The Endothelial Receptor Tyrosine Kinase Tie2 is Essential for Vascular Integrity Dependent/Independent of Inflammation
Bibliographic record
Abstract
Endothelial Receptor Tyrosine Kinase Tie2, and its two principal ligands Angiopoietin1&2 (Angpt‐1&2), play an important role in heath and diseases. Its agonistic ligand Angpt‐1 mainly expressed in perivascular cells whereas Angpt‐2, stored in Weible –Palade‐Bodies, compete with Angpt‐1 and function as partial agonist/antagonist. However, the consequence of the loss of Tie2 and potential contribution to vascular dysfunction in health and disease has not been investigated so far. In the present study we found mice with one copy of Tie2 gene a) are more vulnerable to death in murine sepsis models, endotoxemia (83% vs. 42%, P < 0.05) and Cecal Ligation and Perforation (CLP) (76% vs. 32%, P < 0.05); b) has enhanced vascular leak as measured by Evans's blue extravasation assay. Similarly,siRNA mediated knock‐down of Tie2 results in enhanced vascular leak in lungs with perturbed downstream signaling of Tie2. In vitro by using shRNA ‐lentiparticles we found Angpt‐1 induced prevention of Lipo‐polysaccharide (LPS) ‐mediated vascular barrier dysunction in Tie2 dependent fashion. Above all, the effect of reduced Tie2 expression in‐vivo and in‐vitro is independent of changes to the inflammatory milieu. In conclusion, our study demonstrates a novel inflammation independent role for Tie2 mediating endothelial vascular function in sepsis. Further studies are underway to investigate the upstream and downstream regulators of Tie2 and reveal the diagnostic and therapeutic implication of this important pathway.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.002 | 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".