Single-Dose Radiation-Induced Oral Mucositis Mouse Model
Bibliographic record
Abstract
The generation of a self-resolved radiation-induced oral mucositis (RIOM) mouse model using the highest possibly tolerable single ionizing radiation (RT) dose was needed in order to study RIOM management solutions. We used 10-week-old male BALB/c mice with average weight of 23 g for model production. Mice were treated with an orthovoltage X-ray irradiator to induce the RIOM ulceration at the intermolar eminence of the animal tongue. General anesthesia was injected intraperitoneally for proper animal immobilization during the procedure. Ten days after irradiation, a single RT dose of 10, 15, 18, 20, and 25 Gy generated a RIOM ulcer at the intermolar eminence (posterior upper tongue surface) with mean ulcer floor (posterior epithelium) heights of 190, 150, 25, 10, and 10 μm, respectively, compared to 200 μm in non-irradiated animals. The mean RIOM ulcer size % of the total epithelialized upper surface of the animal tongue was RT dose dependent. At day 10, the ulcer size % was 2, 5, 27, and 31% for 15, 18, 20, and 25 Gy RT, respectively. The mean relative surface area of the total epithelialized upper surface of the tongue was RT dose dependent, since it was significantly decreased to 97, 95, 88, and 38% with 15, 18, 20, and 25 Gy doses, respectively, at day 10 after RT. Subcutaneous injection of 1 mL of 0.9% saline/6 h for 24 h yielded a 100% survival only with 18 Gy self-resolved RIOM, which had 5.6 ± 0.3 days ulcer duration. In conclusion, we have generated a 100% survival self-resolved single-dose RIOM male mouse model with long enough duration for application in RIOM management research. Oral mucositis ulceration was radiation dose dependent. Sufficient hydration of animals after radiation exposure significantly improved their survival.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".