Systemic Glucocorticoid Therapy Reduces Pain and the Number of Endoneurial Tumor Necrosis Factor-Alpha (TNFα)-Positive Mast Cells in Rats With a Painful Peripheral Neuropathy
Bibliographic record
Abstract
Clinical and experimental evidence suggests that glucocorticoids may be effective in the treatment of neuropathic pain, but their mechanism of action is unknown. We gave triamcinolone (3 mg/kg) to rats with an experimental post-traumatic painful peripheral neuropathy, chronic constriction injury (CCI), five days after nerve injury, when the abnormal pain syndrome is known to be present; and pain sensitivity was measured on postoperative days 7 - 14, a period during which symptoms are known to be at approximately peak severity. Additional CCI rats were treated similarly; and then they were sacrificed five days after the injection for an immunocytochemical analysis of endoneurial tumor necrosis factor-alpha (TNFalpha), macrophages, and mast cells in the sciatic nerve proximal to the site of injury. Vehicle-injected CCI rats demonstrated the expected neuropathic pain symptoms. Triamcinolone-treated CCI rats had a statistically significant reduction in the magnitude of heat-hyperalgesia and mechano-allodynia, but there was no effect on cold-allodynia or mechano-hyperalgesia. On the nerve-injured side of vehicle-injected rats, TNFalpha was present in Schwann cells and mast cells. On the nerve-injured side of triamcinolone-treated rats, there was a significant (71.5%) reduction in the number of TNFalpha-positive mast cells. Our results suggest that glucocorticoid therapy for neuropathic pain may work via the reduced expression of TNFalpha in endoneurial mast cells.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".