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Record W2783116181 · doi:10.1016/j.celrep.2017.12.060

Esrrb Complementation Rescues Development of Nanog-Null Germ Cells

2018· article· en· W2783116181 on OpenAlexfundno aff
Man Zhang, Harry G. Leitch, Walfred W. C. Tang, Nicola Festuccia, Elisa Hall-Ponselé, Jennifer Nichols, M. Azim Surani, Austin Smith, Ian Chambers

Bibliographic record

VenueCell Reports · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilMedical Research CouncilDirectorate for Biological SciencesNational Institute for Health and Care ResearchMedical Research Council CanadaNIHR Imperial Biomedical Research CentreUniversity of CambridgeCancer Research UKWellcome Trust
KeywordsHomeobox protein NANOGBiologyGermlineEmbryonic stem cellRex1Nanog Homeobox ProteinComplementationCell biologyNull cellGerm cellGeneticsInduced pluripotent stem cellPhenotypeCell cultureGene

Abstract

fetched live from OpenAlex

The transcription factors (TFs) Nanog and Esrrb play important roles in embryonic stem cells (ESCs) and during primordial germ-cell (PGC) development. Esrrb is a positively regulated direct target of NANOG in ESCs that can substitute qualitatively for Nanog function in ESCs. Whether this functional substitution extends to the germline is unknown. Here, we show that germline deletion of Nanog reduces PGC numbers 5-fold at midgestation. Despite this quantitative depletion, Nanog-null PGCs can complete germline development in contrast to previous findings. PGC-like cell (PGCLC) differentiation of Nanog-null ESCs is also impaired, with Nanog-null PGCLCs showing decreased proliferation and increased apoptosis. However, induced expression of Esrrb restores PGCLC numbers as efficiently as Nanog. These effects are recapitulated in vivo: knockin of Esrrb to Nanog restores PGC numbers to wild-type levels and results in fertile adult mice. These findings demonstrate that Esrrb can replace Nanog function in germ cells.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.117
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.292
Teacher spread0.272 · 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
Published2018
Admission routes1
Has abstractyes

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