Targeted Delivery of Genes to Endothelial Cells and Cell‐ and Gene‐Based Therapy in Pulmonary Vascular Diseases
Bibliographic record
Abstract
Pulmonary arterial hypertension (PAH) is a devastating disease that, despite significant advances in medical therapies over the last several decades, continues to have an extremely poor prognosis. Gene therapy is a method to deliver therapeutic genes to replace defective or mutant genes or supplement existing cellular processes to modify disease. Over the last few decades, several viral and nonviral methods of gene therapy have been developed for preclinical PAH studies with varying degrees of efficacy. However, these gene delivery methods face challenges of immunogenicity, low transduction rates, and nonspecific targeting which have limited their translation to clinical studies. More recently, the emergence of regenerative approaches using stem and progenitor cells such as endothelial progenitor cells (EPCs) and mesenchymal stem cells (MSCs) have offered a new approach to gene therapy. Cell-based gene therapy is an approach that augments the therapeutic potential of EPCs and MSCs and may deliver on the promise of reversal of established PAH. These new regenerative approaches have shown tremendous potential in preclinical studies; however, large, rigorously designed clinical studies will be necessary to evaluate clinical efficacy and safety.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".