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Record W2005544071 · doi:10.1021/bm701203r

Charge-Switching, Amphoteric Glucose-Responsive Microgels with Physiological Swelling Activity

2008· article· en· W2005544071 on OpenAlexafffund
Todd Hoare, Robert Pelton

Bibliographic record

VenueBiomacromolecules · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicHydrogels: synthesis, properties, applications
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSwellingChemistryBiophysicsChemical engineeringCharge (physics)Biology

Abstract

fetched live from OpenAlex

Amphoteric, poly(N-isopropylacrylamide)-based microgels are functionalized with aminophenylboronic acid (PBA) functional groups to produce colloidally stable, glucose-responsive gel nanoparticles that exhibit glucose-dependent swelling responses at physiological temperature, pH, and ionic strength. Up to 2-fold volumetric swelling responses are observed in response to physiological glucose concentrations, the first such physiological response reported for a colloidally stable microgel. Amphoteric microgels can also be designed to both swell and deswell in response to glucose according to the pH of the medium, the concentration of PBA groups grafted to the microgel, and the relative concentrations of the cationic and anionic functional groups in the platform microgel. The increasing anionic charge density on the microgels observed at higher glucose binding fractions can be applied to switch the net charge of the microgels from cationic to anionic as the glucose concentration increases. Preliminary experiments suggest that such amphoteric PBA-microgels have a high capacity for insulin uptake and can selectively release more insulin at higher glucose concentrations under physiological conditions via glucose-induced, "on-off" switching of electrostatic attractions between insulin and the microgel.

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)0.000
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 score0.000
Threshold uncertainty score0.001

Distilled classifier scores by category (both heads)

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 head0.024
GPT teacher head0.242
Teacher spread0.219 · 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

Citations193
Published2008
Admission routes2
Has abstractyes

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