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Record W2906013156 · doi:10.1194/jlr.m090373

Docosahexaenoic acid is both a product of and a precursor to tetracosahexaenoic acid in the rat

2018· article· en· W2906013156 on OpenAlexafffund
Adam H. Metherel, R. J. Scott Lacombe, Raphaël Chouinard‐Watkins, Richard P. Bazinet

Bibliographic record

VenueJournal of Lipid Research · 2018
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Toronto
FundersFonds de Recherche du Québec - SantéDairy Farmers of CanadaPeterborough K. M. Hunter Charitable FoundationNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsMead Johnson Nutrition
KeywordsIn vivoSecretionMetabolismDocosahexaenoic acidChemistryFatty acidBiochemistryEndogenyInternal medicineBiologyPolyunsaturated fatty acidMedicine

Abstract

fetched live from OpenAlex

-DHA, at a steady state, into two groups of male Long-Evans rats and determined the synthesis-secretion kinetics, including daily synthesis-secretion rates of all 20-24 carbon n-3 PUFAs. We determined that the synthesis-secretion coefficient (a measure of the capacity to synthesize a given fatty acid) for the synthesis of DHA from plasma unesterified THA to be 134-fold higher than for THA from DHA. However, when considering the significantly higher endogenous plasma unesterified DHA pool, the daily synthesis-secretion rates were only 7-fold higher for DHA synthesis from THA (96.3 ± 31.3 nmol/d) compared with that for THA synthesis from DHA (11.4 ± 4.1 nmol/d). Furthermore, plasma unesterified THA was converted to DHA and secreted into the plasma at a 2.5-fold faster rate than remaining as THA itself (26.2 ± 6.3 nmol/d), supporting THA's primary role as a precursor to DHA. In conclusion, using a 3 h infusion model in rats, we demonstrate for the first time in vivo that DHA is both a product and a precursor to THA.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.012
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.146
Threshold uncertainty score0.803

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0120.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.086
GPT teacher head0.423
Teacher spread0.336 · 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 teacher head, 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

Citations25
Published2018
Admission routes2
Has abstractyes

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