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Record W173855628 · doi:10.1021/bk-2006-0934.ch010

Chitosan as a Biomaterial for Preparation of Depot-Based Delivery Systems

2006· book-chapter· en· W173855628 on OpenAlexaff
Justin Grant, Christine Allen

Bibliographic record

VenueACS symposium series · 2006
Typebook-chapter
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsChitosanDepotDrug deliveryBiomaterialNanotechnologyMicrosphereNatural polymersMaterials scienceDelivery systemPolymerBiomedical engineeringMedicineChemical engineeringEngineeringComposite material

Abstract

fetched live from OpenAlex

Chitosan is a natural polysaccharide that has become established as a material with great potential for use in biomedical applications. In addition, the recent success of many polymeric depot delivery systems has encouraged further research to identify new materials and develop new systems for use in regional therapy. Several strategies have been developed for preparation of stable chitosan-based depot systems for drug delivery. Chitosan can be physically or chemically crosslinked to prepare microspheres, films and gels. Chitosan has also been blended with a wide range of polymers to produce mostly two-phase systems, which have unique properties that are required for specific applications. These stable chitosan-based depot systems have been investigated for treatment of various diseases including cancer and bacterial infection. This review includes a summary of the favorable chemical, physical and biological properties of chitosan. In addition, the properties of an ideal depot system for use in drug delivery are outlined. Overall, it is hoped that the reader gains an appreciation for the use of chitosan-based systems for the regional or localized delivery of drugs.

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 categoriesMeta-epidemiology (narrow)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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 head0.010
GPT teacher head0.229
Teacher spread0.219 · 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.

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

Citations10
Published2006
Admission routes1
Has abstractyes

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