Selective Down-Regulation of Neutrophil Mac-1 in Endotoxemic Hepatic Microcirculation via IL-10
Bibliographic record
Abstract
Hepatic neutrophil adhesion during endotoxemia is an integrin-independent, CD44-dependent process. Because integrins function in other endotoxemic vasculatures, we used spinning disk confocal intravital microscopy to assess whether LPS down-modulated integrin functions in sinusoids. First, we applied fMLP onto the liver surface, and compared it with systemic LPS administration. Local fMLP caused neutrophil adhesion, crawling, and emigration for at least 2 h. Surprisingly, the number of adherent and crawling neutrophils was markedly reduced in Mac-1(-/-) and ICAM-1(-/-) mice, but not in mice treated with anti-CD44 mAb. By contrast, systemic LPS injection induced a robust accumulation of neutrophils in sinusoids, which was dependent on CD44, but not on integrins. Strikingly, local fMLP could not induce any integrin-dependent adhesion in endotoxemic mice treated with anti-CD44 mAb, indicating that Mac-1-dependent neutrophil adhesion was inhibited by LPS. This response was localized to the hepatic microvasculature because neutrophils still adhered via integrins in brain microvasculature. ICAM-1/ICAM-2 levels were not decreased, but following LPS treatment, Mac-1 was down-regulated in neutrophils localized to liver, but not in the circulation. Mac-1 down-regulation in neutrophils was not observed in IL-10(-/-) mice. In vitro neutrophil incubation with IL-10 induced direct decrease of Mac-1 expression and adhesivity in LPS-stimulated neutrophils. Therefore, our data suggest that Mac-1 is necessary for neutrophil adhesion and crawling during local inflammatory stimuli in sinusoids, but during systemic inflammation, neutrophils are exposed to high concentrations of IL-10, leading to a CD44-dependent, integrin-independent adhesion. This may be a mechanism to keep neutrophils in sinusoids for intravascular trapping.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".