Endothelin-1 induces neutrophil recruitment in adaptive inflammation via TNFα and CXCL1/CXCR2 in mice
Bibliographic record
Abstract
Endothelin mediates neutrophil recruitment during innate inflammation. Herein we address whether endothelin-1 (ET-1) is involved in neutrophil recruitment in adaptive inflammation in mice, and its mechanisms. Pharmacological treatments were used to determine the role of endothelin in neutrophil recruitment to the peritoneal cavity of mice challenged with antigen (ovalbumin) or ET-1. Levels of ET-1, tumour necrosis factor α (TNFα), and CXC chemokine ligand 1 (CXCL1) were determined by enzyme-linked immunosorbent assay. Neutrophil migration and flow cytometry analyses were performed 4 h after the intraperitoneal stimulus. ET-1 induced dose-dependent neutrophil recruitment to the peritoneal cavity. Treatment with the non-selective ET(A)/ET(B) receptor antagonist bosentan, and selective ET(A) or ET(B) receptor antagonists BQ-123 or BQ-788, respectively, inhibited ET-1- and ovalbumin-induced neutrophil migration to the peritoneal cavity. In agreement with the above, the antigen challenge significantly increased levels of ET-1 in peritoneal exudates. The ET-1- and ovalbumin-induced neutrophil recruitment were reduced in TNFR1 deficient mice, and by treatments targeting CXCL1 or CXC chemokine receptor 2 (CXCR2); further, treatment with bosentan, BQ-123, or BQ-788 inhibited ET-1- and antigen-induced production of TNFα and CXCL1. Furthermore, ET-1 and ovalbumin challenge induced an increase in the number of cells expressing the Gr1(+) markers in the granulocyte gate, CD11c(+) markers in the monocyte gate, and CD4(+) and CD45(+) (B220) markers in the lymphocyte gate in an ET(A)- and ET(B)-dependent manner, as determined by flow cytometry analysis, suggesting that ET-1 might be involved in the recruitment of neutrophils and other cells in adaptive inflammation. Therefore, the present study demonstrates that ET-1 is an important mediator for neutrophil recruitment in adaptive inflammation via TNFα and CXCL1/CXCR2-dependent mechanism.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".