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Record W2031339913 · doi:10.1095/biolreprod.114.120931

The Adenosine Salvage Pathway as an Alternative to Mitochondrial Production of ATP in Maturing Mammalian Oocytes1

2014· article· en· W2031339913 on OpenAlexaff
Sara Scantland, Irene Tessaro, Carolina H. Macabelli, Angus D. Macaulay, Gaël Cagnone, Éric Fournier, A.M. Luciano, Claude Robert

Bibliographic record

VenueBiology of Reproduction · 2014
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAdenylate kinaseBiologyOocyteCell biologyAdenosine triphosphateKinasePhosphocreatineAdenosinePhosphodiesteraseMitochondrionOxidative phosphorylationBiochemistryPhosphorylationEndocrinologyEnzymeEnergy metabolismEmbryo

Abstract

fetched live from OpenAlex

Although the oocyte is the largest cell in the body and an unavoidable phase in life, its physiology is still poorly understood, and other cell types provide little insight into its unique nature. Even basic cellular functions in the oocyte such as energy metabolism are not yet fully understood. It is known that the mitochondria of the female gamete exhibit an immature form characterized by limited energy production from glucose and oxidative phosphorylation. We show that the bovine oocyte uses alternative means to maintain ATP production during maturation, namely, the adenosine salvage pathway. Meiosis resumption is triggered by destruction of cyclic AMP by phosphodiesterases producing adenosine monophosphate that is converted into ATP by adenylate kinases and creatine kinases. Inhibition of these enzymes decreased ATP production, and addition of their substrates restored ATP production in denuded oocytes. Addition of phosphocreatine to the oocyte maturation medium influenced the phenotype of the resulting blastocysts. We propose a model in which adenylate kinases and creatine kinases act as drivers of ATP production from added AMP during oocyte maturation.

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)0.003
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.434

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 head0.020
GPT teacher head0.294
Teacher spread0.274 · 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

Citations59
Published2014
Admission routes1
Has abstractyes

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