1
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Rumer KK, Hedou J, Tsai A, Einhaus J, Verdonk F, Stanley N, Choisy B, Ganio E, Bonham A, Jacobsen D, Warrington B, Gao X, Tingle M, McAllister TN, Fallahzadeh R, Feyaerts D, Stelzer I, Gaudilliere D, Ando K, Shelton A, Morris A, Kebebew E, Aghaeepour N, Kin C, Angst MS, Gaudilliere B. Integrated Single-cell and Plasma Proteomic Modeling to Predict Surgical Site Complications: A Prospective Cohort Study. Ann Surg 2022; 275:582-590. [PMID: 34954754 PMCID: PMC8816871 DOI: 10.1097/sla.0000000000005348] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
OBJECTIVE The aim of this study was to determine whether single-cell and plasma proteomic elements of the host's immune response to surgery accurately identify patients who develop a surgical site complication (SSC) after major abdominal surgery. SUMMARY BACKGROUND DATA SSCs may occur in up to 25% of patients undergoing bowel resection, resulting in significant morbidity and economic burden. However, the accurate prediction of SSCs remains clinically challenging. Leveraging high-content proteomic technologies to comprehensively profile patients' immune response to surgery is a promising approach to identify predictive biological factors of SSCs. METHODS Forty-one patients undergoing non-cancer bowel resection were prospectively enrolled. Blood samples collected before surgery and on postoperative day one (POD1) were analyzed using a combination of single-cell mass cytometry and plasma proteomics. The primary outcome was the occurrence of an SSC, including surgical site infection, anastomotic leak, or wound dehiscence within 30 days of surgery. RESULTS A multiomic model integrating the single-cell and plasma proteomic data collected on POD1 accurately differentiated patients with (n = 11) and without (n = 30) an SSC [area under the curve (AUC) = 0.86]. Model features included coregulated proinflammatory (eg, IL-6- and MyD88- signaling responses in myeloid cells) and immunosuppressive (eg, JAK/STAT signaling responses in M-MDSCs and Tregs) events preceding an SSC. Importantly, analysis of the immunological data obtained before surgery also yielded a model accurately predicting SSCs (AUC = 0.82). CONCLUSIONS The multiomic analysis of patients' immune response after surgery and immune state before surgery revealed systemic immune signatures preceding the development of SSCs. Our results suggest that integrating immunological data in perioperative risk assessment paradigms is a plausible strategy to guide individualized clinical care.
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Affiliation(s)
- Kristen K. Rumer
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Julien Hedou
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Amy Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Jakob Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Department of Hematology, Oncology, Clinical Immunology and Rheumatology, University of Tuebingen, Tuebingen, Germany
| | - Franck Verdonk
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Sorbonne University, GRC 29, DMU DREAM, Assistance Publique-Hôpitaux de Paris, France
| | - Natalie Stanley
- Department of Computer Science and Computational Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Edward Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Adam Bonham
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Danielle Jacobsen
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Beata Warrington
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Xiaoxiao Gao
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Martha Tingle
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Tiffany N. McAllister
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Dorien Feyaerts
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Ina Stelzer
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Dyani Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Kazuo Ando
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Andrew Shelton
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Arden Morris
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Electron Kebebew
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Department of Biomedical Data Sciences, Stanford University, Stanford, CA
- Department of Pediatrics, Stanford University, Stanford, CA
| | - Cindy Kin
- Division of General Surgery, Department of Surgery, School of Medicine, Stanford University, Stanford, CA
| | - Martin S. Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, School of Medicine, Stanford University, Stanford, CA
- Department of Pediatrics, Stanford University, Stanford, CA
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2
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Tsai AS, Berry K, Beneyto MM, Gaudilliere D, Ganio EA, Culos A, Ghaemi MS, Choisy B, Djebali K, Einhaus JF, Bertrand B, Tanada A, Stanley N, Fallahzadeh R, Baca Q, Quach LN, Osborn E, Drag L, Lansberg MG, Angst MS, Gaudilliere B, Buckwalter MS, Aghaeepour N. A year-long immune profile of the systemic response in acute stroke survivors. Brain 2019; 142:978-991. [PMID: 30860258 DOI: 10.1093/brain/awz022] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2018] [Revised: 11/18/2018] [Accepted: 12/14/2018] [Indexed: 02/07/2023] Open
Abstract
Stroke is a leading cause of cognitive impairment and dementia, but the mechanisms that underlie post-stroke cognitive decline are not well understood. Stroke produces profound local and systemic immune responses that engage all major innate and adaptive immune compartments. However, whether the systemic immune response to stroke contributes to long-term disability remains ill-defined. We used a single-cell mass cytometry approach to comprehensively and functionally characterize the systemic immune response to stroke in longitudinal blood samples from 24 patients over the course of 1 year and correlated the immune response with changes in cognitive functioning between 90 and 365 days post-stroke. Using elastic net regularized regression modelling, we identified key elements of a robust and prolonged systemic immune response to ischaemic stroke that occurs in three phases: an acute phase (Day 2) characterized by increased signal transducer and activator of transcription 3 (STAT3) signalling responses in innate immune cell types, an intermediate phase (Day 5) characterized by increased cAMP response element-binding protein (CREB) signalling responses in adaptive immune cell types, and a late phase (Day 90) by persistent elevation of neutrophils, and immunoglobulin M+ (IgM+) B cells. By Day 365 there was no detectable difference between these samples and those from an age- and gender-matched patient cohort without stroke. When regressed against the change in the Montreal Cognitive Assessment scores between Days 90 and 365 after stroke, the acute inflammatory phase Elastic Net model correlated with post-stroke cognitive trajectories (r = -0.692, Bonferroni-corrected P = 0.039). The results demonstrate the utility of a deep immune profiling approach with mass cytometry for the identification of clinically relevant immune correlates of long-term cognitive trajectories.
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Affiliation(s)
- Amy S Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Kacey Berry
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Maxime M Beneyto
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Dyani Gaudilliere
- Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford School of Medicine, CA, USA
| | - Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Anthony Culos
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Mohammad S Ghaemi
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Karim Djebali
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Jakob F Einhaus
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Basile Bertrand
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Athena Tanada
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Natalie Stanley
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Ramin Fallahzadeh
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Quentin Baca
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Lisa N Quach
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Elizabeth Osborn
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Lauren Drag
- Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Maarten G Lansberg
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
| | - Marion S Buckwalter
- Stanford Stroke Center, Stanford School of Medicine, CA, USA.,Department of Neurology and Neurological Sciences, Stanford School of Medicine, CA, USA.,Department of Neurosurgery, Stanford School of Medicine, CA, USA
| | - Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford School of Medicine, CA, USA
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3
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Aghaeepour N, Kin C, Ganio EA, Jensen KP, Gaudilliere DK, Tingle M, Tsai A, Lancero HL, Choisy B, McNeil LS, Okada R, Shelton AA, Nolan GP, Angst MS, Gaudilliere BL. Deep Immune Profiling of an Arginine-Enriched Nutritional Intervention in Patients Undergoing Surgery. JOURNAL OF IMMUNOLOGY (BALTIMORE, MD. : 1950) 2017; 199:ji1700421. [PMID: 28794234 PMCID: PMC5807249 DOI: 10.4049/jimmunol.1700421] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/21/2017] [Accepted: 07/11/2017] [Indexed: 01/08/2023]
Abstract
Application of high-content immune profiling technologies has enormous potential to advance medicine. Whether these technologies reveal pertinent biology when implemented in interventional clinical trials is an important question. The beneficial effects of preoperative arginine-enriched dietary supplements (AES) are highly context specific, as they reduce infection rates in elective surgery, but possibly increase morbidity in critically ill patients. This study combined single-cell mass cytometry with the multiplex analysis of relevant plasma cytokines to comprehensively profile the immune-modifying effects of this much-debated intervention in patients undergoing surgery. An elastic net algorithm applied to the high-dimensional mass cytometry dataset identified a cross-validated model consisting of 20 interrelated immune features that separated patients assigned to AES from controls. The model revealed wide-ranging effects of AES on innate and adaptive immune compartments. Notably, AES increased STAT1 and STAT3 signaling responses in lymphoid cell subsets after surgery, consistent with enhanced adaptive mechanisms that may protect against postsurgical infection. Unexpectedly, AES also increased ERK and P38 MAPK signaling responses in monocytic myeloid-derived suppressor cells, which was paired with their pronounced expansion. These results provide novel mechanistic arguments as to why AES may exert context-specific beneficial or adverse effects in patients with critical illness. This study lays out an analytical framework to distill high-dimensional datasets gathered in an interventional clinical trial into a fairly simple model that converges with known biology and provides insight into novel and clinically relevant cellular mechanisms.
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Affiliation(s)
- Nima Aghaeepour
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Cindy Kin
- Department of Surgery, Stanford University School of Medicine, Stanford, CA 94121
| | - Edward A Ganio
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Kent P Jensen
- Division of Immunology and Rheumatology, Department of Medicine, Stanford University School of Medicine, Stanford, CA 94121; and
| | - Dyani K Gaudilliere
- Department of Surgery, Stanford University School of Medicine, Stanford, CA 94121
| | - Martha Tingle
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Amy Tsai
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Hope L Lancero
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Benjamin Choisy
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Leslie S McNeil
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Robin Okada
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Andrew A Shelton
- Department of Surgery, Stanford University School of Medicine, Stanford, CA 94121
| | - Garry P Nolan
- Department of Microbiology and Immunology, Stanford University, Stanford, CA 94121
| | - Martin S Angst
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121
| | - Brice L Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, CA 94121;
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4
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Baca Q, Cosma A, Nolan G, Gaudilliere B. The road ahead: Implementing mass cytometry in clinical studies, one cell at a time. CYTOMETRY PART B-CLINICAL CYTOMETRY 2017; 92:10-11. [PMID: 27874247 DOI: 10.1002/cyto.b.21497] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Affiliation(s)
- Quentin Baca
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
| | - Antonio Cosma
- CEA - Université Paris Sud 11 - INSERM U1184, Immunology of viral infections and autoimmune diseases, Fontenay-aux- Roses, France
| | - Garry Nolan
- Department of Microbiology and Immunology, Stanford University School of Medicine, Stanford, California, USA
| | - Brice Gaudilliere
- Department of Anesthesiology, Perioperative and Pain Medicine, Stanford University School of Medicine, Stanford, California, USA
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5
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Gaudillière B, Ganio EA, Tingle M, Lancero HL, Fragiadakis GK, Baca QJ, Aghaeepour N, Wong RJ, Quaintance C, El-Sayed YY, Shaw GM, Lewis DB, Stevenson DK, Nolan GP, Angst MS. Implementing Mass Cytometry at the Bedside to Study the Immunological Basis of Human Diseases: Distinctive Immune Features in Patients with a History of Term or Preterm Birth. Cytometry A 2015; 87:817-29. [PMID: 26190063 PMCID: PMC4758855 DOI: 10.1002/cyto.a.22720] [Citation(s) in RCA: 34] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
Single-cell technologies have immense potential to shed light on molecular and biological processes that drive human diseases. Mass cytometry (or Cytometry by Time Of Flight mass spectrometry, CyTOF) has already been employed in clinical studies to comprehensively survey patients' circulating immune system. As interest in the "bedside" application of mass cytometry is growing, the delineation of relevant methodological issues is called for. This report uses a newly generated dataset to discuss important methodological considerations when mass cytometry is implemented in a clinical study. Specifically, the use of whole blood samples versus peripheral blood mononuclear cells (PBMCs), design of mass-tagged antibody panels, technical and analytical implications of sample barcoding, and application of traditional and unsupervised approaches to analyze high-dimensional mass cytometry datasets are discussed. A mass cytometry assay was implemented in a cross-sectional study of 19 women with a history of term or preterm birth to determine whether immune traits in peripheral blood differentiate the two groups in the absence of pregnancy. Twenty-seven phenotypic and 11 intracellular markers were simultaneously analyzed in whole blood samples stimulated with lipopolysaccharide (LPS at 0, 0.1, 1, 10, and 100 ng mL(-1)) to examine dose-dependent signaling responses within the toll-like receptor 4 (TLR4) pathway. Complementary analyses, grounded in traditional or unsupervised gating strategies of immune cell subsets, indicated that the prpS6 and pMAPKAPK2 responses in classical monocytes are accentuated in women with a history of preterm birth (FDR<1%). The results suggest that women predisposed to preterm birth may be prone to mount an exacerbated TLR4 response during the course of pregnancy. This important hypothesis-generating finding points to the power of single-cell mass cytometry to detect biologically important differences in a relatively small patient cohort.
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Affiliation(s)
- Brice Gaudillière
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, School of Medicine, Stanford, California 94305
- Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, California 94305
| | - Edward A. Ganio
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, School of Medicine, Stanford, California 94305
| | - Martha Tingle
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, School of Medicine, Stanford, California 94305
| | - Hope L. Lancero
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, School of Medicine, Stanford, California 94305
| | - Gabriela K. Fragiadakis
- Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, California 94305
- Department of Microbiology and Immunology, Stanford University, Stanford, California 94305
| | - Quentin J. Baca
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, School of Medicine, Stanford, California 94305
| | - Nima Aghaeepour
- Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, California 94305
| | - Ronald J. Wong
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California 94305
| | - Cele Quaintance
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California 94305
| | - Yasser Y. El-Sayed
- Department of Obstetrics and Gynecology, Stanford University School of Medicine, Stanford, California 94305
| | - Gary M. Shaw
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California 94305
| | - David B. Lewis
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California 94305
| | - David K. Stevenson
- Department of Pediatrics, Stanford University School of Medicine, Stanford, California 94305
| | - Garry P. Nolan
- Baxter Laboratory in Stem Cell Biology, Department of Microbiology and Immunology, Stanford University, Stanford, California 94305
- Department of Microbiology and Immunology, Stanford University, Stanford, California 94305
| | - Martin S. Angst
- Department of Anesthesiology, Perioperative, and Pain Medicine, Stanford University, School of Medicine, Stanford, California 94305
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6
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Tárnok A. Leukocytes Don't Lie. Cytometry A 2015; 87:791-2. [PMID: 26317921 DOI: 10.1002/cyto.a.22737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2015] [Accepted: 07/31/2015] [Indexed: 11/06/2022]
Affiliation(s)
- Attila Tárnok
- Department of Pediatric Cardiology, Heart Centre Leipzig, University of Leipzig, Leipzig, Germany.,Institute of Clinical Immunology, Medical Faculty, University of Leipzig, Leipzig, Germany
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