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. 2022 Feb 24;10:25. doi: 10.1186/s40478-022-01326-7

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© The Author(s) 2022

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. 1 — Global transcriptomic differences in the CSF of patients with (n = 40) and without (n = 11) MB. A Mapping rate of each CSF sample. B Principal component analysis of CSF samples using the 48 most differentially expressed genes showing clear separation of normal CSF samples from MB CSF samples. C Unsupervised clustering of samples using the 48 most differentially expressed genes showing clear separation of normal CSF samples from MB CSF samples. D Volcano plot showing significantly up- or downregulated genes in CSF. E Volcano plot for differentially expressed circRNAs between normal vs MB CSF samples. F Top 5 circRNAs expression in different subgroups and qRT-PCR validation of circ-463