Treatment of Autoimmune Arthritis Using RNA Interference-Modulated Dendritic Cells
Bibliographic record
Abstract
Dendritic cells (DCs) have a dual ability to either stimulate or suppress immunity, which is primarily associated with the expression of costimulatory molecules. Ag-loaded DCs have shown encouraging clinical results for treating cancer and infectious diseases; however, the use of these cells as a means of suppressing immune responses is only recently being explored. Here, we describe the induction of RNA interference through administering short interfering RNA (siRNA) as a means of specifically generating tolerogenic DCs. Knockdown of CD40, CD80, and CD86, prior to loading DCs with the arthritogenic Ag collagen II, led to a population of cells that could effectively suppress onset of collagen-induced arthritis. Maximum benefits were observed when all three genes were concurrently silenced. Disease suppression was associated with inhibition of collagen II-specific Ab production and suppression of T cell recall responses. Downregulation of IL-2, IFN-gamma, TNF-alpha, and IL-17 and increased FoxP3(+) cells with regulatory activity were observed in collagen-induced arthritis mice treated with siRNA-transfected DCs. Collectively, these data support the use of ex vivo gene manipulation in DCs using siRNA to generate tailor-made tolerogenic vaccines for treating autoimmunity.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 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".