Implications of Heparinoid-Induced Inactivation of Coagulation Cascade Factors and In Vivo Proenzyme Concentration.
Bibliographic record
Abstract
Abstract Heparin is a commonly used anticoagulant in the treatment of thrombosis. We have compared heparinoid-stimulated inhibition rates with the in vivo plasma concentration of antithrombin (AT)-inhibitable coagulation factors. Second order rate constants (k2) for inhibition of activated factors by either AT + unfractionated heparin (AT+UFH) mixtures or a novel covalent complex of AT and heparin (ATH) (Chan et al, J Biol Chem, 272:22111, 1997) were determined by discontinuous assay. A plot of k2 values (mean ± SEM; n ≥5) versus the respective human plasma concentration of coagulation factors revealed a linear correlation (with R2 values of 0.93 for AT+UFH and 0.90 for ATH, excluding factor XII), in which neutralization efficiency was proportional to in vivo factor level (see Figure). Anticoagulant actions of AT+UFH and ATH were more oriented towards treatment than prophylaxis since inhibition of cascade end point enzymes (thrombin and factor Xa) was more rapid than factors involved in coagulation initiation (factors VIIa and XIa). However, ATH exhibited more enhanced inhibition rates against factors VIIa, IXa and XIa than against factor Xa and thrombin, suggestive of an improved prophylactic profile compared to AT+UFH. Intriguingly, factor XII did not follow this trend, further challenging its role in the coagulation cascade. The impact of these assertions requires confirmation by in vivo inhibition studies. Figure Figure
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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 | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".