Major trypsin like-serine proteinases from albacore tuna (<i>Thunnus alalunga</i>) spleen: Biochemical characterization and the effect of extraction media
Bibliographic record
Abstract
This investigation aimed to characterize the proteinases and to study the effect of extraction media on proteinases recovery from albacore tuna spleen. Optimal activity of splenic extract was at pH 9.5 and 55°C. The enzyme was stable in a wide pH range of 6.0–10.0 but unstable at the temperatures greater than 50°C for 30–120 min. The proteolytic activity was strongly inhibited by soybean trypsin inhibitor, N-ethylmaleimide, phenylmethylsulfonyl fluoride (PMSF), and N-p-tosyl-L-lysine chloromethyl ketone (TLCK) and continuously decreased with increasing NaCl concentration. The molecular weights of spleen proteinases were 22, 24, 31, and 34 kDa based on the proteinase activity of zones separated by electrophoresis. Spleen powder isolation with 50 mM sodium phosphate buffer, pH 7.0 containing 1.25 M NaCl and 2% (v/v) Brij 35 gave a higher recovery of proteinase activity than other extractants tested (p < .05). Therefore, the major proteinases from spleen of albacore tuna were trypsin-like serine proteinases. Practical applications Extraction and recovery of proteinases from albacore tuna spleen contribute significantly to reduce the local pollution problem and increase valuable products from albacore tuna processing wastes. Moreover, the characteristics of the enzyme obtained can be utilized in the food, detergent, pharmaceutical, leather and silk industries.
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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) | 0.001 | 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) | 0.001 | 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 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".