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. 2024 Sep 4;51(1):954. doi: 10.1007/s11033-024-09890-y

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© The Author(s) 2024

Open Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, 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 you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. 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-nc-nd/4.0/.

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Fig. 4 — Identification of cell types in fresh L-PRF membranes (n = 4). (A) Cells are color coded by original sample identity. (B) Cell identification based on a supervised annotation algorithm (SingleR): cells are color coded by predicted cell type. (C) Clusters identified by an unsupervised graph-based algorithm: color coded by cluster (left), with cluster identification based on highly differentially expressed genes (right). (D) Feature plots indicating main leukocyte types. Pan leukocyte marker PTPRC (CD45); stem cell marker CD34; granulocyte marker FUT4 (CD15); monocyte markers FCGR3A and CD14; NK cell marker NCAM; T cell markers CD3E, CD4 and CD8A; B cell marker CD19