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Record W2166423281 · doi:10.1002/chem.201502233

Drug Delivery Nanocarriers from a Fully Degradable PEG‐Conjugated Polyester with a Reduction‐Responsive Backbone

2015· article· en· W2166423281 on OpenAlexaff
Basit Yameen, Cristián Vilos, Won Il Choi, Andrew Whyte, Jining Huang, Lori Pollit, Omid C. Farokhzad

Bibliographic record

VenueChemistry - A European Journal · 2015
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticle-Based Drug Delivery
Canadian institutionsUniversity of Waterloo
FundersNational Cancer InstituteU.S. Public Health ServiceNational Institute of Biomedical Imaging and BioengineeringNational Institute of Neurological Disorders and StrokeCentro para el Desarrollo de la Nanociencia y la NanotecnologíaNational Research Foundation of Korea
KeywordsNanocarriersPolyesterPEG ratioDrug deliveryConjugated systemIntracellularPolyethylene glycolNanoparticleChemistryCombinatorial chemistryMaterials sciencePolymerBiophysicsNanotechnologyOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

The remarkably high intracellular concentration of reducing agents is an excellent endogenous stimulus for designing nanocarriers programmed for intracellular delivery of therapeutic agents. However, despite their excellent biodegradability profiles, aliphatic polyesters that are fully degradable in response to the intracellular reducing environment are rare. Herein, a reduction-responsive drug delivery nanocarrier derived from a linear polyester bearing disulfide bonds is reported. The reduction-responsive polyester is synthesized via a convenient polycondensation process. After conjugation of terminal carboxylic acid groups of polyester to polyethylene glycol (PEG), the resulting polymer self-assembles into nanoparticles that are capable of encapsulating dye and anticancer drug molecules. The reduction-responsive nanoparticles display a fast payload release rate in response to the intracellular reducing environment, which translates into superior anticancer activity towards PC-3 cells.

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), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score1.000

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 communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.015
GPT teacher head0.203
Teacher spread0.188 · 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; both teacher heads agree on what is shown here.

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

Citations20
Published2015
Admission routes1
Has abstractyes

Explore more

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