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Record W2052187380 · doi:10.1115/1.4002532

A Novel Method to Attenuate Protein Adsorption Using Combinations of Polyethylene Glycol (PEG) Grafts and Piezoelectric Actuation

2010· article· en· W2052187380 on OpenAlexaff
Po-Ying Yeh, Jayachandran N. Kizhakkedathu, Mu Chiao

Bibliographic record

VenueJournal of Nanotechnology in Engineering and Medicine · 2010
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPolyethylene glycolPEG ratioMaterials scienceAdsorptionProtein adsorptionX-ray photoelectron spectroscopyDesorptionFourier transform infrared spectroscopyPolyethyleneLead zirconate titanateChemical engineeringPolymerSurface modificationBovine serum albuminComposite materialChemistryChromatographyOrganic chemistryFerroelectricity

Abstract

fetched live from OpenAlex

An antifouling treatment based on the combined effects of grafted polyethylene glycol (PEG) polymers and the application of vibration is reported. A gold-coated lead zirconate titanate piezoelectric composite was grafted with PEG used as a model substrate. The PEG grafted surfaces were thoroughly characterized by attenuated total reflectance-Fourier transform infrared spectroscopy and X-ray photoelectron spectroscopy. In vitro protein adsorption onto PEG coated surfaces was studied with and without the application of vibration. Bovine serum albumin (BSA) adsorption onto PEG grafted surfaces followed a similar pattern as reported in literature. However, when piezoelectric vibration was applied on the PEG grafted surface, BSA desorption was observed. At very low graft densities, the vibration significantly reduced the BSA adsorption compared with high PEG graft densities. Theoretical calculations showed that the thickness of PEG layer on the surface was affecting vibration induced protein desorption.

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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
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 head0.015
GPT teacher head0.297
Teacher spread0.283 · 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

Citations4
Published2010
Admission routes1
Has abstractyes

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Same venueJournal of Nanotechnology in Engineering and MedicineSame topicPolymer Surface Interaction StudiesFrench-language works237,207