Genomic Regulation through RNA in Oocyte Maturation of Large Mammals
Bibliographic record
Abstract
The oocyte is a unique cell amongst the 212 cell types that makes an individual. This cell does not divide until it resumes meiosis and remains in a special chromatin status during the dictiate stage of the prophase from oocyte formation in the gonad in the female fetus until it dies through apoptosis or proceeds to ovulation. This status requires unique features to allow transcription to be active during oocyte growth and an automatic pilot system to drive the transition from tetraploidy to haploidy during maturation and fertilization and back to diploidy, all this in a few days in large mammals. Therefore, the regulatory program for all the transformations required for chromosome separation, cell cycle progression, response to sperm entry, and embryonic genome activation must be stored in the oocyte prior to ovarian release or even prior to final chromatin condensation as it inhibits further transcription. The data related to gene regulation during this period is limited for two main reasons: limited amount of material to study in mammals and differences with somatic tissues where gene pathways are much better characterized. Nevertheless, using the genomic amplification approaches and the increasing amount of information in somatic tissues and in oocytes from lower species, it is becoming possible to study this automatic pilot system that drives the mammalian oocyte through maturation-fertilization and embryonic genome activation. This chapter will focus on the progression of our understanding of the oocyte using proteomic and transcriptomic tools.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".