Viral nanoparticles decorated with novel EGFL7 ligands enable intravital imaging of tumor neovasculature
Bibliographic record
Abstract
Angiogenesis is a dynamic process fundamental to the development of solid tumors. Epidermal growth factor-like domain 7 (EGFL7) is a protein whose expression is restricted to endothelial cells undergoing active remodeling that has emerged as a key mediator of this process. EGFL7 expression is associated with poor outcome in several cancers, making it a promising target for imaging or therapeutic strategies. Here, EGFL7 is explored as a molecular target for active neovascularization. Using a combinatorial peptide screening approach, we describe the discovery and characterization of a novel high affinity EGFL7-binding peptide, E7p72, that specifically targets human endothelial cells. Viral nanoparticles decorated with E7p72 peptides specifically target tumor-associated neovasculature with high specificity as assessed by intravital imaging. This work highlights the value of EGFL7 as a target for angiogenic vessels and opens the door for novel targeted therapeutic approaches.
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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) | 0.000 | 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 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".