Probiotics for the Management of Oral Mucositis: An Interpretive Review of Current Evidence
Bibliographic record
Abstract
Mucositis is one of the major side effects of anti-cancer therapies. Mucositis may lead to other abnormalities such as depression, infection, and pain, especially in young patients. Although there is no specific treatment for mucositis, several pharmacological and non-pharmacological options are available to prevent its complications. Probiotics have been recently considered as a preferable protocol to lessen the complications of chemotherapy, including mucositis. Probiotics could affect mucositis by anti-inflammatory and anti-bacterial mechanisms as well as augmenting the overall immune system function. These effects may be mediated through anti microbiota activities, regulating cytokine productions, phagocytosis, stimulating IgA releasement, protection of the epithelial shield, and regulation of immune responses. We have reviewed available literature pertaining to the effects of probiotics on oral mucositis in animal and human studies. While animal studies have reported protective effects of probiotics on oral mucositis, the evidence from human studies is not convincing.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".