Characterization of chronic constriction of the saphenous nerve, a model of neuropathic pain in mice showing rapid molecular and electrophysiological changes
Bibliographic record
Abstract
Neuropathic pain is one of the most inextricable problems encountered in clinics, because few facts are known about its etiology. Nerve injury often leads to allodynia and hyperalgesia, which are symptoms of neuropathic pain. The aim of this study was to understand some molecular and electrophysiological mechanisms of neuropathic pain after chronic constriction of the saphenous nerve (CCS) in mice. After surgery, CCS mice displayed significant allodynia and hyperalgesia, which were sensitive to acute systemic injection of morphine (4 mg/kg), gabapentin (50 mg/kg), amitriptyline (10 mg/kg), and the cannabinoid agonist WIN 55,212-2 (5 mg/kg). These behavioral changes were accompanied after surgery by an increase of c-Fos expression and by an overexpression of mu-opioid and cannabinoid CB1 and CB2 receptors in the spinal cord and the dorsal hind paw skin. In combination with the skin-nerve preparation, this model showed a decrease in functional receptive fields downstream to the injury and the apparition of A-fiber ectopic discharges. In conclusion, CCS injury induced behavioral, molecular, and electrophysiological rearrangements that might help us in better understanding the peripheral mechanisms of neuropathic pain. This model takes advantage of the possible use in the future of genetically modified mice and of an exclusively sensory nerve for a comprehensive study of peripheral mechanisms of neuropathic pain.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".