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Record W2969325347 · doi:10.1039/c9lc00608g

Micropatterned biofunctional lubricant-infused surfaces promote selective localized cell adhesion and patterning

2019· article· en· W2969325347 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueLab on a Chip · 2019
Typearticle
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsToronto Public HealthUniversity of TorontoMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaMcMaster University
KeywordsLubricantAdhesionCell adhesionNanotechnologyCellMaterials scienceChemistryBiophysicsCell biologyComposite materialBiologyBiochemistry

Abstract

fetched live from OpenAlex

Micropatterned biofunctional surfaces provide a wide range of applications in bioengineering. A key characteristic which is sought in these types of bio-interfaces is prevention of non-specific adhesion for enhanced biofunctionality and targeted binding. Lubricant-infused omniphobic coatings have exhibited superior performance in attenuating non-specific adhesion; however, these coatings completely block the surfaces and do not support targeted adhesion or patterning. In this work, we introduce a novel lubricant-infused surface with biofunctional micropatterned domains integrated within an omniphobic layer. This new class of micropatterned lubricant-infused surfaces simultaneously promotes localized and directed binding of desired targets, as well as repellency of undesired species, especially in human whole blood. Furthermore, this modification method is easily translatable to microfluidic devices offering a wider range of applications and improved performance for immunoassays in whole blood and inhibition of clot formation in microfluidic channels. The biofunctional micropatterned lubricant-infused surfaces were created through a bench-top straight forward process by integrating microcontact printing, chemical vapor deposition (CVD) of self-assembled monolayers (SAMs) of fluorosilanes, and further infusion of the SAMs with a bio-compatible fluorocarbon-based lubricant layer. The developed surfaces, patterned with anti-CD34 antibodies, yield enhanced adhesion and controlled localized binding of target biomolecules (e.g. antibodies) and CD34 positive cells (e.g. HUVECs) inside microfluidic devices, outperforming conventional blocking methods (e.g. bovine serum albumin (BSA) or poly(ethylene glycol) (PEG)) in buffer and human whole blood. These surfaces offer a straightforward and effective way to enhance blocking capabilities while preserving the biofunctionality of a micropatterned system in complex biological environments such as whole blood. We anticipate that these micropatterned biofunctional interfaces will find a wide range of applications in microfluidic devices and biosensors for enhanced and localized targeted binding while preventing non-specific adhesion.

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 categoriesInsufficient payload (model declined to judge)
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 score0.014
Threshold uncertainty score0.999

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)0.0010.002

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 head0.011
GPT teacher head0.237
Teacher spread0.225 · 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