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Record W2048581686 · doi:10.1139/cjc-2014-0349

A comparison of covalent and noncovalent strategies for paclitaxel release using poly(ester amide) graft copolymer micelles

2014· article· en· W2048581686 on OpenAlexafffundvenue
Abdolrasoul Soleimani, Mahmoud M. Abd Rabo Moustafa, Aneta Borecki, Elizabeth R. Gillies

Bibliographic record

VenueCanadian Journal of Chemistry · 2014
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMicelleCopolymerChemistryEthylene oxideConjugated systemAmphiphileDrug deliveryCovalent bondPolymer chemistryAmideControlled releaseDrug carrierOrganic chemistryPolymerAqueous solutionNanotechnologyMaterials science

Abstract

fetched live from OpenAlex

Micelles formed from amphiphilic copolymers are promising for the delivery of drug molecules, potentially leading to enhanced properties and efficacies. Critical aspects of these systems include the use of biocompatible, biodegradable polymer backbones as well as the ability to control the incorporation of drugs and their release rates. In this work, a poly(ester amide)–poly(ethylene oxide) graft copolymer with paclitaxel conjugated via ester linkages was prepared and assembled into micelles. For comparison, micelles with physically encapsulated paclitaxel were also prepared. The release rates of these two systems were studied, and the micelles with covalently conjugated paclitaxel exhibited a prolonged release of the drug in comparison to the noncovalent system, which rapidly released the payload. In vitro studies suggested that the poly(ester amide)–poly(ethylene oxide) copolymers were nontoxic, whereas the toxicities of the drug-loaded micelles were dependent on their release rates. Overall, these systems are promising for further development as anticancer drug carriers.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.278
Teacher spread0.253 · 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 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

Citations11
Published2014
Admission routes3
Has abstractyes

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