DNA methylation status of bovine blastocysts obtained from peripubertal oocyte donors
Bibliographic record
Abstract
In the dairy industry, the high selection pressure combined with the increased efficiency of assisted reproduction technologies (ART) are leading toward the use of younger females for reproduction purposes, with the aim to reduce the interval between generations. This situation could impair embryo quality, decreasing the success rate of the ART procedures and the values of resulting offspring. Young Holstein heifers (n = 10) were subjected to ovarian stimulation and oocyte collection at 8, 11, and 14 months of age. All the oocytes were fertilized in vitro with semen from one adult bull, generating three pools of embryos per animal. Each animal was its own control for the evaluation of the effects of age. The EmbryoGENE platform was used to compare the DNA methylation status of blastocysts obtained from oocytes collected at 8 versus 14 and 11 versus 14 months of age. Age-related contrast analysis identified 5,787 and 3,658 differentially methylated regions (DMRs) in blastocysts from heifers at 8 versus 14 and 11 versus 14 months of age, respectively. For both contrasts, the DMRs were distributed nonrandomly in the different DNA regions. The DNA from embryos from 8-month-old donors was more hypermethylated, while the DNA from embryos from 11-month-old donors displayed an intermediate phenotype. According to Ingenuity Pathway Analysis, the upstream regulator genes cellular tumor antigen p53, transforming growth factor β1, tumor necrosis factor, and hepatocyte nuclear factor 4α are particularly associated with methylation sensitive targets, which were more hypermethylated in embryos from younger donors.
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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".