Gene expression signatures of radiation exposure in peripheral white blood cells of smokers and non-smokers
Why this work is in the frame
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Bibliographic record
Abstract
PURPOSE: The issue of potential confounding factors is critical to the development of any approach to radiation biodosimetry, and has not been fully addressed for gene expression-based approaches. MATERIALS AND METHODS: As a step in this direction, we have investigated the effect of smoking on the global radiation gene expression response in ex vivo-irradiated peripheral blood cells using microarray analysis. We also evaluated the ability of gene expression signatures to predict the radiation exposure level of ex vivo-exposed samples from smokers and non-smokers of both genders. RESULTS: We identified eight genes with a radiation response that was significantly affected by smoking status, and confirmed an effect of smoking on the radiation response of the four and a half LIM domains 2 (FHL2) gene using quantitative real-time polymerase chain reaction. The performance of our previously defined 74-gene signature in predicting the radiation dose to samples in this study was unaffected by differences in gender or smoking status, however, giving 98% correct prediction of dose category. This is the same accuracy as that found in the original study from which the signature was derived, using different donors. CONCLUSION: The results support the development of peripheral blood gene expression as a viable strategy for radiation biodosimetry.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it