Injury-elicited differential transcriptional regulation of phospholipid growth factor receptors in the cornea
Bibliographic record
Abstract
The phospholipid growth factors (PLGFs), including lysophosphatidic acid (LPA), have been implicated in corneal wound healing. PLGF concentrations and activities are elevated after corneal injury. Using real-time PCR, we quantified receptor mRNA levels in the healing rabbit cornea. In intact corneas, transcripts for S1P(1), LPA(1), and LPA(3) receptor subtypes were detected, as was lipid phosphate phosphatase 1 (LPP1). After wounding, the trend for endothelium and keratocytes was for significant decreases in transcript numbers for the three receptor subtypes, whereas epithelial cells showed increased transcript numbers, except for an S1P(1) decrease in healing cells. LPP1 transcript numbers were decreased in keratocytes and endothelium, although LPP-specific activity was unchanged. LPA-elicited Ca(2+) transients were significantly reduced in the healing endothelium. Consistent with reduced LPA(3) receptor numbers, dioctylglycerol pyrophosphate, a selective antagonist, reduced LPA-induced Ca(2+) transients 2.7-fold in nonwounded epithelium but only 1.5-fold in wound-healing endothelium. These data for the first time establish physiologically relevant differential changes in the expression of PLGF receptor subtypes and provide evidence for the changing role of LPA(3) receptors in endothelial cells.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".