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Record W3175580573 · doi:10.1016/j.isci.2021.102783

AMPK activation reverts mouse epiblast stem cells to naive state

2021· article· en· W3175580573 on OpenAlexfundno aff
Yajing Liu, Junko Yamane, Akito Tanaka, Wataru Fujibuchi, Jun K. Yamashita

Bibliographic record

VenueiScience · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsnot available
FundersMinistry of Education, Culture, Sports, Science and TechnologyCanadian Internet Registration AuthorityJapan Agency for Medical Research and Development
KeywordsEpiblastAMPKCell biologyStem cellBiologyInduced pluripotent stem cellPopulationReversionProtein kinase AEmbryonic stem cellKinaseGeneticsGenePhenotypeEmbryoEmbryogenesis

Abstract

fetched live from OpenAlex

Despite increasing knowledge on primed and naive pluripotency, the cell signaling that regulates the pluripotency type in stem cells remains not fully understood. Here we show that AMP kinase (AMPK) activators can induce the reversion of primed mouse epiblast stem cells (mEpiSCs) to the naive pluripotent state. The addition of AMPK activators alone or together with leukemia inhibitory factor to primed mEpiSCs induced the appearance of naive-like cells. After passaging in naive culture conditions, the colony morphology, protein expression, and global gene expression profiles indicated the naive state, as did germline transmission ability. Loss-of-function and gain-of-function studies suggested that p38 is a critical downstream target in AMPK activation. Finally, single-cell RNA sequencing analysis revealed that the reversion process through AMPK signaling passes an intermediate naive-like population. In conclusion, the AMPK pathway is a critical driving force in the reversion of primed to naive pluripotency.

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 score0.028
Threshold uncertainty score0.350

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 head0.017
GPT teacher head0.270
Teacher spread0.253 · 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

Citations14
Published2021
Admission routes1
Has abstractyes

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