Imatinib therapy reduces radiation-induced pulmonary mast cell influx and delays lung disease in the mouse
Bibliographic record
Abstract
PURPOSE: Radiotherapy can induce the inflammatory response of alveolitis and the excessive repair response of fibrosis through incompletely defined mechanisms. In previous murine studies we showed the alveolitis response to thoracic irradiation to correlate with pulmonary mast cell numbers and fibrosis severity to partially depend on the extent of alveolitis. Herein we investigate whether the mast cell blocker imatinib reduces the alveolitis and/or fibrosis response to irradiation. MATERIAL AND METHODS: Mice of three strains received 18 Gy whole thorax irradiation and a subset of these were treated with imatinib (100 mg/kg) daily from the day of irradiation until euthanasia due to the presentation of distress symptoms. RESULTS: Imatinib treatment increased the post irradiation survival time of the mice by an average of 23% and significantly reduced the pulmonary mast cell influx. The alveolitis and fibrosis phenotypes, evident histologically, were not altered by imatinib treatment in mice euthanised upon presentation of respiratory distress. The imatinib treated mice did, however, have less disease than did mice receiving radiation alone, when both groups were assessed at a common time point. CONCLUSIONS: We conclude that imatinib treatment reduces radiation-induced mast cell influx into the lungs and delays the alveolitis or fibrosis response of mice.
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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 | 0.001 |
| 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".