Direct binding of anti–DNA topoisomerase I autoantibodies to the cell surface of fibroblasts in patients with systemic sclerosis
Bibliographic record
Abstract
OBJECTIVE: Fibroblasts play a crucial role in the development of systemic sclerosis (SSc), and antifibroblast antibodies (AFAs) capable of inducing a proinflammatory phenotype in fibroblasts have been detected in the sera of SSc patients. This study examined the prevalence of AFAs in SSc and other diseases and the possible correlation between AFAs and known antinuclear antibody specificities in SSc patients. METHODS: Sera from 99 patients with SSc, 123 patients with other autoimmune and nonautoimmune diseases, and 30 age- and sex-matched healthy controls were examined. AFA prevalence was assessed by flow cytometry and further characterized by indirect immunofluorescence, enzyme-linked immunosorbent assay (ELISA), and immunoblotting. Anti-topoisomerase I (anti-topo I) from SSc sera were purified by affinity chromatography on topo I. RESULTS: AFAs were more common in SSc patients (26.3%) than in any other disease groups studied. The presence of AFA was significantly associated with pulmonary involvement and death. AFA-positive sera from SSc patients bound to all human and rodent fibroblasts tested, but not to human primary endothelial cells or smooth muscle cells. All SSc AFAs strongly reacted with topo I by ELISA and immunoblotting. The binding intensity of SSc AFAs correlated strongly with reactivity against topo I on immunoblots of fibroblast extracts and with the immunofluorescence pattern typical of anti-topo I on permeabilized cells. Total IgG and affinity-purified anti-topo I from AFA-positive SSc sera were found to react with the surface of unpermeabilized fibroblasts by flow cytometry as well as by immunofluorescence and confocal microscopy. CONCLUSION: This is the first report establishing that AFAs in SSc are strongly correlated with anti-topo I and, furthermore, that anti-topo I antibodies themselves display AFA activity by reacting with determinants at the fibroblast surface.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 teacher head, 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".