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Record W2319771224 · doi:10.3109/02652048.2013.858792

Development of a novel drug delivery system: chitosan nanoparticles entrapped in alginate microparticles

2014· article· en· W2319771224 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

VenueJournal of Microencapsulation · 2014
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicAdvanced Drug Delivery Systems
Canadian institutionsUniversité Laval
FundersDélégation Générale pour l'Armement
KeywordsChitosanSonicationNanoparticlePolymerDrug carrierMaterials scienceDrug deliveryMicroparticleDissolutionChemical engineeringControlled releaseNanotechnologyAmaranthChromatographyChemistryComposite material

Abstract

fetched live from OpenAlex

A novel carrier using chitosan nanoparticles entrapped into alginate microparticles is proposed for protecting molecules of interest from degradation in the digestive tract. The effects of polymer concentration, sonication, stirring, pH, and processing conditions on the physical characteristics of the carrier were studied. FITC and RBITC were used to localise the polymers within particles using CLSM. Diffusion of amaranth red (AR) from nanoparticles was quantified during dissolution under gastric and intestinal conditions. Under optimal preparation conditions, the size distribution of nanoparticles loaded with AR was uniform (690 nm) with an encapsulation efficacy of 21.9%. Alginate microparticles (285 µm) containing a homogenous distribution of nanoparticles and polymers were obtained. At gastric pH, the carrier released less than 5% of the loaded AR and, at intestinal pH, the release was rapid and complete. The drug carriers developed shows a promising use as a vehicle suitable to protect molecules of interest after oral administration.

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)0.000
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 score0.010
Threshold uncertainty score0.659

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.059
GPT teacher head0.358
Teacher spread0.299 · 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