Anticitrullinated Protein Antibodies Induce Inflammatory Gene Expression Profile in Peripheral Blood Cells from CCP–positive Patients with RA
Bibliographic record
Abstract
OBJECTIVE: Anticitrullinated protein antibodies (ACPA) have major diagnostic significance in rheumatoid arthritis (RA). ACPA are directed against different citrullinated antigens, including filaggrin, fibrinogen, vimentin, and collagen. The presence of ACPA is associated with joint damage and extraarticular manifestations, suggesting that ACPA may have a significant role in the pathogenesis of RA. METHODS: with ACPA. ACPA-positive stained cells were analyzed by flow cytometry and the effect of ACPA on mRNA expression levels was evaluated by real-time PCR. We tested whether the stimulatory effects induced by ACPA could be inhibited by the addition of a new multiepitope citrullinated peptide (Cit-ME). RESULTS: We found that ACPA bind specifically to PBMC from CCP-positive patients with RA through the Fab portion. ACPA induce upregulation of pathogenic cytokine expression (4- to 13-fold increase) in PBMC derived from CCP-positive patients with RA. Moreover, ACPA upregulated IL-1β and IL-6 mRNA expression levels by 10- and 6-fold, respectively, compared to control IgG. Cit-ME, a genuine ligand of ACPA, inhibited the ACPA-induced upregulation of IL-1β and IL-6 by 30%. CONCLUSION: ACPA bind to a limited percentage of PBMC and upregulate inflammatory cytokine expression, suggesting that ACPA is involved in RA pathogenesis. Targeting ACPA to decrease their pathogenic effects might provide a novel direction in developing therapeutic strategies for RA.
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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 | 0.000 | 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) | 0.002 | 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".