Evaluation of the antinociceptive and anti-inflammatory effects of essential oil of Nepeta pogonosperma Jamzad et Assadi in rats
Bibliographic record
Abstract
UNLABELLED: BACKGROUND AND THE PURPOSE OF STUDY: Concerning the different effects of essential oils from Nepeta genus on the central nervous system including pain killing effect, this study was designed to evaluate the antinociceptive and anti-inflammatory effects of essential oil of Nepeta pogonosperma Jamzad et Assadi (NP), a recently identified species. METHODS: Air-dried aerial parts of NP were hydrodistillated and GC-MS analysis of obtained essential oil was conducted. Total 24 male Wister rats weighing 225 ± 25 gm were studied. Essential oil of NP was administered intraperitoneally at the doses of 50 mg/kg, 100 mg/kg and 200 mg/kg for the experimental groups. Control rats received equal volume (2 ml/kg) of normal saline. Antinociception was assessed by tail flick test (after 30 minutes) and formalin test (for further 60 minutes). Then the animal was sacrificed and the paw edema was measured using a water plethysmometer. RESULTS: 4aα,7α,7aβ-nepetalactone and 1,8-cineole were found as the main concentrated components of NP essential oil. All the doses of NP showed antinociception. NP 200 mg/kg reduced the pain sensation in tail flick (p <0.01) and formalin test (p <0.001 in both phases). In paw edema test, NP 100 and 200 mg/kg significantly reduced the inflammation (p <0.01 and p <0.05). CONCLUSION: This study reveals that the essential oil of NP may minimize both the acute and chronic forms of nociception and may have potent role against inflammation, but the dose should be maintained precisely to obtain the intended effect.
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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) | 0.000 | 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".