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Record W2771107559 · doi:10.1016/j.celrep.2017.12.042

Ca2+-Induced Mitochondrial ROS Regulate the Early Embryonic Cell Cycle

2018· article· en· W2771107559 on OpenAlexfundno aff
Yue Han, Shoko Ishibashi, Javier Iglesias‐González, Yaoyao Chen, Nick R. Love, Enrique Amaya

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMitochondrial Function and Pathology
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilHealing FoundationMedical Research Council CanadaUniversity of ManchesterWellcome TrustMedical Research CouncilWellcome
KeywordsXenopusReactive oxygen speciesCell biologyMitochondrial ROSMitochondrionBiologyCell cycleHuman fertilizationEmbryoSecond messenger systemSignal transductionCell divisionApoptosisCellBiochemistryGeneticsGene

Abstract

fetched live from OpenAlex

While it is appreciated that reactive oxygen species (ROS) can act as second messengers in both homeostastic and stress response signaling pathways, potential roles for ROS during early vertebrate development have remained largely unexplored. Here, we show that fertilization in Xenopus embryos triggers a rapid increase in ROS levels, which oscillate with each cell division. Furthermore, we show that the fertilization-induced Ca 2+ wave is necessary and sufficient to induce ROS production in activated or fertilized eggs. Using chemical inhibitors, we identified mitochondria as the major source of fertilization-induced ROS production. Inhibition of mitochondrial ROS production in early embryos results in cell-cycle arrest, in part, via ROS-dependent regulation of Cdc25C activity. This study reveals a role for oscillating ROS levels in early cell cycle regulation in Xenopus embryos.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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 source (direct Gemma or distilled Codex), 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

Citations100
Published2018
Admission routes1
Has abstractyes

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