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Record W2073180117 · doi:10.1016/j.stemcr.2014.04.019

Local BMP-SMAD1 Signaling Increases LIF Receptor-Dependent STAT3 Responsiveness and Primed-to-Naive Mouse Pluripotent Stem Cell Conversion Frequency

2014· article· en· W2073180117 on OpenAlexafffund
Kento Onishi, Peter D. Tonge, András Nagy, Peter W. Zandstra

Bibliographic record

VenueStem Cell Reports · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsUniversity Health NetworkMount Sinai HospitalUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsBiologyStem cellSTAT3Cell biologyGlycoprotein 130Transcription factorSignal transductionGenetics

Abstract

fetched live from OpenAlex

Conversion of EpiSCs to naive ESCs is a rare event that is driven by the reestablishment of the naive transcription factor network. In mice, STAT3 activation is sufficient to drive conversion of EpiSCs to the naive pluripotent stem cell (PSC) state. However, the lack of responsiveness of EpiSCs to LIF presents a bottleneck in this conversion process. Here, we demonstrate that local accumulation of BMP-SMAD1 signaling, in cooperation with GP130 ligands, enhances the recovery of LIF responsiveness by directly controlling transcription of the LIF receptor (Lif-r). Addition of BMP and LIF to EpiSCs increases both LIF responsiveness and conversion frequencies to naive PSCs. Mechanistically, we show that the transcriptional cofactor P300 plays a critical role by mediating complex formation between STAT3 and SMAD1. This demonstration of how the local microenvironment or stem cell niche reactivates dormant signaling responsiveness and developmental potential may be applicable to other stem cell niche-containing systems.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.001
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 head0.229
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 teacher head, not a consensus.

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

Citations26
Published2014
Admission routes2
Has abstractyes

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