Cited by 8

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Proteomic changes during experimental de- and remyelination in the corpus callosum

Szilagyi, Gabor T., Nawrocki, Arkadiusz M., Eros, Krisztian, Schmidt, Janos, Fekete, Katalin, Elkjaer, Maria L., Hyrlov, Kirsten H., Larsen, Martin R., Illes, Zsolt, Gallyas, Ferenc·2020·PLOS ONE

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1371/journal.pone.0230249

Cites

3 of 3 references verified0 citation errors · 0 not checkable

Statistics

Figures

Fig 1 Cluster analysis. Mice were treated or not (C) with 0.2% cuprizone in their food for 4 weeks then were sacrificed after termination of the treatment (4wD), and 2 (2dR) or 14 (2wR) days later. Cluster analysis of 3183 unmodified (A and C) and 1703 single- or multi phosphorylated and/or gycosylated proteins (B and D) identified in corpus callosum homogenate of the mice were performed by using the Perseus software platform (http://www.perseus-framework.org). Heat maps (A and B) and pattern of protein concentration changes in the treatment groups (C and D) are presented. The concentrations were normalised to those of C group and were expressed in log2(fold change) values. Heat map scales are z score based, number of the proteins in a given cluster (A and B) as well as cluster ID next to a given cluster pattern (C and D) are indicated.
Fig 1 Cluster analysis. Mice were treated or not (C) with 0.2% cuprizone in their food for 4 weeks then were sacrificed after termination of the treatment (4wD), and 2 (2dR) or 14 (2wR) days later. Cluster analysis of 3183 unmodified (A and C) and 1703 single- or multi phosphorylated and/or gycosylated proteins (B and D) identified in corpus callosum homogenate of the mice were performed by using the Perseus software platform (http://www.perseus-framework.org). Heat maps (A and B) and pattern of protein concentration changes in the treatment groups (C and D) are presented. The concentrations were normalised to those of C group and were expressed in log2(fold change) values. Heat map scales are z score based, number of the proteins in a given cluster (A and B) as well as cluster ID next to a given cluster pattern (C and D) are indicated.CC BY · PubMed Central
Fig 2 Venn diagrams for the proteins significantly altered in the experimental groups. Distribution of unmodified (A) and single- or multi phosphorylated and/or gycosylated proteins (B) among the different experimental groups are presented. Numbers indicate the number of the proteins in Tables 1 and 2.
Fig 2 Venn diagrams for the proteins significantly altered in the experimental groups. Distribution of unmodified (A) and single- or multi phosphorylated and/or gycosylated proteins (B) among the different experimental groups are presented. Numbers indicate the number of the proteins in Tables 1 and 2.CC BY · PubMed Central
Fig 3 Immunohistochemical analysis of phosphorylation during de- and remyelination. We performed immunohistochemistry utilising phospho (p)-Ser, p-Thr and p-Tyr specific primary antibodies on brain sections of the animals (n = 3) from all four treatment groups. Representative sections are presented (A). For quantitative assessment of phosphorylation during de- and remyelination (B), all nuclei and staining artefacts were eliminated from the sections, and staining intensities of corpus callosum were normalised by an expert blind to the experiment to background i.e. left and right retrosplenial area, ventral part, layer 1 (lightly stained area containing few nuclei left and right to the arrow in A) by using Molecular Devices’ MetaXpress® image analyser software. Data are presented mean ± standard deviation % of the background (n = 3). Filled, dark grey, open and light grey bars denote control, 4-week demyelination, 2-day and 2-week remyelination groups, respectively. * significantly different from C; # significantly different from 4W.
Fig 3 Immunohistochemical analysis of phosphorylation during de- and remyelination. We performed immunohistochemistry utilising phospho (p)-Ser, p-Thr and p-Tyr specific primary antibodies on brain sections of the animals (n = 3) from all four treatment groups. Representative sections are presented (A). For quantitative assessment of phosphorylation during de- and remyelination (B), all nuclei and staining artefacts were eliminated from the sections, and staining intensities of corpus callosum were normalised by an expert blind to the experiment to background i.e. left and right retrosplenial area, ventral part, layer 1 (lightly stained area containing few nuclei left and right to the arrow in A) by using Molecular Devices’ MetaXpress® image analyser software. Data are presented mean ± standard deviation % of the background (n = 3). Filled, dark grey, open and light grey bars denote control, 4-week demyelination, 2-day and 2-week remyelination groups, respectively. * significantly different from C; # significantly different from 4W.CC BY · PubMed Central
Fig 4 Venn diagrams for the shortlisted proteins. Those proteins of Tables 1 and 2 that were PANTHER unclassified or belonged to a biological process of smaller than 50% over- or under-representation were deleted from the list. Distribution of the 157 remaining unmodified and single- or multi phosphorylated and/or gycosylated proteins among the different experimental groups (see Fig 1) are presented. Remyelination only proteins are shaded.
Fig 4 Venn diagrams for the shortlisted proteins. Those proteins of Tables 1 and 2 that were PANTHER unclassified or belonged to a biological process of smaller than 50% over- or under-representation were deleted from the list. Distribution of the 157 remaining unmodified and single- or multi phosphorylated and/or gycosylated proteins among the different experimental groups (see Fig 1) are presented. Remyelination only proteins are shaded.CC BY · PubMed Central
Fig 5 IPA regulator network analysis of RO proteins. IPA regulator network analysis was performed on the 2dR and 2wR groups of RO proteins. The resulting network is presented (A). Occurrence of the network orthologues among genes expressed differentially between human multiple sclerosis lesion types vs. NAWM [20] was studied by using the edgeR package (3.8) software [19]. The results are presented as a heat map. Key for molecule shapes and colors as well as relationship labels is published on http://qiagen.force.com/KnowledgeBase/articles/Basic_Technical_Q_A/Legend. Significant changes represented by node coloring based on the fold changes in protein levels.
Fig 5 IPA regulator network analysis of RO proteins. IPA regulator network analysis was performed on the 2dR and 2wR groups of RO proteins. The resulting network is presented (A). Occurrence of the network orthologues among genes expressed differentially between human multiple sclerosis lesion types vs. NAWM [20] was studied by using the edgeR package (3.8) software [19]. The results are presented as a heat map. Key for molecule shapes and colors as well as relationship labels is published on http://qiagen.force.com/KnowledgeBase/articles/Basic_Technical_Q_A/Legend. Significant changes represented by node coloring based on the fold changes in protein levels.CC BY · PubMed Central

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 3 references

Research works printed but not linked: 34

  1. H. Lassmann, 2014, Multiple sclerosis: lessons from molecular neuropathology, Exp Neurol, 262, 2, 10.1016/j.expneurol.2013.12.003 · DOI
  2. C Larochelle, 2016, Secondary Progression in Multiple Sclerosis: Neuronal Exhaustion or Distinct Pathology?, Trends Neurosci, 39, 325, 10.1016/j.tins.2016.02.001 · DOI
  3. M Kipp, 2017, Multiple sclerosis animal models: a clinical and histopathological perspective, Brain Pathol, 27, 123, 10.1111/bpa.12454 · DOI · Paper page
  4. MM Hiremath, 2008, MHC class II exacerbates demyelination in vivo independently of T cells, J Neuroimmunol, 203, 23, 10.1016/j.jneuroim.2008.06.034 · DOI · Paper page
  5. J Hou, 2018, Exploring the Therapeutic Mechanism of Desmodium styracifolium on Oxalate Crystal-Induced Kidney Injuries Using Comprehensive Approaches Based on Proteomics and Network Pharmacology, Front Pharmacol, 9, 620, 10.3389/fphar.2018.00620 · DOI
  6. JJ Liu, 2018, In vivo brain GPCR signaling elucidated by phosphoproteomics, Science, 360
  7. S Doll, 2018, Rapid proteomic analysis for solid tumors reveals LSD1 as a drug target in an end-stage cancer patient, Mol Oncol
  8. Y Li, 2018, Proteomic approaches for novel systemic lupus erythematosus (SLE) drug discovery, Expert Opin Drug Discov, 1
  9. SR Werner, 2010, Proteomic analysis of demyelinated and remyelinating brain tissue following dietary cuprizone administration, J Mol Neurosci, 42, 210, 10.1007/s12031-010-9354-9 · DOI
  10. MA Partridge, 2016, An initial top-down proteomic analysis of the standard cuprizone mouse model of multiple sclerosis, J Chem Biol, 9, 9, 10.1007/s12154-015-0138-0 · DOI
  11. I Gat-Viks, 2015, Proteomics-level analysis of myelin formation and regeneration in a mouse model for Vanishing White Matter disease, J Neurochem, 134, 513, 10.1111/jnc.13142 · DOI
  12. NA Martin, 2018, Experimental Demyelination and Axonal Loss Are Reduced in MicroRNA-146a Deficient Mice, Front Immunol, 9, 490, 10.3389/fimmu.2018.00490 · DOI · Paper page
  13. S Veto, 2010, polymerase: a potential therapy against oligodendrocyte death, Brain, 133, 822, 10.1093/brain/awp337 · DOI · Paper page
  14. K Engholm-Keller, 2016, Improving the Phosphoproteome Coverage for Limited Sample Amounts Using TiO2-SIMAC-HILIC (TiSH) Phosphopeptide Enrichment and Fractionation, Methods Mol Biol, 1355, 161, 10.1007/978-1-4939-3049-4_11 · DOI
  15. MR Larsen, 2005, Highly selective enrichment of phosphorylated peptides from peptide mixtures using titanium dioxide microcolumns, Mol Cell Proteomics, 4, 873, 10.1074/mcp.T500007-MCP200 · DOI
  16. ME Ritchie, 2015, limma powers differential expression analyses for RNA-sequencing and microarray studies, Nucleic Acids Res, 43, e47, 10.1093/nar/gkv007 · DOI · Paper page
  17. ML Elkjaer, 2019, Unique RNA signature of different lesion types in the brain white matter in progressive multiple sclerosis, Acta Neuropathol Commun, 7, 58, 10.1186/s40478-019-0709-3 · DOI
  18. NA Martin, 2018, Orthologous proteins of experimental de- and remyelination are differentially regulated in the CSF proteome of multiple sclerosis subtypes, PLoS One, 13, e0202530, 10.1371/journal.pone.0202530 · DOI · Paper page
  19. V Schultz, 2017, Acutely damaged axons are remyelinated in multiple sclerosis and experimental models of demyelination, Glia, 65, 1350, 10.1002/glia.23167 · DOI
  20. NH Skotte, 2018, Integrative Characterization of the R6/2 Mouse Model of Huntington's Disease Reveals Dysfunctional Astrocyte Metabolism, Cell Rep, 23, 2211, 10.1016/j.celrep.2018.04.052 · DOI
  21. T Ebrahimi, 2018, alpha1-antitrypsin mitigates NLRP3-inflammasome activation in amyloid beta1-42-stimulated murine astrocytes, J Neuroinflammation, 15, 282, 10.1186/s12974-018-1319-x · DOI
  22. JM Hillis, 2016, Cuprizone demyelination induces a unique inflammatory response in the subventricular zone, J Neuroinflammation, 13, 190, 10.1186/s12974-016-0651-2 · DOI
  23. M Kipp, 2009, The cuprizone animal model: new insights into an old story, Acta Neuropathol, 118, 723, 10.1007/s00401-009-0591-3 · DOI · Paper page
  24. P. LoPresti, 2018, Silent Free Fall at Disease Onset: A Perspective on Therapeutics for Progressive Multiple Sclerosis, Front Neurol, 9, 973, 10.3389/fneur.2018.00973 · DOI
  25. MA Partridge, 2015, Proteomics of a conundrum: Thoughts on addressing the aetiology versus progression of multiple sclerosis, Proteomics Clin Appl, 9, 838, 10.1002/prca.201400141 · DOI
  26. JM Boggs, 2006, Effect of phosphorylation of myelin basic protein by MAPK on its interactions with actin and actin binding to a lipid membrane in vitro, Biochemistry, 45, 391, 10.1021/bi0519194 · DOI
  27. M Myllykoski, 2012, Myelin 2',3'-cyclic nucleotide 3'-phosphodiesterase: active-site ligand binding and molecular conformation, PLoS One, 7, e32336, 10.1371/journal.pone.0032336 · DOI
  28. D Brockschnieder, 2006, Ermin, a myelinating oligodendrocyte-specific protein that regulates cell morphology, J Neurosci, 26, 757, 10.1523/JNEUROSCI.4317-05.2006 · DOI
  29. JK Kim, 2003, Multiple sclerosis: an important role for post-translational modifications of myelin basic protein in pathogenesis, Mol Cell Proteomics, 2, 453, 10.1074/mcp.M200050-MCP200 · DOI
  30. MR Wilson, 2017, Clusterin as a therapeutic target, Expert Opin Ther Targets, 21, 201, 10.1080/14728222.2017.1267142 · DOI
  31. MM van Luijn, 2016, Elevated Expression of the Cerebrospinal Fluid Disease Markers Chromogranin A and Clusterin in Astrocytes of Multiple Sclerosis White Matter Lesions, J Neuropathol Exp Neurol, 75, 86, 10.1093/jnen/nlv004 · DOI
  32. MC Farach-Carson, 2014, Border patrol: insights into the unique role of perlecan/heparan sulfate proteoglycan 2 at cell and tissue borders, Matrix Biol, 34, 64, 10.1016/j.matbio.2013.08.004 · DOI · Paper page
  33. AT Reder, 2013, Aberrant Type I Interferon Regulation in Autoimmunity: Opposite Directions in MS and SLE, Shaped by Evolution and Body Ecology, Front Immunol, 4, 281, 10.3389/fimmu.2013.00281 · DOI
  34. O Stenina-Adognravi, 2019, Thrombospondin-4 in tissue remodeling, Matrix Biol, 75–76, 300, 10.1016/j.matbio.2017.11.006 · DOI

Cited by

Sorted by citations

See all 8

Metadata

Authors
Szilagyi, G. T., Nawrocki, A. M., Eros, K., Schmidt, J., Fekete, K., Elkjaer, M. L., Hyrlov, K. H., Larsen, M. R., Illes, Z., & Gallyas, F.
Venue
PLOS ONE
Published
2020-04-09
Volume
15
Issue
4
Pages
e0230249
ISSN
1932-6203
Cited by
8
References
3
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Proteomic changes during experimental de- and remyelination in the corpus callosum. https://app.cochat.ai/papers/10.1371/journal.pone.0230249
The paper
Szilagyi, G. T., Nawrocki, A. M., Eros, K., Schmidt, J., Fekete, K., Elkjaer, M. L., Hyrlov, K. H., Larsen, M. R., Illes, Z., & Gallyas, F. (2020). Proteomic changes during experimental de- and remyelination in the corpus callosum. PLOS ONE. https://doi.org/10.1371/journal.pone.0230249