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@ARTICLE{Kardell:266784,
      author       = {Kardell, Oliver and von Toerne, Christine and Merl-Pham,
                      Juliane and König, Ann-Christine and Blindert, Marcel and
                      Barth, Teresa K and Mergner, Julia and Ludwig, Christina and
                      Tüshaus, Johanna and Eckert, Stephan and Müller, Stephan A
                      and Breimann, Stephan and Giesbertz, Pieter and Bernhardt,
                      Alexander Maximilian and Schweizer, Lisa and Albrecht,
                      Vincent and Teupser, Daniel and Imhof, Axel and Kuster,
                      Bernhard and Lichtenthaler, Stefan F and Mann, Matthias and
                      Cox, Jürgen and Hauck, Stefanie M},
      title        = {{M}ulticenter {C}ollaborative {S}tudy to {O}ptimize {M}ass
                      {S}pectrometry {W}orkflows of {C}linical {S}pecimens.},
      journal      = {Journal of proteome research},
      volume       = {23},
      number       = {1},
      issn         = {1535-3893},
      address      = {Washington, DC},
      publisher    = {ACS Publications},
      reportid     = {DZNE-2024-00042},
      pages        = {117 - 129},
      year         = {2024},
      abstract     = {The foundation for integrating mass spectrometry (MS)-based
                      proteomics into systems medicine is the development of
                      standardized start-to-finish and fit-for-purpose workflows
                      for clinical specimens. An essential step in this pursuit is
                      to highlight the common ground in a diverse landscape of
                      different sample preparation techniques and liquid
                      chromatography-mass spectrometry (LC-MS) setups. With the
                      aim to benchmark and improve the current best practices
                      among the proteomics MS laboratories of the CLINSPECT-M
                      consortium, we performed two consecutive round-robin studies
                      with full freedom to operate in terms of sample preparation
                      and MS measurements. The six study partners were provided
                      with two clinically relevant sample matrices: plasma and
                      cerebrospinal fluid (CSF). In the first round, each
                      laboratory applied their current best practice protocol for
                      the respective matrix. Based on the achieved results and
                      following a transparent exchange of all lab-specific
                      protocols within the consortium, each laboratory could
                      advance their methods before measuring the same samples in
                      the second acquisition round. Both time points are compared
                      with respect to identifications (IDs), data completeness,
                      and precision, as well as reproducibility. As a result, the
                      individual performances of participating study centers were
                      improved in the second measurement, emphasizing the effect
                      and importance of the expert-driven exchange of best
                      practices for direct practical improvements.},
      keywords     = {Tandem Mass Spectrometry: methods / Chromatography, Liquid:
                      methods / Workflow / Reproducibility of Results / Plasma:
                      chemistry / LC–MS (Other) / LC–MS (Other) / LC–MS
                      (Other) / CSF (Other) / LC–MS (Other) / R package mpwR
                      (Other) / clinical specimen (Other) / data-dependent
                      acquisition (Other) / data-independent acquisition (Other) /
                      interlaboratory (Other) / intralaboratory (Other) / mass
                      spectrometry (Other) / plasma (Other) / round-robin study
                      (Other)},
      cin          = {AG Lichtenthaler / AG Haass / Clinical Research (Munich)},
      ddc          = {540},
      cid          = {I:(DE-2719)1110006 / I:(DE-2719)1110007 /
                      I:(DE-2719)1111015},
      pnm          = {352 - Disease Mechanisms (POF4-352) / 353 - Clinical and
                      Health Care Research (POF4-353)},
      pid          = {G:(DE-HGF)POF4-352 / G:(DE-HGF)POF4-353},
      typ          = {PUB:(DE-HGF)16},
      pmc          = {pmc:PMC10775142},
      pubmed       = {pmid:38015820},
      doi          = {10.1021/acs.jproteome.3c00473},
      url          = {https://pub.dzne.de/record/266784},
}