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Protein Structural Changes During Preparation and Storage of Surimi

2005· article· en· W2130336306 on OpenAlexaff
Marzieh Moosavi‐Nasab, Inteaz Alli, Ashraf A. Ismail, Michael Ngadi

Bibliographic record

VenueJournal of Food Science · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicMeat and Animal Product Quality
Canadian institutionsMcGill University
Fundersnot available
KeywordsChemistryDifferential scanning calorimetryFourier transform infrared spectroscopyChromatographyMyofibrilGel electrophoresisMyosinElectrophoresisTropomyosinDenaturation (fissile materials)Dynamic mechanical analysisPolyacrylamide gel electrophoresisBiochemistryNuclear chemistryChemical engineeringOrganic chemistry

Abstract

fetched live from OpenAlex

ABSTRACT: The changes in protein structure associated with the preparation and frozen storage of surimi were investigated. Raw surimi was prepared by repeatedly washing Alaska pollock flesh with chilled water. The product was either slowly frozen or underwent rapid freezing using liquid air; in either case it was then subjected to frozen storage at ‐20 °C for 24 mo. Fourier transform infrared/attenuated total reflectance (FTIR/ATR) spectroscopy showed that during preparation of surimi, the a‐helix content increased with increased number of washing cycles. Differential scanning calorimetry (DSC) revealed a shift in the thermal transition of actin to a higher temperature during surimi preparation. Electrophoresis, FTIR/ATR spectroscopy, and DSC results revealed a loss of myofibrillar proteins from surimi after 3 washing cycles, suggesting that 3 washing cycles were adequate to prepare surimi. Sodium dodecyl sulfate‐polyacrylamide gel electrophoresis (SDS‐PAGE) showed relatively minor changes in protein subunit structure with some loss of the myosin light chains (MLC); myosin heavy chain (MHC), actin, and tropomyosin were found to be relatively stable. Native‐PAGE showed no major changes in surimi after 24 mo storage at ‐20 °C. FTIR/ ATR spectroscopy indicated a significant decrease in a‐helix relative to p‐sheet structure in surimi after 2 y of storage at ‐20 °C. The loss of α‐helical content was more significant in slowly frozen surimi compared with rapid‐frozen surimi samples. DSC results revealed a shift in the thermal transition of actin to lower temperatures during frozen storage of surimi.

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)0.001
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 score0.271
Threshold uncertainty score0.103

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.046
GPT teacher head0.275
Teacher spread0.230 · 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

Citations45
Published2005
Admission routes1
Has abstractyes

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