Metabolic Dysregulation after Neutron Exposures Expected from an Improvised Nuclear Device
Bibliographic record
Abstract
The increased threat of terrorism across the globe has raised fears that certain groups will acquire and use radioactive materials to inflict maximum damage. In the event that an improvised nuclear device (IND) is detonated, a potentially large population of victims will require assessment for radiation exposure. While photons will contribute to a major portion of the dose, neutrons may be responsible for the severity of the biologic effects and cellular responses. We investigated differences in response between these two radiation types by using metabolomics and lipidomics to identify biomarkers in urine and blood of wild-type C57BL/6 male mice. Identification of metabolites was based on a 1 Gy dose of radiation. Compared to X rays, a neutron spectrum similar to that encountered in Hiroshima at 1-1.5 km from the epicenter induced a severe metabolic dysregulation, with perturbations in amino acid metabolism and fatty acid β-oxidation being the predominant ones. Urinary metabolites were able to discriminate between neutron and X rays on day 1 as well as day 7 postirradiation, while serum markers showed such discrimination only on day 1. Free fatty acids from omega-6 and omega-3 pathways were also decreased with 1 Gy of neutrons, implicating cell membrane dysfunction and impaired phospholipid metabolism, which should otherwise lead to release of those molecules in circulation. While a precise relative biological effectiveness value could not be calculated from this study, the results are consistent with other published studies showing higher levels of damage from neutrons, demonstrated here by increased metabolic dysregulation. Metabolomics can therefore aid in identifying global perturbations in blood and urine, and effectively distinguishing between neutron and photon exposures.
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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 | 0.000 | 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 | 0.001 | 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 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".