The Th1/Th17 balance dictates the fibrosis response in murine radiation-induced lung disease
Bibliographic record
Abstract
Radiotherapy can result in lung diseases pneumonitis or fibrosis dependent on patient susceptibility. Herein we used inbred and genetically altered mice to investigate whether the tissue adaptive immune response to radiation injury influences the development of radiation-induced lung disease. Six inbred mouse strains were exposed to 18 Gy whole thorax irradiation and upon respiratory distress strains prone to pneumonitis with fibrosis presented an increased pulmonary frequency of Thelper (Th)17 cells which was not evident in strains prone solely to pneumonitis. The contribution of Th17 cells to fibrosis development was supported as the known enhanced fibrosis of toll-like receptor 2&4 deficient mice, compared to C57BL/6J mice, occurred with earlier onset neutrophilia, and with increased levels of pulmonary Th17, but not Th1, cells following irradiation. Irradiated Il17-/- mice lacked Th17 cells, and were spared both fibrosis and pneumonitis, as they survived to the end of the experiment with a significantly increased pulmonary Th1 cell frequency, only. Interferon-γ-/- mice, deficient in Th1 cells, developed a significantly enhanced fibrosis response compared to that of C57BL/6J mice. The tissue adaptive immune response influences the pulmonary disease response to radiotherapy, as an increased Th17 cell frequency enhanced and a Th1 response spared, fibrosis in 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".