Identification of gene-based responses in human blood cells exposed to alpha particle radiation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The threat of a terrorist-precipitated nuclear event places humans at danger for radiological exposures. Isotopes which emit alpha (α)-particle radiation pose the highest risk. Currently, gene expression signatures are being developed for radiation biodosimetry and triage with respect to ionizing photon radiation. This study was designed to determine if similar gene expression profiles are obtained after exposures involving α-particles. METHODS: Peripheral blood mononuclear cells (PBMCs) were used to identify sensitive and robust gene-based biomarkers of α-particle radiation exposure. Cells were isolated from healthy individuals and were irradiated at doses ranging from 0-1.5 Gy. Microarray technology was employed to identify transcripts that were differentially expressed relative to unirradiated cells 24 hours post-exposure. Statistical analysis identified modulated genes at each of the individual doses. RESULTS: Twenty-nine genes were common to all doses with expression levels ranging from 2-10 fold relative to control treatment group. This subset of genes was further assessed in independent complete white blood cell (WBC) populations exposed to either α-particles or X-rays using quantitative real-time PCR. This 29 gene panel was responsive in the α-particle exposed WBCs and was shown to exhibit differential fold-changes compared to X-irradiated cells, though no α-particle specific transcripts were identified. CONCLUSION: Current gene panels for photon radiation may also be applicable for use in α-particle 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 | 0.002 | 0.002 |
| 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 | 0.000 |
| 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