Sphingosine-1-Phosphate Is a Novel Regulator of Cystic Fibrosis Transmembrane Conductance Regulator (CFTR) Activity
Bibliographic record
Abstract
The cystic fibrosis transmembrane conductance regulator (CFTR) attenuates sphingosine-1-phosphate (S1P) signaling in resistance arteries and has emerged as a prominent regulator of myogenic vasoconstriction. This investigation demonstrates that S1P inhibits CFTR activity via adenosine monophosphate-activated kinase (AMPK), establishing a potential feedback link. In Baby Hamster Kidney (BHK) cells expressing wild-type human CFTR, S1P (1μmol/L) attenuates forskolin-stimulated, CFTR-dependent iodide efflux. S1P's inhibitory effect is rapid (within 30 seconds), transient and correlates with CFTR serine residue 737 (S737) phosphorylation. Both S1P receptor antagonism (4μmol/L VPC 23019) and AMPK inhibition (80μmol/L Compound C or AMPK siRNA) attenuate S1P-stimluated (i) AMPK phosphorylation, (ii) CFTR S737 phosphorylation and (iii) CFTR activity inhibition. In BHK cells expressing the ΔF508 CFTR mutant (CFTRΔF508), the most common mutation causing cystic fibrosis, both S1P receptor antagonism and AMPK inhibition enhance CFTR activity, without instigating discernable correction. In summary, we demonstrate that S1P/AMPK signaling transiently attenuates CFTR activity. Since our previous work positions CFTR as a negative S1P signaling regulator, this signaling link may positively reinforce S1P signals. This discovery has clinical ramifications for the treatment of disease states associated with enhanced S1P signaling and/or deficient CFTR activity (e.g. cystic fibrosis, heart failure). S1P receptor/AMPK inhibition could synergistically enhance the efficacy of therapeutic strategies aiming to correct aberrant CFTR trafficking.
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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) | 0.000 | 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) | 0.001 | 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".