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Record W2521579368 · doi:10.1530/rep-16-0093

Morphologic and transcriptomic assessment of bovine embryos exposed to dietary long-chain fatty acids

2016· article· en· W2521579368 on OpenAlexafffund
Reza Salehi, M.G. Colazo, Stephen Tsoi, A. Behrouzi, Benjamin K. Tsang, Michael K. Dyck, M. Oba, D.J. Ambrose

Bibliographic record

VenueReproduction · 2016
Typearticle
Languageen
FieldNursing
TopicFatty Acid Research and Health
Canadian institutionsAlberta Ministry of Agriculture and ForestryAgriculture Food and Rural DevelopmentOttawa HospitalUniversity of AlbertaUniversity of Ottawa
FundersAlberta Livestock and Meat AgencyAgriculture Funding ConsortiumCanadian Institutes of Health ResearchAlberta InnovatesAlberta Agriculture and Forestry
KeywordsEmbryoCanolaBiologyPolyunsaturated fatty acidAndrologyLinoleic acidEmbryogenesisTranscriptomeLinolenic acidFatty acidFood scienceAnimal scienceGeneGene expressionBiochemistryCell biology

Abstract

fetched live from OpenAlex

The main objectives of this study were to determine the influence of diets enriched in α-linolenic, linoleic or oleic acid on the development and transcriptomic profile of embryos collected from dairy cattle. Non-lactating Holstein cows received one of the three diets supplemented with 8% rolled oilseeds: flax (FLX, n = 8), sunflower (SUN, n = 7) or canola (CAN, n = 8). After a minimum 35-day diet adaptation, cows were superovulated, artificially inseminated and ova/embryos recovered non-surgically after 7.5 days. Cows fed FLX had less degenerated embryos and more viable embryos than those fed CAN or SUN. In total, 175 genes were differentially expressed in blastocysts from cows fed FLX than in cows fed CAN or SUN. These differentially expressed genes were mainly involved in cellular growth and proliferation, cellular development, and cell survival and viability. In conclusion, dietary n-3 polyunsaturated fatty acids reduced early embryonic degeneration possibly through improving embryonic cell survival and viability.

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.045
GPT teacher head0.333
Teacher spread0.288 · 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

Citations8
Published2016
Admission routes2
Has abstractyes

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