CATIONIC TRYPSIN: A PREDOMINANT PROTEINASE IN PACIFIC SAURY (COLOLABIS SAIRA) PYLORIC CECA
Bibliographic record
Abstract
ABSTRACT Cationic trypsin was purified from Pacific saury (Cololabis saira) pyloric ceca by the successive steps of ammonium sulfate precipitation, anion exchange chromatography and gel filtration chromatography. The purification and yield were 90-fold and 8.9%, respectively. The molecular weight was determined to be 24 kDa using Sephacryl S-200 and SDS-PAGE. Cationic trypsin was stable at pH 7–11 for 30 min at 30C, and its maximal activity against L-arginine methyl ester hydrochloride (TAME) was at pH 8.5. Thermostability for cationic trypsin was up to 50C for 15 min and its temperature optimum was 60C. Cationic trypsin was stabilized by calcium ion. Activity decreased as NaCl concentration (0–30%) increased. Inhibitor susceptibility analysis revealed that the enzyme was inhibited effectively by soybean trypsin inhibitor and N-p-tosyl-L-lysine chloromethyl ketone. The Km and Kcat of the enzyme were 0.17 mM and 200 s−1, respectively. The N-terminal amino acid sequence of cationic trypsin was partially determined as IVGGYECQPH- and was very homologous to other trypsins. PRACTICAL APPLICATIONS Trypsin is a major member of the serine proteases, which constitute a large family of biologically important enzymes. Trypsins from various sources catalyze the hydrolysis of peptide bonds on the carboxyl sides of arginine and lysine. Hence, it is expected that like other trypsins, Pacific saury trypsin would also be used for processing aids in industry applications. Most trypsins are used for a variety of products in the food industry including baked foods, beer, wine, cereal, meat and fish products, and for production of protein hydrolysates and flavor extract. Trypsins are also used in mammalian cell culture to disaggregate adherent cells for research and the production of recombinant proteins, in diabetes diagnosis and therapy, in detergents and bating of leather.
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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 | 0.000 | 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) | 0.000 | 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".