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. 2023 Mar 7;21:79. doi: 10.1186/s12951-023-01834-1

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© The Author(s) 2023

Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

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Fig. 2 — Global identification of proteins in ULF-EVs. A Principal component analysis of total proteins in ULF-EVs. B Kernel density estimation of the relative abundance of proteins in ULF-EVs in four different periods. C Pie chart of intracellular protein locations, which were predicted by BUSCA software. D Protein dynamics of ULF-EVs in four different stages. Global proteins were clustered into six soft partitioning clusters, with distinct clusters falling into different biological functions based on abundance patterns. The purple line represents the abundance trend of the proteins in the cluster