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  3. path(MESH:"Multiple Sclerosis, Relapsing-Remitting")

path(MESH:"Multiple Sclerosis, Relapsing-Remitting")

Equivalencies: 0 | Classes: 0 | Children: 0 | Explore

Entity

Name
Multiple Sclerosis, Relapsing-Remitting
Namespace
MeSH
Namespace Version
20181007
Namespace URL
https://raw.githubusercontent.com/pharmacome/terminology/01c9daa61012b37dd0a1bc962521ba51a15b38f1/external/mesh-names.belns

Appears in Networks 1

Oxidative stress in health and disease: The therapeutic potential of Nrf2 activation v1.0.0

In-Edges 2

a(PUBCHEM:400769) negativeCorrelation path(MESH:"Multiple Sclerosis, Relapsing-Remitting") View Subject | View Object

Patients with relapsing-remitting multiple sclerosis treated with BG-12 for 24 weeks showed significantly fewer new gadolinium-enhancing lesions, with significantly reduced probability of their evolution to T1-hypointense lesions than patients treated with placebo (Macmanus et al., 2011) PubMed:22020111

Appears in Networks:

act(p(HGNC:NFE2L2)) negativeCorrelation path(MESH:"Multiple Sclerosis, Relapsing-Remitting") View Subject | View Object

These studies suggest that Nrf2 activation may represent a promising new therapeutic approach for multiple sclerosis. PubMed:22020111

Appears in Networks:

Out-Edges 2

path(MESH:"Multiple Sclerosis, Relapsing-Remitting") negativeCorrelation a(PUBCHEM:400769) View Subject | View Object

Patients with relapsing-remitting multiple sclerosis treated with BG-12 for 24 weeks showed significantly fewer new gadolinium-enhancing lesions, with significantly reduced probability of their evolution to T1-hypointense lesions than patients treated with placebo (Macmanus et al., 2011) PubMed:22020111

Appears in Networks:

path(MESH:"Multiple Sclerosis, Relapsing-Remitting") negativeCorrelation act(p(HGNC:NFE2L2)) View Subject | View Object

These studies suggest that Nrf2 activation may represent a promising new therapeutic approach for multiple sclerosis. PubMed:22020111

Appears in Networks:

About

BEL Commons is developed and maintained in an academic capacity by Charles Tapley Hoyt and Daniel Domingo-Fernández at the Fraunhofer SCAI Department of Bioinformatics with support from the IMI project, AETIONOMY. It is built on top of PyBEL, an open source project. Please feel free to contact us here to give us feedback or report any issues. Also, see our Publishing Notes and Data Protection information.

If you find BEL Commons useful in your work, please consider citing: Hoyt, C. T., Domingo-Fernández, D., & Hofmann-Apitius, M. (2018). BEL Commons: an environment for exploration and analysis of networks encoded in Biological Expression Language. Database, 2018(3), 1–11.