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Record W4401103871 · doi:10.3390/foods13152406

Hyaluronic Acid-Coated Nanoliposomes as Delivery Systems for Fisetin: Stability, Membrane Fluidity, and Bioavailability

2024· article· en· W4401103871 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.

Bibliographic record

VenueFoods · 2024
Typearticle
Languageen
FieldMedicine
TopicFlavonoids in Medical Research
Canadian institutionsMinistry of Education and Child Care
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsFisetinChemistryLiposomeBioavailabilityMembrane fluidityMembraneHyaluronic acidChemical engineeringHydrophobeBiophysicsOrganic chemistryBiochemistryAntioxidant

Abstract

fetched live from OpenAlex

Fisetin has shown numerous health benefits, whereas its food application is constrained by water insolubility, poor stability, and low bioaccessibility. This work investigated the potential of hyaluronic acid (HA)-coated nanoliposomes for the encapsulation and delivery of fisetin. It was observed that HA can adsorb onto the liposomal membrane through hydrogen bonding and maintain the spherical shape of nanoliposomes. Fluorescence analysis suggested that the HA coating restricted the motion and freedom of phospholipid molecules in the headgroup region and reduced the interior micropolarity of the nanoliposomes but did not affect the fluidity of the hydrophobic core. These effects were more pronounced for the HA with a low molecular weight (35 kDa) and moderate concentration (0.4%). The HA coating improved the storage and thermal stability of the nanoliposomes, as well as the digestive stability and bioaccessibility of the encapsulated fisetin. These findings could guide the development of HA-coated nanoliposomes for the controlled delivery of hydrophobic bioactives such as fisetin in functional foods.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.125
Threshold uncertainty score0.822

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
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)0.0010.000

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 head0.054
GPT teacher head0.350
Teacher spread0.296 · 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