Lipid Phosphate Phosphatase-1 and Ca2+ Control Lysophosphatidate Signaling through EDG-2 Receptors
Post-publication record
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Bibliographic record
Abstract
The serum-derived phospholipid growth factor, lysophosphatidate (LPA), activates cells through the EDG family of G protein-coupled receptors. The present study investigated mechanisms by which dephosphorylation of exogenous LPA by lipid phosphate phosphatase-1 (LPP-1) controls cell signaling. Overexpressing LPP-1 decreased the net specific cell association of LPA with Rat2 fibroblasts by approximately 50% at 37 degrees C when less than 10% of LPA was dephosphorylated. This attenuated cell activation as indicated by diminished responses, including cAMP, Ca(2+), activation of phospholipase D and ERK, DNA synthesis, and cell division. Conversely, decreasing LPP-1 expression increased net LPA association, ERK stimulation, and DNA synthesis. Whereas changing LPP-1 expression did not alter the apparent K(d) and B(max) for LPA binding at 4 degrees C, increasing Ca(2+) from 0 to 50 micrometer increased the K(d) from 40 to 900 nm. Decreasing extracellular Ca(2+) from 1.8 mm to 10 micrometer increased LPA binding by 20-fold, shifting the threshold for ERK activation to the nanomolar range. Hence the Ca(2+) dependence of the apparent K(d) values explains the long-standing discrepancy of why micromolar LPA is often needed to activate cells at physiological Ca(2+) levels. In addition, the work demonstrates that LPP-1 can regulate specific LPA association with cells without significantly depleting bulk LPA concentrations in the extracellular medium. This identifies a novel mechanism for controlling EDG-2 receptor activation.
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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".