Does short-term exposure to elevated levels of natural gamma radiation in Ramsar cause oxidative stress?
Bibliographic record
Abstract
BACKGROUND: Ramsar, a city in northern Iran, has areas with some of the highest recorded levels of natural radiation among inhabited areas measured on the earth. AIMS: To determine whether short-term exposure to extremely high levels of natural radiation induce oxidative stress. MATERIALS AND METHODS: In this study, 53 Wistar rats were randomly divided into five groups of 10-12 animals. Animals in the 1(st) group were kept for 7 days in an outdoor area with normal background radiation while the 2(nd) , 3(rd) , 4(th) and 5(th) groups were kept in four different outdoor areas with naturally elevated levels of gamma radiation in Ramsar. A calibrated RDS-110 survey meter, mounted on a tripod approximately 1 m above the ground, was used to measure exposure rate at each location. On days 7 and 9 blood sampling was performed to assess the serum levels of catalase (CAT) and malondialdehyde (MDA). On day 8, all animals were exposed to a lethal dose of 8 Gy gamma radiations emitted by a Theratron Phoenix (Theratronics, Canada) Cobalt-60 (55 cGy/min) at Radiotherapy Department of Razi Hospital in Rasht, Iran. RESULTS: Findings obtained in this study indicate that high levels of natural radiation cannot induce oxidative stress. CAT and MDA levels in almost all groups were not significantly different (P = 0.69 and P = 0.05, respectively). After exposure to the lethal dose, CAT and MDA levels in all groups were not significantly different (P = 0.054 and P = 0.163, respectively). CONCLUSIONS: These findings indicate that short-term exposure to extremely high levels of natural radiation (up to 196 times higher than the normal background) does not induce oxidative stress.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".