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Record W2954533752 · doi:10.1155/2019/7096416

Indigenous Subarctic Food Systems in Transition: Amino Acid Composition (Including Tryptophan) in Wild-Harvested and Processed Meats

2019· article· en· W2954533752 on OpenAlexafffundabout
Nicole Spiegelaar, Ian Martin, Leonard J. S. Tsuji

Bibliographic record

VenueInternational Journal of Food Science · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsThe Scarborough HospitalUniversity of Toronto
FundersInstitute of Aboriginal Peoples HealthCanadian Institutes of Health Research
KeywordsTryptophanSubarctic climateAmino acidComposition (language)Food scienceChemistryFish <Actinopterygii>Food composition dataBiologyBiochemistryEcologyFishery

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.885
Threshold uncertainty score0.231

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.043
GPT teacher head0.273
Teacher spread0.230 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations17
Published2019
Admission routes3
Has abstractyes

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