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Record W2339731048 · doi:10.1194/jlr.m200153-jlr200

Whole-body β-oxidation of 18:2ω6 and 18:3ω3 in the pig varies markedly with weaning strategy and dietary 18:3ω3

2003· article· en· W2339731048 on OpenAlexaffabout
Richard P. Bazinet, Ewen G. McMillan, Ravi Seebaransingh, Anthony Hayes, Stephen C. Cunnane

Bibliographic record

VenueJournal of Lipid Research · 2003
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsUniversity of GuelphUniversity of Toronto
Fundersnot available
KeywordsWeaningLinoleic acidAnimal sciencePolyunsaturated fatty acidHaptoglobinBiologyFood scienceFatty acidEndocrinologyBiochemistry

Abstract

fetched live from OpenAlex

Segregated early weaning (SEW) into a cleaner nursery increases food intake and growth in pigs, presumably because of reduced immune stimulation compared with conventionally reared, nonsegregated pigs (NSW). The aim of the present study was to evaluate the oxidation of linoleic acid (18:2omega6) and alpha-linolenic acid (18:3omega3) in SEW and NSW pigs. Pigs consumed a control or high 18:3omega3 diet (omega6 PUFA/omega3 PUFA; 21.3 vs. 2.5, respectively) and were weaned at either 14 days old into a SEW nursery or at 21 days old into a conventional NSW nursery. The major acute-phase protein of pigs but not haptoglobin increased in 35-day-old NSW pigs. NSW pigs had 15-25% lower carcass 18:2omega6 and 20-30% lower carcass 18:3omega3 (% composition) at 49 days old. Between 35- and 49-days-old, NSW pigs had a higher whole-body oxidation of 18:2omega6 (40-120%) and 18:3omega3 (30-80%). The high 18:3omega3 diet decreased the whole-body oxidation of 18:2omega6 by 73% and of 18:3omega3 by 63% in NSW pigs. We conclude that moderately cleaner housing SEW significantly decreases 18:2omega6 and 18:3omega3 oxidation in pigs.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
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 head0.117
GPT teacher head0.338
Teacher spread0.222 · 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 designObservational
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

Citations19
Published2003
Admission routes2
Has abstractyes

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