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Record W2886276359 · doi:10.1080/10942912.2018.1494199

Changes in apoptosis factors and activation of caspase-3 in tilapia muscle during storage

2018· article· en· W2886276359 on OpenAlexaff
Yanfu He, Hui Huang, Laihao Li, Xianqing Yang, Yongqiang Zhao

Bibliographic record

VenueInternational Journal of Food Properties · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCell death mechanisms and regulation
Canadian institutionsMinistry of Agriculture
FundersPearl River S and T Nova Program of GuangzhouGuangdong Science and Technology DepartmentNational Natural Science Foundation of China
KeywordsCytochrome cApoptosisCaspase-9Caspase 3TilapiaCytosolCytochromeChemistryCaspaseMitochondrionBiochemistryBiologyMolecular biologyCell biologyEnzymeFish <Actinopterygii>Programmed cell deathFishery

Abstract

fetched live from OpenAlex

The activation of the apoptosis pathway in tilapia muscle during postmortem storage was studied. Changes in caspase-3 activity, ATP content, cytochrome c levels, and ratio of Bcl-2/Bax levels of tilapia muscle were observed during postmortem storage at 20°C. Caspase-3 activity was found to be significantly increased at first, followed by a decrease (P < 0.05); the highest caspase-3 activity was observed at 1 h. The ATP content decreased significantly (P < 0.05), and almost exhausted after 10 h storage. The cytochrome c level in the cytosol showed a significant increase after 5 h of storage (P < 0.05), while the mitochondrial cytochrome c levels showed a decrease. The Bcl-2/Bax ratio was stable from 0–5 h, followed by a rapid decreased at 10–20 h and a significant increased after 20 h (P < 0.05), suggesting that the apoptosis process occurred until 20 h of postmortem storage. Thus, we concluded that the availability of ATP and the increase in cytosolic cytochrome c levels are essential for the activation of caspase-3, and that the former partly limits caspase-3 activity.

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 score0.067
Threshold uncertainty score0.162

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 head0.019
GPT teacher head0.232
Teacher spread0.213 · 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

Citations11
Published2018
Admission routes1
Has abstractyes

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