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. 2023 Sep 28;21:262. doi: 10.1186/s12964-023-01280-4

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© 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/. 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. 7 — REACTOME analysis of SASP classified by stressor type. A A box plot is presented to illustrate the occurrence rates for each stressor type. The horizontal dashed line represents the threshold for selecting common pathway occurrence rates higher than 75%. B A Venn diagram is used to identify the common and specific pathways among the different stressor types. The names of proteins with central roles in each ontology and frequently included in datasets at each time point are indicated. C The main outcomes of the REACTOME analysis are summarized. Common and specific pathways are categorized based on their functions and presented in the box