The Interaction Between Gabapentin and Amitriptyline in the Rat Formalin Test After Systemic Administration
Bibliographic record
Abstract
UNLABELLED: We examined the effects of systemically administered gabapentin on flinching and biting/licking behaviors produced by 2.5% formalin in the rat, compared these with those of amitriptyline, and determined the effects of combinations of gabapentin with amitriptyline. Gabapentin produced a dose-related inhibition of Phase 2, but not Phase 1, flinching and biting/licking behaviors. In contrast, amitriptyline produced an increase in Phase 2 flinching behaviors while simultaneously decreasing biting/licking behaviors. Fifty percent effective dose (ED50) values against biting/licking behaviors were 22.9 +/- 1.3 mg/kg and 8.5 +/- 1.3 mg/kg for gabapentin and amitriptyline, respectively. Combinations of increasing fractional increments of ED50 doses of gabapentin and amitriptyline produced an additive effect against biting/licking behaviors, as revealed by isobolographic analysis. These increments had no effect on flinching behaviors except at the ED25 + ED25 doses, at which flinching was increased, again revealing additivity between the two drugs. Flinching behaviors in rats do not reflect the analgesic properties of systemically administered amitriptyline observed in humans and may not be useful for predicting an effect of combinations of drugs with amitriptyline. Biting/licking behaviors do reflect analgesic properties for both drugs and may be more useful in this regard. IMPLICATIONS: By use of the rat formalin test, a model of persistent pain, we examined the effect of a combination of amitriptyline and gabapentin, which are used to treat chronic pain in humans. The drug combination produced additive analgesia against one outcome, but another outcome was more ambiguous.
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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".