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Record W2525791233 · doi:10.1111/jfbc.12323

Major trypsin like-serine proteinases from albacore tuna (<i>Thunnus alalunga</i>) spleen: Biochemical characterization and the effect of extraction media

2016· article· en· W2525791233 on OpenAlexaff
Tanchanok Poonsin, Pakteera Sripokar, Soottawat Benjakul, Benjamin K. Simpson, Wonnop Visessanguan, Sappasith Klomklao

Bibliographic record

VenueJournal of Food Biochemistry · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicProtein Hydrolysis and Bioactive Peptides
Canadian institutionsMcGill University
FundersThailand Graduate Institute of Science and TechnologyThaksin University
KeywordsAlbacorePMSFChemistryTunaKunitz STI protease inhibitorTrypsinChromatographyBenzamidinePhenylmethylsulfonyl FluorideBiochemistryThunnusEnzymeBiologyFisheryFish <Actinopterygii>

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.518

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.004
GPT teacher head0.211
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2016
Admission routes1
Has abstractyes

Explore more

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