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Factors Affecting Oocyte and Embryo Transcriptomes

2012· review· en· W2118339155 on OpenAlexafffund
Marc‐André Sirard

Bibliographic record

VenueReproduction in Domestic Animals · 2012
Typereview
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversité Laval
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOocyteTranscriptomeBiologyBlastocystEmbryoAndrologyCell biologyMeiosisEmbryonic stem cellFollicular phaseOvarian follicleEmbryogenesisGeneticsGene expressionGeneMedicine

Abstract

fetched live from OpenAlex

The most important factor affecting the oocyte and early embryo transcriptome is the legacy from the follicular environment prior to meiotic resumption. Up to the 8-cell stage, the oocyte responds to maternal instructions stored before resumption of the meiotic division. Recent evidence suggests that properly prepared or programmed oocytes (in vivo) can achieve close to 100% blastocyst rates in standard in vitro conditions/media. Therefore, the optimal oocyte requires perfect follicular timing and differentiation, but the intra-oocyte mechanisms involved in such preparation are not completely understood. In addition, the influence of maternal mRNA storage and degradation, as well as the length of the poly A tail that influences the general pattern of the oocyte/early embryo transcriptome, is an important factor. Several hypotheses have been put forth to explain the depletion of the maternal store, including the potential role of microRNA (miRNA) in this process. The activation of the embryonic genome could be dependent on, or associated with, the process of maternal mRNA degradation, but obviously other functions are being activated at this critical time point. This review will focus on the period from full-size oocytes to the eight-cell stage and will summarize the impact of the important factors, that is, follicle, maternal RNA storage and embryonic genome activation, on the transcriptome.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.960
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.134
GPT teacher head0.390
Teacher spread0.256 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designOther design
Domainnot available
GenreReview

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".

Quick stats

Citations98
Published2012
Admission routes2
Has abstractyes

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