Granulocyte-macrophage colony-stimulating factor (GM-CSF): a chemoattractive agent for murine leukocytes in vivo
Bibliographic record
Abstract
GM-CSF is well recognized as a proliferative agent for hematopoietic cells and exerts a priming function on neutrophils. The aim of this study was to determine if GM-CSF has a role as a neutrophil chemoattractant in vivo and if it can contribute to recruitment during intestinal inflammation. Initial studies in vitro, using the under-agarose gel assay, determined that GM-CSF can induce neutrophil migration at a much lower molar concentration than the fMLP-like peptide WKYMVm (33.5-134 nM vs. 1-10 μM). GM-CSF-induced neutrophil migration was ablated (<95%) using neutrophils derived from GMCSFRβ(-/-) mice and significantly attenuated by 42% in PI3Kγ(-/-)neutrophils. In vivo, a significant increase in leukocyte recruitment was observed using intravital microscopy 4 h post-GM-CSF (10 μg/kg) injection, which was comparable with leukocyte recruitment induced by KC (40 μg/kg). GM-CSF-induced recruitment was abolished, and KC-induced recruitment was maintained in GMCSFRβ(-/-) mice. Furthermore, in vivo migration of extravascular leukocytes was observed toward a gel containing GM-CSF in WT but not GMCSFRβ(-/-) mice. Finally, in a model of intestinal inflammation (TNBS-induced colitis), colonic neutrophil recruitment, assessed using the MPO assay, was attenuated significantly in anti-GM-CSF-treated mice or GMCSFRβ(-/-) mice. These data demonstrate that GM-CSF is a potent chemoattractant in vitro and can recruit neutrophils from the microvasculature and induce extravascular migration in vivo in a β subunit-dependent manner. This property of GM-CSF may contribute significantly to recruitment during intestinal inflammation.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".