Osteoclasts and their circulating precursors in rheumatoid arthritis: Relationships with disease activity and bone erosions
Bibliographic record
Abstract
Patients with rheumatoid arthritis (RA) have very different outcomes, particularly with regard to bone erosions. Since osteoclasts are responsible for bone destruction adjacent to rheumatoid synovium, profiling osteoclasts from circulating precursors in RA could help identify patients at risk for bone destruction. In this study, we sought to determine whether the functional characteristics of osteoclasts generated from their blood precursors were modified by RA activity or were intrinsic to osteoclasts and associated with the RA phenotype (erosive or not). Osteoclasts were generated in vitro from peripheral blood mononuclear cells (PBMCs) of subjects with RA (n = 140), as well as sex- and age-matched healthy controls (n = 101). Osteoclastic parameters were analyzed at baseline and during the follow-up for up to 4 years, with regular assessment of RA activity, bone erosions, and bone mineral density (BMD). As a validation cohort, we examined RA patients from the Early Undifferentiated PolyArthritis (EUPA) study (n = 163). The proportion of CD14+ PBMC was higher in RA than in control subjects, but inversely correlated with the 28-joint disease activity score (DAS28). Also surprisingly, in osteoclast cultures from PBMCs, active RA was associated with lower osteoclastogenic capacity, while in vitro bone resorption per osteoclast and resistance to apoptosis were similar in both active and quiescent RA. In a small subgroup analysis, osteoclasts from subjects with recent RA that had progressed at four years to an erosive RA exhibited at baseline greater resistance to apoptosis than those from patients remaining non-erosive. Our findings establish that when RA is active, circulating monocytes have a reduced potential to generate osteoclasts from PBMCs in vitro. In addition, osteoclasts associated with erosive disease had resistance to apoptosis from the start of 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".