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      Proteomic analysis of plasma to identify novel biomarkers for intra-amniotic infection and/or inflammation in preterm premature rupture of membranes

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          Abstract

          To identify potential plasma biomarkers associated with microbial invasion of the amniotic cavity (MIAC) and/or intraamniotic inflammation (IAI) in women with preterm premature rupture of membranes (PPROM). This retrospective cohort study included 182 singleton pregnant women with PPROM (23–33 weeks) who underwent amniocentesis. Plasma samples; all subjects were chosen from these participants and were analyzed using label-free liquid chromatography-tandem mass spectrometry for proteome profiling using a nested case–control study design (cases with MIAC/IAI vs. non-MIAC/IAI controls [ n = 9 each]). Three identified target molecules for MIAC/IAI were further verified by ELISA in the study cohort ( n = 182). Shotgun proteomic analysis revealed 17 differentially expressed proteins ( P < 0.05) in the plasma of MIAC/IAI cases. In particular, the levels of FCGR3A and haptoglobin, but not LRP1, were found to be increased in the plasma of patients with MIAC, IAI, and both MIAC/IAI compared with those without these conditions. Moreover, these differences remained significant after adjusting for gestational age at sampling. The area under the curves of plasma FCGR3A and haptoglobin ranged within 0.59–0.65 with respect to each of the three outcome measures. Plasma FCGR3A and haptoglobin were identified as potential independent biomarkers for less-invasively detecting MIAC/IAI in women with PPROM.

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          MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

          Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.
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            Comparing the Areas under Two or More Correlated Receiver Operating Characteristic Curves: A Nonparametric Approach

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              The Perseus computational platform for comprehensive analysis of (prote)omics data.

              A main bottleneck in proteomics is the downstream biological analysis of highly multivariate quantitative protein abundance data generated using mass-spectrometry-based analysis. We developed the Perseus software platform (http://www.perseus-framework.org) to support biological and biomedical researchers in interpreting protein quantification, interaction and post-translational modification data. Perseus contains a comprehensive portfolio of statistical tools for high-dimensional omics data analysis covering normalization, pattern recognition, time-series analysis, cross-omics comparisons and multiple-hypothesis testing. A machine learning module supports the classification and validation of patient groups for diagnosis and prognosis, and it also detects predictive protein signatures. Central to Perseus is a user-friendly, interactive workflow environment that provides complete documentation of computational methods used in a publication. All activities in Perseus are realized as plugins, and users can extend the software by programming their own, which can be shared through a plugin store. We anticipate that Perseus's arsenal of algorithms and its intuitive usability will empower interdisciplinary analysis of complex large data sets.
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                Author and article information

                Contributors
                jelee9137@kist.re.kr
                pkh0419@snubh.org
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                6 April 2023
                6 April 2023
                2023
                : 13
                : 5658
                Affiliations
                [1 ]GRID grid.222754.4, ISNI 0000 0001 0840 2678, Department of Biotechnology, College of Life Sciences and Biotechnology, , Korea University, ; Seoul, 02841 Korea
                [2 ]GRID grid.35541.36, ISNI 0000000121053345, Biomedical Research Division, Chemical and Biological Integrative Research Center, , Korea Institute of Science and Technology, ; Seoul, 02792 Korea
                [3 ]GRID grid.413967.e, ISNI 0000 0001 0842 2126, Department of Obstetrics and Gynecology, , University of Ulsan College of Medicine, Asan Medical Center, ; Seoul, Korea
                [4 ]GRID grid.412480.b, ISNI 0000 0004 0647 3378, Department of Obstetrics and Gynecology, , Seoul National University College of Medicine, Seoul National University Bundang Hospital, ; 82, Gumi-Ro 173 Beon-Gil, Bundang-Gu, Seongnam, 463-707 Korea
                Article
                32884
                10.1038/s41598-023-32884-y
                10079851
                37024561
                3c09d6f7-564f-4058-8212-71941fd375e7
                © The Author(s) 2023

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 16 November 2022
                : 4 April 2023
                Funding
                Funded by: Korea Health Technology R&D Project through the Korea Health Industry Development Institute funded by the Ministry of Health & Welfare
                Award ID: HI20C0013
                Award Recipient :
                Funded by: National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT)
                Award ID: 2020R1F1A1048362
                Award Recipient :
                Categories
                Article
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                © The Author(s) 2023

                Uncategorized
                biomarkers,molecular medicine
                Uncategorized
                biomarkers, molecular medicine

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