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Record W2774841222 · doi:10.1194/jlr.m081380

Complete assessment of whole-body n-3 and n-6 PUFA synthesis-secretion kinetics and DHA turnover in a rodent model

2017· article· en· W2774841222 on OpenAlexafffund
Adam H. Metherel, R. J. Scott Lacombe, Raphaël Chouinard‐Watkins, Kathryn E. Hopperton, Richard P. Bazinet

Bibliographic record

VenueJournal of Lipid Research · 2017
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaFonds de Recherche du Québec - SantéDairy Farmers of CanadaMead Johnson Nutrition
KeywordsDocosapentaenoic acidPolyunsaturated fatty acidArachidonic acidDocosahexaenoic acidLinoleic acidSecretionMetabolismChemistryBiosynthesisFatty acidKineticsBiochemistryInternal medicineEndocrinologyBiologyEnzymeMedicine

Abstract

fetched live from OpenAlex

-DPAn-6. Eight 11-week-old Long Evans rats fed a 10% fat diet were infused with the labeled PUFAs over 3 h, and plasma enrichment of labeled products was measured every 30 min. The DHA synthesis-secretion rate (94 ± 34 nmol/day) did not differ from other PUFA products (range, 21.8 ± 4.3 nmol/day to 408 ± 116 nmol/day). Synthesis-secretion rates of n-6 and n-3 PUFA homologs were similar, except 22:4n-6 and DPAn-6 had lower synthesis rates. However, daily turnover from newly synthesized DHA (0.067 ± 0.023%) was 56-fold to 556-fold slower than all other PUFA turnover and was 130-fold slower than that determined directly from the total plasma unesterified DHA pool. In conclusion, n-6 and n-3 PUFA synthesis-secretion kinetics suggest that differences in turnover, not in synthesis-secretion rates, primarily determine PUFA plasma levels.

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)0.005
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.811
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.135
GPT teacher head0.447
Teacher spread0.312 · 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 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

Citations30
Published2017
Admission routes2
Has abstractyes

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