Sphingosine-1-Phosphate
Bibliographic record
Abstract
OBJECTIVE: Sphingosine-1-phosphate (S1P) is a potent bioactive phospholipid responsible for a variety of vascular cell responses. Hypoxia-inducible factor-1 (HIF-1) is a transcriptional activator of genes essential for adaptation to low oxygen. S1P and HIF-1 are both important mediators of vascular cell responses such as migation, proliferation, and survival. Studies have shown that nonhypoxic stimuli can activate HIF-1 in oxygenated conditions. Here, we attempt to determine whether S1P can modulate the vascular activation of HIF-1. METHODS AND RESULTS: We show that in vascular endothelial and smooth muscle cells, activation of the S1P type-2 receptor by S1P strongly increases HIF-1 alpha protein levels, the active subunit of HIF-1. This is achieved through pVHL-independent stabilization of HIF-1 alpha. We demonstrate that the HIF-1 nuclear complex, formed on S1P stimulation, is transcriptionally active and specifically binds to a hypoxia-responsive elements. Moreover, S1P activates the expression of genes known to be closely regulated by HIF-1. CONCLUSIONS: Our results identify S1P as a novel and potent nonhypoxic activator of HIF-1. We believe that understanding the role played by HIF-1 in S1P gene regulation will have a strong impact on different aspects of vascular biology.
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 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.004 |
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".