Decoy Receptor 3 Attenuates Collagen-induced Arthritis by Modulating T Cell Activation and B Cell Expansion
Bibliographic record
Abstract
OBJECTIVE: To investigate the immune-modulated effects of decoy receptor 3 (DCR3) in an experimental model of rheumatoid arthritis (RA). METHODS: We delivered DCR3 plasmid into collagen-induced arthritis (CIA) mice using the hydrodynamic method and evaluated the serum level of DCR3 protein by ELISA. After immunization, we assessed disease severity of arthritis incidence, arthritis scores, paw thickness, and means of arthritic limbs, and used hematoxylin and eosin staining to observe synovial hyperplasia. We analyzed numbers of murine splenocytes and inguinal lymphocyte cells, cell populations, and serum proinflammatory cytokines by flow cytometry. We investigated B cell proliferation by carboxyfluorescein succinimidyl ester assay. We evaluated serum levels of total IgG2a and type II collagen-specific IgG and IgG2a using ELISA. RESULTS: DCR3 expression in sera significantly attenuated disease severity in CIA mice. We found that DCR3 inhibited the volume of inguinal lymph nodes, numbers of CD19+ B cells, and populations of interferon-γ, interleukin 4 (IL-4), IL-17A, and Foxp3-producing CD4+ T cell in vivo. We found that DCR3 inhibited Pam3CSK4 (Toll-like receptor 1/2 ligand)-induced B220+ B cell proliferation in vitro. DCR3 treatment reduced the serum level of IL-6, total IgG2a, and CII-specific IgG2a antibody. CONCLUSION: We postulated that the protective effects of DCR3 in CIA resulted from modulation of the immune system by maintaining the B/T cell balance and decreasing lymphocyte expansion. We suggest DCR3 as a prophylactic and potential therapeutic agent in the treatment of RA.
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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) | 0.000 | 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".