Regulation of angiopoietin expression by bacterial lipopolysaccharide
Bibliographic record
Abstract
Angiopoietins are ligands for Tie-2 receptors and play important roles in angiogenesis and inflammation. While angiopoietin-1 (Ang-1) inhibits inflammatory responses, angiopoietin-2 (Ang-2) promotes cytokine production and vascular leakage. In this study, we evaluated in vivo and in vitro effects of Escherichia coli lipopolysaccharides (LPS) on angiopoietin expression. Wild-type C57/BL6 mice were injected with saline (control) or E. coli LPS (20 mg/ml ip) and killed 6, 12, and 24 h later. The diaphragm, lung, and liver were excised and assayed for mRNA and protein expression of Ang-1, Ang-2, and Tie-2 protein and tyrosine phosphorylation. LPS injection elicited a severalfold rise in Ang-2 mRNA and protein levels in the three organs. By comparison, both Ang-1 and Tie-2 levels in the diaphragm, liver, and lung were significantly attenuated by LPS administration. In addition, Tie-2 tyrosine phosphorylation in the lung was significantly reduced in response to LPS injection. In vitro exposure to E. coli LPS elicited cell-specific changes in Ang-1 expression, with significant induction in Ang-1 expression being observed in cultured human epithelial cells, whereas significant attenuation of Ang-1 expression was observed in response to E. coli LPS exposure in primary human skeletal myoblasts. In both cell types, E. coli LPS elicited substantial induction of Ang-2 mRNA, a response that was mediated in part through NF-kappaB. We conclude that in vivo endotoxemia triggers functional inhibition of the Ang-1/Tie-2 receptor pathway by reducing Ang-1 and Tie-2 expression and inducing Ang-2 levels and that this response may contribute to enhanced vascular leakage in sepsis.
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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".