Purification of protein C from canine plasma
Bibliographic record
Abstract
BACKGROUND: In order to characterize the functional properties of canine protein C (CnPC), the zymogen needs to be purified from plasma. The goals of this study were (1) to purify protein C from fresh frozen canine plasma by barium chloride and ammonium sulphate precipitation, followed by immunoaffinity chromatography using a monoclonal mouse antibody against human protein C (HPC4) and (2) to characterize this protein's structure. RESULTS: The purified protein contained three glycosylated forms of a heavy chain (~49 kDa) and a glycosylated light chain (~ 25 kDa). Tandem mass spectra of the peptides obtained following trypsin digestion and liquid chromatography identified this protein to be protein C (vitamin K-dependent protein C precursor, gi|62078422) with 100% probability. Three glycosylation sites (Asn139, Asn202, and Asn350) were identified by detection of peptides containing an N-linked glycosylation consensus sequon with a 3-dalton increase in mass following incubation of the protein with PNGase F in 18O-labeled water. Following incubation with Protac (a specific activator of protein C), the heavy chain showed a slight decrease in molecular size and amidolytic activity measured by a synthetic chromogenic substrate containing an amide bond [H-D-(γ-carbobenzoxyl)-lysyl-prolyl-arginine-paranitroanilide diacetate salt]. The amidolytic activity was increased by ~303-fold in the final protein preparation compared to that in plasma. The purified protein showed concentration-dependent anti-factor V and anti-factor VIII activities in canine plasma in coagulometric factor assays. CONCLUSIONS: These studies showed that CnPC could be purified from plasma using HPC4 and that this protein showed amidolytic and anti-coagulant properties upon activation with Protac.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 |
| 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 teacher head, 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".