Determinants of synoviocyte clearance of arthritogenic bacteria.
Bibliographic record
Abstract
OBJECTIVE: Persistence of intracellular organisms may play a critical role in the initiation and perpetuation of synovitis in reactive arthritis (ReA). We investigated factors that may influence local clearance of arthritogenic pathogens in ReA. METHODS: We studied 11 HLA-B27 positive patients with spondyloarthropathies and contrasted these patients with 6 HLA-B27 negative control patients with rheumatoid arthritis or osteoarthritis. We employed an ex vivo system in which human synoviocytes derived from patients with ReA are cocultured with arthritogenic pathogens, and intracellular clearance is measured by quantitating colony-forming units over time. RESULTS: The clearance kinetics of the organisms bore no relationship to the HLA-B27 status of the patient. Clearance of S. typhimurium over a 10 day period was accompanied by a progressive rise in nitric oxide (NO) production, but this appeared not to be rate-limiting, since (1) clearance kinetics were comparable between high versus low NO-producing synoviocytes; and (2) L-NMMA inhibition of NO production did not alter clearance kinetics of S. typhimurium. Interferon-g (IFN-g) was observed to have a small but measurable effect on bacterial clearance. In certain patients with ReA there was a paradoxical stimulatory response to IFN-g, in which the addition of IFN-g was accompanied by an increase in intracellular bacteria. This effect was found to be attributable to IFN-g mediated suppression of NO production in these cells. This pattern was not observed in B27 negative synoviocytes. CONCLUSION: Intracellular persistence of arthritogenic organisms may contribute to the cellular basis of ReA, but the molecular basis of the bacteriocidal pathways in synoviocytes has not been fully resolved. Our findings indicate that a direct effect of HLA-B27 on these events is unlikely, but that alterations in cytokine response profiles may play a contributory role. Characterizing these mechanisms holds the promise of more specific therapeutic interventions in this disease.
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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) | 0.004 | 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".