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The Multifaceted Profile of Activated Microglia
Abstract
Although relatively neglected previously, research efforts in the past decade or so have identified a pivotal role for glial cells in regulating neuronal function. Particular emphasis has been placed on increasing our understanding of the function of microglia because a change from the ramified "resting" state of these cells has been associated with the pathogenesis of several neurodegenerative diseases, notably Alzheimer's disease. However, it is not clear whether activation of microglia and the associated inflammatory changes play a part in triggering disease processes or whether cell activation is a response to the early changes associated with the disease. In either case, the possibility exists that modulation of microglial activation may be beneficial in some circumstances, underlying the need to pursue research in this area. The original morphological categorization of microglia by Del Rio Hortega into ameboid, ramified, and intermediate forms, must now be elaborated to encompass a functional description. The evidence which has been generated recently suggests that microglia are probably never in a "resting" state and that several intermediate transitional states, based on function and morphology, probably exist. A more complete understanding of these states and the triggers which lead to a change from one to another state, and the factors which modulate the molecular switch that determines the persistence of the "activated" state remain to be identified.
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Age-related increases in expression of pro-inflammatory cytokines including Il-1β, Il-6, and Tnf-α were attenuated in TAC-treated hippocampus relative to vehicle-treated controls.
“Consistent with a crucial role for activated microglia as the primary source of pro-inflammatory cytokines in the brain,39 the age-related increases in expression of pro-inflammatory cytokines including Il-1β, Il-6, and Tnf-α were also attenuated in TAC-treated hippocampus relative to vehicle-treated controls (Figure 4G).”
From TERT activation targets DNA methylation and multiple aging hallmarks (2024) · cites this paper as [39]
Microglia exhibit a non-activated phenotype with long processes and branches, determined by low expression levels of CD45.
“They exhibit a non-activated phenotype with long processes and branches, which is determined by low expression levels of CD45 and MHC class II [44, 45].”
From CX3CL1/CX3CR1 axis attenuates early brain injury via promoting the delivery of exosomal microRNA-124 from neuron to microglia after subarachnoid hemorrhage (2020) · cites this paper as [44]
Microglia exhibit a non-activated phenotype with long processes and branches, determined by low expression levels of MHC class II.
“They exhibit a non-activated phenotype with long processes and branches, which is determined by low expression levels of CD45 and MHC class II [44, 45].”
From CX3CL1/CX3CR1 axis attenuates early brain injury via promoting the delivery of exosomal microRNA-124 from neuron to microglia after subarachnoid hemorrhage (2020) · cites this paper as [44]
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“M1 microglia are generally considered pro-inflammatory whereas, M2 microglia are generally anti-inflammatory [29–34].”
TERT activation targets DNA methylation and multiple aging hallmarks
Shim, H. S., Iaconelli, J., Shang, X., Li, J., Lan, Z. D., Jiang, S., Nutsch, K., Beyer, B. A., Lairson, L. L., Boutin, A. T., et al. (2024) · Cell · doi:10.1016/j.cell.2024.05.048 · Cited by 104
Haber, M., Abdel Baki, S. G., Grin'kina, N. M., Irizarry, R., Ershova, A., Orsi, S., Grill, R. J., Dash, P., & Bergold, P. J. (2013) · Experimental Neurology · doi:10.1016/j.expneurol.2013.09.002 · Cited by 95
Chen, X., Jiang, M., Li, H., Wang, Y., Shen, H., Li, X., Zhang, Y., Wu, J., Yu, Z., & Chen, G. (2020) · Journal of Neuroinflammation · doi:10.1186/s12974-020-01882-6 · Cited by 85
Bone marrow-derived macrophages from aged rats are more responsive to inflammatory stimuli
Barrett, J. P., Costello, D. A., O’Sullivan, J., Cowley, T. R., & Lynch, M. A. (2015) · Journal of Neuroinflammation · doi:10.1186/s12974-015-0287-7 · Cited by 76
Self-citationWang, J.-W., Chen, S.-D., Zhang, X.-L., & Jonas, J. B. (2016) · Journal of Glaucoma · doi:10.1097/ijg.0000000000000200 · Cited by 69
Hua, K., Schindler, M. K., McQuail, J. A., Forbes, M. E., & Riddle, D. R. (2012) · PLoS ONE · doi:10.1371/journal.pone.0052728 · Cited by 60
The Role of the Classical Complement Cascade in Synapse Loss During Development and Glaucoma
Rosen, A. M., & Stevens, B. (2010) · Advances in Experimental Medicine and Biology · doi:10.1007/978-1-4419-5635-4_6 · Cited by 60
Lakosa, A., Rahimian, A., Tomasi, F., Marti, F., Reynolds, L. M., Tochon, L., David, V., Danckaert, A., Canonne, C., Tahraoui, S., et al. (2023) · Neuropsychopharmacology · doi:10.1038/s41386-023-01563-x · Cited by 10
Metadata
- Authors
- Lynch, M. A.
- Venue
- Molecular Neurobiology
- Published
- 2009-07-23
- Volume
- 40
- Issue
- 2
- Pages
- 139-156
- ISSN
- 0893-7648
- 1559-1182
- Cited by
- 268
- References
- 32
- Language
- en
- Licence
- www.springer.com/tdm (tdm)
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 ›
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