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Beyond Neurons: Evidence That Immune and Glial Cells Contribute to Pathological Pain States
Abstract
Chronic pain can occur after peripheral nerve injury, infection, or inflammation. Under such neuropathic pain conditions, sensory processing in the affected body region becomes grossly abnormal. Despite decades of research, currently available drugs largely fail to control such pain. This review explores the possibility that the reason for this failure lies in the fact that such drugs were designed to target neurons rather than immune or glial cells. It describes how immune cells are a natural and inextricable part of skin, peripheral nerves, dorsal root ganglia, and spinal cord. It then examines how immune and glial activation may participate in the etiology and symptomatology of diverse pathological pain states in both humans and laboratory animals. Of the variety of substances released by activated immune and glial cells, proinflammatory cytokines (tumor necrosis factor, interleukin-1, interleukin-6) appear to be of special importance in the creation of peripheral nerve and neuronal hyperexcitability. Although this review focuses on immune modulation of pain, the implications are pervasive. Indeed, all nerves and neurons regardless of modality or function are likely affected by immune and glial activation in the ways described for pain.
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Metadata
- Authors
- Watkins, L. R., & Maier, S. F.
- Venue
- Physiological Reviews
- Publisher
- American Physiological Society
- Published
- 2002-01-10
- Volume
- 82
- Issue
- 4
- Pages
- 981-1011
- ISSN
- 0031-9333 (ISSN-L)
- 1522-1210
- OpenAlex
- W2160779124
- Cited by
- 733
- References
- 279
- FWCI
- 2.90
- Type
- journal article
- Language
- en
- Open access
- closed
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.
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.