Effect of delipidant agents during in vitro culture on the development, lipid content, gene expression and cryotolerance of bovine embryos
Bibliographic record
Abstract
In vitro produced embryos are still sensitive to the freezing process which can be explained, in part, by the high-lipid accumulation that characterizes these embryos. Therefore, we aimed to evaluate the effect of delipidating agents, L-carnitine and the trans-10 cis-12 conjugated linoleic acid (CLA) isomer, on blastocyst development, lipid content, gene expression and cryotolerance when added to embryo culture media. Embryos were cultured in four different media: T1: control (n = 616), synthetic oviduct fluid (SOF) media with 5% foetal bovine serum (FBS); T2: L-carnitine (n = 648), SOF medium with 5% FBS and 0.6 mg/ml of L-carnitine; T3: CLA (n = 627), SOF medium with 5% FBS and 100 μM trans-10 cis-12 CLA; and T4: L-carnitine + CLA: (n = 597), SOF medium with 5% FBS plus 0.6 mg/ml L-carnitine and 100 μM trans-10 cis-12 CLA. Supplementation of culture medium with either or both delipidating agents reduced (p < .05) blastocyst rate on D7 (T1 = 49 ± 3.5; T2 = 39 ± 3.0; T3 = 42 ± 3.9 and T4 = 39 ± 3.9), but did not affected gene expression (p > .05). Although embryos cultured in the presence of L-carnitine contained fewer (p < .05) lipid droplets than the control embryos, they showed a lower re-expansion rate 24 hr post-thaw than those (p < .05). In conclusion, although L-carnitine reduced the amount of lipids in cultured embryos, the use of L-carnitine and CLA during in vitro culture was not able to improve the embryo production and the response to cryopreservation.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".