Partial volume rat lung irradiation: Temporal fluctuations of in-field and out-of-field DNA damage and inflammatory cytokines following irradiation
Bibliographic record
Abstract
PURPOSE: The current study investigated the early activation of inflammatory cytokines and macrophages in different regions of the lung following partial volume irradiation. We examined temporal fluctuations in DNA damage, cytokine expression and macrophage activation during 16 weeks post-irradiation. MATERIALS AND METHODS: We irradiated the lower lung of Sprague-Dawley rats with 10 Gy. A micronucleus assay was used to examine DNA damage. Real-time Reverse Transcription-Polymerase Chain Reaction (RT-PCR) was used to analyse the RNA expression of Interleukin-1 alpha (IL-1a), Interleukin-1 beta (IL-1ss), Interleukin-6 (IL-6), Tumour Necrosis Factor alpha (TNF-a) and Transforming Growth Factor beta (TGF-ss) relative to Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH). The activation of macrophages was determined using the antibody ED-1 for immunohistochemical analysis. RESULTS: The expression of DNA damage, the activation of macrophages and the expression of inflammatory cytokines all fluctuated in a cyclic pattern. The initial induction of cytokine expression and the activation of macrophages occurred at very early times (1 h) following irradiation. Waves of cytokine expression and macrophage activation were also seen at later times (up to 16 weeks) following irradiation. DNA damage also occurred in a cyclic pattern though this was less pronounced out-of-field. The levels of cytokines and activated macrophages were elevated to a similar degree both in- and out-of-field, whereas there was a greater micronuclei yield in-field than out-of-field. CONCLUSIONS: An inflammatory response triggered by the partial volume irradiation occurs in the whole rat lung at very early times following irradiation and is maintained in a cyclic pattern to later times when the onset of functional symptoms is expected. We hypothesize that Reactive Oxygen Species (ROS) induced by this response play an important role in the induction of both in-field and out-of-field DNA damage.
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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".