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Record W1971916457 · doi:10.1039/c2lc40139h

In vitro and in vivo testing of glucose-responsive insulin-delivery microdevices in diabetic rats

2012· article· en· W1971916457 on OpenAlexafffund
Michael Chu, Jian Chen, Cláudia R. Gordijo, Simon Chiang, Alexander Ivovic, Khajag Koulajian, Adria Giacca, Xiao Yu Wu, Yu Sun

Bibliographic record

VenueLab on a Chip · 2012
Typearticle
Languageen
FieldMedicine
TopicPancreatic function and diabetes
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaCanadian Institutes of Health Research
KeywordsIn vivoInsulin deliveryIn vitroDiabetes mellitusInsulinBiomedical engineeringMedicineChemistryInternal medicineEndocrinologyBiologyType 1 diabetesBiochemistryBiotechnology

Abstract

fetched live from OpenAlex

We have developed glucose-responsive implantable microdevices for closed-loop delivery of insulin and conducted in vivo testing of these devices in diabetic rats. The microdevices consist of an albumin-based bioinorganic membrane that utilizes glucose oxidase (GOx), catalase (CAT) and manganese dioxide (MnO(2)) nanoparticles to convert a change in the environmental glucose level to a pH stimulus, which regulates the volume of pH-sensitive hydrogel nanoparticles and thereby the permeability of the membrane. The membrane is integrated with microfabricated PDMS (polydimethylsiloxane) structures to form compact, stand-alone microdevices, which do not require tethering wires or tubes. During in vitro testing, the microdevices showed glucose-responsive insulin release over multiple cycles at clinically relevant glucose concentrations. In vivo, the microdevices were able to counter hyperglycemia in diabetic rats over a one-week period. The in vitro and in vivo testing results demonstrated the efficacy of closed-loop biosensing and rapid response of the 'smart' insulin delivery devices.

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)0.001
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 score0.158
Threshold uncertainty score0.396

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.020
GPT teacher head0.253
Teacher spread0.233 · 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

Citations64
Published2012
Admission routes2
Has abstractyes

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