Regenerative Potential of Aqueous Extract of Neem Azadirachta indica on the Stomach and Ileum Following Ethanol-induced Mucosa Lesion in Adult Wistar Rats
Bibliographic record
Abstract
BACKGROUND: possesses regenerative potential on the stomach and ileum at 500 mg/kg dose given every 12 hours after mucosa lesion was brought by the administration of 1 ml of 50% ethanol for 21 consecutive days in adult Wistar rats. METHODS: Adult male Wistar rats used in the study were divided into 3 groups: group A received oral normal saline and served as control; group B received 1.0 ml of 50% ethanol orally every 12 hours; and group C received neem extract (500 mg/kg) orally 12 hours after ethanol (50%, 1.0 ml) administration to verify its regenerative potential. The experiment lasted for 21 days after which the animals were sacrificed following chloroform inhalation and the stomach and ileum excised and processed for histological and morphometric examinations. RESULTS: Ethanol treated rats showed marked gross mucosal lesions in the stomach and ileum. Ulcerated mucosa with marked apoptotic bodies and destruction of glandular elements were evident in the animals (group B). Neem extract administered 12 hours after the ethanol administration showed regenerative potential against ethanol-induced mucosal damage. This was characterized by mild restoration of the ulcerated mucosa epithelium and reorganization of the cyto-architechtural outline in group C. CONCLUSIONS: Our investigation suggests that neem extract has a regenerative potential and may be adopted in the management of gastrointestinal disorders such as ulcer.
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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".