Effect of a chamomile extract in protecting against radiation‐induced intestinal mucositis
Bibliographic record
Abstract
Compounds that prevent radiation‐induced mucositis may offer new therapeutic strategies for maintaining intestinal integrity in patients undergoing radiotherapy. A specially formulated chamomile extract was studied with the hope of proving efficacy in this regard. Intestinal mucositis was induced in rats by exposing them to whole body gamma‐irradiation. Rats were treated orally with the extract for 5 days before and 2 days after radiation exposure. One day later, rats were sacrificed. Histological examination of segments of small intestine showed shortening and fusion of villi, activation of mucus secreting glands, inflammatory cell infiltration of lamina propria, and mucosal atrophy. Intestinal homogenates showed an increase in tumor necrosis factor, a pro‐inflammatory cytokine, and myeloperoxidase, an indicator of cellular infiltration, as well as in thiobarbituric acid reactive substances and a reduction in glutathione content. Intestinal injury was further evidenced by an increase in diamine oxidase and a reduction in citrulline levels in the serum. A rise in apoptosis was evidenced by an increase in cytosolic cytochrome c, caspase‐3, and depletion of mitochondrial B‐cell lymphoma‐2/ Bax ratio. Most histological changes and associated derangement in related parameters were largely prevented by the chamomile extract, thus paving the way to a new therapeutic approach towards the management of radiation‐induced intestinal mucositis.
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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 | 0.001 | 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".