Macrophage-specific metalloelastase (MMP-12) truncates and inactivates ELR+ CXC chemokines and generates CCL2, -7, -8, and -13 antagonists: potential role of the macrophage in terminating polymorphonuclear leukocyte influx
Bibliographic record
Abstract
Through the activity of macrophage-specific matrix metalloproteinase-12 (MMP-12), we found that macrophages dampen the lipopolysaccharide (LPS)-induced influx of polymorphonuclear leukocytes (PMNs)-thus providing a new mechanism for the termination of PMN recruitment in acute inflammation. MMP-12 specifically cleaves human ELR(+) CXC chemokines (CXCL1, -2, -3, -5, and -8) at E-LR, the critical receptor-binding motif or, for CXCL6, carboxyl-terminal to it. Murine (m) MMP-12 also cleaves mCXCL1, -2, and -3 at E-LR. MMP-12-cleaved mCXCL2 (macrophage-inflammatory protein-2 [MIP-2]) and mCXCL3 (dendritic cell inflammatory protein-1 [DCIP-1]) lost chemotactic activity. Furthermore, MMP-12 processed and inactivated monocyte chemotactic proteins CCL2, -7, -8, and -13 at position 4-5 generating CCR antagonists. Indeed, PMNs and macrophages in bronchoalveolar lavage fluid were significantly increased 72 hours after intranasal instillation of LPS in Mmp12(-/-) mice compared with wild type. Specificity occurred at 2 levels. Macrophage MMP-1 and MMP-9 did not cleave in the ELR motif. Second, unlike human ELR(+)CXC chemokines, mCXCL5 (LPS-induced CXC chemokine [LIX]) was not inactivated. Rather, mMMP-12 cleavage at Ser4-Val5 activated the chemokine, promoting enhanced PMN early infiltration in wild-type mice compared with Mmp12(-/-) mice 8 hours after LPS challenge in air pouches. We propose that the macrophage, specifically through MMP-12, assists in orchestrating the regulation of acute inflammatory responses by precise proteolysis of ELR(+)CXC and CC chemokines.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".