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| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 蔡幸真(Hsing-Chen Tsai) | |
| dc.contributor.author | Chung-Yu Chen | en |
| dc.contributor.author | 陳仲宇 | zh_TW |
| dc.date.accessioned | 2022-11-23T08:56:40Z | - |
| dc.date.available | 2022-02-16 | |
| dc.date.available | 2022-11-23T08:56:40Z | - |
| dc.date.copyright | 2022-02-16 | |
| dc.date.issued | 2022 | |
| dc.date.submitted | 2022-02-09 | |
| dc.identifier.citation | 1. worldometer, COVID-19 CORONAVIRUS PANDEMIC. 2021. 2. World Health Organization, Naming the coronavirus disease (COVID-19) and the virus that causes it. 2020. 3. International Committee of Taxonomy of Viruses, Virus Taxonomy: 2020 Release. 2020. 4. Chen, Y., Q. Liu, and D. Guo, Emerging coronaviruses: Genome structure, replication, and pathogenesis. Journal of Medical Virology, 2020. 92(4): p. 418-423. 5. Wu, A., et al., Genome Composition and Divergence of the Novel Coronavirus (2019-nCoV) Originating in China. Cell Host Microbe, 2020. 27(3): p. 325-328. 6. Phan, T., Genetic diversity and evolution of SARS-CoV-2. Infection, Genetics and Evolution, 2020. 81: p. 104260. 7. Brian, D.A. and R.S. Baric, Coronavirus Genome Structure and Replication. 2005, Springer Berlin Heidelberg. p. 1-30. 8. Rahimi, A., A. Mirzazadeh, and S. Tavakolpour, Genetics and genomics of SARS-CoV-2: A review of the literature with the special focus on genetic diversity and SARS-CoV-2 genome detection. Genomics, 2021. 113(1): p. 1221-1232. 9. Perlman, S. and J. Netland, Coronaviruses post-SARS: update on replication and pathogenesis. Nature Reviews Microbiology, 2009. 7(6): p. 439-450. 10. Sloan, K.E. and M.T. Bohnsack, Unravelling the Mechanisms of RNA Helicase Regulation. Trends in Biochemical Sciences, 2018. 43(4): p. 237-250. 11. Machitani, M., et al., RNA‐dependent RNA polymerase, RdRP, a promising therapeutic target for cancer and potentially COVID‐19. Cancer Science, 2020. 111(11): p. 3976-3984. 12. Subissi, L., et al., One severe acute respiratory syndrome coronavirus protein complex integrates processive RNA polymerase and exonuclease activities. Proceedings of the National Academy of Sciences, 2014. 111(37): p. E3900-E3909. 13. Menachery, V.D., K. Debbink, and R.S. Baric, Coronavirus non-structural protein 16: Evasion, attenuation, and possible treatments. Virus Research, 2014. 194: p. 191-199. 14. Snijder, E.J., E. Decroly, and J. Ziebuhr, The Nonstructural Proteins Directing Coronavirus RNA Synthesis and Processing. 2016, Elsevier. p. 59-126. 15. Cui, J., F. Li, and Z.-L. Shi, Origin and evolution of pathogenic coronaviruses. Nature Reviews Microbiology, 2019. 17(3): p. 181-192. 16. Wang L, S.Z., Zhang S, et al., Review of Bats and SARS. Emerging Infectious Diseases, 2006. 12(12): p. 1834-1840. 17. Liu, K., et al., Cross-species recognition of SARS-CoV-2 to bat ACE2. Proceedings of the National Academy of Sciences, 2021. 118(1): p. e2020216118. 18. Wrobel, A.G., et al., Structure and binding properties of Pangolin-CoV spike glycoprotein inform the evolution of SARS-CoV-2. Nature Communications, 2021. 12(1). 19. Kirtipal, N., S. Bharadwaj, and S.G. Kang, From SARS to SARS-CoV-2, insights on structure, pathogenicity and immunity aspects of pandemic human coronaviruses. Infection, Genetics and Evolution, 2020. 85: p. 104502. 20. Wacharapluesadee, S., et al., Evidence for SARS-CoV-2 related coronaviruses circulating in bats and pangolins in Southeast Asia. Nature Communications, 2021. 12(1). 21. Shang, J., et al., Cell entry mechanisms of SARS-CoV-2. Proceedings of the National Academy of Sciences, 2020. 117(21): p. 11727-11734. 22. De Wit, E., et al., SARS and MERS: recent insights into emerging coronaviruses. Nature Reviews Microbiology, 2016. 14(8): p. 523-534. 23. Knoops, K., et al., SARS-Coronavirus Replication Is Supported by a Reticulovesicular Network of Modified Endoplasmic Reticulum. PLoS Biology, 2008. 6(9): p. e226. 24. Masters, P.S.P., S., Fields Virology. 6th ed. 2013. 25. J Alsaadi, E.A. and I.M. Jones, Membrane binding proteins of coronaviruses. Future Virology, 2019. 14(4): p. 275-286. 26. Forani, J., COVID-19 reaches Antarctica, pandemic now on every continent, in CTV NEWS. 2020. 27. COVID-19 Weekly Epidemiological Update, World Health Organization, Editor. 2021. 28. Havers, F.P., et al., Seroprevalence of Antibodies to SARS-CoV-2 in 10 Sites in the United States, March 23-May 12, 2020. JAMA Internal Medicine, 2020. 180(12): p. 1576. 29. Stringhini, S., et al., Seroprevalence of anti-SARS-CoV-2 IgG antibodies in Geneva, Switzerland (SEROCoV-POP): a population-based study. The Lancet, 2020. 396(10247): p. 313-319. 30. He, X., et al., Temporal dynamics in viral shedding and transmissibility of COVID-19. Nature Medicine, 2020. 26(5): p. 672-675. 31. Samudrala, P.K., et al., Virology, pathogenesis, diagnosis and in-line treatment of COVID-19. European Journal of Pharmacology, 2020. 883: p. 173375. 32. Mercurio, I., et al., Protein structure analysis of the interactions between SARS-CoV-2 spike protein and the human ACE2 receptor: from conformational changes to novel neutralizing antibodies. Cellular and Molecular Life Sciences, 2021. 78(4): p. 1501-1522. 33. Angeletti, S., et al., COVID‐2019: The role of the nsp2 and nsp3 in its pathogenesis. Journal of Medical Virology, 2020. 92(6): p. 584-588. 34. Imai, Y., et al., Angiotensin-converting enzyme 2 protects from severe acute lung failure. Nature, 2005. 436(7047): p. 112-116. 35. Richard P. Marshall, e.a., Angiotensin II and the fibroproliferative response to acute lung injury. Am J Physiol Lung Cell Mol Physiol, 2003. 286(1): p. 156-164. 36. Li, X., et al., Molecular immune pathogenesis and diagnosis of COVID-19. Journal of Pharmaceutical Analysis, 2020. 10(2): p. 102-108. 37. Aid, M., et al., Vascular Disease and Thrombosis in SARS-CoV-2-Infected Rhesus Macaques. Cell, 2020. 183(5): p. 1354-1366.e13. 38. al., L.K.-C.e., Comprehensive mapping of immune perturbations associated with severe COVID-19. Science Immunology, 2020. 5(49). 39. Radermecker, C., et al., Neutrophil extracellular traps infiltrate the lung airway, interstitial, and vascular compartments in severe COVID-19. Journal of Experimental Medicine, 2020. 217(12). 40. Onder, G., G. Rezza, and S. Brusaferro, Case-Fatality Rate and Characteristics of Patients Dying in Relation to COVID-19 in Italy. JAMA, 2020. 41. Dhar Chowdhury, S. and A.M. Oommen, Epidemiology of COVID-19. Journal of Digestive Endoscopy, 2020. 11(01): p. 03-07. 42. Siddiqi, H.K. and M.R. Mehra, COVID-19 illness in native and immunosuppressed states: A clinical–therapeutic staging proposal. The Journal of Heart and Lung Transplantation, 2020. 39(5): p. 405-407. 43. Alene, M., et al., Magnitude of asymptomatic COVID-19 cases throughout the course of infection: A systematic review and meta-analysis. PLOS ONE, 2021. 16(3): p. e0249090. 44. Van Kessel, S.A.M., et al., Post-acute and long-COVID-19 symptoms in patients with mild diseases: a systematic review. Family Practice, 2021. 45. Peiris, J., et al., Coronavirus as a possible cause of severe acute respiratory syndrome. The Lancet, 2003. 361(9366): p. 1319-1325. 46. Liu, X., et al., Metabolic Defects of Peripheral T Cells in COVID-19 Patients. The Journal of Immunology, 2021. 206(12): p. 2900-2908. 47. Malin, J.J., Remdesivir against COVID-19 and Other Viral Diseases. Clinical Microbiology Reviews, 2020. 34(1). 48. Singh, B., Chloroquine or hydrochloroquine for prevention and treatment of COVID-19. Cochrane Database of Systematic Reviews, 2021. 2(2): p. CD013587. 49. Dhama, K., Coronavirus Disease 2019-COVID-19. Clinical Microbiology Reviews, 2020. 33(4): p. e00028-20. 50. Tan, L., et al., Lymphopenia predicts disease severity of COVID-19: a descriptive and predictive study. Signal Transduction and Targeted Therapy, 2020. 5(1). 51. Revzin, M.V., et al., Multisystem Imaging Manifestations of COVID-19, Part 1: Viral Pathogenesis and Pulmonary and Vascular System Complications. RadioGraphics, 2020. 40(6): p. 1574-1599. 52. Perico, L., et al., Immunity, endothelial injury and complement-induced coagulopathy in COVID-19. Nature Reviews Nephrology, 2021. 17(1): p. 46-64. 53. Smadja, D.M., et al., COVID-19 is a systemic vascular hemopathy: insight for mechanistic and clinical aspects. Angiogenesis, 2021. 54. Hypoxemia in the ICU: prevalence, treatment, and outcome. Annals of Intensive Care, 2018. 8(1). 55. Frija-Masson, J., et al., Residual ground glass opacities three months after Covid-19 pneumonia correlate to alteration of respiratory function: The post Covid M3 study. Respiratory Medicine, 2021. 184: p. 106435. 56. Parekh, M., et al., Review of the Chest CT Differential Diagnosis of Ground-Glass Opacities in the COVID Era. Radiology, 2020. 297(3): p. E289-E302. 57. Pourbagheri-Sigaroodi, A., et al., Laboratory findings in COVID-19 diagnosis and prognosis. Clinica Chimica Acta, 2020. 510: p. 475-482. 58. Russell, C.D., J.E. Millar, and J.K. Baillie, Clinical evidence does not support corticosteroid treatment for 2019-nCoV lung injury. The Lancet, 2020. 395(10223): p. 473-475. 59. Liu, B.M., Role of Host Immune and Inflammatory Responses in COVID-19 Cases with Underlying Primary Immunodeficiency: A Review. Journal of Interferon Cytokine Research, 2020. 40(12): p. 549-554. 60. Mokhtari, T., et al., COVID-19 and multiorgan failure: A narrative review on potential mechanisms. Journal of Molecular Histology, 2020. 51(6): p. 613-628. 61. Bader, F., et al., Heart failure and COVID-19. Heart Failure Reviews, 2021. 26(1): p. 1-10. 62. Masi, P., et al., Systemic Inflammatory Response Syndrome Is a Major Contributor to COVID-19–Associated Coagulopathy. Circulation, 2020. 142(6): p. 611-614. 63. Xu, Z., et al., Pathological findings of COVID-19 associated with acute respiratory distress syndrome. The Lancet Respiratory Medicine, 2020. 8(4): p. 420-422. 64. Statsenko, Y., et al., Prediction of COVID-19 severity using laboratory findings on admission: informative values, thresholds, ML model performance. BMJ Open, 2021. 11(2): p. e044500. 65. Zhan, H., et al., Diagnostic Value of D-Dimer in COVID-19: A Meta-Analysis and Meta-Regression. Clinical and Applied Thrombosis/Hemostasis, 2021. 27: p. 107602962110109. 66. Chung, M.K., et al., COVID-19 and Cardiovascular Disease. Circulation Research, 2021. 128(8): p. 1214-1236. 67. Caro‐Codón, J., et al., Characterization of NT‐proBNP in a large cohort of COVID‐19 patients. European Journal of Heart Failure, 2021. 23(3): p. 456-464. 68. Mehta, P., et al., COVID-19: consider cytokine storm syndromes and immunosuppression. The Lancet, 2020. 395(10229): p. 1033-1034. 69. Cao, B., et al., A Trial of Lopinavir–Ritonavir in Adults Hospitalized with Severe Covid-19. New England Journal of Medicine, 2020. 382(19): p. 1787-1799. 70. Nalbandian, A., et al., Post-acute COVID-19 syndrome. Nature Medicine, 2021. 27(4): p. 601-615. 71. Del Rio, C., L.F. Collins, and P. Malani, Long-term Health Consequences of COVID-19. JAMA, 2020. 324(17): p. 1723. 72. Ali, R.M.M. and M.B.I. Ghonimy, Post-COVID-19 pneumonia lung fibrosis: a worrisome sequelae in surviving patients. Egyptian Journal of Radiology and Nuclear Medicine, 2021. 52(1). 73. Ambardar, S.R., et al., Post-COVID-19 Pulmonary Fibrosis: Novel Sequelae of the Current Pandemic. Journal of Clinical Medicine, 2021. 10(11): p. 2452. 74. Cheung, C.Y., et al., Cytokine Responses in Severe Acute Respiratory Syndrome Coronavirus-Infected Macrophages In Vitro: Possible Relevance to Pathogenesis. Journal of Virology, 2005. 79(12): p. 7819-7826. 75. Reusch, N., et al., Neutrophils in COVID-19. Frontiers in Immunology, 2021. 12(952). 76. Ackermann, M., et al., Patients with COVID-19: in the dark-NETs of neutrophils. Cell Death Differentiation, 2021. 77. Chua, R.L., et al., COVID-19 severity correlates with airway epithelium–immune cell interactions identified by single-cell analysis. Nature Biotechnology, 2020. 38(8): p. 970-979. 78. Liao, M., et al., Single-cell landscape of bronchoalveolar immune cells in patients with COVID-19. Nature Medicine, 2020. 26(6): p. 842-844. 79. Giamarellos-Bourboulis, E.J., et al., Complex Immune Dysregulation in COVID-19 Patients with Severe Respiratory Failure. Cell Host Microbe, 2020. 27(6): p. 992-1000.e3. 80. Wack, A., Monocyte and dendritic cell defects in COVID-19. Nature Cell Biology, 2021. 23(5): p. 445-447. 81. Van Eeden, C., et al., Natural Killer Cell Dysfunction and Its Role in COVID-19. International Journal of Molecular Sciences, 2020. 21(17): p. 6351. 82. Zheng, M., et al., Functional exhaustion of antiviral lymphocytes in COVID-19 patients. Cellular Molecular Immunology, 2020. 17(5): p. 533-535. 83. Odak, I., et al., Reappearance of effector T cells is associated with recovery from COVID-19. EBioMedicine, 2020. 57: p. 102885. 84. Schultheiß, C., et al., Next-Generation Sequencing of T and B Cell Receptor Repertoires from COVID-19 Patients Showed Signatures Associated with Severity of Disease. Immunity, 2020. 53(2): p. 442-455.e4. 85. Grifoni, A., et al., Targets of T Cell Responses to SARS-CoV-2 Coronavirus in Humans with COVID-19 Disease and Unexposed Individuals. Cell, 2020. 181(7): p. 1489-1501.e15. 86. Rydyznski Moderbacher, C., et al., Antigen-Specific Adaptive Immunity to SARS-CoV-2 in Acute COVID-19 and Associations with Age and Disease Severity. Cell, 2020. 183(4): p. 996-1012.e19. 87. Crotty, S., T Follicular Helper Cell Biology: A Decade of Discovery and Diseases. Immunity, 2019. 50(5): p. 1132-1148. 88. Sekine, T., et al., Robust T Cell Immunity in Convalescent Individuals with Asymptomatic or Mild COVID-19. Cell, 2020. 183(1): p. 158-168.e14. 89. Zander, R., et al., CD4+ T Cell Help Is Required for the Formation of a Cytolytic CD8+ T Cell Subset that Protects against Chronic Infection and Cancer. Immunity, 2019. 51(6): p. 1028-1042.e4. 90. Schulien, I., et al., Characterization of pre-existing and induced SARS-CoV-2-specific CD8+ T cells. Nature Medicine, 2021. 27(1): p. 78-85. 91. Piccoli, L., et al., Mapping Neutralizing and Immunodominant Sites on the SARS-CoV-2 Spike Receptor-Binding Domain by Structure-Guided High-Resolution Serology. Cell, 2020. 183(4): p. 1024-1042.e21. 92. Long, Q.-X., et al., Antibody responses to SARS-CoV-2 in patients with COVID-19. Nature Medicine, 2020. 26(6): p. 845-848. 93. Sette, A. and S. Crotty, Adaptive immunity to SARS-CoV-2 and COVID-19. Cell, 2021. 184(4): p. 861-880. 94. Mathis, D. and S.E. Shoelson, Immunometabolism: an emerging frontier. Nature Reviews Immunology, 2011. 11(2): p. 81-83. 95. O'Neill, L.A.J., R.J. Kishton, and J. Rathmell, A guide to immunometabolism for immunologists. Nature Reviews Immunology, 2016. 16(9): p. 553-565. 96. Man, K., V.I. Kutyavin, and A. Chawla, Tissue Immunometabolism: Development, Physiology, and Pathobiology. Cell Metabolism, 2017. 25(1): p. 11-26. 97. Kumar, V., How could we forget immunometabolism in SARS-CoV2 infection or COVID-19? International Reviews of Immunology, 2021. 40(1-2): p. 72-107. 98. Codo, A.C., et al., Elevated Glucose Levels Favor SARS-CoV-2 Infection and Monocyte Response through a HIF-1α/Glycolysis-Dependent Axis. Cell Metabolism, 2020. 32(3): p. 437-446.e5. 99. Wu, D., et al., Type 1 Interferons Induce Changes in Core Metabolism that Are Critical for Immune Function. Immunity, 2016. 44(6): p. 1325-1336. 100. Lau, Y.L., J.S.M. Peiris, and H.K.W. Law, Role of dendritic cells in SARS coronavirus infection. Hong Kong Medical Journal, 2012. 18(4). 101. Everts, B., et al., TLR-driven early glycolytic reprogramming via the kinases TBK1-IKKɛ supports the anabolic demands of dendritic cell activation. Nature Immunology, 2014. 15(4): p. 323-332. 102. Yang, D., et al., Attenuated Interferon and Proinflammatory Response in SARS-CoV-2–Infected Human Dendritic Cells Is Associated With Viral Antagonism of STAT1 Phosphorylation. The Journal of Infectious Diseases, 2020. 222(5): p. 734-745. 103. Miyamoto, S., A.N. Murphy, and J.H. Brown, Akt mediates mitochondrial protection in cardiomyocytes through phosphorylation of mitochondrial hexokinase-II. Cell Death Differentiation, 2008. 15(3): p. 521-529. 104. Keppel, M.P., et al., Activation-Specific Metabolic Requirements for NK Cell IFN-γ Production. The Journal of Immunology, 2015. 194(4): p. 1954-1962. 105. Wang, K., et al., CD147-spike protein is a novel route for SARS-CoV-2 infection to host cells. Signal Transduction and Targeted Therapy, 2020. 5(1). 106. Siu, K.-L., et al., Severe Acute Respiratory Syndrome Coronavirus M Protein Inhibits Type I Interferon Production by Impeding the Formation of TRAF3·TANK·TBK1/IKKϵ Complex. Journal of Biological Chemistry, 2009. 284(24): p. 16202-16209. 107. Wang, H., et al., Regulation of Human Natural Killer Cell IFN-γ Production by MicroRNA-146a via Targeting the NF-κB Signaling Pathway. Frontiers in Immunology, 2018. 9(293). 108. Marçais, A., et al., The metabolic checkpoint kinase mTOR is essential for IL-15 signaling during the development and activation of NK cells. Nature Immunology, 2014. 15(8): p. 749-757. 109. Siska, P.J., et al., Metabolic stress and disease-stage specific basigin expression of peripheral blood immune cell subsets in COVID-19 patients. 2020, Cold Spring Harbor Laboratory. 110. Kumar, V., T cells and their immunometabolism: A novel way to understanding sepsis immunopathogenesis and future therapeutics. European Journal of Cell Biology, 2018. 97(6): p. 379-392. 111. Marfia, G., et al., Decreased serum level of sphingosine‐1‐phosphate: a novel predictor of clinical severity in COVID‐19. EMBO Molecular Medicine, 2021. 13(1). 112. Laterre, P.F., et al., Association of Interleukin 7 Immunotherapy With Lymphocyte Counts Among Patients With Severe Coronavirus Disease 2019 (COVID-19). JAMA Network Open, 2020. 3(7): p. e2016485. 113. Wilson, C.S. and D.J. Moore, B cell metabolism: an understudied opportunity to improve immune therapy in autoimmune type 1 diabetes. Immunometabolism, 2020. 2(2). 114. Waters, L.R., et al., Initial B Cell Activation Induces Metabolic Reprogramming and Mitochondrial Remodeling. iScience, 2018. 5: p. 99-109. 115. Thompson, E.A., et al., Metabolic programs define dysfunctional immune responses in severe COVID-19 patients. Cell Reports, 2021. 34(11): p. 108863. 116. Bharadwaj, S., et al., SARS-CoV-2 and Glutamine: SARS-CoV-2 Triggered Pathogenesis via Metabolic Reprograming of Glutamine in Host Cells. Frontiers in Molecular Biosciences, 2021. 7(462). 117. Caro-Maldonado, A., et al., Metabolic Reprogramming Is Required for Antibody Production That Is Suppressed in Anergic but Exaggerated in Chronically BAFF-Exposed B Cells. The Journal of Immunology, 2014. 192(8): p. 3626-3636. 118. Ajaz, S., et al., Mitochondrial metabolic manipulation by SARS-CoV-2 in peripheral blood mononuclear cells of patients with COVID-19. American Journal of Physiology-Cell Physiology, 2021. 320(1): p. C57-C65. 119. Fuss, I.J., et al., Isolation of Whole Mononuclear Cells from Peripheral Blood and Cord Blood. Current Protocols in Immunology, 2009. 85(1). 120. Geanon, D., et al., A Streamlined CyTOF Workflow To Facilitate Standardized Multi-Site Immune Profiling of COVID-19 Patients. 2020, Cold Spring Harbor Laboratory. 121. Poláková, I., et al., Implementation of Mass Cytometry for Immunoprofiling of Patients with Solid Tumors. Journal of Immunology Research, 2019. 2019: p. 6705949. 122. Weng, R.R., et al., Epigenetic modulation of immune synaptic-cytoskeletal networks potentiates γδ T cell-mediated cytotoxicity in lung cancer. Nature Communications, 2021. 12(1). 123. Chen, T.J. and N. Kotecha, Cytobank: Providing an Analytics Platform for Community Cytometry Data Analysis and Collaboration. 2014, Springer Berlin Heidelberg. p. 127-157. 124. Böttcher, C., et al., Human microglia regional heterogeneity and phenotypes determined by multiplexed single-cell mass cytometry. Nature Neuroscience, 2019. 22(1): p. 78-90. 125. Hsieh, W.-C., et al., NK cell receptor and ligand composition influences the clearance of SARS-CoV-2. Journal of Clinical Investigation, 2021. 131(21). 126. Jang, J.S., et al., Single-cell mass cytometry on peripheral blood identifies immune cell subsets associated with primary biliary cholangitis. Scientific Reports, 2020. 10(1). 127. Zhang, Z., et al., Dynamic Programmed Death 1 Expression by Virus-Specific CD8 T Cells Correlates With the Outcome of Acute Hepatitis B. Gastroenterology, 2008. 134(7): p. 1938-1949.e3. 128. Shoshan-Barmatz, V., et al., VDAC, a multi-functional mitochondrial protein regulating cell life and death. Molecular Aspects of Medicine, 2010. 31(3): p. 227-285. 129. Maldonado, E.N., VDAC–Tubulin, an Anti-Warburg Pro-Oxidant Switch. Frontiers in Oncology, 2017. 7(4). 130. Bao, Q. and Y. Shi, Apoptosome: a platform for the activation of initiator caspases. Cell Death Differentiation, 2007. 14(1): p. 56-65. 131. Gold, M.C. and D.M. Lewinsohn, Mucosal associated invariant T cells and the immune response to infection. Microbes and Infection, 2011. 13(8-9): p. 742-748. 132. Gebru, Y.A., et al., Pathophysiological Roles of Mucosal-Associated Invariant T Cells in the Context of Gut Microbiota-Liver Axis. Microorganisms, 2021. 9(2): p. 296. 133. Kilercik, M., et al., A new haematocytometric index: Predicting severity and mortality risk value in COVID-19 patients. PLOS ONE, 2021. 16(8): p. e0254073. 134. Chernyak, B.V., et al., COVID-19 and Oxidative Stress. Biochemistry (Moscow), 2020. 85(12-13): p. 1543-1553. 135. Green, S.J., Covid-19 accelerates endothelial dysfunction and nitric oxide deficiency. Microbes and Infection, 2020. 22(4-5): p. 149-150. 136. Maucourant, C., et al., Natural killer cell immunotypes related to COVID-19 disease severity. Science Immunology, 2020. 5(50): p. eabd6832. 137. Sadighi Akha, A.A., Aging and the immune system: An overview. Journal of Immunological Methods, 2018. 463: p. 21-26. 138. Rodriguez, L., et al., Systems-Level Immunomonitoring from Acute to Recovery Phase of Severe COVID-19. Cell Reports Medicine, 2020. 1(5): p. 100078. 139. Raulien, N., et al., Fatty Acid Oxidation Compensates for Lipopolysaccharide-Induced Warburg Effect in Glucose-Deprived Monocytes. Frontiers in Immunology, 2017. 8(609). 140. Gibellini, L., et al., Altered bioenergetics and mitochondrial dysfunction of monocytes in patients with COVID‐19 pneumonia. EMBO Molecular Medicine, 2020. 12(12). 141. Shi, C.-S., et al., SARS-Coronavirus Open Reading Frame-9b Suppresses Innate Immunity by Targeting Mitochondria and the MAVS/TRAF3/TRAF6 Signalosome. The Journal of Immunology, 2014. 193(6): p. 3080-3089. 142. Mao, K. and D.J. Klionsky, Participation of mitochondrial fission during mitophagy. Cell Cycle, 2013. 12(19): p. 3131-3132. 143. Ganji, R. and P.H. Reddy, Impact of COVID-19 on Mitochondrial-Based Immunity in Aging and Age-Related Diseases. Frontiers in Aging Neuroscience, 2021. 12(502). 144. Jumana Saleh, C.P., Keshav K Singh, Marvin Edeas, Mitochondria and microbiota dysfunction in COVID-19 pathogenesis. Mitochondrion, 2020. 54: p. 1-7. 145. Syn, N.L., et al., De-novo and acquired resistance to immune checkpoint targeting. The Lancet Oncology, 2017. 18(12): p. e731-e741. 146. Saito, H., et al., PD-1 Expression on Circulating CD8+ T-Cells as a Prognostic Marker for Patients With Gastric Cancer. Anticancer Research, 2019. 39(1): p. 443-448. 147. Ma, J., et al., PD1Hi CD8+ T cells correlate with exhausted signature and poor clinical outcome in hepatocellular carcinoma. Journal for ImmunoTherapy of Cancer, 2019. 7(1). 148. Pauken, K.E., et al., The PD-1 Pathway Regulates Development and Function of Memory CD8+ T Cells following Respiratory Viral Infection. Cell Reports, 2020. 31(13): p. 107827. 149. Ahn, E., et al., Role of PD-1 during effector CD8 T cell differentiation. Proceedings of the National Academy of Sciences, 2018. 115(18): p. 4749-4754. 150. Sauce, D.A., Jorge R; Larsen, Martin; Haro, Laurine; Autran, Brigitte; Freeman, Gordon J; Appay, Victor, PD-1 expression on human CD8 T cells depends on both state of differentiation and activation status. AIDS, 2007. 21(15): p. 2005-2013. 151. Shi, J., et al., Single-Cell Transcriptomic Profiling of MAIT Cells in Patients With COVID-19. Frontiers in Immunology, 2021. 12(3112). 152. Parrot, T., et al., MAIT cell activation and dynamics associated with COVID-19 disease severity. Science Immunology, 2020. 5(51): p. eabe1670. 153. Wang, H., et al., MAIT cells protect against pulmonary Legionella longbeachae infection. Nature Communications, 2018. 9(1). 154. Jouan, Y., et al., Phenotypical and functional alteration of unconventional T cells in severe COVID-19 patients. Journal of Experimental Medicine, 2020. 217(12). 155. Deschler, S., et al., Mucosal-Associated Invariant T (MAIT) Cells Are Highly Activated and Functionally Impaired in COVID-19 Patients. Viruses, 2021. 13(2): p. 241. 156. Mickiewicz, B., et al., Integration of metabolic and inflammatory mediator profiles as a potential prognostic approach for septic shock in the intensive care unit. Critical Care, 2015. 19(1): p. 11. 157. Herrera-Van Oostdam, A.S., et al., Immunometabolic signatures predict risk of progression to sepsis in COVID-19. PLOS ONE, 2021. 16(8): p. e0256784. 158. Cheng, K., et al., Genome‐scale metabolic modeling reveals SARS‐CoV‐2‐induced metabolic changes and antiviral targets. Molecular Systems Biology, 2021. 17(11). | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/79249 | - |
| dc.description.abstract | 新冠肺炎至2022年1月14日為止已奪走超過553萬條生命，而且自2019年底已在全世界造成3億2千多萬人感染。科學家們正努力探索新冠病毒的全貌以希望能找出治療方法和研發疫苗來對抗這令人戰慄的敵人。免疫代謝指的是免疫細胞在活化狀態下細胞內代謝路徑的變化。過去有許多文獻發現免疫細胞在面對新冠病毒感染會改變它們的代謝路徑，但目前探討新冠肺炎感染下免疫代謝的縱貫性研究仍很稀少。在此，我們利用質譜流式細胞儀來進行縱貫性研究並探討輕症和重症新冠肺炎病人的免疫代謝。我們使用了26個免疫標記以及17個代謝標的來分析台大醫院和台北市和平醫院新冠肺炎病人的周邊血單核球細胞。我們從7位輕症和2位重症病人取得了35個檢體，並從健康參與者收集了5個檢體做為控制組。我們從這些樣本發現在健康控制組、輕症和重症病人之間，其免疫細胞的組成比例也不盡相同。除此之外，也觀察到在從重症復原的病人中，骨髓衍生細胞的能量生成會從糖解作用轉換成脂肪酸氧化，而且也在重症病人的骨髓衍生細胞發現粒線體損傷。另外，我們在預後不好的病人發現PD-1在CD8+ T細胞有表現量上升的現象，顯示CD8+ T cells上的PD-1表現量可能能作為新冠肺炎預後的指標。而在最後，我們找到一群T細胞MAIT，在重症病人中表現高量的VDAC伴隨著細胞量急劇減少，顯示MAIT上的VDAC表現量可能能用於預測新冠肺炎病人的嚴重度。總結來說，我們從新冠肺炎病人的周邊血細胞發現多個獨特的特徵，提供一個研究並揭開新冠病毒全貌的方向。 | zh_TW |
| dc.description.provenance | Made available in DSpace on 2022-11-23T08:56:40Z (GMT). No. of bitstreams: 1 U0001-1401202214331300.pdf: 4246532 bytes, checksum: 09bb43a552db11051b5bfdcec914dc13 (MD5) Previous issue date: 2022 | en |
| dc.description.tableofcontents | 口試委員會審定書 i 序言及謝詞 ii 中文摘要 iii Abstract iv Contents vi List of Figures x List of Tables xi List of Supplementary Figures xii List of Supplementary Tables xiii List of Abbreviations xiv 1. Introduction 1 1.1 SARS-CoV-2 1 1.1.1 Terminology of COVID-19 and SARS-CoV-2 1 1.1.2 Virology of SARS-CoV-2 1 1.1.3 Transmission of SARS-CoV-2 2 1.1.4 Replication of SARS-CoV-2 3 1.2 COVID-19 4 1.2.1 Epidemiology of COVID-19 4 1.2.2 Pathogenesis of COVID-19 5 1.2.3 Clinical features of COVID-19 6 1.3 Immunometabolism of COVID-19 9 1.3.1 The role of immune cells in patients with COVID-19 9 1.3.2 Immunometabolism in patients with COVID-19 12 1.4 Aims of the study 16 2. Material and Methods 17 2.1 Study population 17 2.2 Single-cell mass cytometry 17 2.2.1 PBMC isolation 17 2.2.2 Cell fixation 19 2.2.3 Sample Barcoding 20 2.2.4 Antibody Staining 20 2.2.5 Data acquisition 21 2.3 Data analysis 22 2.3.1 Identification of cell subpopulation with unsupervised clustering tools 22 2.3.2 Calculation of Metabolic index 22 2.3.3 Non-clustered heatmaps 23 3. Results 24 3.1 Sample recruitment and demographics 24 3.2 Different cell population compositions are revealed in COVID-19 patients 25 3.3 Energy source shifts from glycolysis to β-oxidation in myeloid cells of the patient convalescing from severe condition 28 3.4 Impaired mitochondrial function was revealed in myeloid cells of the patient with worse prognosis 29 3.5 Low expression of PD-1 on CD8+ T cells may be a marker of bad prognosis 30 3.6 Highly-expressed VDAC on MAIT cells discriminates severe COVID-19 patients from the mild 30 4. Discussion 32 5. Conclusion 41 6. Reference 42 7. Figures 53 8. Tables 61 9. Supplementary Figures 63 10. Supplementary Tables 73 | |
| dc.language.iso | en | |
| dc.title | 新冠肺炎病人週邊血球之單細胞免疫代謝分析 | zh_TW |
| dc.title | Single-cell immunometabolic profiling of peripheral blood cells in COVID-19 patients | en |
| dc.date.schoolyear | 110-1 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 楊宏志(Chih-Cheng Chang),陳世淯(Tzung-Jeng Hwang) | |
| dc.subject.keyword | 新冠肺炎,新冠病毒,免疫代謝,電壓依賴性陰離子選擇性通道1,程式性細胞死亡蛋白-1, | zh_TW |
| dc.subject.keyword | COVID-19,SARS-CoV-2,Immunometabolism,VDAC,PD-1, | en |
| dc.relation.page | 75 | |
| dc.identifier.doi | 10.6342/NTU202200063 | |
| dc.rights.note | 同意授權(全球公開) | |
| dc.date.accepted | 2022-02-09 | |
| dc.contributor.author-college | 醫學院 | zh_TW |
| dc.contributor.author-dept | 毒理學研究所 | zh_TW |
| 顯示於系所單位： | 毒理學研究所 | |
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