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. 2023 Jul 20;13:11765. doi: 10.1038/s41598-023-38762-x

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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/.

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Clustering transcriptome data via weighted gene correlation network analysis (WGCNA). Dendrograms of all genes and modules with different colors for HPMECs (A) and HCAECs (B). Scatter plots of the fold change (FC) of the eigengenes of identified modules from control to high-dose (10 mM) NMN in the non-poly(I:C)-activated condition (x-axis) vs. the poly(I:C)-activated condition (y-axis) for HPMECs (C) and HCAECs (D). Boxplots of eigengene expression and list of pathways overrepresented in the HPMEC p-green and p-sienna3 modules (E) and the HCAEC c-magenta and c-purple modules (F).