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1.
Cell Discov ; 8(1): 70, 2022 Jul 25.
Article in English | MEDLINE | ID: covidwho-1960340

ABSTRACT

Little is known regarding why a subset of COVID-19 patients exhibited prolonged positivity of SARS-CoV-2 infection. Here, we found that patients with long viral RNA course (LC) exhibited prolonged high-level IgG antibodies and higher regulatory T (Treg) cell counts compared to those with short viral RNA course (SC) in terms of viral load. Longitudinal proteomics and metabolomics analyses of the patient sera uncovered that prolonged viral RNA shedding was associated with inhibition of the liver X receptor/retinoid X receptor (LXR/RXR) pathway, substantial suppression of diverse metabolites, activation of the complement system, suppressed cell migration, and enhanced viral replication. Furthermore, a ten-molecule learning model was established which could potentially predict viral RNA shedding period. In summary, this study uncovered enhanced inflammation and suppressed adaptive immunity in COVID-19 patients with prolonged viral RNA shedding, and proposed a multi-omic classifier for viral RNA shedding prediction.

2.
Med Care Res Rev ; : 10775587221111105, 2022 Jul 17.
Article in English | MEDLINE | ID: covidwho-1938197

ABSTRACT

Since the summer of 2020, the rate of coronavirus cases in the United States has been higher in rural areas than in urban areas, raising concerns that patients with coronavirus disease 2019 (COVID-19) will overwhelm under-resourced rural hospitals. Using data from the University of Minnesota COVID-19 Hospitalization Tracking Project and the U.S. Department of Health and Human Services, we document disparities in COVID-19 hospitalization rates between rural and urban areas. We show that rural-urban differences in COVID-19 admission rates were minimal in the summer of 2020 but began to diverge in fall 2020. Rural areas had statistically higher hospitalization rates from September 2020 through early 2021, after which rural-urban admission rates re-converged. The insights in this article are relevant to policymakers as they consider the adequacy of hospital resources across rural and urban areas during the COVID-19 pandemic.

3.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-338547

ABSTRACT

The restrictive measures that have been imposed from March 2020 on business activities in several countries to reduce the spread of the COVID-19 pandemic can be interpreted as shocks to global supply chains. We propose some agent-based models to evaluate the economic effects of different lockdown policies on the global automotive supply chain. Our analysis involves 3,323 companies belonging to 135 economic sectors and connected by 11,182 trade links. This network was sampled from 2018 to 2020. As far as know, this is the first study to map the global automotive supply chain across both industries and countries at the level of single companies. By reconstructing the network and simulating the effects of diverse lockdown policies, we get two significant insights. Companies characterized by a high elasticity of substitution of productive inputs in the short-term suffer less from restrictions than those with a rigid inputs mix, either because of their specific production technology or market position. This has a significant aggregate impact on economic activity. Therefore, targeted lockdown policies may bear less economic costs than generalized ones, such as locking down all companies in specific sectors. Our simulations provide useful information for policymakers about the relative costs of possible lockdown interventions.

4.
Convergence ; : 13548565221102594, 2022.
Article in English | Sage | ID: covidwho-1862000

ABSTRACT

The current study adopted a mixed-methods approach to examine both qualitative and quantitative data of Chinese WeChat users? strategies in response to COVID-19 conspiracy theories disseminated in WeChat. Thematic analysis based on 30 interviewees suggested interesting patterns about how such conspiracy theories were disseminated based on relationship types within WeChat groups and how different types of debunking strategies were used to counter conspiracy theories based on the relational outcomes and contexts. Quantitative data based on 588 participants suggested COVID-19 information exposures from different sources, conspiracy beliefs, exposures of conspiracy beliefs and face concerns influence WeChat users? responses to address COVID-19-related information in WeChat platform.

5.
SSRN; 2022.
Preprint in English | SSRN | ID: ppcovidwho-336345

ABSTRACT

The rapid and wide spread of the COVID-19 pandemic has caused severe supply chain disruptions worldwide. The purpose of this study is to investigate the growing literature on the economic impact of COVID-19 on supply chains. We focus on research methodology scholars have employed, especially, the quantitative methods and data analysis to various sectors either at a global, national, or firm level, in order to measure the pandemic effect. By summarizing the findings from different angles, we contribute to advance the knowledge in this domain and the perspective for further research, and provide insights for decision-makers and policy-makers to manage the impacts of COVID-19.

6.
Antiviral Res ; 199: 105271, 2022 03.
Article in English | MEDLINE | ID: covidwho-1850635

ABSTRACT

COVID-19, an infectious disease caused by the SARS-CoV-2 virus, emerged globally in early 2020 and has remained a serious public health issue. To date, although several preventative vaccines have been approved by FDA and EMA, vaccinated individuals increasingly suffer from breakthrough infections. Therapeutic antibodies may provide an alternative strategy to neutralize viral infection and treat serious cases; however, the clinical data and our experiments show that some FDA-approved monoclonal antibodies lose function against COVID-19 variants such as Omicron. Therefore, in this study, we present a novel therapeutic agent, SI-F019, an ACE2-Fc fusion protein whose neutralization efficiency is not compromised, but actually strengthened, by the mutations of dominant variants including Omicron. Comprehensive biophysical analyses revealed the mechanism of increased inhibition to be enhanced interaction of SI-F019 with all the tested spike variants, in contrast to monoclonal antibodies which tended to show weaker binding to some variants. The results imply that SI-F019 may be a broadly useful agent for treatment of COVID-19.


Subject(s)
COVID-19 , SARS-CoV-2 , Angiotensin-Converting Enzyme 2 , Antibodies, Neutralizing , Antibodies, Viral/therapeutic use , COVID-19/drug therapy , Humans , SARS-CoV-2/genetics , Spike Glycoprotein, Coronavirus
7.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-334322

ABSTRACT

More than 450 million individuals have recovered from COVID-19, but little is known about the host responses to long COVID. We performed proteomic and metabolomic analyses of 991 blood and urine specimens from 144 COVID-19 patients with comprehensive clinical data and up to 763 days of follow up. Our data showed that the lungs and kidneys are the most vulnerable organs in long COVID patients. Pulmonary and renal long COVID of one-year revisit can be predicted by a machine learning model based on clinical and multi-omics data collected during the first month from the disease onset with an ACC of 87.5%. Serum protein SFTPB and ATR were associated with pulmonary long COVID and might be potential therapeutic targets. Notably, our data show that all the patients with persistent pulmonary ground glass opacity or patchy opacity lesions developed into pulmonary fibrosis at two-year revisit. Together, this study depicts the longitudinal clinical and molecular landscape of COVID-19 with up to two-year follow-up and presents a method to predict pulmonary and renal long COVID.

8.
Stigma and Health ; : No Pagination Specified, 2022.
Article in English | APA PsycInfo | ID: covidwho-1773934

ABSTRACT

This study provided a systemic review of the content of 50 behavioral and social science studies investigating enactment and outcomes of anti-Asian stigma related to coronavirus disease (COVID-19) published in the final quarter of 2020 and during 2021. Based on a systematic search of several databases in December of 2021, 500 studies describing the impact of COVID-related stigma on Asian Americans were identified. From this group, 50 studies meeting the inclusion criteria were analyzed focusing on health and social consequences of stigma. The studies were described by five stigma themes: the enactment of stigma, health consequences of stigma, stigma in the social media, Asian American stigma in education, and policy and political consequences of anti-Asian stigma. The studies appeared in a wide range of scholarly journals using several methodologies. While some studies exclusively focused on health impacts of stigma, all considered how Asian Americans have been scapegoated for COVID-19. Spread of blame and digital stigma on the social media has been particularly damaging to psychological well-being. Discussion of these studies provided an informative systemic overview for how scholars from various disciplines have investigated the antecedents and possible mechanisms leading to anti-Asian hate. This study serves as a baseline for other scholars who want to build on this body of research in future studies as Omicron and other potential future variants of COVID unfold. (PsycInfo Database Record (c) 2022 APA, all rights reserved)

9.
Infect Drug Resist ; 15: 685-696, 2022.
Article in English | MEDLINE | ID: covidwho-1725145

ABSTRACT

INTRODUCTION: Carbapenemase-mediated antimicrobial resistance is currently a hot spot of global concern. Carbapenem-resistant organisms are highly prevalent in hospitals associated with difficult-to-treat infections, resulting in poor clinical outcome due to limited treatment options. It is urgently needed to have a rapid, efficient, and convenient molecular assay for identifying such resistant strains. METHODS: For this end, we developed a new laboratory assay targeting Klebsiella pneumoniae carbapenemase (KPC) and New Delhi metallo-ß-lactamase (NDM) based on loop-mediated isothermal amplification, CRISPR-Cas12a, and lateral flow immunochromatographic strip (CRISPR-Cas-LAMP-lateral flow strip). The method was designed to use a guide RNA (gRNA) to recognize the target DNA and guide Cas12a to cleave the target DNA, and simultaneously cleave any single-stranded DNA within the cleavage reaction system. RESULTS: The cleavage products are visible to the naked eye on the lateral flow strip. This method is highly sensitive in direct detection of bacteria in samples containing at least 3×105 CFU/mL without the need for bacterial culture. DISCUSSION: It provides shorter turnaround time and higher specificity than the conventional bacterial culture and susceptibility testing method. This new assay is applicable for extensive use in hospital infection control, as well as identification and treatment of resistant strains due to simple operation and inexpensive apparatuses.

10.
J Genet Genomics ; 48(9): 792-802, 2021 09 20.
Article in English | MEDLINE | ID: covidwho-1720311

ABSTRACT

Gut microbial dysbiosis has been linked to many noncommunicable diseases. However, little is known about specific gut microbiota composition and its correlated metabolites associated with molecular signatures underlying host response to infection. Here, we describe the construction of a proteomic risk score based on 20 blood proteomic biomarkers, which have recently been identified as molecular signatures predicting the progression of the COVID-19. We demonstrate that in our cohort of 990 healthy individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discover that a core set of gut microbiota can accurately predict the above proteomic biomarkers among 301 individuals using a machine learning model and that these gut microbiota features are highly correlated with proinflammatory cytokines in another independent set of 366 individuals. Fecal metabolomics analysis suggests potential amino acid-related pathways linking gut microbiota to host metabolism and inflammation. Overall, our multi-omics analyses suggest that gut microbiota composition and function are closely related to inflammation and molecular signatures of host response to infection among healthy individuals. These results may provide novel insights into the cross-talk between gut microbiota and host immune system.


Subject(s)
Gastrointestinal Microbiome/physiology , Inflammation/metabolism , COVID-19/microbiology , Dysbiosis/microbiology , Gastrointestinal Microbiome/genetics , Humans , Inflammation/genetics , Proteomics/methods
11.
Antiviral research ; 2022.
Article in English | EuropePMC | ID: covidwho-1711045

ABSTRACT

COVID-19, an infectious disease caused by the SARS-CoV-2 virus, emerged globally in early 2020 and has remained a serious public health issue. To date, although several preventative vaccines have been approved by FDA and EMA, vaccinated individuals increasingly suffer from breakthrough infections. Therapeutic antibodies may provide an alternative strategy to neutralize viral infection and treat serious cases;however, the clinical data and our experiments show that some FDA-approved monoclonal antibodies lose function against COVID-19 variants such as Omicron. Therefore, in this study, we present a novel therapeutic agent, SI–F019, an ACE2-Fc fusion protein whose neutralization efficiency is not compromised, but actually strengthened, by the mutations of dominant variants including Omicron. Comprehensive biophysical analyses revealed the mechanism of increased inhibition to be enhanced interaction of SI–F019 with all the tested spike variants, in contrast to monoclonal antibodies which tended to show weaker binding to some variants. The results imply that SI–F019 may be a broadly useful agent for treatment of COVID-19. Graphical Image 1

12.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-311429

ABSTRACT

Background: The COVID-19 pandemic is spreading globally with high disparity in the susceptibility of the disease severity. Identification of the key underlying factors for this disparity is highly warranted. Results: : Here we describe constructing a proteomic risk score (PRS) based on 20 blood proteomic biomarkers which related to the progression to severe COVID-19. Among COVID-19 patients, per 10% increment in the PRS was associated with a 57% higher risk of progressing to clinically severe phase (RR=1.57;95% CI, 1.35-1.82). We demonstrate that in our own cohort of 990 individuals without infection, this proteomic risk score is positively associated with proinflammatory cytokines mainly among older, but not younger, individuals. We further discovered that a core set of gut microbiota could accurately predict the blood proteomic biomarkers of COVID-19 using a machine learning model. The core OTU-predicted PRS had a significant correlation with actual PRS both cross-sectionally (n=132, p<0.001) and prospectively (n=169, p<0.05). Most of the core OTUs were highly correlated with proinflammatory cytokines. Fecal metabolomics analysis suggested potential amino acid-related pathways linking the above core gut microbiota to inflammation. Conclusions: : Our study suggests that gut microbiota may underlie the predisposition of healthy individuals to COVID-19-sensitive proteomic biomarkers.

13.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-328813

ABSTRACT

Background: Classification of disease severity is crucial for the management of COVID-19. Several studies have shown that individual proteins can be used to classify the severity of COVID-19. Here, we aimed to investigate whether integrating the four types of protein context data, namely, protein complexes, stoichiometric ratios, pathways and network degrees will improve the severity classification of COVID-19. Methods: : A SWATH-based proteomic data set of 54 sera samples from 40 COVID-19 patients was employed as the training cohort. Results: : Machine learning prioritized two complexes, one stoichiometric ratio, five pathways, twelve proteins and five network degrees. A model based on these 25 features led to effective classification of severe cases with an AUC of 0.965, outperforming the models with proteins only. Complement component C9, transthyretin (TTR) and TTR-RBP complex, the stoichiometric ratio of SAA2/ YLPM1, and the network extent of SIRT7 and A2M were highlighted in this classifier. This classifier was further validated with a TMT-based proteomic data set from the same cohort and an independent SWATH-based proteomic data set from Germany, reaching an AUC of 0.900 and 0.908, respectively. Machine learning models integrating protein context information achieved higher AUCs than models with only one feature type. Conclusion: Our results show that the integration of protein context including protein complexes, stoichiometric ratios, pathways, network degrees, and proteins improves phenotype prediction.

14.
EuropePMC; 2021.
Preprint in English | EuropePMC | ID: ppcovidwho-325171

ABSTRACT

The diagnosis and disease course monitoring of COVID-19 are mainly based on RT-PCR analysis of RNAs extracted from pharyngeal or nasopharyngeal swabs with potential live virus, posing a high risk to medical practitioners. Here, we investigated the feasibility of applying serum proteomics to classify COVID-19 patients in the nucleic acid positive (NCP) and negative (NCN) stages. We analyzed the proteome of 320 inactivated serum samples from 144 COVID-19 patients, and 45 controls and shortlisted 42 regulated proteins in the severe group and 12 regulated proteins in the non-severe group. Together with several key clinical indexes including days after symptom onset, platelet counts and magnesium, we developed machine learning models to classify NCP and NCN with an AUC of 0.94 for the severe cases and 0.89 for the non-severe cases. This study suggests the feasibility of utilizing quantitative serum proteomics for NCP-NCN classification.Funding: This work was supported by grants from the National Key R&D Program of China(No. 2020YFE0202200), National Natural Science Foundation of China (81672086), Zhejiang Province Analysis Test Project (2018C37032), the National Natural Science Foundation of China (81972492, 21904107), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Zhejiang Medical and Health Science and Technology Plan (2021KY394), Hangzhou Agriculture andSociety Advancement Program (20190101A04), and Westlake Education Foundation, Tencent Foundation.Conflict of Interest: Tiannan Guo is shareholder of Westlake Omics Inc. W.G. and N.X. are employees of Westlake Omics Inc. The remaining authors declare no competing interests.Ethical Approval: This study has been approved by both the Ethical/Institutional Review Boards of Taizhou Hospital and Westlake University. Informed contents from patients were waived by the boards.

15.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-308036

ABSTRACT

Background: COVID-19 Emerged as a novel zoonotic disease in late 2019 and quickly spread across Wuhan before spreading to other parts of China and rest of the world. Due to the rapid spread of the disease, local hospitals were inundated with COVID-19 patients putting a strain on the healthcare system. Little was known about the transmission and potential clinical management of COVID-19 at that time.Methods: A temporary COVID-19 hospital was built within one week. The confirmed COVID-19 cases were either directly recruited to the hospital or were transferred from other hospitals. Patients were admitted for both quarantine and treatment, as required. Data were collected as part of standard clinical care and retrospectively analyzed.Findings: A total of 2,959 patients were recruited during the operation period of this hospital between February 4, 2020, and April 8, 2020. These patients included 838 severe patients of which 72 were classified as critical, and 66 patients died. No infection was reported among healthcare workers.Interpretation: Setting up a dedicated hospital for COVID-19 provided a critical resource during the peak of the pandemic in Wuhan by enabling both quarantine and treatment for the infected patients. The mortality in this hospital was comparable to other hospitals at the time. These data suggest that this approach may prove beneficial in controlling infectious disease spread and limit mortality and prevent strain on existing healthcare system to enable them to care for non-COVID-19 patients.Funding Statement: This study was supported by funding from Beijing Nova Program Interdisciplinary Cooperation Project (DC;No. Z191100001119021), Chinese PLA General Hospital Youth Project (DC;No.QNF19074), Beijing Nova Program Project (DC;No. Z171100001117012), and China 13th Five-year National Key Grant (LXX;No.2018ZX09201013).Declaration of Interests: The authors declare that there are no competing interests.Ethics Approval Statement: This study was approved by the ethics committee of the Chinese PLA General Hospital, with a waiver of informed consent.

16.
Am J Reprod Immunol ; : e13528, 2022 Feb 11.
Article in English | MEDLINE | ID: covidwho-1685180

ABSTRACT

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a new type of coronavirus that has caused fatal infectious diseases and global spread. This novel coronavirus attacks target cells through the interaction of spike protein and angiotensin-converting enzyme II (ACE2), leading to different clinical symptoms. However, for a successful pregnancy, a well-established in-uterine environment includes a specific immune environment, and multi-interactions between specific cell types are prerequisites. The immune-related changes in patients infected with novel coronavirus could interfere with the immune microenvironment in the uterus, leading to fetal loss. We first reviewed the intrauterine environment in the normal development process and the possible pregnancy outcome in the infection state. Then, we summarized the immune response induced by SARS-CoV-2 in patients and analyzed the changes in ACE2 expression in the female reproductive system. Finally, the present observational evidence of infection in pregnant women was also reviewed.

17.
Cell Rep ; 38(3): 110271, 2022 01 18.
Article in English | MEDLINE | ID: covidwho-1588135

ABSTRACT

The utility of the urinary proteome in infectious diseases remains unclear. Here, we analyzed the proteome and metabolome of urine and serum samples from patients with COVID-19 and healthy controls. Our data show that urinary proteins effectively classify COVID-19 by severity. We detect 197 cytokines and their receptors in urine, but only 124 in serum using TMT-based proteomics. The decrease in urinary ESCRT complex proteins correlates with active SARS-CoV-2 replication. The downregulation of urinary CXCL14 in severe COVID-19 cases positively correlates with blood lymphocyte counts. Integrative multiomics analysis suggests that innate immune activation and inflammation triggered renal injuries in patients with COVID-19. COVID-19-associated modulation of the urinary proteome offers unique insights into the pathogenesis of this disease. This study demonstrates the added value of including the urinary proteome in a suite of multiomics analytes in evaluating the immune pathobiology and clinical course of COVID-19 and, potentially, other infectious diseases.


Subject(s)
COVID-19/urine , Immunity , Metabolome , Proteome/analysis , SARS-CoV-2/immunology , Adolescent , Adult , Aged , Aged, 80 and over , COVID-19/blood , COVID-19/immunology , COVID-19/pathology , Case-Control Studies , Child , Child, Preschool , China , Cohort Studies , Female , Humans , Immunity/physiology , Male , Metabolome/immunology , Metabolomics , Middle Aged , Patient Acuity , Proteome/immunology , Proteome/metabolism , Proteomics , Urinalysis/methods , Young Adult
18.
J Phys Ther Sci ; 33(12): 903-907, 2021 Dec.
Article in English | MEDLINE | ID: covidwho-1555684

ABSTRACT

[Purpose] With the COVID-19 pandemic, more and more articles have been published to explore the role of physical therapy on COVID-19. In order to analyze the research hotspots and the trends of physical therapy and COVID-19, we conducted bibliometric and visual analysis. [Methods] Data were collected from the Science Citation Index Expanded (SCI-EXPANDED) and Social Sciences Citation Index (SSCI) of the Web of Science Core Collect (WoSCC) from 2019 to 2021. CiteSpace and VOSviewer were used to perform the visual analysis of keywords and references to help quickly get key information. [Results] A total of 466 publications were retrieved. Exercise, sedentary behavior, and mental health were research hotspots. The relationship between exercise and immunity, as well as the management of COVID-19 patients after discharge were the research trends. [Conclusion] This study provided relevant information for future research. Findings suggested that physical therapy is beneficial for suspected or confirmed COVID-19 patients during isolation. It is hoped that academic exchanges can be quickly established in the face of infectious diseases. And in the future, we should focus on the rehabilitation of discharged patients.

19.
Curr Res Pharmacol Drug Discov ; 2: 100057, 2021.
Article in English | MEDLINE | ID: covidwho-1555254

ABSTRACT

SARS-CoV-2, a newly emerged and highly pathogenic coronavirus, is identified as the causal agent of Coronavirus Disease (2019) (COVID-19) in the late December 2019, in China. The virus has rapidly spread nationwide and spilled over to the other countries around the globe, resulting in more than 120 million infections and 2.6 million deaths until the time of this review. Unfortunately, there are still no specific drugs available against this disease, and it is very necessary to call upon more scientists to work together to stop a further spread. Hence, the recent progress in the development of drugs may help scientific community quickly understand current research status and further develop new effective drugs. Herein, we summarize the cellular entry and replication process of this virus and discuss the recent development of potential viral based drugs that target bio-macromolecules in different stages of the viral life cycle, especially S protein, 3CLPro, PLPro, RdRp and helicase.

20.
EuropePMC; 2020.
Preprint in English | EuropePMC | ID: ppcovidwho-293976

ABSTRACT

Severe COVID-19 patients account for most of the mortality of this disease. Early detection and effective treatment of severe patients remain major challenges. Here, we performed proteomic and metabolomic profiling of sera from 46 COVID-19 and 53 control individuals. We then trained a machine learning model using proteomic and metabolomic measurements from a training cohort of 18 non-severe and 13 severe patients. The model correctly classified severe patients with an accuracy of 93.5%, and was further validated using ten independent patients, seven of which were correctly classified. We identified molecular changes in the sera of COVID-19 patients implicating dysregulation of macrophage, platelet degranulation and complement system pathways, and massive metabolic suppression. This study shows that it is possible to predict progression to severe COVID-19 disease using serum protein and metabolite biomarkers. Our data also uncovered molecular pathophysiology of COVID-19 with potential for developing anti-viral therapies.<br><br>Funding: This work is supported by grants from Westlake Special Program for COVID19 (2020), and Tencent foundation (2020), National Natural Science Foundation of China (81972492, 21904107, 81672086), Zhejiang Provincial Natural Science Foundation for Distinguished Young Scholars (LR19C050001), Hangzhou Agriculture and Society Advancement Program (20190101A04). <br><br>Conflict of Interest: The research group of T.G. is partly supported by Tencent, Thermo Fisher Scientific, SCIEX and Pressure Biosciences Inc. C.Z., Z.K., Z.K. and S.Q. are employees of DIAN Diagnostics.

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