Spinal Cord
A statistically significant positive correlation was observed between the amount of GFAP and Iba1 burden in the spinal cord (Pearson correlation = 0.612, P,0.002) whereas negative correlations were observed between the GFAP burden and the Luxol fast blue burden (Pearson correlation =20.525, P= 0.007), and between the IBa1 burden and the Luxol fast blue burden (Pearson correlation =20.609, P =0.001) suggesting that astrogliosis and microgliosis are associated with the loss of myelin in the spinal cord PubMed:23383175
A statistically significant positive correlation was observed between the amount of GFAP and Iba1 burden in the spinal cord (Pearson correlation = 0.612, P,0.002) whereas negative correlations were observed between the GFAP burden and the Luxol fast blue burden (Pearson correlation =20.525, P= 0.007), and between the IBa1 burden and the Luxol fast blue burden (Pearson correlation =20.609, P =0.001) suggesting that astrogliosis and microgliosis are associated with the loss of myelin in the spinal cord PubMed:23383175
In addition, anatabine markedly decreased the Iba1 immunostaining in the spinal cord of EAE mice showing that anatabine reduces the infiltration of macrophage/ microglia in the spinal cord of EAE mice (Fig. 10) PubMed:23383175
A statistically significant positive correlation was observed between the amount of GFAP and Iba1 burden in the spinal cord (Pearson correlation = 0.612, P,0.002) whereas negative correlations were observed between the GFAP burden and the Luxol fast blue burden (Pearson correlation =20.525, P= 0.007), and between the IBa1 burden and the Luxol fast blue burden (Pearson correlation =20.609, P =0.001) suggesting that astrogliosis and microgliosis are associated with the loss of myelin in the spinal cord PubMed:23383175
Interestingly, anatabine significantly prevented demyelination associated with EAE in the spinal cord (Fig. 12) PubMed:23383175
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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.