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Record W3006327472 · doi:10.1021/acsomega.9b04430

Dual Reduction/Acid-Responsive Disassembly and Thermoresponsive Tunability of Degradable Double Hydrophilic Block Copolymer

2020· article· en· W3006327472 on OpenAlexafffund
Keaton Maruya-Li, Chaitra Shetty, Arman Moini Jazani, Newsha Arezi, Jung Kwon Oh

Bibliographic record

VenueACS Omega · 2020
Typearticle
Languageen
FieldChemistry
TopicAdvanced Polymer Synthesis and Characterization
Canadian institutionsConcordia University
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsCopolymerEthylene oxideAcetalPolymer chemistryChemistryDisulfide LinkageEthylene glycolOxideCovalent bondMaterials scienceCombinatorial chemistryChemical engineeringOrganic chemistryPolymer

Abstract

fetched live from OpenAlex

We report a thermoresponsive double hydrophilic block copolymer degradable in response to dual reduction and acidic pH at dual locations. The copolymer consists of a poly(ethylene oxide) block covalently connected through an acid-labile acetal linkage with a thermoresponsive polymethacrylate block containing pendant oligo(ethylene oxide) and disulfide groups. The copolymer undergoes temperature-driven self-assembly in water to form nanoassemblies with acetal linkages at the core/corona interface and disulfide pendants in the core, exhibiting dual reduction/acid responses at dual locations. The physically assembled nanoaggregates are converted to disulfide-core-crosslinked nanogels through disulfide-thiol exchange reaction, retaining enhanced colloidal stability, yet degraded to water-soluble unimers upon reduction/acid-responsive degradation. Further, the copolymer exhibits improved tunability of thermoresponsive property upon the cleavage of junction acetal and pendant disulfide linkages individually and in combined manner. This work suggests that dual location dual reduction/acid-responsive degradation is a versatile strategy toward effective drug delivery exhibiting disulfide-core-crosslinking capability and disassembly as well as improved thermoresponsive tunability.

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 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 score0.003
Threshold uncertainty score0.799

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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 head0.017
GPT teacher head0.238
Teacher spread0.221 · 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.

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

Citations15
Published2020
Admission routes2
Has abstractyes

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