New insights regarding tissue Se and Hg interactions on oxidative stress from plasma IsoP and IsoF measures in the Canadian Inuit population
Bibliographic record
Abstract
Despite animal and in vitro studies demonstrating pro-oxidative effects of Hg, previous human work showed no relationship between tissue Hg and plasma levels of F2-isoprostanes (IsoPs), a whole-body oxidative stress marker. We hypothesized that another IsoP species, isofurans (IsoFs), was a more sensitive indicator of Hg-mediated oxidative stress, which can be modified by tissue Se status. A cross-sectional study was carried out involving individuals from a random subset (n = 233) of Inuit adults from a population-based survey (n = 2,595) of 36 Canadian Arctic Inuit communities to assess the relationships of plasma IsoPs to Se and Hg status indicators. F2-IsoPs were inversely correlated with blood Se (r = -0.186, P = 0.005) and toenail Se (r = -0.146, P = 0.044), but not correlated with Hg. IsoFs were inversely correlated with blood Se (r = -0.164, P = 0.014) and positively correlated with Hg (r = 0.228, P < 0.001) and Hg:Se (r = 0.340, P < 0.001). The strength of the correlations remained unchanged after multivariate adjustments. Multivariate analysis showed that F2-IsoPs were not positively associated with Hg but with Hg:Se (β = 0.148, P = 0.021). We conclude that Se and Hg status and their interactions are important factors modulating F2-IsoP and IsoF levels such that the Inuit may be protected from Hg-induced oxidative stress because of their high Se status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".