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.
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".