Functional analysis of fibrin γ-chain cross-linking by activated factor XIII: determination of a cross-linking pattern that maximizes clot stiffness
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Bibliographic record
Abstract
Activated coagulation factor XIII (FXIIIa) cross-links the gamma-chains of fibrin early in clot formation. Cross-linking of the alpha-chains occurs more slowly, leading to high molecular weight multimer formations that can also contain gamma-chains. To study the contribution of FXIIIa-induced gamma-chain cross-linking on fibrin structure and function, we created 2 recombinant fibrinogens (gammaQ398N/Q399N/K406R and gammaK406R) that modify the gamma-chain cross-linking process. In gammaK406R, gamma-dimer cross-links were absent, but FXIIIa produced a cross-linking pattern similar to that observed in tissue transglutaminase cross-linked fibrin(ogen) with mainly alpha-gamma cross-links. In Q398N/Q399N/K406R, cross-links with any gamma-chain involvement were completely absent, and only alpha-chain cross-linking occurred. Upon cross-linking, recombinant normal fibrin yielded a 3.5-fold increase in stiffness, compared with a 2.5-fold increase by alpha-chain cross-linking alone (gammaQ398N/Q399N/K406R). gammaK406R fibrin showed a 1.5-fold increase in stiffness after cross-linking. No major differences in clot morphology, polymerization, and lysis rates were observed, although fiber diameter was slightly lower in cross-linked normal fibrin relative to the variants. Our results show that gamma-chain cross-linking contributes significantly to clot stiffness, in particular through gamma-dimer formation; alpha-gamma hybrid cross-links had the smallest impact on clot stiffness.
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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 | 0.001 |
| 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 it