Gene Expression Responses in Lymphoblastoid Cells after Radiation Exposure
Bibliographic record
Abstract
Individual differences in response to radiation are well known, but the molecular basis for these differences is not well understood, and molecular indicators that are useful in assessing individual variation are lacking. Cells from patients developing unexpected radiation responses have occasionally been analyzed for rare genetic anomalies (such as alleles of the ATM gene), but few data exist on the long-term effects of genetic variation on radiation response. We hypothesize that much of the variation in the response to radiation is due to differences in the genes that respond to radiation exposure, and that changes in gene expression may serve as surrogate markers of individual response. As a first step in developing a selection of suitable markers of gene expression, we used cDNA microarrays to identify genes that were altered in expression in lymphoblastoid cells 4 h after exposure to 1 Gy X rays. We found changes in gene expression ranging from a 10-fold repression to a 12-fold induction. Some of the responsive genes have been noted previously in other cell types, whereas others are reported for the first time. Using these data, we are beginning to characterize the range of structural, temporal and functional variations in the responsive genes. The results of this work will assist in developing response markers both for prescreening for sensitive individuals and for risk assessment.
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How this classification was reachedexpand
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.001 | 0.001 |
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 teacher head, 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".