Gene expression analysis of bovine blastocysts produced by parthenogenic activation or fertilisation
Bibliographic record
Abstract
The processes underlying the very first moments of embryonic development are still not well characterised in mammals. To better define the kinetics of events taking place following fertilisation, it would be best to have perfect synchronisation of sperm entry. With fertilisation occurring during a time interval of 6 to 12h in the same group of fertilised oocytes, this causes a major variation in the time of activation of embryonic development. Bovine parthenogenesis could potentially result in better synchronisation and, if so, would offer a better model for studying developmental competence. In the present study, bovine oocytes were either parthenogenetically activated or fertilised and cultured in vitro for 7 days. Gene expression analysis for those two groups of embryos at early and expanded stages was performed with BlueChip, a customised 2000-cDNA array developed in our laboratory and enriched in clones from various stages of bovine embryo development. The microarray data analysis revealed that only a few genes were differentially expressed, showing the relative similarity between those two kinds of embryos. Nevertheless, the fact that we obtained a similar diversity of developmental stages with parthenotes suggests that synchronisation is more oocyte-specific than sperm entry-time related. We then analysed our data with Ingenuity pathway analysis. Networks of genes involved in blastocyst implantation but also previous stages of embryo development, like maternal-to-embryonic transition, were identified. This new information allows us to better understand the regulatory mechanisms of embryonic development associated with embryo status.
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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 | 0.001 | 0.001 |
| 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".