Interferon-α Abrogates the Suppressive Effect of Apoptotic Cells on Dendritic Cells in an<i>In Vitro</i>Model of Systemic Lupus Erythematosus Pathogenesis
Bibliographic record
Abstract
OBJECTIVE: An increased incidence of apoptotic cells and an increased activation of dendritic cells (DC) may be involved in the pathogenesis of systemic lupus erythematosus (SLE). We investigated the characteristics of apoptotic neutrophils and monocyte-derived DC of patients with SLE, their interaction, and the influence of autoantibodies and inflammatory cytokines on this interaction. METHODS: Kinetics of neutrophil apoptosis and DC activation were studied by flow cytometry. To analyze the interaction of apoptotic cells with phagocytes, crossover coculture experiments were performed with DC from patients with SLE and apoptotic Jurkat T cells as well as with apoptotic neutrophils from patients with SLE and the monocytic cell line U937. SLE serum and cytokines were added to this coculture, and activation and suppression of DC were quantified by levels of inflammatory cytokine secretion. RESULTS: Apoptotic neutrophils and DC from patients with SLE showed no inherent defects compared to healthy controls, and the suppressive nature of their interaction was not affected. Autoantibodies as well as the inflammatory cytokines interleukin 17 (IL-17) and IL-1β had no influence on the interaction in this setup. Interferon (IFN)-α, however, substantially reduced the suppressive effect of apoptotic cells on DC. CONCLUSION: The data suggest that aberrant immune reactivity in SLE is not generally due to an intrinsic defect in apoptotic cells, their processing, or their interaction with DC, but likely arises from the milieu in which this interaction takes place. Our study highlights the importance of IFN-α during early stages of SLE and its potential as a therapeutic target.
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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) | 0.001 | 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 | 0.001 |
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".