Indigenous Subarctic Food Systems in Transition: Amino Acid Composition (Including Tryptophan) in Wild-Harvested and Processed Meats
Bibliographic record
Abstract
Indigenous people of northern Canada traditionally lived a nomadic lifestyle subsisting on wild game and fish for thousands of years. With colonization came an increasing dependence on imported processed foods. This dietary change has often been reported to be one of the factors leading to Indigenous health and wellbeing disparities worldwide. We determined the amino acid (AA) profile including tryptophan (Trp) of wild meats (game and fish) and processed meats found in the traditional and modern diets of Indigenous subarctic communities in Canada. Trp is a limited essential AA necessary for synthesis of serotonin (5-HT), an important neurotransmitter and homeostatic regulator. The dietary ratio of Trp relative to other large neutral AAs (LNAA) can alter Trp transport and 5-HT synthesis in the brain. We determined AA composition of wild meats and processed meats using standardized NaOH and HCl hydrolysis for Trp and other AAs, respectively, followed by ultraperformance liquid chromatography. A Principal Components Analysis revealed that overall AA composition is significantly different between wild and processed meats. (M)ANOVA showed significantly higher protein in wild meats (wet weight, ww). Trp was significantly lower in processed meat samples (n=15; 0.18g/100g ± 0.02 ww) compared to wild meat samples (n=25; 0.24g/100g ± 0.06 ww). The proportion of Trp:LNAA and Trp in sample protein were not significantly different between wild (1:21-1:27, 0.92-1.27 g/100g protein) and processed (1:20-1:24, 1.03-1.27 g/100g protein) meats. Within wild meats, AA composition is significantly different between fish and waterfowl, fish and moose, and moose and goose. (M)ANOVA results indicate significantly higher protein in goose compared to moose and fish and in moose compared to fish. We compared our Trp findings to previous analyses and discuss the substantial gap in human nutritional studies of Trp.
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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 | 0.001 | 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".