Evidence-Based Complementary and Alternative Medicine

Evidence-Based Complementary and Alternative Medicine / 2021 / Article

Corrigendum | Open Access

Volume 2021 |Article ID 9760307 | https://doi.org/10.1155/2021/9760307

Keiichi Koizumi, Makito Oku, Shusaku Hayashi, Akiko Inujima, Naotoshi Shibahara, Luonan Chen, Yoshiko Igarashi, Kazuyuki Tobe, Shigeru Saito, Makoto Kadowaki, Kazuyuki Aihara, "Corrigendum to “Suppression of Dynamical Network Biomarker Signals at the Predisease State (Mibyou) before Metabolic Syndrome in Mice by a Traditional Japanese Medicine (Kampo Formula) Bofutsushosan”", Evidence-Based Complementary and Alternative Medicine, vol. 2021, Article ID 9760307, 1 page, 2021. https://doi.org/10.1155/2021/9760307

Corrigendum to “Suppression of Dynamical Network Biomarker Signals at the Predisease State (Mibyou) before Metabolic Syndrome in Mice by a Traditional Japanese Medicine (Kampo Formula) Bofutsushosan”

Received17 Apr 2021
Accepted17 Apr 2021
Published24 Apr 2021

In the article titled “Suppression of Dynamical Network Biomarker Signals at the Predisease State (Mibyou) before Metabolic Syndrome in Mice by a Traditional Japanese Medicine (Kampo Formula) Bofutsushosan” [1], the authors wish to clarify that the DNB scores of the untreated group shown in blue in Figure 3 were recalculated from data obtained from the Gene Expression Omnibus (GEO) repository, accession number: GSE112653 [2], and were presented for comparison. The authors confirm that this does not affect the results and conclusions of the article.

References

  1. K. Koizumi, M. Oku, S. Hayashi et al., “Suppression of dynamical network biomarker signals at the predisease state (Mibyou) before metabolic syndrome in mice by a traditional Japanese medicine (Kampo formula) bofutsushosan,” Evidence-Based Complementary and Alternative Medicine, vol. 2020, p. 9129134, 2020. View at: Publisher Site | Google Scholar
  2. K. Koizumi, M. Oku, S. Hayashi et al., “Identifying pre-disease signals before metabolic syndrome in mice by dynamical network biomarkers,” Scientific Reports, vol. 9, p. 8767, 2019. View at: Publisher Site | Google Scholar

Copyright © 2021 Keiichi Koizumi et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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