Blockade of in vivo VEGF-mediated angiogenesis by antisense gene therapy: role of Flk-1 and Flt-1 receptors
Bibliographic record
Abstract
Angiogenesis, the formation of new blood vessels from preexisting ones, is a critical component of various pathologies such as tumor progression, rheumatoid arthritis, and retinopathies. Vascular endothelial growth factor (VEGF) is a mitogenic and chimiotactic factor capable of inducing angiogenesis through the activation of its receptors, fetal liver kinase-1 (Flk-1) and fms-like tyrosine kinase-1 (Flt-1), expressed on endothelial cells. The purpose of the present study was to assess if a treatment with antisense (AS) oligonucleotides directed against VEGF receptors Flk-1 or Flt-1 mRNA could prevent VEGF-mediated angiogenesis. With the use of miniosmotic pumps, phosphate-buffered saline, VEGF, or VEGF combined with AS-Flk-1, AS-Flt-1, or AS-scrambled oligonucleotides were released in mouse testis for 14 days. VEGF (1, 2.5, and 5 microg) increased the formation of new capillary blood vessels by 236, 246, and 287%, respectively. The combination of AS-Flk-1 or AS-Flt-1 (200 microg) to VEGF (2.5 microg) reduced by 87 and 85% the formation of new blood vessels, respectively, and the expression of their corresponding proteins. These data demonstrate the therapeutical potential of AS-Flk-1 or AS-Flt-1 to prevent VEGF-mediated angiogenesis in vivo.
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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".