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Record W4318042624 · doi:10.3390/nu15030610

C57bl/6 Mice Show Equivalent Taste Preferences toward Ruminant and Industrial Trans Fatty Acids

2023· article· en· W4318042624 on OpenAlexafffund
Farzad Mohammadi, Nicolas Bertrand, Iwona Rudkowska

Bibliographic record

VenueNutrients · 2023
Typearticle
Languageen
FieldNursing
TopicBiochemical Analysis and Sensing Techniques
Canadian institutionsUniversité Laval
FundersFonds de Recherche du Québec - SantéNatural Sciences and Engineering Research Council of Canada
KeywordsElaidic acidTasteLecithinChemistryFood scienceFatty acidBiochemistryInternal medicineMedicineLinoleic acid

Abstract

fetched live from OpenAlex

Two distinct types of trans fatty acids (TFA) are found in the diet. Industrial TFA such as elaidic acid (EA) have deleterious effects on metabolic risk factors, and oppositely ruminant TFA including trans-palmitoleic acid (TPA) may have beneficial effects. The objective is to evaluate the taste preference between EA, TPA, lecithin or water. In this study, 24 female C57BL/6 mice were microchipped and placed in two separate IntelliCages®. Nano encapsulated TFA or lecithin were added to drinking water in different corners of the cage with normal diet. The study was carried out over 5 weeks, during which mice were exposed to water only (weeks 1 and 3), TFA or lecithin (week 2), and EA or TPA (weeks 4 and 5). Mice weights, corner visits, nose pokes (NP), and lick number were measured each week. The results demonstrated that mice consume more TFA, either EA or TPA, compared with lecithin. In addition, the mice licked more EA compared with TPA in one cage; conversely, in the other cage they licked more TPA compared with EA. However, when TFA positions were swapped, mice had equal licks for EA and TPA. In sum, mice preferred TFA, in equal matter compared with controls; therefore, the results demonstrate the potential for TFA-type substitution in diet.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.450
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.081
GPT teacher head0.296
Teacher spread0.215 · 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

Citations1
Published2023
Admission routes2
Has abstractyes

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