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Record W2335582356 · doi:10.1093/cvr/cvu098.140

P718A novel TGF beta-dependent signalling pathway regulating vascular smooth muscle cell differentiation

2014· article· en· W2335582356 on OpenAlexaff
Christina Pagiatakis, Dandan Sun, Stephanie Wales, J. C. McDermott

Bibliographic record

VenueCardiovascular Research · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicTGF-β signaling in diseases
Canadian institutionsYork University
Fundersnot available
KeywordsRHOAMyocardinVascular smooth muscleCell biologyHedgehog signaling pathwaySerum response factorBiologyPhenotypic switchingCalponinCellular differentiationNeural crestSignal transductionPhenotypeEndocrinologyGene expressionGeneActinSmooth muscleGenetics

Abstract

fetched live from OpenAlex

Purpose: Vascular smooth muscle cells (VSMCs) do not terminally differentiate; they fluctuate between a proliferative and differentiated state in response to various extracellular signals. This phenotypic modulation is a major factor that contributes to vascular diseases such as atherosclerosis and post-angioplasty restenosis. Thus, the mechanisms regulating VSMC phenotype are of great interest. TGFβ has been implicated in inducing VSMC differentiation via RhoA/ROCK signalling, whereby it induces a contractile phenotype in neural crest stem cells by up-regulating smooth muscle structural genes. Previous work in our lab showed that RhoA is involved in regulating contractile genes via regulation of myocardin expression. Therefore, we hypothesized that TGFβ is involved in regulating smooth muscle cell differentiation via downstream targets of RhoA/ROCK and components of the canonical TGFβ pathway. Methods: We utilized primary VSMCs and mouse embryonic fibroblast cells (10T1/2) in a conversion assay where cells were induced to express VSMC genes. We utilized siRNA to knock down gene expression, along with gene transfection techniques, reporter assays and pharmacological inhibitors. Results: Treatment of 10T1/2 cells with TGFβ results in a potent induction of VSMC marker genes at the transcriptional and protein levels, which is attenuated by inhibition of RhoA/ROCK signalling. Since canonical TGFβ signalling induces formation of Smad protein complexes which regulate gene expression of numerous target genes, a possible effector could be a downstream component of TGFβ signalling, TAZ, a potent transcriptional regulator and nuclear retention factor that is recruited to sites of Smad-mediated transcription in a TGFβ-dependent manner. Our studies show that in 10T1/2 cells, TAZ is required for TGFβ induction of smooth muscle marker genes. Interestingly, these observations appear to be ROCK dependent. Furthermore, we have observed a synergistic effect between TAZ and Smad3 in regulating smooth muscle differentiation, an effect which is enhanced by serum response factor (SRF). Interestingly, SRF is also required for the TGFβ induction of smooth muscle markers in 10T1/2 cells. Conclusions: These data provide evidence of a novel signalling pathway that links RhoA/ROCK-dependent TGFβ signalling to induction of smooth muscle genes in embryonic fibroblasts through a mechanism involving regulation and expression of TAZ and SRF proteins. These observations elucidate a novel level of control of VSMC induction which may have implications for vascular diseases and congenital vascular malformations.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.121
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.036
GPT teacher head0.274
Teacher spread0.238 · 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

Citations0
Published2014
Admission routes1
Has abstractyes

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