Differences in prethrombin-1 activation with human or bovine factor Va can be attributed to the heavy chain
Bibliographic record
Abstract
Human and bovine factor Va (FVa) function similarly in the activation of prothrombin but differently in the activation of prethrombin-1 (Pre-1). Pre-1 activation with human FVa proceeds at about 22 percent of the rate with bovine FVa. The dependencies of initial rates on the FVa and Pre-1 concentrations indicate that the differential activity is expressed in kcat differences, rather than differences in the assembly of prothrombinase or the K(m) value of the substrate. The heavy and light chains of both species of FVa were separated and interspecies hybrids were constructed in the presence of Ca(++). Studies of the activation of Pre-1 with these hybrids indicate that the species difference can be attributed specifically to the heavy chain of FVa. Analyses of the reactions by SDS-PAGE indicated that cleavage at Arg271 occurs at about the same rate with both species of FVa, but cleavage at Arg320 with human FVa is specifically retarded. A major difference in primary structure between the human and bovine FVa heavy chains comprises 10 residues at COOH-terminus, adjacent to the negatively charged hirudin-like DYDYQ sequence. These residues have pI values of 12.5 and 4.26 in human and bovine FVa, respectively. The lower value would complement the negatively charged DYDYQ sequence but the higher value would counteract it. Thus, we suggest that the differences in the COOH-terminus of the heavy chain are responsible for the differences in Pre-1 activation, and that it specifically influences cleavage at Arg320 in Pre-1.
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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 | 0.000 |
| 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) | 0.002 | 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".