Wound healing effect of methanolic leaf extract of Napoleona vogelii (Family: Lecythidaceae) in rats
Bibliographic record
Abstract
OBJECTIVE: To investigate the wound healing property of Napoleona vogelii leaf extract in folkloric medicine. METHODS: Both sexes of adult albino rats (n=25) were used in this study and another group (n=30) were subjected to acute toxicity test (LD50) of the plant extract. For the LD50, three randomized groups of 5 rats were first treated with 10, 100, 1 000 mg/kg body weight (bw), orally. This was followed by a second treatment of 1500, 3000, and 5 000 mg/kg bw of the leaf extract with continual monitoring of the animals for mortality or non-mortality. Incision wounds (1.5 cm) were created on the skin of five groups of 5 rats using surgical blade under anesthesia. The first group was topically treated with petroleum jelly alone, group 2 was topically applied 400 mg/mL w/v of the reference drug, Neobacin, while group 3-5 were topically treated with 5-50 mg/mL w/v of the plant extract, respectively. RESULTS: The percentage yield of the extract was 49.80% w/w dry matter. The phytochemical analysis revealed several bioactive constituents including glycosides, tannins, alkaloids, perpenoids, saponins, steroids, proteins, and carbohydrates. The LD50 was beyond our experimental limit and was not determined. Increased concentrations (5, 20, and 50 mg/mL w/v) of the extract had significant (ANOVA, P<0.05) healing effect on the incision wounds giving rise to 125%-140% while treatment with Neobacin resulted in 150% healing effect on the third treatment regimen compared to the control (100%). CONCLUSIONS: These data indicate that Napoleona vogelii leaf extract contains potent bioactive compounds containing wound healing activity, substantiating its use as a wound healer in folkloric medicine.
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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) | 0.000 | 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".