<sup>56</sup> Fe ion exposure increases the incidence of lung and brain tumors at a similar rate in male and female mice
Bibliographic record
Abstract
Abstract The main deterrent to long-term space travel is the risk of Radiation Exposure Induced Death (REID). The National Aeronautics and Space Administration (NASA) has adopted Permissible Exposure Levels (PELs) to limit the probability of REID to 3% for the risk of death due to radiation-induced carcinogenesis. The most significant contributor to current REID estimates for astronauts is the risk of lung cancer. Recently updated lung cancer estimates from Japan’s atomic bomb survivors showed that the excess relative risk of lung cancer by age 70 is roughly four-fold higher in females compared to males. However, whether sex differences may impact the risk of lung cancer due to exposure to high charge and energy (HZE) radiation is not well studied. Thus, to evaluate the impact of sex differences on the risk of solid cancer development post-HZE radiation exposure, we irradiated Rb fl/fl ; Trp53 fl/+ male and female mice infected with Adeno-Cre with various doses of 320 kVp X-rays or 600 MeV/n 56 Fe ions and monitored them for any radiation-induced malignancies. We observed that lung adenomas/carcinomas and esthesioneuroblastomas (ENBs) were the most common primary malignancies in X-ray and 56 Fe ion-exposed mice, respectively. In addition, 1 Gy 56 Fe ion exposure compared to X-rays led to a significantly higher incidence of lung adenomas/carcinomas (p=0.02) and ENBs (p<0.0001). However, we did not find a significantly higher incidence of any solid malignancies in female mice as compared to male mice, regardless of radiation quality. Furthermore, gene expression analysis of ENBs suggested a distinct gene expression pattern with similar hallmark pathways altered, such as MYC targets and MTORC1 signaling, in X-ray and 56 Fe ion-induced ENBs. Thus, our data revealed that 56 Fe ion exposure significantly accelerated the development of lung adenomas/carcinomas and ENBs compared to X-rays, but the rate of solid malignancies was similar between male and female mice, regardless of radiation quality.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".