Donor cell transplantation for myocardial disease: does it complement current pharmacological therapies?This paper is one of a selection of papers published in this Special Issue, entitled Young Investigators' Forum.
Bibliographic record
Abstract
Heart failure secondary to ischemic heart disease, hypertension, and myocardial infarction is a common cause of death in developed countries. Although pharmacological therapies are very effective, poor prognosis and shorter life expectancy of heart disease patients clearly indicate the need for alternative interventions to complement the present therapies. Since the progression of heart disease is associated with the loss of myocardial cells, the concept of donor cell transplantation into host myocardium is emerging as an attractive strategy to repopulate the damaged tissue. To this end, a number of donor cell types have been tested for their ability to increase the systolic function of diseased hearts in both experimental and clinical settings. Although initial clinical trials with bone marrow stem cells are encouraging, long-term consequences of such interventions are yet to be rigorously examined. While additional laboratory studies are required to address several issues in this field, there is also a clear need for further characterization of drug interactions with donor cells in these interventions. Here, we provide a brief summary of current pharmacological and cell-based therapies for heart disease. Further, we discuss the potential of various donor cell types in myocardial repair, mechanisms underlying functional improvement in cell-based therapies, as well as potential interactions between pharmacological and cell-based therapies.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.162 | 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".