Impact of the LH surge on granulosa cell transcript levels as markers of oocyte developmental competence in cattle
Bibliographic record
Abstract
In the case of in vitro embryonic production, it is known that not all oocytes detain the developmental capacity to form an embryo. This capacity appears to be acquired through completion of folliculogenesis, during which the oocyte and follicular cells influence their respective destinies. The differentiation status of granulosa cells (GCs) could therefore offer an indicator of oocyte quality. The aim of this study was to compare mRNA transcript abundance in GCs associated with oocytes that subsequently reach or not the blastocyst stage. GCs were collected from cattle following an ovarian stimulation protocol that did or did not include the administration of LH. GCs were classified according to the developmental stage achieved by the associated oocytes. Transcript abundance was measured by microarray. Follicles (n=189) obtained from cows before and after the LH surge were essentially similar and the rates of oocytes reaching the blastocyst stage were not significantly different (52 vs 41%), but blastocyst quality was significantly better in the post-LH-surge group. In GCs from the pre-LH-surge group and associated with developmentally competent oocytes, 18 overexpressed and 22 underexpressed transcripts were found, including novel uncharacterized transcripts, whereas no differentially expressed transcripts were associated with developmentally different oocytes in the post-LH-surge group. The novel transcriptomic response associated with LH appeared to mask the difference. Based on oocyte developmental competence, the period prior to the LH surge appears best suited for studying competence-associated mRNA transcripts in bovine follicle cells.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 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) | 0.000 | 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 teacher head, 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".