A Selenocysteine Derivative Therapy Affects Radiation-Induced Pneumonitis in the Mouse
Bibliographic record
Abstract
The mechanism leading to the radiation-induced lung response of pneumonitis is largely unknown. Here we investigated whether treatment with 3,3'-diselenodipropionic acid (DSePA), which reduces radiation-induced oxidative stress in acute response models, decreases the lung response to irradiation. Mice of the C3H/HeJ (alveolitis/pneumonitis-responding) strain received 18 Gy whole-thorax irradiation, and a subset of these mice was treated with DSePA (2 mg/kg) three times per week, beginning at 2 hours after radiation treatment, and continuing in the postirradiation period until death because of respiratory distress symptoms. DSePA treatment increased the postirradiation survival time of mice by an average of 32 days (P = 0.0002). Radiation-treated and DSePA-treated mice presented lower levels of lipid peroxidation and augmented glutathione peroxidase in the lungs, compared with those levels measured in mice receiving radiation only, when mice receiving radiation only were killed because of distress symptoms, whereas catalase and superoxide dismutase levels did not show consistent differences among treatment groups. DSePA treatment decreased pneumonitis and the numbers of mast cells, neutrophils, and lymphocytes in the lungs and bronchoalveolar lavage, respectively, of irradiated mice relative to mice exposed to radiation alone. DSePA treatment also decreased the radiation-induced increase in granulocyte colony-stimulating factor levels in the bronchoalveolar lavage and lung-tissue expression of intercellular adhesion molecule-1 and E-selectin, while increasing the expression of glutathione peroxidase-4. We conclude that DSePA treatment reduces radiation-induced pneumonitis in mice by delaying oxidative damage and the inflammatory cell influx.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".