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Record W2073557419 · doi:10.1163/1568562042368022

Promotion of U937 cell adhesion on polypropylene surfaces bearing phosphorylcholine functionalities

2004· article· en· W2073557419 on OpenAlexafffund
Yong‐Kuan Gong, Fackson Mwale, M. R. Wertheimer, Françoise M. Winnik

Bibliographic record

VenueJournal of Biomaterials Science Polymer Edition · 2004
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsUniversité de Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAttenuated total reflectionContact anglePhosphorylcholinePolypropyleneX-ray photoelectron spectroscopyPolymer chemistryGraftingAmine gas treatingReductive aminationFourier transform infrared spectroscopyMaterials scienceWettingAdhesionChemistryNuclear chemistryChemical engineeringOrganic chemistryInfrared spectroscopyBiochemistryComposite materialPolymer

Abstract

fetched live from OpenAlex

Phosphorylcholine (PC) groups were grafted onto ammonia plasma-treated biaxially-oriented polypropylene (BOPP) surfaces, via (a) reductive amination of phosphorylcholine glyceraldehyde and (b) a two-step procedure involving the chemical amplification of surface amine groups with tris(2-aminoethyl amine) and subsequent reductive amination of phosphorylcholine glyceraldehyde. The occurrence of grafting was ascertained by X-ray photoelectron spectroscopy (XPS) and attenuated total reflectance Fourier-transform infrared (ATR-FT-IR) spectroscopy. The wettability of PC-modified surfaces was assessed by dynamic contact-angle measurements using the Wilhelmy plate method. Human U937 macrophages adhered and proliferated to a significantly larger extent on PC-modified surfaces, compared to unmodified or ammonia plasma-modified BOPP.

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)0.0000.000
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)0.0010.000

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 head0.279
Teacher spread0.255 · 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

Citations21
Published2004
Admission routes2
Has abstractyes

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Same venueJournal of Biomaterials Science Polymer EditionSame topicPolymer Surface Interaction StudiesFrench-language works237,207