Cross-linking of IgGs bound on circulating neutrophils leads to an activation of endothelial cells: possible role of rheumatoid factors in rheumatoid arthritis-associated vascular dysfunction
Bibliographic record
Abstract
BACKGROUND: Rheumatoid arthritis is characterized by the presence of circulating auto-antibodies, including rheumatoid factors, which recognize the Fc portion of IgGs. The neutrophil is the most abundant circulating leukocyte and it expresses high levels of FcγRs on its surface. The aim of the present study was to examine the capacity of circulating human neutrophils to be activated by rheumatoid factors and the consequences of these events on endothelium. METHODS: Neutrophil-bound IgGs were cross-linked with anti-human IgGs to mimick the presence of circulating rheumatoid factors and FcγRs-dependent signalling events and functions were examined. The IgG and IgM composition of rheumatoid factors isolated from the serum of RA patients was characterized. Adhesion of neutrophils to endothelial cells was quantified in response to the addition of rheumatoid factors. RESULTS: Cross-linking of IgGs bound on neutrophils leads to FcγRs-dependent tyrosine phosphorylation, mobilisation of intracellular calcium and the extracellular release of superoxide anions and lysozyme. Incubation of endothelial cells with the supernatant of activated neutrophils increases ICAM-1 expression and IL-8 production by endothelial cells. Finally, rheumatoid factors enhance neutrophil adhesion to endothelial cells. CONCLUSIONS: Our results show that activation of neutrophils' FcγRs by rheumatoid factors could participate in rheumatoid arthritis-associated vascular damage.
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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 | 0.000 |
| 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".