Interleukin‐6 downregulation with mesenchymal stem cell differentiation results in loss of immunoprivilege
Bibliographic record
Abstract
Allogeneic mesenchymal stem cell (MSC) transplantation improves cardiac function, but cellular differentiation results in loss of immunoprivilege and rejection. To explore the mechanism involved in this immune rejection, we investigated the influence of interleukin-6 (IL-6), a factor secreted by MSCs, on immune privilege after myogenic, endothelial and smooth muscle cell differentiation induced by 5-azacytidine, VEGF, and transforming growth factor-β (TGF-β), respectively. Both RT-PCR and ELISA showed that myogenic differentiation of MSCs was associated with significant downregulation of IL-6 expression (P < 0.01), which was also observed following endothelial (P < 0.01) and smooth muscle cell differentiation (P < 0.05), indicating that IL-6 downregulation was dependent on differentiation but not cell phenotype. Flow cytometry demonstrated that IL-6 downregulation as a result of myogenic differentiation was associated with increased leucocyte-mediated cell death in an allogeneic leucocyte co-culture study (P < 0.01). The allogeneic reactivity associated with IL-6 downregulation was also observed following MSC differentiation to endothelial and smooth muscle cells (P < 0.01), demonstrating that leucocyte-mediated cytotoxicity was also dependent on differentiation but not cell phenotype. Restoration of IL-6 partially rescued the differentiated cells from leucocyte-mediated cell death. These findings suggest that rejection of allogeneic MSCs after implantation may be because of a reduction in cellular IL-6 levels, and restoration of IL-6 may be a new target to retain MSC immunoprivilege.
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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".