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Intracellular Delivery of Colloidally Stable Core-Cross-Linked Triblock Copolymer Micelles with Glutathione-Responsive Enhanced Drug Release for Cancer Therapy

2017· article· en· W2587929901 on OpenAlexafffund
Depannita Biswas, So Young An, Yijing Li, Xiangtao Wang, Jung Kwon Oh

Bibliographic record

VenueMolecular Pharmaceutics · 2017
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCanada Research Chairs
KeywordsNanocarriersMicelleGlutathioneChemistryAmphiphileCopolymerEthylene glycolBiophysicsDrug deliveryIntracellularPEG ratioDynamic light scatteringIn vivoPoloxamerCancer cellCancerAqueous solutionBiochemistryNanoparticleMaterials scienceNanotechnologyOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

Design and development of amphiphilic block copolymer-based nanocarriers exhibiting enhanced colloidal stability upon dilution in the blood and cellular glutathione-responsive rapid drug release is highly desired for tumor-targeting chemotherapy. Herein, we report a novel ABA-type triblock copolymer consisting of a hydrophilic central poly(ethylene glycol) block and two terminal hydrophobic blocks of a polymethacrylate having pendant disulfides (PHMssEt), thus PHMssEt-b-PEG-b-PHMssEt (ssTP). Aqueous self-assembly and the following disulfide-exchange reaction of the resulting ssTP allow for formation of core-cross-linked micelles (CCMs) through the formation of new disulfide linkages, retaining enhanced colloidal stability in physiological conditions and in the presence of proteins. Further, they exhibit reduction-responsive enhanced release of encapsulated drugs in response to cellular concentrations of glutathione in cancer cells, confirmed by dynamic light scattering and spectroscopic analysis. Combined with these results, in vitro (cells) and in vivo (mouse model) biological results suggest that ssTP-based CCMs are effective candidates as intracellular nanocarriers targeting tumors for cancer therapy.

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)0.001
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 score0.007
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.031
GPT teacher head0.332
Teacher spread0.301 · 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

Citations27
Published2017
Admission routes2
Has abstractyes

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