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Record W4390470443 · doi:10.31665/jfb.2023.18360

Binding of carotenoids to proteins: a review

2023· review· en· W4390470443 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Food Bioactives · 2023
Typereview
Languageen
FieldMedicine
TopicAntioxidant Activity and Oxidative Stress
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarotenoidChemistryBinding affinitiesIn silicoAlgaeAntioxidantPigmentSolubilityAffinitiesBiochemistryBiologyOrganic chemistryBotanyGene

Abstract

fetched live from OpenAlex

Carotenoids are lipophilic natural pigments distributed in plants, certain types of algae, fungi and animals. The extensive conjugated double bond system in carotenoids is responsible for their unique color, antioxidant capacity and provide health benefits. However, the hydrophobic nature of carotenoids impacts their color and bioactivity during the development of food products due to their low solubility in aqueous media. The complexation of these molecules with proteins has proven to be an efficient approach for enhancing carotenoid’s solubility and protection against oxidative degradation and hence improving their functional properties and biological activities. This review compiles the molecular interactions between carotenoids and proteins, their physiological relevance, potential applications and characterization of their binding affinities, stabilities, and activities in terms of in-silico analysis and beyond. Overall, the deep understanding and interpretation of binding at the molecular level provide fundamental aspects for the inclusion of carotenoid bioactive compounds in fortified foods and pharmaceuticals.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.784
Threshold uncertainty score0.979

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0040.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.147
GPT teacher head0.414
Teacher spread0.268 · 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