Differential effects of heat-inactivated, secretome-deficient MSC and metabolically active MSC in sepsis and allogenic heart transplantation
Bibliographic record
Abstract
Abstract Mesenchymal stem cells (MSCs) are used in various clinical and preclinical models for immunomodulation. However, it remains unclear how the immunomodulatory effect of MSC is communicated. MSC-induced immunomodulation is known to be mediated through both MSC-secreted cytokines and direct cell-cell interactions. Recently, it has been demonstrated that metabolically inactive, heat-inactivated MSCs (HI-MSCs) have similar anti-inflammatory capacities in LPS-induced sepsis compared with viable MSC. To further investigate the immunomodulatory effects of MSC, we introduced MSC and HI-MSC in two animal models with different immunological causes. In the first model, allogeneic hearts were transplanted from C57BL/6 mice to BALB/c recipients. MSC in combination with mycophenolate mofetil (MMF) significantly improved graft survival compared with MMF alone, whereas the application of HI-MSC had no effect on graft survival. We revealed that control MSC dose-dependently inhibited CD3+ and CD8+ T-cell proliferation in vitro, whereas HI-MSC had no effect. In the second model, sepsis was induced in mice via cecal ligation and puncture. HI-MSC treatment significantly improved the overall survival, whereas control MSCs had no effect. in vitro studies demonstrated that HI-MSCs are more effectively phagocytosed by monocytes than control MSCs and induced cell death in particular of activated CD16+ monocytes, which may explain the immune protective effect of HI-MSC in the sepsis model. The results of our study demonstrate that MSC-mediated immunomodulation in sepsis is dependent on a passive recognition of MSC by monocytes, whereas fully functional MSCs are required for inhibition of T-cell-mediated allograft rejection.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| 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".