Melanocortin 4 Receptor Mediates Neuropathic Pain Through p38MAPK in Spinal Cord
Bibliographic record
Abstract
BACKGROUND: Neuropathic pain is characterised by spontaneous ongoing or shooting pain and evoked amplified pain responses after noxious or non-noxious stimuli. Neuropathic pain develops as a result of lesions or disease affecting the somatosensory nervous system either in the periphery or centrally. Melanocortin 4 receptor (MC4R) plays an important role in the initiation of neuropathic pain but the underlying mechanisms are still unclear. METHODS: Adult male Wistar rats were given chronic constriction injury (CCI) or sham operations. Part of CCI rats were intrathecally treated with HS014 (MC4R antagonist) or SB203580 (p38MAPK inhibitor). On the third, seventh and fourteenth day, the thermal threshold of operated paws was tested. In addition, the MC4R or phosphorylated p38MAPK (p-p38MAPK) levels of lumbar spinal cord were tested with ELISA (enzyme-linked immunosorbent assay), western blot and immunohistochemistry. RESULTS: Here we demonstrate that (1) both HS014 and SB203580 reduced CCI reduced hyperalgesia (2) p-p38MAPK was increased after CCI with a time course parallel to that of the MC4R change, (3) The p38 activation was prevented by blocking MC4R with an antagonist HS014, but MC4R-IR was not prevented by SB203580. (4) MC4R and p-p38MAPK were located in the same cells. CONCLUSION: The mechanisms of neuropathic pain mediated by MC4R is related to the inhibition of p38MAPK activation. P38MAPK may be a downstream of MC4R.
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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) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".