS2, ANPEP, DPP4, NRP1 on fetal and adult ocular surface and mouse lacrimal glands were assessed by single cell seq analysis. Our results indicated that conjunctivitis was a rare and self-limited complication in adults with COVID-19 while the existence of coronavirus receptors on human ocular surface and mouse lacrimal glands indicated the risk of SARS-CoV-2 infection. Our research firstly examined SARS-CoV-2 receptors, including the new discovered one, NRP1, on the fetal ocular surface and in the mouse lacrimal glands.