Direct G protein signalling mediates components of the vascular smooth muscle response to insulin‐like growth factor
Bibliographic record
Abstract
Like many organs, the vasculature possesses an intrinsic repair ability that is critical for homeostasis. This ability is intimately linked to smooth muscle cells (SMCs) through their unique phenotypic plasticity, which allows them to proliferate and migrate in response to specific stimuli. However, phenotypic modulation is also the major underlying phenomenon behind pathogenic vascular disease and post‐surgery repair Physiological control of the SMC response involves the presence of circulating factors, such as Insulin‐like Growth Factor‐ 1 (IGF‐1). IGF‐1 acts via its receptor, a member of the tyrosine kinase receptor family, but it may also require a G protein. Thus, the objective of this study was to investigate the structural aspects of IGR‐1R coupling to a G protein in SMCs, as well as the contribution of this pathway to the cellular response. In primary SMCs, the IGF‐1R was found to interact with both G αi and G β subunits and in the case of G αi , this was a direct interaction. We found that IGF‐1‐induced activation of ERK1/2 was prevented with a G βγ inhibitor, which also inhibited cell proliferation in response to IGF‐1. Specific cell‐penetrating G αi inhibitor peptides were synthesized and these enabled identification of several unique downstream targets. These findings support the conclusion that the responses of vascular SMCs to IGF‐1 are elicited at least in part through interaction with a G protein. Source of research support: Canadian Institutes for Health Research
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".