Sphingosine-1-Phosphate Signaling Regulates Myogenic Responsiveness in Human Resistance Arteries
Bibliographic record
Abstract
We recently identified sphingosine-1-phosphate (S1P) signaling and the cystic fibrosis transmembrane conductance regulator (CFTR) as prominent regulators of myogenic responsiveness in rodent resistance arteries. However, since rodent models frequently exhibit limitations with respect to human applicability, translation is necessary to validate the relevance of this signaling network for clinical application. We therefore investigated the significance of these regulatory elements in human mesenteric and skeletal muscle resistance arteries. Mesenteric and skeletal muscle resistance arteries were isolated from patient tissue specimens collected during colonic or cardiac bypass surgery. Pressure myography assessments confirmed endothelial integrity, as well as stable phenylephrine and myogenic responses. Both human mesenteric and skeletal muscle resistance arteries (i) express critical S1P signaling elements, (ii) constrict in response to S1P and (iii) lose myogenic responsiveness following S1P receptor antagonism (JTE013). However, while human mesenteric arteries express CFTR, human skeletal muscle resistance arteries do not express detectable levels of CFTR protein. Consequently, modulating CFTR activity enhances myogenic responsiveness only in human mesenteric resistance arteries. We conclude that human mesenteric and skeletal muscle resistance arteries are a reliable and consistent model for translational studies. We demonstrate that the core elements of an S1P-dependent signaling network translate to human mesenteric resistance arteries. Clear species and vascular bed variations are evident, reinforcing the critical need for further translational study.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".