MétaCan
Menu
Back to cohort
Record W2514442816 · doi:10.1039/c6cp04527h

A comparison of adsorbed and grafted fibronectin coatings under static and dynamic conditions

2016· article· en· W2514442816 on OpenAlexaff
Vanessa Montaño‐Machado, Ludivine Hugoni, Sergio Diaz‐Rodriguez, R. Tolouei, Pascale Chevallier, Emmanuel Pauthe, Diego Mantovani

Bibliographic record

VenuePhysical Chemistry Chemical Physics · 2016
Typearticle
Languageen
FieldEngineering
TopicNanofabrication and Lithography Techniques
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsAdsorptionFibronectinMaterials scienceChemistryChemical physicsBiological systemNanotechnologyChemical engineeringPolymer scienceOrganic chemistryEngineeringBiologyBiochemistryCell

Abstract

fetched live from OpenAlex

Coatings for medical devices are expected to improve their surface biocompatibility mainly by being bioactive, i.e. stimulating healing-oriented interactions with living cells, tissues and organs. In particular, for stent applications, coatings are often designed to enhance the endothelialization process. The coating strategy will be primarily responsible for the interfacial properties between the substrate and the coating, which must show high stability. Therefore, the present work aims at comparing the stability of adsorbed and grafted fibronectin, a protein well-known to promote endothelialization. Fibronectin coatings were deposited on fluorocarbon films generated by a plasma-based process on stainless steel substrates. Then, deformation tests were performed in order to simulate the stenting procedure and stability tests were completed under static and under-flow conditions. Coatings were characterized by XPS, AFM, water contact angle, immunostaining and ToF-SIMS analyses. The results show higher stability for the grafted coatings; indeed, the integrity of the protein simply adsorbed was strongly compromised especially after under-flow tests. Both coatings exhibited similar behavior after deformation and static tests. These results clearly show the impact of the coating strategy on the overall stability of the coatings as well as the importance of under-flow investigations.

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)0.000
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 score0.021
Threshold uncertainty score0.530

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)0.0000.000

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 head0.009
GPT teacher head0.278
Teacher spread0.268 · 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

Citations12
Published2016
Admission routes1
Has abstractyes

Explore more

Same venuePhysical Chemistry Chemical PhysicsSame topicNanofabrication and Lithography TechniquesFrench-language works237,207