Bacterial peptidoglycan drives synovial inflammation in osteoarthritis
Bibliographic record
Abstract
Abstract Peptidoglycan (PG) is a potent inflammatory mediator. We have previously demonstrated that PG is present in the synovial tissue of osteoarthritis (OA) patients but its role in OA inflammation remains unknown. We hypothesized that PG in synovial tissue drives inflammation in OA. Intraoperative synovial tissue and synovial fluid samples were obtained from 56 consecutive patients with OA, with no prior history of infection. PG in synovial tissue was detected by immunohistochemical (IHC) staining of serial sections of 10 mm2 of tissue with anti-PG antiserum. PG was found in 33/56 (59%) of the tissue samples using IHC, with a median of eight PG occurrences per 10 mm2 in PG-positive samples. Tissue inflammation and fibrosis were assessed by histopathology. Cellular localization was further characterized in three PG-positive tissue samples by immunofluorescent microscopy (IFM). PG was localized to cells demonstrating mononuclear and fibroblastic morphology primarily in and around areas of vascularization and inflammation. CD68+ macrophages and to a lesser degree CD90+ synovial sublining fibroblasts. In multiplex assay analysis of synovial fluid cytokine levels, IL-6 and PG abundance were positively correlated. Fibroblasts and macrophages stimulated with PG in vitro secreted high levels of innate cytokines, paricularly IL-6 when measured by supernatant cytokine quantification. Together these data support the hypothesis that PG in synovial tissue drives joint inflammation in OA.
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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 | 0.000 | 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) | 0.001 | 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".