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Record W3120989223 · doi:10.1071/rdv33n2ab60

60 High lipid exposure during in vitro maturation alters the lipid profile of bovine oocyte and benefits blastocyst development

2021· article· en· W3120989223 on OpenAlexaff
Camila Bruna de Lima, Érika Cristina dos Santos, Jessica Ispada, Marc‐André Sirard, Christina R. Ferreira, Marcella Pecora Milazzotto

Bibliographic record

VenueReproduction Fertility and Development · 2021
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsBlastocystIn vitro maturationLipid metabolismChemistryEmbryo cultureOocyteAndrologyLipid dropletBiochemistryBiologyEmbryogenesisEmbryo

Abstract

fetched live from OpenAlex

Lipid metabolism provides a potent source of energy and has an important role in the acquisition of oocyte competence. However, there are conflicting reports about how lipid exposure during in vitro maturation (IVM) impacts the gamete and further embryo development. In this study, we performed IVM of oocytes in the presence of lipid-rich culture media and used a broad lipid screening to accurately map the impact on the lipid profile and developmental potential. For that, nonpolar lipids were extracted from fetal bovine serum (FBS) with organic solvents (Bligh-Dyer method) and then used to supplement IVM medium (TCM-199 bicarbonate + 10% FBS, hormones, pyruvate and antibiotics). COCs obtained from abattoir ovaries were submitted to IVM (4 biological replicates) in 2 groups: OC (control; IVM medium) and OHL (high lipid; IVM medium supplemented with extra 10% FBS nonpolar lipids). After 24 h, we collected mature oocytes and those remaining followed to IVF and then to IVC (synthetic oviductal fluid with amino acids, SOFaa, with 5% FBS) for 7 days at 38.5°C, 20% O2, and 5% CO2 in air in high humidity. Expanded blastocysts were collected (BC and BHL) and blastocyst rates were assessed. Lipid extracts of individual oocytes and embryos (n = 10/group) were analysed by multiple reaction monitoring (MRM)-profiling mass spectrometry. A total of 379 lipids from 10 classes were investigated [triacylglycerol (TAG), cholesteryl esters (CE), free fatty acids (FFA), acyl-carnitine, sphingomyelin (SM) and phospholipids derived from choline (PC), ethanolamine (PE), glycerol (PG), serine (PS), and inositol (PI)]. Exploratory data analysis was performed by principal component analysis (PCA; Metaboanalyst 4.0), and fold-change (FC) values were calculated based on the relative intensity of lipid ions (FC > 2 and P < 0.05). IVC rates were compared by t-test (α = 5%). PCA revealed a clear distinction in the lipid content for both oocytes and blastocysts (control vs. treated). More specifically, there was 2-fold enrichment for total TAG and CE in control groups and a 1.5-fold enrichment for total FFA in the treated groups at the oocyte and the blastocyst stages. Surprisingly, the average blastocyst rate was higher in the group derived from oocytes exposed to a high-lipid environment (41.56 ± 7.73 vs. 22.62 ± 1.67; P = 0.003), which led us to investigate specific lipid ions. Groups OHL and BHL had increased contents of structural and signalling phospholipids (PC, SM, PE, and PS) and up to 3 times more oleic and linoleic acids, which have been associated with improved oocyte maturation and blastocyst development. Here, we demonstrate how distinct lipid exposures during IVM can robustly alter the lipid profile of oocytes. But more interestingly, it is clear that these are long-term effects, still observed at the blastocyst stage. More studies are required to verify the metabolic impact of this alternative lipid supplementation; however, these results indicate that high lipid exposure is not necessarily detrimental and, at a certain point, may even counteract lipid accumulation commonly observed during in vitro embryo production.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.020
GPT teacher head0.234
Teacher spread0.214 · 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 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

Citations3
Published2021
Admission routes1
Has abstractyes

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