Endothelium-Targeted Gene and Cell-Based Therapies for Cardiovascular Disease
Bibliographic record
Abstract
Most common cardiovascular diseases are accompanied by endothelial dysfunction. Because of its predominant role in the pathogenesis of cardiovascular disease, the vascular endothelium is an attractive therapeutic target. The identification of promoter sequences capable of rendering endothelial-specific transgene expression together with the recent development of vectors with enhanced tropism for endothelium may offer opportunities for the design of new strategies for modulation of endothelial function. Such strategies may be useful in the treatment of chronic diseases such as hypertension, atherosclerosis, and ischemic artery disease, as well as in acute myocardial infarction and during open heart surgery for prevention of ischemia and reperfusion (I/R)-induced injury. The recent identification of putative endothelial progenitor cells in peripheral blood may allow the design of autologous cell-based strategies for neovascularization of ischemic tissues and for the repair of injured blood vessels and bioengineering of vascular prosthesis. "Proof-of-concept" for some of these strategies has been established in animal models of cardiovascular disease. However the successful translation of these novel strategies into clinical application will require further developments in vector and delivery technologies. Further characterization of the processes involved in mobilization, migration, homing, and incorporation of endothelial progenitor cells into the target tissues is necessary, and the optimal conditions for therapeutic application of these cells need to be defined and standardized.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| 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 | 0.001 | 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".