Characterisation of myeloid cells in circulation and synovial fluid of patients with psoriatic arthritis
Bibliographic record
Abstract
OBJECTIVE: Psoriatic arthritis (PsA) is an inflammatory arthritis associated with psoriasis. Adding to studies focused on the role of T cells and macrophages, we sought to investigate the systemic activation of leukocytes in PsA. METHODS: We assessed the activation state of leukocyte populations, including polymorphonuclear neutrophils (PMNs) and monocyte/macrophages, in blood and synovial fluid (SF) by multicolour flow cytometry. We also evaluated the correlation between leukocyte numbers and expression of activation markers with disease activity parameters. RESULTS: SF PMNs showed an elevated activation state compared with blood PMNs, but a reduced activation state compared with oral PMNs of non-arthritic controls. In vitro stimulation caused SF PMNs to become further activated, demonstrating that they retain a reserve capacity for activation in response to specific triggers. We found significant variability between patients in the expression of SF PMN CD activation markers, indicating a range of possible activation states across patients. However, PMN CD marker expression remained consistent over two sequential visits in a subset of patients, indicating patient-specific distinct inflammatory states during flares. We further found that markers of disease activity increased with elevated SF macrophage numbers. Expression of several CD markers on blood or SF cells, for example, PMN expression of the high-affinity Fc-receptor CD64, correlated with disease activity markers, including pain score and Disease Activity in Psoriatic Arthritis score. CONCLUSION: These preliminary findings support a potential role for surface antigens on PMNs and monocytes/macrophages as prognostic or disease activity monitoring tools.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".