Autoimmune antiphospholipid antibodies and cryoglobulinemia
Bibliographic record
Abstract
In addition to their role in the thrombotic manifestations of the antiphospholipid syndrome (APS), autoimmune antiphospholipid (aPL) antibodies may also be responsible for direct injury to the blood vessel wall, although the mechanism is unclear. Cryoglobulinemia has been reported infrequently in patients with APS and is one potential means of blood vessel injury. The aim of the present study was to determine if autoimmune aPL antibodies and their target antigens contribute to the formation of cryoprecipitates. Cryoglobulins were identified and isolated from 5 of 8 patients with autoimmune aPL antibodies. Using identical concentrations of immunoglobulins isolated from matched sera and washed cryoprecipitates there was a significant enrichment (at least 100%) of aCL antibodies in the cryoprecipitates from 4 of 5 patients. This involved IgG, IgM and IgA isotypes with specificity for both beta2-glycoprotein I (GPI) and prothrombin (PT). The target antigens were detected in cryoprecipitates from all 5 aPL positive patients and in cryoprecipitates from 3 controls. These results suggest that anti-beta2-GPI and anti-PT antibodies in association with their target antigens are integrally involved in the formation of cryoprecipitates in patients with autoimmune aPL antibodies and provide insight into a potential mechanism for blood vessel injury.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".