Group V secreted phospholipase A<sub>2</sub>contributes to LPS‐induced leukocyte recruitment
Bibliographic record
Abstract
Secreted phospholipases A(2) (sPLA(2)s) are well known for their contribution in the biosynthesis of inflammatory eicosanoids. These enzymes also participate in the inflammatory process by regulating chemokine production and protein expression of adhesion molecules. The majority of sPLA(2) isoforms are up-regulated by proinflammatory stimuli such as bacterial lipopolysaccharide (LPS), which predominantly increases the expression of group V sPLA(2) (sPLA(2)-V). Furthermore, it has recently been shown that sPLA(2)-V is a critical messenger in the regulation of cell migration during allergic airway responsiveness. Herein, we investigated the effect of sPLA(2)-V on LPS-mediated leukocyte recruitment and its capacity to modulate adhesion molecule expression. We conducted our study in the murine air pouch model, using sPLA(2)-V null mice (sPLA(2)-V(-/-)) and control wild-type (WT) littermates. We observed that LPS (1 microg/ml)-mediated leukocyte emigration in sPLA(2)-V(-/-) was attenuated by 52% and 86% upon 6 and 12 h of treatment respectively, as compared to WT mice. In WT mice, treatment with the cell-permeable sPLA(2) inhibitor (12-epi-scalaradial; SLD) reduced LPS-mediated leukocyte recruitment by 67%, but had no additional inhibitory effect in sPLA(2)-V(-/-) mice. Protein analyses from the air pouch skin were carried out upon LPS-challenge, and the expression of intercellular adhesion molecule (ICAM)-1 and vascular cell adhesion molecule (VCAM)-1 were both significantly reduced in sPLA(2)-V(-/-) mice as compared to control WT mice. Together, our data demonstrate the role of sPLA(2)-V in LPS-induced ICAM-1 and VCAM-1 protein overexpression and leukocyte recruitment, supporting the contribution of sPLA(2)-V in the development of inflammatory innate immune responses.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".