MétaCan
Menu
Back to cohort
Record W2144277066 · doi:10.3109/02652048.2010.509518

Comparison of emulsion and vibration nozzle methods for microencapsulation of laccase and glucose oxidase by interfacial reticulation of poly(ethyleneimine)

2010· article· en· W2144277066 on OpenAlexaff
Yufen Zhang, Dominic Rochefort

Bibliographic record

VenueJournal of Microencapsulation · 2010
Typearticle
Languageen
FieldEngineering
TopicElectrochemical sensors and biosensors
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsMaterials scienceEmulsionEthyleneimineLaccaseMembraneGlucose oxidaseAspergillus nigerChemical engineeringChromatographyPolymerComposite materialChemistryNanotechnologyOrganic chemistryBiosensorEnzymeBiochemistry

Abstract

fetched live from OpenAlex

Microcapsules for enzyme immobilization were successfully fabricated via interfacial cross-linking of poly(ethyleneimine) (PEI). A method based on laminar jet break-up technique using a commercial instrument developed to produce alginate beads is reported for the first time for production of PEI microcapsules. The diameter, wall thickness and pore size of membranes were obtained from confocal laser scanning microscopy by labelling PEI and proteins. The composition of membranes was analysed by elemental analysis. Larger microcapsules (ca 200 µm diameter) were obtained with the encapsulation device. In comparison, the emulsion method produced smaller capsules (ca 20 µm diameter) but with a wider size distribution. Encapsulation efficiency for both methods was analysed by bicinchoninic acid and fluorescence assays, yielding efficiencies of 94 ± 2% and 83 ± 3% for the emulsion method and encapsulation device, respectively. Glucose oxidase from Aspergillus Niger and Laccase from Trametes Versicolor were encapsulated by both microencapsulation methods and their activities were compared.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.310
Teacher spread0.300 · 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

Citations26
Published2010
Admission routes1
Has abstractyes

Explore more

Same venueJournal of MicroencapsulationSame topicElectrochemical sensors and biosensorsFrench-language works237,207