Wild foods as drivers of blood ergothioneine and selenoneine concentrations among Inuit living in Nunavik: results from the cross-sectional Qanuilirpitaa? 2017 survey
Bibliographic record
Abstract
BACKGROUND: Wild foods traditionally harvested by Inuit, also called country foods, are potential sources of ergothioneine and selenoneine, 2 closely related antioxidants with potential health benefits. OBJECTIVE: To determine concentrations of these compounds and methylated metabolites in blood samples from 1291 Nunavik residents (Nunavimmiut) aged ≥16 y who participated in the cross-sectional Qanuilirpitaa? 2017 Health Survey and associated dietary habits. METHODS: Blood levels were measured using isotope dilution-liquid chromatography-tandem MS. Associations with dietary profiles or selected dietary habits (documented by a food frequency questionnaire) were investigated using multivariate models. RESULTS: Geometric mean concentrations (95% confidence interval [CI]) of ergothioneine, S-methyl-ergothioneine, selenoneine, and Se-methyl-selenoneine, were 92.5 mg/L (88.4, 96.8), 139 μg/L (133, 146), 355 μg/L (328, 385) and 11.6 μg/L (10.7, 12.5), respectively. Geometric mean ratios (GMR) (95% CI) comparing females with males were 1.27 (1.18, 1.39) and 1.82 (1.57, 2.11) for ergothioneine and selenoneine, respectively. GMR comparing ≥60 y olds to youth aged 16 to 19 y were 1.75 (1.52, 2.02) and 2.78 (2.04, 3.69) for ergothioneine and selenoneine, respectively. Blood selenoneine concentrations of Hudson Strait residents exceeded those of Ungava Bay (2.38 [1.97, 2.86]) and Hudson Bay residents (2.70 [2.22, 3.28]). GMR comparing the high-country food consumption profile with none (or very low) profile were 1.33 (1.10, 1.61) and 2.35 (1.65, 3.36) for ergothioneine and selenoneine, respectively. Country foods positively associated with ergothioneine concentrations included Arctic char (1.07 [1.04, 1.10]) and caribou meat (1.06 [1.03, 1.10]), whereas country foods positively linked to selenoneine concentrations comprised Arctic char (1.07 [1.02, 1.12]) and beluga mattaaq (1.15 [1.08, 1.22]). CONCLUSIONS: Although comparative data are limited, blood selenoneine and ergothioneine concentrations among Nunavimmiut appear substantially higher than in other non-Indigenous populations. Access to country food is important to maintain the dietary intake of these bioactive food components that may be beneficial for the health of Nunavimmiut.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".