Characterization of merocytic dendritic cells homeostasis
Bibliographic record
Abstract
Abstract In contrast to conventional dendritic cells (cDC), when merocytic DC (mcDC) present antigens (Ag) derived from apoptotic bodies, T cell anergy is reversed rather than induced. Although helpful to tumor clearance, reversing T cell anergy is detrimental in autoimmunity. Interestingly, mcDC are present in higher proportion in type 1 diabetes (T1D)-prone NOD mice than in B6 mice. Still, little is known about the immunological properties of mcDC that define them as a DC subset. Phenotypic characterization of mcDC revealed that they express the cDC-restricted transcription factor, Zbtb46. Moreover, we found that mcDC are potent inducers of mixed lymphocyte reactions, a key trait defining them as cDC. Investigation of other transcription factors associated with specific cDC functions, such as Irf4 and Irf8, reveal that mcDC are heterogeneous, with phenotypic and functional characteristics more closely resembling CD8α cDC. Comparative gene profiles by principal component analysis revealed that mcDC clustered more closley to CD8α cDC than other DC subsets. Still, mcDC are distinct from CD8α cDC, as mcDC are present in Batf3-deficient mice. Together, these data demonstrate that mcDC are a cDC subset with unique ability to break antigen specific tolerance. Understanding the homeostatic regulation of this new cDC subset will permit to develop new therapies for diseases, such as autoimmunity or cancer where they can be either pathogenic or beneficial.
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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 | 0.001 | 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".