Uptake of apoptotic dendritic cells by viable dendritic cells: a novel mechanism of inducing immune tolerance (48.7)
Bibliographic record
Abstract
Abstract Dendritic cells (DCs) are professional antigen-presenting cells, which can be affected by the death of other cells in close proximity. Spontaneous DC apoptosis has been observed in patients with sepsis and breast cancer. Additionally defects in DC apoptosis have also been associated with development of autoimmune diseases. However, the mechanisms of how DC apoptosis affects immune responses are unclear. Here we show that apoptotic DCs can mediate induction of immune tolerance by converting immature DCs into tolerogenic DCs. The uptake of apoptotic DCs by viable DCs prevents LPS-induced activation and T-cell proliferation, and also results in the upregulation of TGF-beta2 gene expression and TGF-beta1 secretion, which mediates differentiation of naïve T cells into regulatory T cells (Tregs). Additionally, delivery of apoptotic DCs prevents LPS-induced DC maturation and migration to lymph nodes in mice. Moreover, intranasal delivery of apoptotic DCs to LPS-inflamed lungs results in rapid resolution of inflammation along with production of TGF-beta1 and expansion of Tregs. Delivery of apoptotic DCs followed by immunization with ovalbumin (OVA) in Complete Freund’s Adjuvant (CFA) resulted in generation of OVA-specific Tregs in wild-type mice and expansion of Tregs in T-cell receptor transgenic (OT-II) mice. Taken together, our findings identify apoptotic DCs as potent inducers of immunological 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) | 0.000 | 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".