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      Correction: Parallel Workflow for High-Throughput (>1,000 Samples/Day) Quantitative Analysis of Human Insulin-Like Growth Factor 1 Using Mass Spectrometric Immunoassay

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      The PLOS ONE Staff
      PLoS ONE
      Public Library of Science

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          Abstract

          Dr. Mary F. Lopez is incorrectly listed as an author on this article. The authors apologize for this error. The correct author list is as follows: Paul E. Oran, Olgica Trenchevska, Dobrin Nedelkov, Chad R. Borges, Matthew R. Schaab, Douglas S. Rehder, Jason W. Jarvis, Nisha D. Sherma, Luhui Shen, Bryan Krastins, Dawn C. Schwenke, Peter D. Reaven, Randall W. Nelson The legends for Figures 3 and 4 are incorrectly switched. The publisher apologizes for this error. The correct figure legend pairings can be found below. 10.1371/journal.pone.0092801.g003 Figure 3 IGF1 methods comparison. A) Scatter plot. B) Difference plot. 10.1371/journal.pone.0092801.g004 Figure 4 Histogram of IGF1 concentrations determined by MSIA for 1054 EDTA treated human plasma samples. Additionally, the following sentence should be added to the Acknowledgements section: “This work was supported in part with resources and of facilities at the Phoenix VA Health Care System. The contents do not represent the views of the Department of Veterans Affairs or the United States Government.” The complete Acknowledgements read: “We would also like to express gratitude and acknowledge the following ACT NOW study investigators for their assistance with sample collection: Ralph A. DeFronzo, MD. MaryAnn Banerji, MD, FACP, George A. Bray, MD, Thomas A. Buchanan, MD, Stephen C. Clement, MD, Robert R. Henry, MD, Abbas E. Kitabchi, Ph.D., MD, FACP, FACE, Sunder Mudaliar, MD, Robert E. Ratner, MD, FACP, Frankie B. Stentz, MS, PhD, Nicolas Musi, MD. This work was supported in part with resources and of facilities at the Phoenix VA Health Care System. The contents do not represent the views of the Department of Veterans Affairs or the United States Government.”

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          Parallel Workflow for High-Throughput (>1,000 Samples/Day) Quantitative Analysis of Human Insulin-Like Growth Factor 1 Using Mass Spectrometric Immunoassay

          Insulin-like growth factor 1 (IGF1) is an important biomarker for the management of growth hormone disorders. Recently there has been rising interest in deploying mass spectrometric (MS) methods of detection for measuring IGF1. However, widespread clinical adoption of any MS-based IGF1 assay will require increased throughput and speed to justify the costs of analyses, and robust industrial platforms that are reproducible across laboratories. Presented here is an MS-based quantitative IGF1 assay with performance rating of >1,000 samples/day, and a capability of quantifying IGF1 point mutations and posttranslational modifications. The throughput of the IGF1 mass spectrometric immunoassay (MSIA) benefited from a simplified sample preparation step, IGF1 immunocapture in a tip format, and high-throughput MALDI-TOF MS analysis. The Limit of Detection and Limit of Quantification of the resulting assay were 1.5 μg/L and 5 μg/L, respectively, with intra- and inter-assay precision CVs of less than 10%, and good linearity and recovery characteristics. The IGF1 MSIA was benchmarked against commercially available IGF1 ELISA via Bland-Altman method comparison test, resulting in a slight positive bias of 16%. The IGF1 MSIA was employed in an optimized parallel workflow utilizing two pipetting robots and MALDI-TOF-MS instruments synced into one-hour phases of sample preparation, extraction and MSIA pipette tip elution, MS data collection, and data processing. Using this workflow, high-throughput IGF1 quantification of 1,054 human samples was achieved in approximately 9 hours. This rate of assaying is a significant improvement over existing MS-based IGF1 assays, and is on par with that of the enzyme-based immunoassays. Furthermore, a mutation was detected in ∼1% of the samples (SNP: rs17884626, creating an A→T substitution at position 67 of the IGF1), demonstrating the capability of IGF1 MSIA to detect point mutations and posttranslational modifications.
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            Journal
            PLoS One
            PLoS ONE
            plos
            plosone
            PLoS ONE
            Public Library of Science (San Francisco, USA )
            1932-6203
            2014
            22 May 2014
            : 9
            : 5
            : e95812
            Article
            PONE-D-14-14601
            10.1371/journal.pone.0095812
            4031086
            24851902
            525f2d04-9105-49b4-8268-14a4c16bd6fe
            Copyright @ 2014

            This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

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