Comparative effects of Rauwolfia vomitoria and chlorpromazine on social behaviour and pain
Bibliographic record
Abstract
BACKGROUND: Rauwolfia vomitoria has been used in Nigeria to manage psychiatric disorders despite orthodox medicine. AIMS: This research was therefore aimed at comparing the effects of R. vomitoria, chlorpromazine and reserpine on social behaviour and pain in mice. MATERIALS AND METHODS: Ninety male CD-1 mice (32 - 38g body weight) were grouped into 3 with 5 subgroups (n=6) each. Mice were given chlorpromazine (0.0, 0.25, 1.0, 2.0, 4.0 mg/kg i.p.), 30 minutes before testing and R. vomitoria (0.0, 0.25, 1.0, 2.0, 4.0 mg/kg, i.p.) and reserpine (0.0, 0.1, 0.4, 0.8, 1.6 mg/kg, i.p) 24 hours before testing. Nesting score assessed social behaviour while the tail flick and hot plate analgesiometers assessed pain. RESULTS: Chlorpromazine dose-dependently decreased nesting score (F(4,25) = 5.5660; p< 0.01), indicating decreased social behaviour (social loss) in the mice. Although R. vomitoria did not affect nesting score, reserpine decreased the nesting score (social loss). In the pain test, chlorpromazine did not alter tail flick latency but decreased hind paw lick latency in the hot plate at 2.0 and 4.0 mg/kg (p< 0.01), indicating increased pain sensitivity at these doses which may indirectly increase social withdrawal and thus aggravating depression. R. vomitoria however, increased tail flick and hind paw lick latencies in the hot plate test (p< 0.05) indicating decreased pain sensitivity. Reserpine, like R. vomitoria, increased latency of hind paw lick in the hot plate. CONCLUSION: R. vomitoria has a high potential as an antipsychotic and may have advantage over chlorpromazine; it is not necessary to isolate active components from this herb.
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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 | 0.001 |
| 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".