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Record W2570163555 · doi:10.1021/acs.jafc.6b04962

Rapid and Efficient Conversion of All-<i>E</i>-astaxanthin to 9<i>Z</i>- and 13<i>Z</i>-Isomers and Assessment of Their Stability and Antioxidant Activities

2017· article· en· W2570163555 on OpenAlexafffund
Cheng Yang, Lianfu Zhang, Hua Zhang, Qingrui Sun, Ronghua Liu, Jing Li, Leiyan Wu, Rong Tsao

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2017
Typearticle
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsAgriculture and Agri-Food Canada
FundersMinistry of Education of the People's Republic of ChinaAgriculture and Agri-Food CanadaNational Natural Science Foundation of China
KeywordsAstaxanthinAntioxidantChemistryDPPHBioavailabilityNutraceuticalIsomerizationHigh-performance liquid chromatographyIn vivoChromatographyEthyl acetateNuclear chemistryCatalysisOrganic chemistryBiochemistryBiology

Abstract

fetched live from OpenAlex

catalyst, yielding 22.7% and 16.9% of 9Z- and 13Z-astaxanthin, respectively, in 2 h, with 92-95% purity after semipreparative HPLC purification. 13Z-Astaxanthin had higher antioxidant activity than all-E- and 9Z-astaxanthins in oxygen radical absorbing capacity assay for lipophilic compounds, photochemiluminescence, and cellular antioxidant activity (CAA) assays, and 9Z-astaxanthin was higher in DPPH radical-scavenging activity assay and lower in CAA assay. All isomers were relatively stable between pH 2.0 and 11.6, except 13Z- and 9Z-astaxanthins at pH 2.0, suggesting they may be converted after passing the gastric phase in vivo. Metal ions did not significantly (p < 0.05) affect the stability. Results of the current study provides a means for further study into the mechanisms related to in vivo transformation and bioavailability of Z-astaxanthins, and their application in the development of functional foods and nutraceutical products.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.485
Threshold uncertainty score0.436

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.021
GPT teacher head0.261
Teacher spread0.239 · 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

Citations91
Published2017
Admission routes2
Has abstractyes

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