The comparative study of acetyl-11-keto-beta-boswellic acid (AKBA) and aspirin in the prevention of intestinal adenomatous polyposis in APCMin/+ mice
Bibliographic record
Abstract
Acetyl-11-keto-beta-BA (AKBA), a component of the gum resin of Boswellia serrata, has been recognized as a promising agent for the prevention of intestinal tumorigenesis. Aspirin, a non-steroidal anti-inflammatory drug (NSAID), has also been considered to have the activity against intestinal tumorigenesis. However, the prevention of colonic cancer is insufficient and no definitive recommendation has been made for clinic use. Herein, we compared the efficacy of AKBA with that of aspirin in an adenomatous polyposis coli intestinal neoplasia consecutive weeks. Mice were sacrificed by anesthetizing. The whole intestine was removed from each mouse. The number, size and histopathology of intestinal adenomatous polyps were examined under microscopy. The adenomatous polyps were removed for further analysis by the assays of western blotting and immunohistochemical staining. AKBA significantly prevented the formation of intestinal adenomatous polyps without toxicity to mice. Statistical analysis indicated that AKBA's activity both in the prevention of small intestinal and colonic polyps was more potently than aspirin. Histopathologic examination revealed that AKBA's effect, that is the reduction of polyp size and degree of dysplasia, was more prominent in larger sized polyps, especially those originating in colon. These effects of AKBA were associated with its role in the induction of apoptosis in carcinomas. The assays of western blotting and immunohistochemistry staining indicated that the efficacy of AKBA might arise from its activity in the modulation of the Wnt/β-catenin pathway and NF-κB/COX-2 pathway in adenomatous polyps. Conclusion, AKBA by oral application prevented intestinal tumorigenesis more potential than aspirin.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".