ELR-CXC Chemokine Receptor Antagonism Targets Inflammatory Responses at Multiple Levels
Bibliographic record
Abstract
The ELR-CXC chemokines play important roles in neutrophilic inflammation. We report in this study that a fully human ELR-CXC chemokine antagonist that we have generated, CXCL8((3-72))K11R/G31P (G31P), has potent anti-inflammatory effects that arise through its actions at multiple levels. G31P inhibited CXCL8-induced chemotactic responses and intracellular Ca(2+) flux in CXCR1-transfected HEK cells and neutrophils, and responses of neutrophils to CXCR2-exclusive ligands. G31P desensitized heterologous G protein-coupled receptors on neutrophils, 52-86% reducing their Ca(2+) flux and chemotactic responses to leukotriene B(4), C5a, and the bacterial tripeptide fMLP. G31P also 60-90% blocked neutrophil chemotactic responses to mediators present in 10 of 12 sputum samples from cystic fibrosis or bronchiectasis subjects with bacterial pneumonia. Moreover, whereas A549 bronchial epithelial cells (which expressed CXCR1) secreted approximately 29,000 pg/ml CXCL8 in response to in vitro endotoxin challenge, G31P reduced this response by up to 98%, presumably by interrupting an autocrine inflammatory loop. The anti-inflammatory effects of G31P extended also to reversing the antiapoptotic influence of ELR-CXC chemokines on neutrophils. That these effects were relevant in vivo was confirmed in a guinea pig model of airway endotoxemia, wherein the human form of G31P >95% blocked neutrophil infiltration into and activation within the airways, as determined by airway levels of the neutrophil primary, secondary, and tertiary granule markers myeloperoxidase, lactoferrin, and matrix metalloproteinase-9, respectively, and the epithelial cell marker matrix metalloproteinase-2. These data suggest that the beneficial effects of ELR-CXC chemokine antagonism arise through effects that occur at multiple levels, including epithelial cells, neutrophils, and alternate G protein-coupled receptors.
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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) | 0.001 | 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 | 0.000 |
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".