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Record W2037360889 · doi:10.1016/j.bbrc.2012.12.085

Src family kinase inhibitor PP2 accelerates differentiation in human intestinal epithelial cells

2013· article· en· W2037360889 on OpenAlexafffund
Amira Seltana, Amel Guezguez, Manon Lepage, Nùria Basora, Jean‐François Beaulieu

Bibliographic record

VenueBiochemical and Biophysical Research Communications · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDigestive system and related health
Canadian institutionsUniversité de Sherbrooke
FundersCanadian Institutes of Health Research
KeywordsProto-oncogene tyrosine-protein kinase SrcCell biologyCellular differentiationBiologyKinaseCell growthBiochemistry

Abstract

fetched live from OpenAlex

The proto-oncogene Src is an important protein tyrosine kinase involved in signaling pathways that control cell adhesion, growth, migration and survival. Here, we investigated the involvement of Src family kinases (SFKs) in human intestinal cell differentiation. We first observed that Src activity peaked in early stages of Caco-2/15 cell differentiation. Inhibition of SFKs with PP2, a selective SFK inhibitor, accelerated the overall differentiation program. Interestingly, all polarization and terminal differentiation markers tested, including sucrase-isomaltase, lactase-phlorizin hydrolase and E and Li-cadherins were found to be significantly up-regulated after only 3 days of treatment in the newly differentiating cells. Further investigation of the effects of PP2 revealed a significant up-regulation of the two main intestinal epithelial cell-specific transcription factors Cdx2 and HNF1α and a reduction of polycomb PRC2-related epigenetic repressing activity as measured by a decrease in H3K27me3, two events closely related to the control of cell terminal differentiation in the intestine. Taken together, these data suggest that SFKs play a key role in the control of intestinal epithelial cell terminal differentiation.

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 score0.018
Threshold uncertainty score0.475

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 studies0.0000.001
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 head0.057
GPT teacher head0.357
Teacher spread0.300 · 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

Citations19
Published2013
Admission routes2
Has abstractyes

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