Antidepressant, Anxiolytic and Antinociceptive Activities of Constituents from Rosmarinus Officinalis
Bibliographic record
Abstract
PURPOSE: Rosmarinus officinalis, traditionally known as rosemary, has been widely used in traditional medicines and has long been known as the herb of remembrance. However, few studies have investigated the effects of non-volatile components of rosemary on central nervous system function. METHODS: Fractionation of R. officinalis led to the isolation of salvigenin, rosmanol and cirsimaritin, which were investigated in mouse models of acute toxicity, antinociception (tail immersion and hot plate tests), depression (tail suspension and forced swim tests) and anxiety (elevated plus maze and light/dark box paradigms). RESULTS: Rosmanol, cirsimaritin and salvigenin were not found to exhibit any signs of acute toxicity (50-200 mg/kg), but elicited antinociceptive, antidepressant and anxiolytic activities. CONCLUSION: Rosmanol, cirsimaritin and salvigenin, all previously shown to have biphasic modulation of GABAA receptors, demonstrated CNS activity in mouse models of antinociception, antidepressant and anxiolysis. The anxiolytic activity of all three compounds was not ameliorated by flumazenil, but was inhibited by pentylenetetrazol, suggesting a mode of action via GABAA receptors at a site other than the high affinity benzodiazepine binding site. This article is open to POST-PUBLICATION REVIEW. Registered readers (see "For Readers") may comment by clicking on ABSTRACT on the issue's contents page.
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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 | 0.000 | 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 | 0.000 |
| 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".