Rapid Interaction Between CTLA4-Ig (Abatacept) and Synovial Macrophages from Patients with Rheumatoid Arthritis
Bibliographic record
Abstract
To the Editor: We have demonstrated that macrophages could be considered one of the main direct target cells for treatment with CTLA4-Ig (abatacept) in patients with rheumatoid arthritis (RA), in mixed cultures of macrophages and activated T cells, or in primary single cultures of RA synovial macrophages1,2,3. Previous studies showed that a significant downregulation of tumor necrosis factor-α (TNF-α), interleukin 1β (IL-1β), and IL-6 was evident for cultured human macrophages treated with CTLA4-Ig, through direct interaction with B7 molecules on the surface of RA synovial macrophages at 24 h1. The interaction between CTLA4-Ig and B7 molecules (CD80/CD86) masked their expression on RA synovial macrophages1. From those results, we carried out further evaluations of cytokine production and modulation in RA synovial macrophage primary cultures at the gene expression level and after different short-term CTLA4-Ig treatments (3 and 12 hours), to further investigate the timing of the interaction of CTLA4-Ig and synovial macrophages. As well, we analyzed transforming growth factor-β (TGF-β) gene expression and production. Synovial macrophages were obtained, with informed … Address correspondence to Prof. M. Cutolo; E-mail: mcutolo{at}unige.it
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.007 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".