Lipid phosphate phosphatase-1 regulates lysophosphatidic acid-induced calcium release, NF-κB activation and interleukin-8 secretion in human bronchial epithelial cells
Bibliographic record
Abstract
LPA (lysophosphatidic acid), a potent bioactive phospholipid, elicits diverse cellular responses through activation of the G-protein-coupled receptors LPA1-LPA4. LPA-mediated signalling is partially regulated by LPPs (lipid phosphate phosphatases; LPP-1, -2 and -3) that belong to the phosphatase superfamily. This study addresses the role of LPPs in regulating LPA-mediated cell signalling and IL-8 (interleukin-8) secretion in HBEpCs (human bronchial epithelial cells). Reverse transcription-PCR and Western blotting revealed the presence and expression of LPP-1-3 in HBEpCs. Exogenous [3H]oleoyl LPA was hydrolysed to [3H]-mono-oleoylglycerol. Infection of HBEpCs with an adenoviral construct of human LPP-1 for 48 h enhanced the dephosphorylation of exogenous LPA by 2-3-fold compared with vector controls. Furthermore, overexpression of LPP-1 partially attenuated LPA-induced increases in the intracellular Ca2+ concentration, phosphorylation of IkappaB (inhibitory kappaB) and translocation of NF-kappaB (nuclear factor-kappaB) to the nucleus, and almost completely prevented IL-8 secretion. Infection of cells with an adenoviral construct of the mouse LPP-1 (R217K) mutant partially attenuated LPA-induced IL-8 secretion without altering LPA-induced changes in intracellular Ca2+ concentration, phosphorylation of IkappaB, NF-kappaB activation or IL-8 gene expression. Our results identify LPP-1 as a key regulator of LPA signalling and IL-8 secretion in HBEpCs. Thus LPPs could represent potential targets in regulating leucocyte infiltration and airway inflammation.
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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".