Regulation of autotaxin expression and secretion by lysophosphatidate and sphingosine 1-phosphate
Bibliographic record
Abstract
Autotaxin (ATX) is a secreted enzyme, which produces extracellular lysophosphatidate (LPA) from lysophosphatidylcholine (LPC). LPA activates six G protein-coupled receptors and this is essential for vasculogenesis during embryonic development. ATX is also involved in wound healing and inflammation, and in tumor growth, metastasis, and chemo-resistance. It is, therefore, important to understand how ATX is regulated. It was proposed that ATX activity is inhibited by its product LPA, or a related lipid called sphingosine 1-phosphate (S1P). We now show that this apparent inhibition is ineffective at the high concentrations of LPC that occur in vivo. Instead, feedback regulation by LPA and S1P is mediated by inhibition of ATX expression resulting from phosphatidylinositol-3-kinase activation. Inhibiting ATX activity in mice with ONO-8430506 severely decreased plasma LPA concentrations and increased ATX mRNA in adipose tissue, which is a major site of ATX production. Consequently, the amount of inhibitor-bound ATX protein in the plasma increased. We, therefore, demonstrate the concept that accumulation of LPA in the circulation decreases ATX production. However, this feedback regulation can be overcome by the inflammatory cytokines, TNF-α or interleukin 1β. This enables high LPA and ATX levels to coexist in inflammatory conditions. The results are discussed in terms of ATX regulation in wound healing and cancer.
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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) | 0.001 | 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".