Albacore tuna (<i>Thunnus alalunga</i>) spleen trypsin partitioning in an aqueous two-phase system and its hydrolytic pattern on Pacific white shrimp (<i>Litopenaeus vannamei</i>) shells
Bibliographic record
Abstract
Partitioning behaviors of trypsin from the spleen of albacore tuna (Thunnus alalunga) in an aqueous two-phase system (ATPS) were investigated. Partitioning behaviors of proteins were influenced by polyethylene glycol (PEG) molecular mass and concentration, types and concentration of salts, NaCl concentration, and temperature. Trypsin was preferentially partitioned into the PEG-rich top phase. The best ATPS conditions for trypsin partitioning from albacore tuna spleen were 15% PEG 4000–15% NaH2PO4 at 40°C without the addition of NaCl, which increased the purity by 5.54-fold with the recovered activity of 71.92%. Based on SDS-PAGE, the enzyme after ATPS separation was near homogeneity and the result of SDS-substrate gel electrophoresis revealed that the band intensity of enzyme in ATPS fraction increased, indicating the enhanced specific activity of splenic extract. The study further investigated the effect of fractionated trypsin on the hydrolysis of Pacific white shrimp (Litopenaeus vannamei) shells. Electrophoretic study revealed that trypsin after ATPS separation was a potential enzyme for extraction of carotenoprotein from Pacific white shrimp shell waste. Therefore, ATPS was an effective method for purification and recovery of trypsin from the spleen of albacore tuna and it could be used as an alternative cheap proteinase for the extraction of carotenoprotein from shrimp shells.
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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 | 0.000 |
| 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 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".