Effects of a synthetic PEG-ylated Tie-2 agonist peptide on endotoxemic lung injury and mortality
Bibliographic record
Abstract
A synthetic 7-mer, HHHRHSF, was recently identified by screening a phage display library for binding to the Tie-2 receptor. A polyethylene-oxide clustered version of this peptide, termed vasculotide (VT), was reported to activate Tie-2 and promote angiogenesis in a mouse model of diabetic ulcer. We hypothesized that VT administration would defend endothelial barrier function against sepsis-associated mediators of permeability, prevent lung vascular leakage arising in endotoxemia, and improve mortality in endotoxemic mice. In confluent human microvascular endothelial cells, VT prevented endotoxin-induced (lipopolysaccharides, LPS O111:B4) gap formation, loss of monolayer resistance, and translocation of labeled albumin. In 8-wk-old male C57Bl6/J mice given a ∼70% lethal dose of endotoxin (15 mg/kg ip), VT prevented lung vascular leakage and reversed the attenuation of lung vascular endothelial cadherin induced by endotoxemia. These protective effects of VT were associated with activation of Tie-2 and its downstream mediator, Akt. Echocardiographic studies showed only a nonsignificant trend toward improved myocardial performance associated with VT. Finally, we evaluated survival in this mouse model. Pretreatment with VT improved survival by 41.4% (n = 15/group, P = 0.02) and post-LPS administration of VT improved survival by 33.3% (n = 15/group, P = 0.051). VT-mediated protection from LPS lethality was lost in Tie-2 heterozygous mice, in agreement with VT's proposed receptor specificity. We conclude that this synthetic Tie-2 agonist, completely unrelated to endogenous Tie-2 ligands, is sufficient to activate the receptor and its downstream pathways in vivo and that the Tie-2 receptor may be an important target for therapeutic evaluation in conditions of pathological vascular leakage.
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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 | 0.000 |
| 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".