SARS-CoV-2 spike protein induces the cytokine release syndrome by stimulating T cells to produce more IL-2 (preprint)

Cytokine release syndrome (CRS) is one of the leading causes of mortality in COVID-19 patients caused by the SARS-CoV-2 coronavirus. However, the mechanism of CRS induced by SARS-CoV-2 is vague. This study shows that dendritic cells loaded with spike protein of SARS-CoV-2 stimulate T cells to release much more IL-2, which subsequently cooperates with spike protein to facilitate peripheral blood mononuclear cells to release IL-1{beta}, IL-6, and IL-8. These effects are achieved via IL-2 stimulation of NK cells to release TNF- and IFN-{gamma}, as well as T cells to release IFN-{gamma}. Mechanistically, IFN-{gamma} and TNF- enhance the transcription of CD40, and the interaction of CD40 and its ligand stabilizes the membrane expression of TLR4 which serves as a receptor of spike protein on the surface of monocytes. As a result, there is a constant interaction between spike protein and TLR4, leading to continuous activation of NF-{kappa}B. Furthermore, TNF- also activates NF-{kappa}B signaling in monocytes, which further cooperates with IFN-{gamma} and spike protein to modulate NF-{kappa}B-dependent transcription of CRS-related inflammatory cytokines. Targeting TNF-/IFN-{gamma} in combination with TLR4 may represent a promising therapeutic approach for alleviating CRS in individuals with COVID-19.

Interaction between Coronavirus and host cytoskeleton: a review

Coronavirus is a positive-strand RNA virus with the largest genome among all RNA viruses and can affect a wide range of vertebrate in connection, as well as human. Host cell cytoskeletons have been reported to involved in the process of virus entry, intracellular replication transport, assembly and egress of coronavirus, although many detailed mechanisms are still unclear. This article provides a brief overview of the function of the most prominent coronavirus-induced or -hijacked cytoskeletal structures including actin, microtubu1es and intermediate filaments. This article will provide evidence for future research on the interaction between the coronavirus and the host cytoskeleton.

Targeted photodynamic neutralization of SARS-CoV-2 mediated by singlet oxygen (preprint)

The SARS-CoV-2 virus has been on a rampage for more than two years. Vaccines in combination with neutralizing antibodies (NAbs) against SARS-CoV-2 carry great hope in the treatment and final elimination of COVID-19. However, the relentless emergence of variants of concern (VOC), including the most recent Omicron variants, presses for novel measures to counter these variants that often show immune evasion. Hereby we developed a targeted photodynamic approach to neutralize SARS-CoV-2 by engineering a genetically encoded photosensitizer (SOPP3) to a diverse list of antibodies targeting the WT spike protein, including human antibodies isolated from a 2003 SARS patient, potent monomeric and multimeric nanobodies targeting RBD, and non-neutralizing antibodies (non-NAbs) targeting the more conserved NTD region. As confirmed by pseudovirus neutralization assay, this targeted photodynamic approach significantly increased the efficacy of these antibodies, especially that of non-NAbs, against not only the WT but also the Delta strain and the heavily immune escape Omicron strain (BA.1). Subsequent measurement of infrared phosphorescence at 1270 nm confirmed the generation of singlet oxygen (1O2) in the photodynamic process. Mass spectroscopy assay uncovered amino acids in the spike protein targeted by 1O2. Impressively, Y145 and H146 form an oxidization hotspot, which overlaps with the antigenic supersite in NTD. Taken together, our study established a targeted photodynamic approach against the SARS-CoV-2 virus and provided mechanistic insights into the photodynamic modification of protein molecules mediated by 1O2.

Lung Swapping Autoencoder: Learning a Disentangled Structure-texture Representation of Chest Radiographs (preprint)

Well-labeled datasets of chest radiographs (CXRs) are difficult to acquire due to the high cost of annotation. Thus, it is desirable to learn a robust and transferable representation in an unsupervised manner to benefit tasks that lack labeled data. Unlike natural images, medical images have their own domain prior; e.g., we observe that many pulmonary diseases, such as the COVID-19, manifest as changes in the lung tissue texture rather than the anatomical structure. Therefore, we hypothesize that studying only the texture without the influence of structure variations would be advantageous for downstream prognostic and predictive modeling tasks. In this paper, we propose a generative framework, the Lung Swapping Autoencoder (LSAE), that learns factorized representations of a CXR to disentangle the texture factor from the structure factor. Specifically, by adversarial training, the LSAE is optimized to generate a hybrid image that preserves the lung shape in one image but inherits the lung texture of another. To demonstrate the effectiveness of the disentangled texture representation, we evaluate the texture encoder $Enc^t$ in LSAE on ChestX-ray14 (N=112,120), and our own multi-institutional COVID-19 outcome prediction dataset, COVOC (N=340 (Subset-1) + 53 (Subset-2)). On both datasets, we reach or surpass the state-of-the-art by finetuning $Enc^t$ in LSAE that is 77% smaller than a baseline Inception v3. Additionally, in semi-and-self supervised settings with a similar model budget, $Enc^t$ in LSAE is also competitive with the state-of-the-art MoCo. By "re-mixing" the texture and shape factors, we generate meaningful hybrid images that can augment the training set. This data augmentation method can further improve COVOC prediction performance. The improvement is consistent even when we directly evaluate the Subset-1 trained model on Subset-2 without any fine-tuning.

Intravenous Immunoglobulin-based Adjuvant Therapy for Severe COVID-19: a Single-center Retrospective Cohort Study (preprint)

Objective Coronavirus disease 2019 (COVID-19) is a major challenge facing the world. Certain guidelines recommend intravenous immunoglobulin (IVIG) for adjuvant treatment of COVID-19. However, there is a lack of clinical evidence to support the use of IVIG.Methods This single-center retrospective cohort study included all adult patients with laboratory-confirmed severe COVID-19 in the Respiratory and Critical Care Unit of Dabie Mountain Regional Medical Center, China. Patient information, including demographic data, laboratory indicators, the use of glucocorticoids and IVIG, hospital mortality, the application of mechanical ventilation, and the length of hospital stay was collected. The primary outcome was the composite end point, including death and the use of mechanical ventilation. The secondary outcome was the length of hospital stay.Results Of the 285 patients with confirmed COVID-19, 113 severely ill patients were included in this study. Compared with the non-IVIG group, more patients in the IVIG group reached the composite end point [12 (25.5%) vs 5 (7.6%), P=0.008]. However, there was no statistically significant difference in the primary outcome between the two groups (P=0.167) after adjusting for confounding factors. Patients in the IVIG group had a longer hospital stay [23.0 (19.0-31.0) vs 16.0 (13.8-22.0), P<0.001]. After adjusting for confounding factors, there was still a statistically significant difference between the two groups (P=0.041).Conclusion Adjuvant therapy with IVIG did not improve the in-hospital mortality rate or the need for mechanical ventilation in patients with severe COVID-19. In contrast, the application of IVIG was related to a longer hospital stay.

Effects of Diabetes and Blood Glucose on COVID-19 Mortality: A Retrospective Observational Study (preprint)

OBJECTIVE To investigate the association of diabetes and blood glucose on mortality of patients with Coronavirus disease 2019 (COVID-19). RESEARCH DESIGN AND METHODS This is a retrospective observational study of all patients with COVID-19 admitted to Huo-Shen-Shan Hospital, Wuhan, China. The hospital was built only for treating COVID-19 and opened on February 5, 2020. The primary endpoint is all-cause mortality during hospitalization. RESULTS Among 2877 hospitalized patients, 15.5% (387/2877) had a history of diabetes and 1.9% (56/2877) died in hospital. After adjustment for confounders, patients with diabetes had a 2-fold increase in the hazard of mortality as compared to patients without diabetes (adjusted HR 2.11, 95%CI: 1.16-3.83, P=0.014). The glucose above 4mmol/L was significantly associated with subsequent mortality on COVID-19(adjusted HR 1.17, 95%CI: 1.10-1.24, per 1mmol/L increase, P<0.001). CONCLUSIONS Diabetes and glucose were associated with increased mortality in patients with COVID-19. These data support that blood glucose should be properly controlled for possibly better survival outcomes in patients with COVID-19.

Research Progress of Peracetic Acid Inactivation of Virus in Wastewater Disinfection

Peracetic acid( PAA),a high-efficiency broad-spectrum disinfectant,is recommended by the government for the prevention and control of new coronavirus epidemics.The basic properties of PAA and its efficient ability of inactivating viruses were introduced in this review.The disinfection principle of PAA was clarified and the advantages of PAA were analyzed by comparing with other disinfection methods.Finally, the paper summarized the application methods of PAA in practical disinfection,in order to provide reference for its application in the prevention and control of new coronavirus epidemics.

The Effect of the Progressive Multi-Dimensional Policies on Imported COVID-19 Curtailment in China (preprint)

Background: As countries are lifting restrictions and resuming international travels, the rising risk of COVID-19 importation remains concerning, given that the SARS-CoV-2 virus could be transmitted unintentionally through the global transportation network. To explore and assess the effective strategies for curtailing the epidemic risk from international importation nationwide, we evaluate the “Joint Prevention and Control” mechanism that China adopted, which was made up of nineteen containment policies including quarantine, nucleic acid testing (NAT), border closure and flight service adjustment.Methods: To illustrate how the multi-pronged policies affect the confirmation of imported COVID-19 cases, the change of diagnosis time of the cases from border arrival to a clinical confirmation were selected as the key variable. Based on 1,314 epidemiological-survey cases from February 29 to May 25, 2020 in China, we applied negative binomial regression models to predict how each policy is associated with the variation of the diagnosis time. We then compared the average means of the marginal effect of each policy before and after its implementation in different port-of-entry cities.Findings: We found that multi-dimensional interventional policies are effective, when they were implemented in a synchronized manner. Strategies, such as centralized quarantine and NAT, flight service adjustment and border closure, were found to facilitate an early identification of infected inbound case. Specifically, from arrival to clinical confirmation, a coordinated implementation of these aforementioned policies is associated with a maximum reduction in diagnosis interval up to 3.38 days, 2.35 days and 2.23 days, respectively.Interpretation: The study suggests that the prevention of a domestic spreading of COVID-19 from importation can be effective when the intervention polices are implemented in a timely, multi-dimensional and synchronized manner.Funding Statement: This research was supported by a research grant from the Sustainability Institute, The Ohio State University.Declaration of Interests: Authors declare no competing interests.

Clinical Course And Risk Factors For In-hospital Death In Critical COVID-19 In Wuhan, China (preprint)

BACKGROUND The risk factors for mortality of COVID-19 classified as critical type have not been well described. OBJECTIVES This study aimed to described the clinical outcomes and further explored risk factors of in-hospital death for COVID-19 classified as critical type. METHODS This was a single-center retrospective cohort study. From February 5, 2020 to March 4, 2020, 98 consecutive patients classified as critical COVID-19 were included in Huo Shen Shan Hospital. The final date of follow-up was March 29, 2020. The primary outcome was all-cause mortality during hospitalization. Multivariable Cox regression model was used to explore the risk factors associated with in-hospital death. RESULTS Of the 98 patients, 43 (43.9%) died in hospital, 37(37.8%) discharged, and 18(18.4%) remained in hospital. The mean age was 68.5 (63, 75) years, and 57 (58.2%) were female. The most common comorbidity was hypertension (68.4%), followed by diabetes (17.3%), angina pectoris (13.3%). Except the sex (Female: 68.8% vs 49.1%, P=0.039) and angina pectoris (20.9% vs 7.3%, P = 0.048), there was no difference in other demographics and comorbidities between non-survivor and survivor groups. The proportion of elevated alanine aminotransferase, creatinine, D-dimer and cardiac injury marker were 59.4%, 35.7%, 87.5% and 42.9%, respectively, and all showed the significant difference between two groups. The acute cardiac injury, acute kidney injury (AKI), and acute respiratory distress syndrome (ARDS) were observed in 42.9%, 27.8% and 26.5% of the patients. Compared with survivor group, non-survivor group had more acute cardiac injury (79.1% vs 14.5%, P<0.0001), AKI (50.0% vs 10.9%, P<0.0001), and ARDS (37.2% vs 18.2%, P=0.034). Multivariable Cox regression showed increasing hazard ratio of in-hospital death associated with acute cardiac injury (HR, 6.57 [95% CI, 1.89-22.79]) and AKI (HR, 2.60 [95% CI, 1.15-5.86]). CONCLUSIONS COVID-19 classified as critical type had a high prevalence of acute cardiac and kidney injury, which were associated with a higher risk of in-hospital mortality.

Molecular mechanisms of Cardiac Injury associated with myocardial SARS-CoV-2 infection (preprint)

BackgroundCoronavirus Disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has spread around the world. Developing cardiac injury is a common condition in COVID-19 patients, but the pathogenesis remains unclear. MethodsThe RNA-Seq dataset (GES150392) compared expression profiling of mock human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) and SARS-cov-2-infected hiPSC-CMs were obtained from Gene Expression Omnibus (GEO). We identified the differentially expressed genes (DEGs) between those two groups. Through gene set enrichment analysis (GSEA), Gene Ontology (GO) analysis, Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis, and CLINVAR human diseases analysis to identify the main effect of SARS-CoV-2 on cardiomyocytes. A protein-protein interaction (PPI) network was constructed to visualize interactions and functions of the hub genes. ResultsA total of 1554 DEGs were identified (726 upregulated genes and 828 downregulated genes). Gene enrichment analysis shown that SARS-CoV-2 activate immuno-inflammatory responses via multiple signal pathways, including TNF, IL6-JAK-STAT3, IL2-STAT5, NF-{kappa}B, IL17, and Toll-like receptor signaling pathway in hiPSC-CMs. Whereas, the muscle contraction, cellular respiration and cell cycle of hiPSC-CMs were inhibited by SARS-CoV-2. CLINVAR human diseases analysis shown SRAS-Cov-2 infection was associated with myocardial infarction, cardiomyopathy and Limb-girdle muscular dystrophy. 15 hub genes were identified based on PPI network. Function analysis revealed that 11 upregulated hub genes were mainly enriched in cytokine activity, chemokine activity, Inflammatory response, leukocyte chemotaxis, and lipopolysaccharide-mediated signaling pathway. Furthermore, 4 downregulated hub genes were related to cell cycle regulation. ConclusionThe present study elucidates that the SARS-CoV-2 infection induced a strong defensive response in cardiomyocyte, leading to excessive immune inflammation, cell hypoxia, functional contractility reduction and apoptosis, ultimately result in myocardial injury.

Generation of antibodies against COVID-19 virus for development of diagnostic tools (preprint)

The COVID-19 China coronavirus started in Dec 2019 was challenged by the lack of accurate serological diagnostic tool for this deadly disease to quickly identify and isolate the infected patients. The generation of COVID-19-specific antibodies is essential for such tasks. Here we report that polyclonal and monoclonal antibodies were generated by immunizing animals with synthetic peptides corresponding to different areas of Nucleoprotein (N) of COVID-19. The specificities of the COVID-19 antibodies were assessed by Western Blot analysis against NPs from COVID-19, MERS and SARS. Antibodies were used for immunohistochemistry staining of the tissue sections from COVID-19 infected patient, as a potential diagnostic tool. A Sandwich ELISA kit was quickly assembled for quantitation of the virus/NP of COVID-19 concentrations in the vaccine preparations. Development of POCT is also aggressively undergoing.