Gastroprotective and antielastase effects of protein inhibitors from <i>Erythrina velutina</i> seeds in an experimental ulcer model
Bibliographic record
Abstract
Trypsin and chymotrypsin inhibitors from Erythrina velutina seeds have been previously isolated by our group. In previous studies using a sepsis model, we demonstrated the antitumor and anti-inflammatory action of these compounds. This study aimed to evaluate the gastroprotective and antielastase effects of protein inhibitors from E. velutina seeds in an experimental stress-induced ulcer model. Two protein isolates from E. velutina seeds, with antitrypsin (PIAT) and antichymotrypsin (PIAQ) activities, were tested. Both protein isolates showed a high affinity and inhibitory effect against human neutrophil elastase, with 84% and 85% inhibition, respectively. Gastric ulcer was induced using ethanol (99%) in 6 groups of animals (female Wistar rats, n = 6). Before ulcer induction, these animals were treated for 5 days with one of the following: (1) PIAT (0.2 mg·kg−1), (2) PIAT (0.4 mg·kg−1), (3) PIAQ (0.035 mg·kg−1), (4) ranitidine hydrochloride (50 mg·kg−1), (5) saline solution (0.9%), or (6) no intervention (sham). Both PIAT and PIAQ protected gastric mucosa, preventing hemorrhagic lesions, edema, and mucus loss. No histologic toxic effects of PIAT or PIAQ were seen in liver and pancreatic cells. Our results show that protein isolates from E. velutina seeds have potential gastroprotective effects, placing these compounds as natural candidates for gastric ulcer prevention.
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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) | 0.001 | 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".