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 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) | 0.001 | 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".