Regulation of MHC Class II Expression and Antigen Processing in Murine and Human Mesenchymal Stromal Cells by IFN-γ, TGF-β, and Cell Density
Bibliographic record
Abstract
Mesenchymal stromal cells (MSC) possess immunosuppressive properties, yet when treated with IFN-gamma they acquire APC functions. To gain insight into MSC immune plasticity, we explored signaling pathways induced by IFN-gamma required for MHC class II (MHC II)-dependent Ag presentation. IFN-gamma-induced MHC II expression in mouse MSC was enhanced by high cell density or serum deprivation and suppressed by TGF-beta. This process was regulated by the activity of the type IV CIITA promoter independently of STAT1 activation and the induction of the IFN regulatory factor 1-dependent B7H1/PD-L1 encoding gene. The absence of direct correlation with the cell cycle suggested that cellular connectivity modulates IFN-gamma responsiveness for MHC II expression in mouse MSC. TGF-beta signaling in mouse MSC involved ALK5 and ALK1 TGF-beta RI, leading to the phosphorylation of Smad2/Smad3 and Smad1/Smad5/Smad8. An opposite effect was observed in human MSC where IFN-gamma-induced MHC II expression occurred at the highest levels in low-density cultures; however, TGF-beta reduced IFN-gamma-induced MHC II expression and its signaling was similar as in mouse MSC. This suggests that the IFN-gamma-induced APC features of MSC can be modulated by TGF-beta, serum factors, and cell density in vitro, although not in the same way in mouse and human MSC, via their convergent effects on CIITA expression.
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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 | 0.000 |
| 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".