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. 2023 Nov 20;6:1179. doi: 10.1038/s42003-023-05548-w

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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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 3 — a Unsupervised clustering of the top 50 reactions with the greatest fold change of flux relative to the mean flux of control models. Flux distribution was determined using eFBA. b Metabolic pathways to which the top 50 reactions are assigned, demonstrating the percentage of the top 50 reactions belonging to each pathway. c The top five subsystems with the highest reaction count were determined by assigning the top 50 most changed reactions to the Recon 3D subsystems. d Unsupervised clustering of NAD+ metabolism reactions based on the fold change of flux relative to the mean flux of control models. Flux distribution was determined using eFBA. e Unsupervised clustering of estimated flux for the NAD+ involving reactions in the mitochondria. Flux distribution was determined using eFBA. f Unsupervised clustering of estimated flux for the NAD+ involving reactions in the cytosol. Flux distribution was determined using eFBA.