{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,10,21]],"date-time":"2026-10-21T23:20:09Z","timestamp":1792624809402,"version":"4.5.0"},"reference-count":46,"publisher":"Wiley","issue":"4","license":[{"start":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T00:00:00Z","timestamp":1742169600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"},{"start":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T00:00:00Z","timestamp":1742169600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Cytometry Pt A"],"published-print":{"date-parts":[[2025,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:p>Profiling the human immune system is essential to understanding its role in disease, but it requires advanced and novel technologies. Spectral flow cytometry (SFM) enables deep profiling at the single\u2010cell level. It is able to detect many fluorescent parameters within one measurement; therefore, it is vastly useful when patient material is limited. However, designing and analyzing these high\u2010dimensional datasets remains complex. We optimized a 42\u2010parameter panel (40 commercially available fluorochromes, one stacked fluorochrome and an autofluorescent (AF) parameter) that enables the identification of innate and adaptive immune cell composition. It is the first 42\u2010parameter panel that is optimized on peripheral whole blood, and it outperforms other published OMIPs of 40 colors in terms of complexity. With this panel, we are able to identify neutrophils, basophils, eosinophils, monocytes, dendritic cells, CD4 T cells, CD8 T cells, regulatory T cells, mucosal\u2010associated invariant T (MAIT) cells, \u03b3\u03b4 T cells, B cells, NK cells, dendritic cells, and innate lymphoid cells (ILCs). Furthermore, with the utilization of co\u2010stimulatory, checkpoint, activation, homing, and maturation markers, this panel enables deeper phenotyping. Within one measurement, more than 80 distinct immune cell subsets were identified by FlowSOM and annotated manually. In conclusion, with this high\u2010dimensional SFM panel, we aim to generate immune profiles to understand disease and monitor therapy response.<\/jats:p>","DOI":"10.1002\/cyto.a.24927","type":"journal-article","created":{"date-parts":[[2025,3,17]],"date-time":"2025-03-17T08:14:56Z","timestamp":1742199296000},"page":"226-232","update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":13,"title":["OMIP\u2010112: 42\u2010Parameter (40\u2010Color) Spectral Flow Cytometry Panel for Comprehensive Immunophenotyping of Human Peripheral Blood Leukocytes"],"prefix":"10.1002","volume":"107","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-0968-9601","authenticated-orcid":false,"given":"Laurien A.","family":"Waaijer","sequence":"first","affiliation":[{"name":"Department of Laboratory Medicine Radboud University Medical Center  Nijmegen the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Bram","family":"van Cranenbroek","sequence":"additional","affiliation":[{"name":"Department of Laboratory Medicine Radboud University Medical Center  Nijmegen the Netherlands"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hans J. 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