Treatment of gastric ulcers and diarrhea with the Amazonian herbal medicine sangre de grado
Bibliographic record
Abstract
Sangre de grado is an Amazonian herbal medicine used to facilitate the healing of gastric ulcers and to treat gastritis, diarrhea, skin lesions, and insect stings. This study was designed to evaluate the gastrointestinal applications. Gastric ulcers were induced in rats by brief serosal exposure of the fundus to acetic acid (80%). Sangre de grado was administered in drinking water at 1:1,000 and 1:10,000 dilutions from the postoperative period to day 7. Guinea pig ileum secretory responses to capsaicin, electrical field stimulation, and the neurokinin-1 (NK-1) agonist [Sar(9),Met(O(2))(11)]substance P were examined in Ussing chambers. Sangre de grado facilitated the healing of experimental gastric ulcer, reducing myeloperoxidase activity, ulcer size, and bacterial content of the ulcer. The expression of proinflammatory genes tumor necrosis factor-alpha, inducible nitric oxide synthase (iNOS), interleukin (IL)-1beta, IL-6, and cyclooxygenase-2 was upregulated by ulcer induction but reduced by sangre de grado treatment, particularly iNOS and IL-6. In Ussing chambers, sangre de grado impaired the secretory response to capsaicin but not to electrical field stimulation or the NK-1 agonist. We conclude that sangre de grado is a potent, cost-effective treatment for gastrointestinal ulcers and distress via antimicrobial, anti-inflammatory, and sensory afferent-dependent actions.
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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".