Identification of IDO-Positive and IDO-Negative Human Dendritic Cells after Activation by Various Proinflammatory Stimuli
Bibliographic record
Abstract
Dendritic cells (DCs) can induce tolerance or immunity. We identified and characterized an IDO-expressing and an IDO-negative human DC population after stimulation by various proinflammatory stimuli. IDO expression was strongly dependent on the maturation status of the cells (CD83-positive cells only). The two DC subpopulations remained IDO positive and IDO negative, respectively, over a time period of at least 48 h. IDO enzyme activity of human DCs was highest during stimulation by strongly maturation-inducing TLR ligands such as highly purified LPS (TLR4 ligand) or polyriboinosinic-polyribocytidilic acid (TLR3 ligand); factors of the adaptive immune system such as IFN-γ, a mixture of cytokines, and IFN-α had lesser stimulatory capacity for IDO induction and activity. After stimulation with CD40L, IDO-positive DCs expressed significantly increased levels of B7 family molecules such as CD40, CD80, CD86, ICOS ligand, as well as PD-L1 (B7-H1) and PD-L2 (B7-DC) compared with the IDO-negative DC subset. At the same time, the inhibitory receptors Ig-like transcripts 3 and 4 were significantly downregulated on IDO-positive cells. Functionally, IDO-positive DCs produced significantly more IL-1β and IL-15 and less IL-10 and IL-6 than the IDO-negative subset after CD40L stimulation. These results show that IDO expression is associated with a distinctive phenotype and functional capacity in mature DCs. It seems likely that the IDO-positive DC subset possesses a regulatory function and might skew a T cell response toward tolerance.
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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 | 0.001 | 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) | 0.000 | 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".