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Record W2810723462 · doi:10.1039/c8nr04312d

Enzymatic film formation of nature-derived phenolic amines

2018· article· en· W2810723462 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueNanoscale · 2018
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsKootenay Association for Science & Technology
FundersNational Research Foundation of Korea
KeywordsEnzymeChemistryOrganic chemistryMaterials science

Abstract

fetched live from OpenAlex

An enzyme-instructed method is developed for material-independent, cytocompatible coating of phenolic amines, inspired by melanogenesis found in nature. Tyrosinase-based film formation proceeds smoothly in an aqueous solution at neutral pH, and can use various phenolic amines including catecholamines, such as tyrosine, tyramine, dopamine, norepinephrine, and DOPA, as a coating precursor. Compared with polydopamine coating, the method is fast and efficient, and forms uniform films. Its high cytocompatibility is advantageously applied to cell-surface engineering, where chemically labile Jurkat cells are coated individually without any noticeable decrease in viability. Considering the huge potential of polyphenolic-based coatings, the strategy developed herein will provide an advanced tool for manipulating biological entities, including living cells, in biomedical and medicinal applications.

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.

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 score0.006
Threshold uncertainty score0.661

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)0.0010.001

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 head0.014
GPT teacher head0.278
Teacher spread0.264 · 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