Modulation of Alloimmune Responses by Interleukin-10 Prevents Rejection of Implanted Allogeneic Smooth Muscle Cells and Restores Postinfarction Ventricular Function
Bibliographic record
Abstract
Interleukin-10 (IL-10) gene transduction into allogeneic smooth muscle cells (SMCs) was evaluated to improve the long-term benefits of allogeneic cell transplantation into infarcted myocardium. Allogeneic cells, including SMCs, have been demonstrated to restore cardiac function and repair the infarcted myocardium, but late rejection of the transplanted cells by the host immune system may reverse the benefits of cell therapy. In a rat myocardial infarction model, three groups of rats were injected with either unmodified autologous, unmodified allogeneic, or allogeneic + IL-10 SMCs into the infarct region. Three weeks later, most of the allogeneic cells were rejected, whereas autologous cells were engrafted in the myocardium. IL-10 gene transduction of the allogeneic SMCs significantly improved the cell survival. To understand the mechanism of this improved survival, we evaluated the host immune responses against the SMCs. Allogeneic SMCs expressing IL-10 decreased leukocyte-mediated cytotoxicity in coculture, decreased the number of cytotoxic CD8(+) T-cells, and increased the number of CD4(+)CD25(+) regulatory T-cells in vitro and in vivo. Furthermore, IL-10 prevented the production of antidonor antibodies by the recipients against the allogeneic SMCs. Transplantation of unmodified autologous SMCs, but not unmodified allogeneic SMCs, significantly improved fractional shortening and left ventricular dimensions compared to the media-injected control group. However, IL-10 gene-enhanced allogeneic SMCs improved ventricular function, increased wall thickness, and decreased scar length in association with their enhanced survival. We conclude that IL-10 gene-enhanced cell therapy with allogeneic SMCs prevents detrimental alloimmune responses in the recipient, thereby increasing the survival of transplanted allogeneic SMCs and more effectively restoring cardiac function.
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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".