Cell-Based Gene Transfer of Vascular Endothelial Growth Factor Attenuates Monocrotaline-Induced Pulmonary Hypertension
Bibliographic record
Abstract
BACKGROUND: Pulmonary arterial hypertension is characterized by increased pulmonary vascular resistance secondary to a decrease in the caliber and number of pulmonary vascular channels. We hypothesized that the targeted overexpression of an angiogenic factor within the lung would potentially minimize the development and progression of pulmonary arterial hypertension by preventing the loss of existing vessels or by inducing the development of new blood vessels within the lung. METHODS AND RESULTS: We used a cell-based method of gene transfer to the pulmonary microvasculature by delivering syngeneic smooth muscle cells overexpressing vascular endothelial growth factor (VEGF)-A to inbred Fisher 344 rats in which pulmonary hypertension was induced with the pulmonary endothelial toxin monocrotaline. Four weeks after simultaneous endothelial injury and cell-based gene transfer, right ventricular (RV) hypertension and RV and vascular hypertrophy were significantly decreased in the VEGF-treated animals. Four weeks after gene transfer, the plasmid VEGF transcript was still detectable in the pulmonary tissue of animals injected with VEGF-transfected cells, demonstrating survival of the transfected cells and persistent transgene expression. In addition, delay of cell-based gene transfer until after the development of pulmonary hypertension also resulted in a significant decrease in the progression of RV hypertension and hypertrophy. CONCLUSIONS: These results indicate that cell-based VEGF gene transfer is an effective method of preventing the development and progression of pulmonary hypertension in the monocrotaline model and suggest a potential therapeutic role for angiogenic factors in the therapy of this devastating disease.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".