Analgesic, anti-inflammatory and non-ulcerogenic properties of Annickia chlorantha aqueous stem bark extract.
Bibliographic record
Abstract
Annickia chlorantha is used in Cameroon to treat stomach problemsand many other diseases. The purpose of this study was to evaluate analgesic,anti-inflammatory and non-ulcerogenic properties of aqueous stem bark extract of Annickia chlorantha (ASBEAC). These properties were tested on in vivo induced pain models by intraperitoneal injection of acetic acid and paw injection of formaldehyde:25 rats were divided into 5 batches of 5 animals: negative control received distilled water (5 mL/kg), positive control received indomethacin (50 mg/kg) and three test groups received ASBEAC (125, 250 and 500 mg/kg). Anti-inflammatory activity was assessed by in vitro method using membrane stabilization at different extract concentrations (25-1600 ug/mL).For non-ulcerogenic test, 20 rats were divided into 4 groups of 5 animals: negative control received distilled water (5 mL/kg), two test groups receivedASBEAC (250 and 500 mg/kg), and positive control received indomethacin (50 mg/kg).The results show that, ASBEAC significantly reduced (p< 0.001), with dose-dependent manner, the number of abdominal contortions with a maximum inhibition percentage (76.47%) at the dose of 500 mg/kg. Significant inhibition of pain(p<0.001), in a dose-dependent mode, for the pain test induced by paw injection of formaldehyde were also noted. With a maximum inhibition percentage of 40.69% and 30.35%, respectively for phases 1 and 2. For anti-inflammatory test,ASBEAC (200-1600 ug/mL) significantly (p <0.001) protected heat-induced hemolysis of erythrocytes.The non ulcerogenic test show that ASBEAC at all doses did not cause ulcer, but significantly increased and in a dose-dependent manner, themucus secretion. This study indicates that ASBEAC has analgesic, anti-inflammatory and non-ulcerogenic properties.
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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) | 0.001 | 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".