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Multi-center evaluation of the VITEK® MS system for mass spectrometric identification of non-Enterobacteriaceae Gram-negative bacilli

  • R. Manji
  • M. Bythrow
  • J. A. Branda
  • C.-A. D. Burnham
  • M. J. Ferraro
  • O. B. Garner
  • R. Jennemann
  • M. A. Lewinski
  • A. B. Mochon
  • G. W. Procop
  • S. S. Richter
  • J. A. Rychert
  • L. Sercia
  • L. F. Westblade
  • C. C. GinocchioEmail author
Article

Abstract

Studies have demonstrated that matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS) is a rapid, accurate method for the identification of clinically relevant bacteria. The purpose of this study was to evaluate the performance of the VITEK MS v2.0 system (bioMérieux) for the identification of the non-Enterobacteriaceae Gram-negative bacilli (NEGNB). This multi-center study tested 558 unique NEGNB clinical isolates, representing 18 genera and 33 species. Results obtained with the VITEK MS v2.0 were compared with reference 16S rRNA gene sequencing and when indicated recA sequencing and phenotypic analysis. VITEK MS v2.0 provided an identification for 92.5 % of the NEGNB isolates (516 out of 558). VITEK MS v2.0 correctly identified 90.9 % of NEGNB (507 out of 558), 77.8 % to species level and 13.1 % to genus level with multiple species. There were four isolates (0.7 %) incorrectly identified to genus level and five isolates (0.9 %), with one incorrect identification to species level. The remaining 42 isolates (7.5 %) were either reported as no identification (5.0 %) or called “mixed genera” (2.5 %) since two or more different genera were identified as possible identifications for the test organism. These findings demonstrate that the VITEK MS v2.0 system provides accurate results for the identification of a challenging and diverse group of Gram-negative bacteria.

Keywords

Species Level Cystic Fibrosis Patient Mixed Genus Incorrect Identification Clinical Trial Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgements

This study was sponsored by bioMérieux, Durham. NC, USA. We sincerely thank the technical staff at each clinical trial site for their support. We thank David Pincus, Constance Bradford, and Karen MacDonald for providing technical support and statistical analysis.

Transparency declaration

John A. Branda, Jenna A. Rychert, and Mary Jane Farraro have received research funding from bioMérieux and Becton Dickinson and Co. Christine C. Ginocchio has received research funding and/or consulting fees from bioMérieux, Becton Dickinson, Biofire, Biohelix, Nanosphere, Curetis, and Luminex. Gary Procop has received research funding from bioMérieux, Bruker, CDC and Luminex. Sandra S. Richter has received research funding from bioMérieux, Nanosphere, and Forest Laboratories. Carey-Ann Burnham has received research funding from bioMérieux, Accler8, Cepheid, and T2 Biosystems. None of the other authors has any conflicts to disclose.

References

  1. 1.
    Bassetti M, Taramasso L, Giacobbe DR, Pelosi P (2012) Management of ventilator-associated pneumonia: epidemiology, diagnosis and antimicrobial therapy. Expert Rev Anti Infect Ther 10:585–596PubMedCrossRefGoogle Scholar
  2. 2.
    Bergfors E, Trollfors B, Taranger J, Lagergård T, Sundh V, Zackrisson G (1999) Parapertussis and pertussis: differences and similarities in incidence, clinical course, and antibody responses. Int J Infect Dis 3:140–146PubMedCrossRefGoogle Scholar
  3. 3.
    Bos AC, Beemsterboer P, Wolfs TF, Versteegh FG, Arets HG (2011) Bordetella species in children with cystic fibrosis: what do we know? The role in acute exacerbations and chronic course. J Cyst Fibros 10:307–312PubMedCrossRefGoogle Scholar
  4. 4.
    Daniels NA (2011) Vibrio vulnificus oysters: pearls and perils. Clin Infect Dis 52:788–792PubMedCrossRefGoogle Scholar
  5. 5.
    Dortet L, Legrand P, Soussy CJ, Cattoir V (2006) Bacterial identification, clinical significance, and antimicrobial susceptibilities of Acinetobacter ursingii and Acinetobacter schindleri, two frequently misidentified opportunistic pathogens. J Clin Microbiol 44:4471–4478PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Howard A, O’Donoghue M, Feeney A, Sleator RD (2012) Acinetobacter baumannii: an emerging opportunistic pathogen. Virulence 3:243–250PubMedCrossRefGoogle Scholar
  7. 7.
    Janda JM, Abbott SL (2010) The genus Aeromonas: taxonomy, pathogenicity, and infection. Clin Microbiol Rev 23:35–73PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Lai CC, Teng LJ, Hsueh PR, Yuan A, Tsai KC, Tang JL, Tien HF (2004) Clinical and microbiological characteristics of Rhizobium radiobacter infections. Clin Infect Dis 38:149–153PubMedCrossRefGoogle Scholar
  9. 9.
    Lipuma JJ (2005) Update on the Burkholderia cepacia complex. Curr Opin Pulm Med 11:528–533PubMedCrossRefGoogle Scholar
  10. 10.
    Lipuma JJ (2010) The changing microbial epidemiology in cystic fibrosis. Clin Microbiol Rev 23:299–323PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Vila J, Pachón J (2012) Therapeutic options for Acinetobacter baumannii infections: an update. Expert Opin Pharmacother 13:2319–2336PubMedCrossRefGoogle Scholar
  12. 12.
    Govan JR, Brown PH, Maddison J, Doherty CJ, Nelson JW, Dodd M, Greening AP, Webb AK (1993) Evidence for transmission of Pseudomonas cepacia by social contact in cystic fibrosis. Lancet 342:15–19PubMedCrossRefGoogle Scholar
  13. 13.
    Hadjiliadis D (2007) Special considerations for patients with cystic fibrosis undergoing lung transplantation. Chest 131:1224–1231PubMedCrossRefGoogle Scholar
  14. 14.
    Ferreira L, Sánchez-Juanes F, Garcia-Fraile P, Rivas R, Mateos PF, Martínez-Molina E, González-Buitrago JM, Velázquez E (2011) MALDI-TOF mass spectrometry is a fast and reliable platform for identification and ecological studies of species from family Rhizobiaceae. PLoS One 6(5):e20223PubMedCentralPubMedCrossRefGoogle Scholar
  15. 15.
    Barzilay EJ, Schaad N, Magloire R, Mung KS, Boncy J, Dahourou GA, Mintz ED, Steenland MW, Vertefeuille JF, Tappero JW (2013) Cholera surveillance during the Haiti epidemic—the first 2 years. N Engl J Med 368:599–609PubMedCrossRefGoogle Scholar
  16. 16.
    Benagli C, Demarta A, Caminada AP, Ziegler D, Petrini O (2012) A rapid MALDI-TOF MS identification database at genospecies level for clinical and environmental Aeromonas strains. PLoS One 7(10):e48441PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Newton AE, Heiman KE, Schmitz A, Török T, Apostolou A, Hanson H, Gounder P, Bohm S, Kurkjian K, Parsons M, Talkington D, Stroika S, Madoff LC, Elson F, Sweat D, Cantu V, Akwari O, Mahon BE, Mintz ED (2011) Cholera in United States associated with epidemic in Hispaniola. Emerg Infect Dis 17:2166–2168PubMedGoogle Scholar
  18. 18.
    Weber DJ, Wolfson JS, Swartz MN, Hooper DC (1984) Pasteurella multocida infections. Report of 34 cases and review of the literature. Med (Baltimore) 63:133–154CrossRefGoogle Scholar
  19. 19.
    Brisse S, Stefani S, Verhoef J, Van Belkum A, Vandamme P, Goessens W (2002) Comparative evaluation of the BD Phoenix and VITEK 2 automated instruments for identification of isolates of the Burkholderia cepacia complex. J Clin Microbiol 40:1743–1748PubMedCentralPubMedCrossRefGoogle Scholar
  20. 20.
    Chatzigeorgiou KS, Sergentanis TN, Tsiodras S, Hamodrakas SJ, Bagos PG (2011) Phoenix 100 versus Vitek 2 in the identification of Gram-positive and Gram-negative bacteria: a comprehensive meta-analysis. J Clin Microbiol 49:3284–3291PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Donay JL, Mathieu D, Fernandes P, Prégermain C, Bruel P, Wargnier A, Casin I, Weill FX, Lagrange PH, Herrmann JL (2004) Evaluation of the automated Phoenix system for potential routine use in the clinical microbiology laboratory. J Clin Microbiol 42:1542–1546PubMedCentralPubMedCrossRefGoogle Scholar
  22. 22.
    McGregor A, Schio F, Beaton S, Boulton V, Perman M, Gilbert G (1995) The MicroScan WalkAway diagnostic microbiology system—an evaluation. Pathology 27:172–176PubMedCrossRefGoogle Scholar
  23. 23.
    Stefaniuk E, Baraniak A, Gniadkowski M, Hryniewicz W (2003) Evaluation of the BD Phoenix automated identification and susceptibility testing system in clinical microbiology laboratory practice. Eur J Clin Microbiol Infect Dis 22:479–485PubMedCrossRefGoogle Scholar
  24. 24.
    Bizzini A, Jaton K, Romo D, Bille J, Prod’hom G, Greub G (2011) Matrix-assisted laser desorption ionization-time of flight mass spectrometry as an alternative to 16S rRNA gene sequencing for identification of difficult-to-identify bacterial strains. J Clin Microbiol 49:693–696PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Ferroni A, Sermet-Gaudelus I, Abachin E, Quesne G, Lenoir G, Berche P, Gaillard JL (2002) Use of 16S rRNA sequencing for identification of nonfermenting gram-negative bacilli recovered from patients attending a cystic fibrosis center. J Clin Microbiol 40:3793–3797PubMedCentralPubMedCrossRefGoogle Scholar
  26. 26.
    Mellmann A, Cloud J, Maier T, Keckevoet U, Ramminger I, Iwen P, Dunn J, Hall G, Wilson D, Lasala P, Kostrzewa M, Harmsen D (2008) Evaluation of matrix-assisted laser desorption ionization-time-of-flight mass spectrometry in comparison to 16S rRNA gene sequencing for species identification of nonfermenting bacteria. J Clin Microbiol 46:1946–1954PubMedCentralPubMedCrossRefGoogle Scholar
  27. 27.
    Mulet M, Gomila M, Scotta C, Sánchez D, Lalucat J, García-Valdés (2012) Concordance between whole-cell matrix-assisted laser-desorption/ionizatio time-of-flight mass spectrometry and multilocus sequence analysis approaches in species discrimination within the genus Pseudomonas. Syst Appl Microbiol 35:455–464PubMedCrossRefGoogle Scholar
  28. 28.
    Álvarez-Buylla A, Culebras E, Picazo JJ (2012) Identification of Acinetobacter species: is brucker biotyper MALDI-TOF mass spectrometry a good alternative to molecular techniques? Infect Gen Evol 12:345–349CrossRefGoogle Scholar
  29. 29.
    Benagli C, Rossi V, Dolina M, Tonolla M, Petrini O (2011) Matrix-assisted laser desorption ionization-time of flight mass spectrometry for the identification of clinically relevant bacteria. PLoS One 6(1):e16424PubMedCentralPubMedCrossRefGoogle Scholar
  30. 30.
    Bizzini A, Durussel C, Bille J, Greub G, Prod’hom G (2010) Performance of matrix-assisted laser desorption ionization-time of flight mass spectrometry for identification of bacterial strains routinely isolated in a clinical microbiology laboratory. J Clin Microbiol 48:1549–1554PubMedCentralPubMedCrossRefGoogle Scholar
  31. 31.
    Carbonnelle E, Grohs P, Jacquier H, Day N, Tenza S, Dewailly A, Vissouarn O, Rottman M, Herrmann JL, Podglajen I, Raskine L (2012) Robustness of two MALDI-TOF mass spectrometry systems for bacterial identification. J Microbiol Methods 89:133–136PubMedCrossRefGoogle Scholar
  32. 32.
    Cherkaoui A, Hibbs J, Emonet S, Tangomo M, Girard M, Francois P, Schrenzel J (2010) Comparison of two matrix-assisted laser desorption ionization-time of flight mass spectrometry methods with conventional phenotypic identification for routine identification of bacteria to the species level. J Clin Microbiol 48:1169–1175PubMedCentralPubMedCrossRefGoogle Scholar
  33. 33.
    Degand N, Carbonnelle E, Dauphin B, Beretti JL, Le Bourgeois M, Sermet-Gaudelus I, Segonds C, Berche P, Nassif X, Ferroni A (2008) Matrix-assisted laser desorption ionization-time of flight mass spectrometry for identification on nonfermenting Gram-negative bacilli isolated from cystic fibrosis patients. J Clin Microbiol 46:3361–3367PubMedCentralPubMedCrossRefGoogle Scholar
  34. 34.
    Desai AP, Stanley T, Atuan M, McKey J, Lipuma JJ, Rogers B, Jerris R (2012) Use of matrix assisted laser desorption ionization-time of flight mass spectrometry in a paediatric clinical laboratory for identification of bacteria commonly isolated from cystic fibrosis patients. J Clin Pathol 65:835–838PubMedCrossRefGoogle Scholar
  35. 35.
    Dieckman R, Strauch E, Alter T (2010) Rapid identification and characterization of Vibrio species using whole cell MALDI-TOF mass spectrometry. J Appl Microbiol 109:199–211Google Scholar
  36. 36.
    Dubois D, Grare M, Prere MF, Segonds C, Marty N, Oswald E (2012) Performances of the Vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry system for rapid identification of bacteria in routine clinical microbiology. J Clin Microbiol 50:2568–2576PubMedCentralPubMedCrossRefGoogle Scholar
  37. 37.
    Eigner U, Holfelder M, Oberdorfer K, Betz-Wild U, Bertsch D, Fahr AM (2009) Performance of a matrix-assisted laser desorption ionization-time-of-flight mass spectrometry system for the identification of bacterial isolates in the clinical routine laboratory. Clin Lab 55:289–296PubMedGoogle Scholar
  38. 38.
    El-Bouri K, Johnston S, Rees E, Thomas I, Bome-Mannathoko N, Jones C, Reid M, Ben-Ismaeil B, Davies AR, Harris LG, Mack D (2012) Comparison of bacterial identification by MALDI-TOF mass spectrometry and conventional diagnostic microbiology methods: agreement, speed and cost implications. Br J Biomed Sci 69:47–55PubMedGoogle Scholar
  39. 39.
    Fernández-Olmos A, Garcia-Castillo M, Morosini M-I, Lamas A, Maiz L, Canon R (2012) MALDI-TOF MS improves routine identification of non-fermenting Gram negative isolates from cystic fibrosis patients. J Cyst Fibros 11:59–62PubMedCrossRefGoogle Scholar
  40. 40.
    Ferroni A, Suarez S, Beretti JL, Dauphin B, Bille E, Meyer J, Bougnoux ME, Alanio A, Berche P, Nassif X (2010) Real-time identification of bacteria and Candida species in positive blood culture broths by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 48:1542–1548PubMedCentralPubMedCrossRefGoogle Scholar
  41. 41.
    Hazen TH, Martinez RJ, Chen Y, Lafon PC, Garrett NM, Parsons MB, Bopp CA, Sullards MC, Sobecky PA (2009) Rapid identification of Vibrio parahaemolyticus by whole-cell lysate matrix-assisted laser desorption ionization-time of flight mass spectrometry. Appl Environ Microbiol 75:6745–6756PubMedCentralPubMedCrossRefGoogle Scholar
  42. 42.
    Lambiase A, Del Pezzo M, Cerbone D, Raia V, Rossano F, Catania MR (2013) Rapid identification of Burkholderia cepacia complex species recovered from cystic fibrosis patients using matrix-assisted laser desorption ionization time-of-flight mass spectrometry. J Microbiol Methods 92:145–149PubMedCrossRefGoogle Scholar
  43. 43.
    Marko DC, Saffert RT, Cunningham SA, Hyman J, Walsh J, Arbefeville S, Howard W, Pruessner J, Safwat N, Cockerill FR, Bossler AD, Patel R, Richter SS (2012) Evaluation of the Bruker Biotyper and Vitek MS matrix-assisted laser desorption ionization-time of flight mass spectrometry systems for identification of nonfermenting Gram-negative bacilli isolated from cultures from cystic fibrosis patients. J Clin Microbiol 50:2034–2039PubMedCentralPubMedCrossRefGoogle Scholar
  44. 44.
    Martiny D, Busson L, Wybo I, El Haj RA, Dediste A, Vandenberg O (2012) Comparison of the Microflex LT and Vitek MS systems for routine identification of bacteria by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 50:1313–1325PubMedCentralPubMedCrossRefGoogle Scholar
  45. 45.
    Risch M, Radjenovic D, Han JN, Wydler M, Nydegger U, Risch L (2010) Compariosn of MALDI TOF with conventional identification of clinically relevant bacteria. Swiss Med Wkly 140:w13095PubMedGoogle Scholar
  46. 46.
    Sedo O, Vorac A, Zdrahal Z (2011) Optimization of mass spectral profiling in MALDI-TOF MS profiling of Acinetobacter species. Syst Appl Microbiol 34:30–34PubMedCrossRefGoogle Scholar
  47. 47.
    Stevenson LG, Drake SK, Murray PR (2010) Rapid identification of bacteria in positive blood culture broths by matrix-assisted laser desorption ionization-time of flight mass spectrometry. J Clin Microbiol 48:444–447PubMedCentralPubMedCrossRefGoogle Scholar
  48. 48.
    Vanlaere E, Sergeant K, Dawyndt P, Kallow W, Erhard M, Sutton H, Dare D, Devreese B, Samyn B, Vandamme P (2008) Matrix-assisted laser desorption ionization-time of flight mass spectrometry of intact cells allows rapid identification of Burkholderia cepacia complex. J Microbiol Meth 75:279–286CrossRefGoogle Scholar
  49. 49.
    Van Veen SQ, Claas EC, Kuijper EJ (2010) High-throughput identification of bacteria and yeast by matrix-assisted laser desorption ionization-time of flight mass spectrometry in conventional medical microbiology laboratories. J Clin Microbiol 48:900–907PubMedCentralPubMedCrossRefGoogle Scholar
  50. 50.
    Bizzini A, Greub G (2010) Matrix-assisted laser desorption ionization time-of-flight mass spectrometry, a revolution in clinical microbial identification. Clin Microbiol Infect 16:1614–1619PubMedCrossRefGoogle Scholar
  51. 51.
    Croxatto A, Prod’hom G, Greub G (2012) Applications of MALDI-TOF mass spectrometry in clinical diagnostic microbiology. FEMS Microbiol Rev 36:380–407PubMedCrossRefGoogle Scholar
  52. 52.
    Sauer S, Freiwald A, Maier T, Kube M, Reinhardt R, Kostrzewa M, Geider K (2008) Classification and identification of bacteria by mass spectrometry and computational analysis. PLoS One 3(7):e2843PubMedCentralPubMedCrossRefGoogle Scholar
  53. 53.
    Van Belkum A, Welker M, Erhard M, Chatellier S (2012) Biomedical mass spectrometry in today’s and tomorrow’s clinical microbiology laboratories. J Clin Microbiol 50:1513–1517PubMedCentralPubMedCrossRefGoogle Scholar
  54. 54.
    Welker M, Moore ER (2011) Applications of whole-cell matrix-assisted laser-desorption/ionization time-of-flight mass spectrometry in systematic microbiology. Syst Appl Microbiol 34:2–11PubMedCrossRefGoogle Scholar
  55. 55.
    Welker M (2011) Proteomics for routine identification of microorganisms. Proteomics 11:3143–3153PubMedCrossRefGoogle Scholar
  56. 56.
    Rychert J, Burnham C-A, Bythrow M, Garner C, Ginocchio CC, Jennemann R, Lewinski MA, Manji R, Mochon AB, Procop GW, Richter SS, Sercia L, Westblade LF, Ferraro MJ, Branda JA (2013) Multicenter evaluation of the VITEK MS MALDI-TOF mass spectrometry system for the identification of gram-positive aerobic bacteria. J Clin Microbiol 51:2225–2231PubMedCentralPubMedCrossRefGoogle Scholar
  57. 57.
    Clinical and Laboratory Standards Institute (2004) Nucleic acid sequencing methods in diagnostic laboratory medicine. MM09-A. Clinical and Laboratory Standards Institute, WayneGoogle Scholar
  58. 58.
    Clinical and Laboratory Standards Institute (2008) Interpretive criteria for identification of bacteria and fungi by DNA target sequencing. MM18-A. Clinical and Laboratory Standards Institute, WayneGoogle Scholar
  59. 59.
    Cesarini S, Bevivino A, Tabacchioni S, Chiarini L, Dalmastri C (2009) RecA gene sequence and Multilocus Sequence Typing for species-level resolution of Burkholderia cepacia complex isolates. Lett Appl Microbiol 49:580–588PubMedCrossRefGoogle Scholar
  60. 60.
    Espinal P, Seifert H, Dijkshoorn L, Vila J, Roca I (2011) Rapid and accurate identification of egnomic species from the Acinetobacter baumannii (Ab) group by MALDI-TOF MS. Clin Microbiol Infect 18:1097–1103PubMedCrossRefGoogle Scholar
  61. 61.
    Bessede E, Angla-Gre M, Delagarde Y, Sep Hieng S, Menard A, Megraud F (2011) Matrix-assisted laser-desorption/ionization biotyper: experience in the routine of a University hospital. Clin Microbiol Infect 17:533–538PubMedCrossRefGoogle Scholar
  62. 62.
    Gaillot O, Blondiaux N, Loïez C, Wallet F, Lemaître N, Herwegh S, Courcol RJ (2011) Cost-effectiveness of switch to matrix-assisted laser desorption ionization-time of flight mass spectrometry for routine bacterial identification. J Clin Microbiol 49:4412PubMedCentralPubMedCrossRefGoogle Scholar
  63. 63.
    Neville SA, Lecordier A, Ziochos H, Chater MJ, Gosbell IB, Maley MW, van Hal SJ (2011) Utility of matrix-assisted laser desorption ionization-time of flight mass spectrometry following introduction for routine laboratory bacterial identification. J Clin Microbiol 49:2980–2984PubMedCentralPubMedCrossRefGoogle Scholar
  64. 64.
    Tan KE, Ellis BC, Lee R, Stamper PD, Zhang SX, Carroll KC (2012) Prospective evaluation of a matrix-assisted laser desorption ionization-time of flight mass spectrometry system in a hospital clinical microbiology laboratory for identification of bacteria and yeasts: a bench-by-bench study for assessing the impact on time to identification and cost-effectiveness. J Clin Microbiol 50:3301–3308PubMedCentralPubMedCrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • R. Manji
    • 1
  • M. Bythrow
    • 1
  • J. A. Branda
    • 2
  • C.-A. D. Burnham
    • 3
  • M. J. Ferraro
    • 2
  • O. B. Garner
    • 4
  • R. Jennemann
    • 5
  • M. A. Lewinski
    • 4
  • A. B. Mochon
    • 4
  • G. W. Procop
    • 6
  • S. S. Richter
    • 6
  • J. A. Rychert
    • 2
  • L. Sercia
    • 6
  • L. F. Westblade
    • 3
    • 7
  • C. C. Ginocchio
    • 1
    • 7
    Email author
  1. 1.Department of Pathology and Laboratory MedicineNorth Shore-LIJ Health System LaboratoriesLake SuccessUSA
  2. 2.Department of PathologyMassachusetts General Hospital and Harvard Medical SchoolBostonUSA
  3. 3.Department of Pathology and ImmunologyWashington University School of MedicineSt. LouisUSA
  4. 4.Department of Pathology and Laboratory MedicineDavid Geffen School of Medicine at UCLALos AngelesUSA
  5. 5.Barnes Jewish HospitalSt. LouisUSA
  6. 6.Department of Clinical PathologyCleveland ClinicClevelandUSA
  7. 7.Department of Pathology and Laboratory MedicineHofstra North Shore-LIJ School of MedicineHempsteadUSA

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