Sphingosine‐1‐Phosphate acutely modulates the CFTR (Cystic Fibrosis Transmembrane Regulator) transporter in an AMPK‐dependent manner
Bibliographic record
Abstract
Introduction Sphingosine‐1‐Phosphate (S1P) is a primary modulator of resistance artery tone. Its bioavailability is controlled by a rheostat between sphingosine kinase 1 and intracellular S1P phosphohydrolase 1. We have found that the transport by CFTR is the rate‐limiting step for the intracellular hydrolysis of S1P. We hypothesized that S1P limits its own degradation by an AMPK‐dependent modulation of CFTR conductance. Methods CFTR conductance was assessed using the iodide efflux technique (conventional and real‐time) in baby hamster kidney (BHK) cells, which stably express human wild type CFTR. AMPK phosphorylation was determined using Western blots Results BHK cells were found to endogenously express Sk1, SPP1 and the S1P 1 and S1P 2 receptors (n=8). S1P (1μM, n=6) significantly reduced iodide conductance by 43% (conventional) and 75% (real‐time). The negative effect of S1P on CFTR iodide conductance was enhanced following S1P 2 overexpression but reduced following pretreatment with the S1P 2 blocker JTE013 (5μM, n=6). The inhibitory effect of S1P was associated with AMPK phosphorylation and blocked by the AMPK inhibitor Compound C (80μM, n=5). Accordingly, AMPK activation by AICAR mimicked the effect of S1P on iodide conductance. Conclusions The S1P 2 ‐ and AMPK‐dependent modulation of CFTR conductance describes a novel pathway through which S1P could potentially regulate its own degradation.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".