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Inhibition of BMP-mediated SMAD pathway supports the pluripotency of pig embryonic stem cells in the absence of feeder cells

2024· article· en· W4398224659 on OpenAlexaff
Kwang‐Hwan Choi, Dong‐Kyung Lee, Jinsol Jeong, Yelim Ahn, Du‐Min Go, Dae-Yong Kim, Chang‐Kyu Lee

Bibliographic record

VenueTheriogenology · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicPluripotent Stem Cells Research
Canadian institutionsBiotechnology Research Institute
FundersKorea Evaluation Institute of Industrial TechnologyNational Research Foundation of KoreaMinistry of Trade, Industry and Energy
KeywordsCell biologyEmbryonic stem cellBiologyTranscriptomeStem cellSMADRex1Induced pluripotent stem cellSignal transductionGene expressionGeneGenetics

Abstract

fetched live from OpenAlex

Here, we examined the effects of the BMP signaling pathway inhibitor LDN-193189 on the pluripotency of porcine embryonic stem cells (ESCs) in the absence of feeder cells using molecular and transcriptomic techniques. Additionally, the effects of some extracellular matrix components on porcine ESC pluripotency were evaluated to develop an optimized and sustainable feeder-free culture system for porcine ESCs. Feeder cells were found to play an important role in supporting the pluripotency of porcine ESCs by blocking trophoblast and mesodermal differentiation through the inhibition of the BMP pathway. Additionally, treatment with LDN-193189, an inhibitor of the BMP pathway, maintained the pluripotency and homogeneity of porcine ESCs for an extended period in the absence of feeder cells by stimulating the secretion of chemokines and suppressing differentiation, based on transcriptome analysis. Conclusively, these results suggest that LDN-193189 could be a suitable replacement for feeder cells in the maintenance of porcine ESC pluripotency during culture. Additionally, these findings contribute to the understanding of pluripotency gene networks and comparative embryogenesis.

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)0.000
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 score0.004
Threshold uncertainty score0.420

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.240
Teacher spread0.226 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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