Heparin inhibits the interaction of DNA topoisomerase I/anti–topoisomerase I immune complexes with heparan sulfate on dermal fibroblasts
Bibliographic record
Abstract
OBJECTIVE: Previous studies have demonstrated that the systemic sclerosis (SSc)-associated autoantigen DNA topoisomerase I (topo I) binds specifically to the surface of fibroblasts when released in the extracellular environment and recruits anti-topo I autoantibodies, which subsequently leads to the adhesion and activation of monocytes. This study aimed to characterize the molecular interactions of topo I with fibroblast surfaces in order to elucidate the pathogenic role of topo I/anti-topo I immune complexes (ICs) in SSc. METHODS: Topo I directly coupled to fluorochromes was used to follow its binding to fibroblast surfaces by flow cytometry and fluorescence microscopy. Purified IgG from normal subjects or SSc patients was added with topo I to the cells; unfractionated heparin (UFH) and low molecular weight heparin (LMWH) were used to determine their effects on the binding of topo I and topo I/anti-topo I IC to fibroblast surfaces. RESULTS: Heparan sulfate (HS) proteoglycans on fibroblast surfaces were found to act as coreceptors for topo I binding. The addition of anti-topo I autoantibodies from SSc sera led to the amplification of topo I binding to HS chains. UFH and LMWH were shown to inhibit topo I and topo I/anti-topo I IC binding to HS chains. CONCLUSION: This study is the first to show that topo I binds specifically to HS proteoglycans on fibroblast surfaces and that anti-topo I autoantibodies from SSc patients amplify topo I binding to HS chains. The accumulation of topo I on cell surfaces by anti-topo I autoantibodies could contribute to the initiation of an inflammatory cascade stimulating the fibrosis. UFH and LMWH inhibited the binding of topo I/anti-topo I IC to fibroblasts, suggesting a potential therapeutic role in SSc-associated fibrosis.
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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) | 0.001 | 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 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".