Protein composition of clots detected in pooled cryoprecipitate units
Bibliographic record
Abstract
BACKGROUND: On rare occasions, upon thawing of stored cryoprecipitate components, clots are observed on visual inspection. Although it has been assumed that the clot reflects fibrinogen to fibrin conversion, there are few published studies that document that this assumption is correct. Our studies were conducted to further identify the protein characteristics of the clotted material. STUDY DESIGN AND METHODS: Clotted material isolated from four thawed cryoprecipitate pools was examined by solubilization procedures and electrophoresis analysis. RESULTS: Solubilization of much of the clotted material in phosphate-buffered saline warmed to 37°C suggested the presence of soluble fibrin. Gel electrophoresis under reducing conditions showed that the most prevalent bands exhibited molecular weights corresponding to the α, β, and γ subunits of fibrinogen with a much lighter band exhibiting the molecular weight of fibrinogen γ-γ dimer, consistent with the presence of partially crosslinked fibrin. The presence of the dimer indicated that the clotted material was caused by the action of thrombin, but also reflected the action of Factor XIIIa. No ongoing clot formation was observed. CONCLUSION: Our studies indicate that, on rare occasions, fibrinogen conversion to fibrin is responsible for observable clots in thawed cryoprecipitate pools. These clots are structurally heterogeneous, including both noncrosslinked (soluble) and crosslinked (insoluble) fibrin. This diversity in the fibrin structure may account for some of the diversity in the limited literature regarding their presence in cryoprecipitate pools.
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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) | 0.002 | 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".