Direct Binding of Lupus Anticoagulant Antibodies to Nonbilayer Phosphatidylethanolamine
Bibliographic record
Abstract
The present study describes a new phase-specific assay system for the detection of anti-phospholipid antibodies, based on the finding by 3IP NMR analysis that phospholipid can be quantitatively retained on nitrocellulose paper in a phase-sensitive fashion. Using this system, we demonstrate that human hybridoma lupus anticoagulant antibodies bind directly to nonbilayer phase phosphatidylethanolamine, a lipid architecture that we have shown specifically inhibits lupus anticoagulant activity and is recommended for confirmation of the diagnosis of these antibodies. We have analyzed 33 human hybridoma antibodies, of which 16 had lupus anticoagulant antibody activity. Seventy-five percent of the lupus anticoagulant antibodies bound directly to nonbilayer phase phosphatidylethanolamine, while only 12% bound to immobilized lamellar phase phosphatidylethanolamine. In contrast, none of the 17 hybridoma antibodies without lupus anticoagulant activity bound to either lamellar or nonbilayer phase phosphatidylethanolamine. Forty-four percent and 62%, respectively, of the lupus anticoagulant antibodies bound to dioleoylphosphati-dylserine and cardiolipin, both negatively charged bilayer phase phospholipids. These data provide the first direct demonstration of the preferential reactivity of human lupus anticoagulant antibodies with nonbilayer phosphati-dylethanolamine. The structurally sensitive solid phase assay system described here provides the means to study a variety of phospholipid epitopes and to further analyse the role of phospholipid architecture in anti-phospholipid antibody syndromes.
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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".