Tolerogenic effect of mouse fibroblasts on dendritic cells
Bibliographic record
Abstract
There is controversy about the immunomodulatory effect of fibroblasts on dendritic cells (DCs). To clarify this issue, in this study, we have evaluated different features of fibroblast-primed DCs including their ability to express co-inhibitory and co-stimulatory molecules, pro-inflammatory and anti-inflammatory cytokines and their ability to induce T-cell proliferation. We also examined migratory capacity of DCs to lymphatic tissues and present fibroblast-derived antigens after encountering fibroblasts. The results of our in vitro study showed that both co-inhibitory (programmed death ligand 1 and ligand 2 and B7H4) and co-stimulatory (CD86) molecules were up-regulated when DCs were co-cultured with fibroblasts. In an animal model, we showed that intra- peritoneal injection (IP) of both syngeneic and allogeneic fibroblasts significantly increased both total DC count and expression level of co-inhibitory and co-stimulatory molecules on DCs. Priming of DCs with syngeneic and allogeneic fibroblasts reduced the proliferation of CD4(+) and CD8(+) T cells. Even activation of fibroblast- primed DCs failed to restore their ability to induce T-cell proliferation. Likewise, priming of DCs with fibroblasts blocked the ability of ovalbumin-pulsed DCs to induce proliferation of ovalbumin-specific CD4(+) T cells. Compared with non-activated DCs, fibroblast-primed DCs had significantly higher expression levels of interleukin-10 and indoleamine 2, 3 dioxygenase. Fibroblast-primed DCs had a significantly reduced interleukin-12 expression level compared with that of activated DCs. After priming with fibroblasts, DCs were able to migrate to lymphatic tissues and present fibroblast-derived antigens (ovalbumin). In conclusion, after priming with fibroblasts, DCs gain tolerogenic features. This finding suggests the potential role of fibroblasts in the maintenance of immune tolerance.
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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) | 0.001 | 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".