Protracted Exposure to a Sub-background Radiation Environment Negatively Impacts the Anhydrobiotic Recovery of Desiccated Yeast Sentinels
Bibliographic record
Abstract
ABSTRACT: Experiments that examine the impacts of subnatural background radiation exposure provide a unique approach to studying the biological effects of low-dose radiation. These experiments often need to be conducted in deep underground laboratories in order to filter surface-level cosmic radiation. This presents some logistical challenges in experimental design and necessitates a model organism with minimal maintenance. As such, desiccated yeast ( Saccharomyces cerevisiae ) is an ideal model system for these investigations. This study aimed to determine the impact of prolonged sub-background radiation exposure in anhydrobiotic (desiccated) yeast at SNOLAB in Sudbury, Ontario, Canada. Two yeast strains were used: a normal wild type and an isogenic recombinational repair-deficient rad51 knockout strain ( rad51 Δ). Desiccated yeast samples were stored in the normal background surface control laboratory (68.0 nGy h -1 ) and in the sub-background environment within SNOLAB (10.1 nGy h -1 ) for up to 48 wk. Post-rehydration survival, growth rate, and metabolic activity were assessed at multiple time points. Survival in the sub-background environment was significantly reduced by a factor of 1.39 and 2.67 in the wild type and rad51 ∆ strains, respectively. Post-rehydration metabolic activity measured via alamarBlue reduction remained unchanged in the wild type strain but was 26% lower in the sub-background rad51 ∆ strain. These results demonstrate that removing natural background radiation negatively impacts the survival and metabolism of desiccated yeast, highlighting the potential importance of natural radiation exposure in maintaining homeostasis of living organisms.
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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) | 0.000 | 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) | 0.002 | 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 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".