ADAMTS13 activity in sickle cell disease
Bibliographic record
Abstract
Sickle red blood cell (SRBC)-endothelial adhesion plays a central role in sickle cell disease (SCD)-related vaso-occlusion. As unusually large von Willebrand factor (ULVWF) multimers mediate SRBC-endothelial adhesion, we investigated the activity of ADAMTS13, the metalloprotease responsible for cleaving ULVWF multimers, in SCD. ADAMTS13 activity was determined using a quantitative immunoblotting assay. VWF:Ag and VWF:RCo were determined using commercial assays. The high-molecular-weight VWF multimer percentage was determined by employing gel electrophoresis. ADAMTS13 activity was similar among asymptomatic patients (n = 8), patients at presentation with a painful crisis (n = 23), and healthy controls. ADAMTS13/VWF:Ag ratios were lower in patients compared to healthy HbAA controls, with the lowest values at presentation with a painful crisis (P = 0.02). Division of samples in those with VWF:RCo/VWF:Ag ratios < 0.70 and those with ratios >or= 0.70 revealed significantly more samples with ratios >or= 0.70 (P = 0.01) collected during painful crises. ULVWF multimers were detected in 6 patient samples and in 1 control sample. ADAMTS13/VWF:Ag ratios were inversely related to the duration of symptoms at presentation with an acute vaso-occlusive event (r(s)-0.67, P = 0.002). Although SCD is characterized by elevated VWF:Ag levels, no severe ADAMTS13 deficiency was detected in our patients.
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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 | 0.001 |
| 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 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".