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Record W2523076888 · doi:10.1530/rep-16-0155

Effect of kit ligand on natriuretic peptide precursor C and oocyte maturation in cattle

2016· article· en· W2523076888 on OpenAlexaff
P. F. Lima, Cinthia Marenza Ormond, Ester Siqueira Caixeta, Rodrigo Garcia Barros, Christopher A. Price, J. Buratini

Bibliographic record

VenueReproduction · 2016
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversité de MontréalCegep de Saint Hyacinthe
FundersConselho Nacional de Desenvolvimento Científico e TecnológicoFundação de Amparo à Pesquisa do Estado de São Paulo
KeywordsOocyteIn vitro maturationMeiosisMessenger RNAChemistryAndrologyHuman fertilizationBiologyCell biologyEmbryoAnatomyGeneBiochemistry

Abstract

fetched live from OpenAlex

In vitro maturation (IVM) of oocytes in cattle is inefficient, and there is great interest in the development of approaches to improve maturation and fertilization rates. Intraovarian signalling molecules are being explored as potential additives to IVM media. One such factor is kit ligand (KITL), which stimulates the growth of oocytes. We determined if KITL enhances oocyte maturation in cattle. The two main isoforms of KITL (KITL1 and KITL2) were expressed in bovine cumulus-oocyte complexes (COC), and levels of mRNA increased during FSH-stimulated IVM. The addition of KITL to the culture medium increased the percentage of oocytes that reached meiosis II but did not affect cumulus expansion after 22 h of IVM. Addition of KITL reduced the levels of mRNA encoding natriuretic peptide precursor C (NPPC), a protein that holds oocytes in meiotic arrest, and increased the levels of mRNA encoding YBX2, an oocyte-specific factor involved in meiosis. Removal of the oocyte from the COC resulted in increased KITL mRNA levels and decreased NPPC mRNA levels in cumulus cells, and addition of denuded oocytes reversed these effects. Taken together, our results suggest that KITL enhances bovine oocyte nuclear maturation through a mechanism that involves NPPC, and that the oocyte regulates cumulus expression of KITL mRNA.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score0.197

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.010
GPT teacher head0.275
Teacher spread0.266 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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

Citations12
Published2016
Admission routes1
Has abstractyes

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