Neuropathic pain behaviours in a chronic-relapsing model of experimental autoimmune encephalomyelitis (EAE)
Bibliographic record
Abstract
Multiple sclerosis (MS) is an inflammatory demyelinating disease of the central nervous system (CNS). While the primary symptoms of MS are losses of sensory and motor functions, it is now recognized that chronic pain is also a major concern affecting between 50% and 80% of MS patients. To date, however, few studies have examined the underlying mechanisms of chronic pain in MS or in the animal model, experimental autoimmune encephalomyelitis (EAE), which shares many features of MS pathology. We, therefore, set out to characterize the changes in pain sensitivity that arises in a chronic-relapsing model of EAE. We show here that female C57BL/6 mice immunized with myelin oligodendrocyte glycoprotein (MOG(35-55)) develop a robust allodynia to both cold and tactile stimuli. Allodynia emerges early in the disease process, often before any signs of neurological deficit and is independent of the overall symptom severity in these mice. "Classical" cellular substrates for neuropathic pain and allodynia such as altered expression of sensory neuropeptides in the dorsal horn of the spinal do not appear to underlie these changes in sensory function. There is, however, a significant influx of CD3+ T cells and increased astrocyte and microglia/macrophage reactivity in the superficial dorsal horn of mice with MOG(35-55) EAE. This suggests that inflammation and reactive gliosis may be key mediators of allodynia in MOG(35-55) EAE similar to peripheral nerve and spinal cord injury models. Taken together, our results show that the MOG(35-55) EAE model is a useful tool to study neuropathic pain in MS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".