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Record W2088640632 · doi:10.3109/1061186x.2013.824455

Physicochemical, pharmaceutical and biological approaches toward designing optimized and efficient hydrophobically modified chitosan-based polymeric micelles as a nanocarrier system for targeted delivery of anticancer drugs

2013· review· en· W2088640632 on OpenAlex
Mohammad Mahmoudzadeh, Afshin Fassihi, Jaber Emami, Neal M. Davies, Farid Abedin Dorkoosh

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 drug targeting · 2013
Typereview
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsChitosanNanocarriersMicelleDrug deliveryAmphiphileNanotechnologyChemistryAnticancer drugCombinatorial chemistryMaterials scienceDrugCopolymerOrganic chemistryPharmacologyPolymerMedicineAqueous solution

Abstract

fetched live from OpenAlex

Hydrophobically modified chitosan-based polymeric micelles (CBPMs) are formed through self-aggregation of chitosan amphiphilic derivatives. Their core-shell structure, diversity and the fact that all of their properties are adjustable through reconciling the interactions among their three main constituents: chitosan, hydrophilic segment and hydrophobic segment as well as with the outside medium through changing the ratio and chemical structure of each component's, chemical structure distinguish them from other chitosan-based drug delivery systems (DDSs) and give rise to these promising candidates for targeted delivery of lipophilic anticancer drugs. The majority of review articles conducted previously on chitosan-based DDSs have only made simple differential comparisons between such systems and the anticancer drugs that have been delivered through them. In this review article, all the basic properties of CBPMs including physicochemical, pharmaceutical and biological properties are technically detailed and discussed. The intention of this article is to outline and discuss salient features of CBPMs to contribute to the understanding of optimized strategies for the design of stable and efficient CBPMs.

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)0.000
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: none
Teacher disagreement score0.336
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.055
GPT teacher head0.291
Teacher spread0.236 · 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