Gabapentin reverses central pain sensitization following a collagenase-induced intrathalamic hemorrhage in rats
Bibliographic record
Abstract
Aude Castel, Pascal VachonFaculty of Veterinary Medicine, Department of Veterinary Biomedicine, University of Montreal, Saint-Hyacinthe, QC, CanadaPurpose: The treatment of central neuropathic pain remains amongst the biggest challenges for pain specialists. The main objective of this study was to assess gabapentin (GBP), amitriptyline (AMI), and carbamazepine (CARBA) for the treatment of a rodent central neuropathic pain model.Methods: Male Sprague Dawley rats were trained on the rotarod, Hargreaves, Von Frey and acetone behavioral tests, and baseline values were obtained prior to surgery. A stereotaxic injection of either a collagenase solution or saline was made in the right ventral posterolateral thalamic nucleus. The rats were tested on days 2, 4, 8, and 11 postsurgery. They were retested at regular intervals from day 15 to day 25 postsurgery, after oral administration of either the vehicle (n=7 and n=8 rats with intracerebral injections of collagenase and saline, respectively) or the different drugs (GBP [60 mg/kg], AMI [10 mg/kg], CARBA [100 mg/kg]; n=8 rats/drug).Results: A significant decrease in the mechanical thresholds and no change in heat threshold were observed in both hind limbs in the collagenase group, as we had previously shown elsewhere. Reversal of the mechanical hypersensitivity was achieved only with GBP (P<0.05). AMI and CARBA, at the dosages used, failed to show any effect on mechanical thresholds. Transient cold allodynia was observed in some collagenase-injected rats but failed to be statistically significant.Conclusion: Intrathalamic hemorrhaging in the ventrolateral thalamic nucleus induced a bilateral mechanical allodynia, which was reversed by GBP but not AMI or CARBA.Keywords: central pain, thalamus, amitriptyline, carbamazepine
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".