The DOI matches its Crossref record; 64 of the 64 references it cites were found in a registry or an index.
COVID-19 and Neutrophils: The Relationship between Hyperinflammation and Neutrophil Extracellular Traps
Open accessAbstract
Coronavirus disease 2019 (COVID-19) is a virus-induced respiratory disease that may progress to acute respiratory distress syndrome (ARDS) and is triggered by immunopathological mechanisms that cause excessive inflammation and leukocyte dysfunction. Neutrophils play a critical function in the clearance of bacteria with specific mechanisms to combat viruses. The aim of this review is to highlight the current advances in the pathways of neutrophilic inflammation against viral infection over the past ten years, focusing on the production of neutrophil extracellular traps (NETs) and its impact on severe lung diseases, such as COVID-19. We focused on studies regarding hyperinflammation, cytokine storms, neutrophil function, and viral infections. We discuss how the neutrophil’s role could influence COVID-19 symptoms in the interaction between hyperinflammation (overproduction of NETs and cytokines) and the clearance function of neutrophils to eliminate the viral infection. We also propose a more in-depth investigation into the neutrophil response mechanism targeting NETosis in the different phases of COVID-19.
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“Findings from this study and others indicate that inflammatory responses serve as a primary driver of the progressive and persistent pathophysiologic features of severe COVID-19 (43–46).”
From Lung epithelial and endothelial damage, loss of tissue repair, inhibition of fibrinolysis, and cellular senescence in fatal COVID-19 (2021) · cites this paper as [43]
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“NETs have been shown to promote tissue factor activation and fibrin deposition, consistent with our observations, suggesting a role for NETs in intra-alveolar thrombosis and the formation or organization of platelet-rich clots (43, 45).”
From Lung epithelial and endothelial damage, loss of tissue repair, inhibition of fibrinolysis, and cellular senescence in fatal COVID-19 (2021) · cites this paper as [43]
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Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China
Huang, C., Wang, Y., Li, X., Ren, L., Zhao, J., Hu, Y., Zhang, L., Fan, G., Xu, J., Gu, X., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30183-5 · Cited by 48,884
Clinical characteristics of coronavirus disease 2019 in China
Guan, W.-J., Ni, Z.-Y., Hu, Y., Liang, W.-H., Ou, C.-Q., He, J.-X., Liu, L., Shan, H., Lei, C.-L., Hui, D. S. C., et al. (2020) · New England Journal of Medicine · doi:10.1056/nejmoa2002032 · Cited by 30,246
Chen, N., Zhou, M., Dong, X., Qu, J., Gong, F., Han, Y., Qiu, Y., Wang, J., Liu, Y., Wei, Y., et al. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30211-7 · Cited by 21,415
Wang, D., Hu, B., Hu, C., Zhu, F., Liu, X., Zhang, J., Wang, B., Xiang, H., Cheng, Z., Xiong, Y., et al. (2020) · JAMA · doi:10.1001/jama.2020.1585 · Cited by 20,148
La certeza de lo impredecible: Cultura Educación y Sociedad en tiempos de COVID19
Martínez González, M. (2020) · DSPACE System - Metalibrary (University of the Coast) · Cited by 18,463
Neutrophil Extracellular Traps Kill Bacteria
Brinkmann, V., Reichard, U., Goosmann, C., Fauler, B., Uhlemann, Y., Weiss, D. S., Weinrauch, Y., & Zychlinsky, A. (2004) · Science · doi:10.1126/science.1092385 · Cited by 10,268
COVID-19: consider cytokine storm syndromes and immunosuppression
Mehta, P., McAuley, D. F., Brown, M., Sanchez, E., Tattersall, R. S., & Manson, J. J. (2020) · The Lancet · doi:10.1016/s0140-6736(20)30628-0 · Cited by 9,664
Ruan, Q., Yang, K., Wang, W., Jiang, L., & Song, J. (2020) · Intensive Care Medicine · doi:10.1007/s00134-020-05991-x · Cited by 4,898
Dysregulation of Immune Response in Patients With Coronavirus 2019 (COVID-19) in Wuhan, China
Qin, C., Zhou, L., Hu, Z., Zhang, S., Yang, S., Tao, Y., Xie, C., Ma, K., Shang, K., Wang, W., et al. (2020) · Clinical Infectious Diseases · doi:10.1093/cid/ciaa248 · Cited by 4,775
Novel cell death program leads to neutrophil extracellular traps
Fuchs, T. A., Abed, U., Goosmann, C., Hurwitz, R., Schulze, I., Wahn, V., Weinrauch, Y., Brinkmann, V., & Zychlinsky, A. (2007) · The Journal of Cell Biology · doi:10.1083/jcb.200606027 · Cited by 3,197
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D’Agnillo, F., Walters, K.-A., Xiao, Y., Sheng, Z.-M., Scherler, K., Park, J., Gygli, S., Rosas, L. A., Sadtler, K., Kalish, H., et al. (2021) · Science Translational Medicine · doi:10.1126/scitranslmed.abj7790 · Cited by 237
NETosis and Neutrophil Extracellular Traps in COVID-19: Immunothrombosis and Beyond
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Hyperinflammatory Response in COVID-19: A Systematic Review
Silva, M. J. A., Ribeiro, L. R., Gouveia, M. I. M., Marcelino, B. D. R., dos Santos, C. S., Lima, K. V. B., & Lima, L. N. G. C. (2023) · Viruses · doi:10.3390/v15020553 · Cited by 174
Two Years into the COVID-19 Pandemic: Lessons Learned
da Silva, S. J. R., do Nascimento, J. C. F., Mendes, R. P. G., Guarines, K. M., da Silva, C. T. A., da Silva, P. G., de Magalhães, J. J. F., Vigar, J. R. J., Silva‐Júnior, A., Kohl, A., et al. (2022) · ACS Infectious Diseases · doi:10.1021/acsinfecdis.2c00204 · Cited by 155
Islam, M. M., & Takeyama, N. (2023) · International Journal of Molecular Sciences · doi:10.3390/ijms242115805 · Cited by 133
Metadata
- Authors
- Borges, L., Pithon-Curi, T. C., Curi, R., & Hatanaka, E.
- Affiliations
- Universidade Cruzeiro do Sul (BR)
- Instituto de Ciências da Atividade Física e Esportes (ICAFE), Universidade Cruzeiro do Sul, São Paulo, SP, Brazil
- Instituto Butantan (BR)
- Corresponding author
- Borges, Leandro
- Venue
- Mediators of Inflammation
- Publisher
- Wiley
- Published
- 2020-12-02
- Volume
- 2020
- Pages
- 1-7
- ISSN
- 0962-9351 (ISSN-L)
- 1466-1861
- PMC
- PMC7732408
- OpenAlex
- W3109283769
- Cited by
- 235
- References
- 64
- Citations by year
- 2026: 8 · 2025: 17 · 2024: 36 · 2023: 59 · 2022: 66 · 2021: 49
- FWCI
- 4.25
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Mediators of Inflammation (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- Conselho Nacional de Desenvolvimento Científico e Tecnológico (88882.314890/2013-01)
- Fundação de Amparo à Pesquisa do Estado de São Paulo (88882.314890/2013-01)
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (88882.314890/2013-01)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › Neutrophil, Myeloperoxidase and Oxidative Mechanisms
- Health Sciences › Medicine › Infectious Diseases › COVID-19 Clinical Research Studies
- Life Sciences › Immunology and Microbiology › Immunology › Inflammation biomarkers and pathways
- Keywords
- COVID-19 pandemic, neutrophils, neutrophil extracellular traps, NETosis, hyperinflammation, cytokine storm, acute respiratory distress syndrome, neutrophil dysfunction, lung disease
- MeSH terms
- Host Microbial Interactions, Cytokine Release Syndrome, COVID-19, SARS-CoV-2, Humans, Immunity, Innate, Inflammation, Lung, Neutrophils, Respiratory Distress Syndrome, Models, Immunological, Inflammation Mediators, Pandemics, Extracellular Traps
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