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Record W2032733766 · doi:10.1055/s-0031-1273644

Nanoencapsulation: A New Trend in Delivering Botanical Health Products

2011· article· en· W2032733766 on OpenAlexaff
HH Hussien, Robin J. Marles, Shahriar Khadem

Bibliographic record

VenuePlanta Medica · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBee Products Chemical Analysis
Canadian institutionsHealth Canada
Fundersnot available
KeywordsBioavailabilityNutraceuticalChemistryHealth benefitsGenerally recognized as safeBioactive compoundTraditional medicineBiotechnologyMedicineBiochemical engineeringFood sciencePharmacologyBiologyBiochemistry

Abstract

fetched live from OpenAlex

Natural health products are valuable sources of bioactive compounds. In recent years, natural products have drawn a great deal of attention because of their potential to treat or prevent several serious chronic diseases, such as cancer and heart diseases. However, because of their low solubility and poor absorption, nanoencapsulation of phytochemicals is one of the most important innovations to enhance their bioavailability by changing their pharmacokinetics. Nanoencapsulation of botanicals involves forming active substance-loaded particles with diameters ranging from 1 to 1000nm, where botanical medicinal substances, such as limonene or lutein, are entrapped within a semi-permeable matrix. Applications of nanoencapsulation include controlled release, particle coating, taste masking, stabilization, and improvement of shelf life. Labile compounds, such as fatty acids, vitamins, antioxidants, hormones, and coenzymes, sensitive to any number of factors, can lose biological activity when unprotected, and the resulting decomposition products may also be toxic. Encapsulating unstable compounds can protect them from undesirable changes while retaining their pharmacological efficacy. Novel technologies have been developed to nanoencapsulate a multitude of bioactive ingredients in dietary supplements. It is expected that such nanoencapsulation product engineering practices will become very profitable in the near future given the enhanced functional properties and stability of these new formulations of botanicals and other supplements. Acknowledgements: Thanks go to our colleagues in the Clinical Trials Division, Natural Health Products Directorate, Health Canada.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.058
GPT teacher head0.220
Teacher spread0.162 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations0
Published2011
Admission routes1
Has abstractyes

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