Mesenchymal Stem/Stromal Cells Induce the Generation of Novel IL-10–Dependent Regulatory Dendritic Cells by SOCS3 Activation
Bibliographic record
Abstract
Suppression of immune response by mesenchymal stem/stromal cells (MSCs) is well documented. However, their regulatory effects on immune cells, especially regulatory dendritic cells, are not fully understood. We have identified a novel Sca-1(+)Lin(-)CD117(-) MSC population isolated from mouse embryonic fibroblasts (MEF) that suppressed lymphocyte proliferation in vitro. Moreover, the Sca-1(+)Lin(-)CD117(-) MEF-MSCs induced hematopoietic stem/progenitor cells to differentiate into novel regulatory dendritic cells (DCs) (Sca-1(+)Lin(-)CD117(-) MEF-MSC-induced DCs) when cocultured in the absence of exogenous cytokines. Small interfering RNA silencing showed that Sca-1(+)Lin(-)CD117(-) MEF-MSCs induced the generation of Sca-1(+)Lin(-)CD117(-) MEF-MSC-induced DCs via IL-10-activated SOCS3, whose expression was regulated by the JAK-STAT pathway. We observed a high degree of H3K4me3 modification mediated by MLL1 and a relatively low degree of H3K27me3 modification regulated by SUZ12 on the promoter of SOCS3 during SOCS3 activation. Importantly, infusion of Sca-1(+)CD117(-)Lin(-) MEF-MSCs suppressed the inflammatory response by increasing DCs with a regulatory phenotype. Thus, our results shed new light on the role of MSCs in modulating regulatory DC production and support the clinical application of MSCs to reduce the inflammatory response in numerous disease states.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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) | 0.002 | 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".