Macrophage proliferation distinguishes 2 subgroups of knee osteoarthritis patients
Bibliographic record
Abstract
Osteoarthritis (OA) is a leading cause of disability, globally. Despite an emerging role for synovial inflammation in OA pathogenesis, attempts to target inflammation therapeutically have had limited success. A better understanding of the cellular and molecular processes occurring in the OA synovium is needed to develop novel therapeutics. We investigated macrophage phenotype and gene expression in synovial tissue of OA and inflammatory-arthritis (IA) patients. Compared with IA, OA synovial tissue contained higher but variable proportions of macrophages (P < 0.001). These macrophages exhibited an activated phenotype, expressing folate receptor-2 and CD86, and displayed high phagocytic capacity. RNA sequencing of synovial macrophages revealed 2 OA subgroups. Inflammatory-like OA (iOA) macrophages are closely aligned to IA macrophages and are characterized by a cell proliferation signature. In contrast, classical OA (cOA) macrophages display cartilage remodeling features. Supporting these findings, when compared with cOA, iOA synovial tissue contained higher proportions of macrophages (P < 0.01), expressing higher levels of the proliferation marker Ki67 (P < 0.01). These data provide new insight into the heterogeneity of OA synovial tissue and suggest distinct roles of macrophages in pathogenesis. Our findings could lead to the stratification of OA patients for suitable disease-modifying treatments and the identification of novel therapeutic targets.
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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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".