The influence of follicle size, FSH‐enriched maturation medium, and early cleavage on bovine oocyte maternal mRNA levels
Bibliographic record
Abstract
Transcription is arrested in the bovine oocyte within the first few hours of in vitro maturation, thus the stored maternal mRNAs accumulated in the oocyte are essential to sustain development until the Maternal-Zygotic Transition. In vivo matured oocytes have superior blastocyst formation rates than in vitro matured oocytes, suggesting that the mRNA content of these oocytes is of higher quality. To determine which transcripts may be associated with developmental competence, a Suppressive Subtractive Hybridization was performed between oocytes collected by ovariectomy at 6 hr post-LH surge and oocytes from slaughterhouse collected after 6 hr of maturation, resulting in a library enriched in these functionally important mRNAs. The clones were spotted onto a cDNA microarray and transcripts potentially associated with developmental competence were hybridized onto these slides. Hybridizations were performed with transcripts up-regulated in oocytes cultured for 6 hr in the presence or absence of rFSH in vitro, and secondly with transcripts up regulated in early-cleaving embryos versus those at the one-cell stage at 36 hr postfertilization. From these hybridizations, 13 candidates were selected. Their functional association with embryonic competence was validated by measuring their relative transcript levels by quantitative real-time PCR in eight different conditions: oocytes cultured with or without rFSH, early--versus late-cleaving embryos, and oocytes from different follicle sizes (1-3, 3-5, 5-8, and >8 mm of diameter). The gene candidates CCNB2, PTTG1, H2A, CKS1, PSMB2, SKIIP, CDC5L, RGS16, and PRDX1 showed a significant quantitative association with competence compared to BMP15, GDF9, CCNB1, and STK6.
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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 | 0.001 |
| 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".