New Insights into the Pro-Inflammatory Activities of Ang1 on Neutrophils: Induction of MIP-1β Synthesis and Release
Bibliographic record
Abstract
We reported the expression of angiopoietin Tie2 receptor on human neutrophils and the capacity of angiopoietins (Ang1 and Ang2) to induce pro-inflammatory activities, such as platelet-activating factor synthesis, β2-integrin activation and neutrophil migration. Recently, we observed differential effects between both angiopoietins, namely, the capacity of Ang1, but not Ang2, to promote rapid interleukin-8 synthesis and release, as well as neutrophil viability. Herein, we addressed whether Ang1 and/or Ang2 could modulate the synthesis and release of macrophage inflammatory protein-1β (MIP-1β) by neutrophils. Neutrophils were isolated from blood of healthy volunteers; intracellular and extracellular MIP-1β protein concentrations were assessed by ELISA. After 24 hours, the basal intracellular and extracellular MIP-1β protein concentrations were ≈500 and 100 pg/106 neutrophils, respectively. Treatment with Ang1 (10 nM) increased neutrophil intracellular and extracellular MIP-1β concentrations by 310 and 388% respectively. Pretreatment with PI3K (LY294002), p38 MAPK (SB203580) and MEK (U0126) inhibitors completely inhibited Ang1-mediated increase of MIP-1β intracellular and extracellular protein levels. Pretreatment with NF-κB complex inhibitors, namely Bay11-7085 and IKK inhibitor VII or with a transcription inhibitor (actinomycin D) and protein synthesis inhibitor (cycloheximide), did also abrogate Ang1-mediated increase of MIP-1β intracellular and extracellular protein levels. We validated by RT-qPCR analyses the effect of Ang1 on the induction of MIP-1β mRNA levels. Our study is the first one to report Ang1 capacity to induce MIP-1β gene expression, protein synthesis and release from neutrophils, and that these effects are mediated by PI3K, p38 MAPK and MEK activation and downstream NF-κB activation.
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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) | 0.000 | 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) | 0.001 | 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".