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Record W2980728391 · doi:10.1021/acs.jafc.9b04215

Morphology and Structure of Solid Lipid Nanoparticles Loaded with High Concentrations of β-Carotene

2019· article· en· W2980728391 on OpenAlexaff
Jakob Schjoerring‐Thyssen, Karsten Olsen, Klaus Koehler, Eric Jouenne, Dérick Rousseau, Mogens L. Andersen

Bibliographic record

VenueJournal of Agricultural and Food Chemistry · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicFood Chemistry and Fat Analysis
Canadian institutionsToronto Metropolitan University
FundersInnovationsfonden
KeywordsSunflower oilTriglycerideEmulsionCaroteneAmorphous solidChemistryNanoparticleLecithinChromatographyMaterials scienceChemical engineeringOrganic chemistryFood scienceCholesterolBiochemistryNanotechnology

Abstract

fetched live from OpenAlex

Solid lipid nanoparticles (SLNs) containing up to 37.5 wt % all-trans β-carotene in the lipid phase are potential water-dispersible food colorants. SLNs have been made by hot-melt high-pressure homogenization with fully hydrogenated sunflower oil and with polysorbate 80 and sunflower lecithin as stabilizers. Atomic force microscopy revealed the SLNs had thin platelet structures most likely derived from the triglyceride crystal β-form, as detected by X-ray diffraction. No indications of crystalline β-carotene were detected. High-performance liquid chromatography analysis showed the extensive isomerization of β-carotene into more than 10 cis isomers, suggesting that it is present as an amorphous mixture. The high β-carotene loadings did not affect the triglyceride crystal structure and the morphology of the SLNs. It is suggested the SLNs consist of a platelet core of crystalline triglyceride surrounded by an amorphous β-carotene-containing layer. The layered structure is suggested to affect the coloring power of the SLNs at β-carotene loadings above 15 wt % of the lipid phase.

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 score0.081
Threshold uncertainty score0.160

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 head0.006
GPT teacher head0.176
Teacher spread0.170 · 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

Citations21
Published2019
Admission routes1
Has abstractyes

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