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Record W2126095137 · doi:10.1002/btpr.5

Dendrimer‐grafted cell adhesion peptide–modified PDMS

2008· article· en· W2126095137 on OpenAlexaff
Andrew S. Mikhail, Kim S. Jones, Heather Sheardown

Bibliographic record

VenueBiotechnology Progress · 2008
Typearticle
Languageen
FieldMaterials Science
TopicDendrimers and Hyperbranched Polymers
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDendrimerPeptideAdhesionGraftingCell adhesionBiophysicsLinkerContact angleSurface modificationChemistryPolymer chemistryElastomerMaterials sciencePolymerChemical engineeringOrganic chemistryBiochemistryPhysical chemistry

Abstract

fetched live from OpenAlex

Surface concentration of cell adhesion peptides is thought to play a role in the interactions between biomaterials and cells. The high density of functional groups at the periphery of dendrimers has been exploited in various applications, but their full potential for generating surfaces with high functional group concentrations has not yet been realized. Poly(dimethylsiloxane) elastomers were surface modified with both polyethylene oxide (PEO) and generation 3 diaminobutane dendrimers. PEO and the dendrimers were subsequently used as linker molecules for surface grafting of cell adhesion peptides. ATR-FTIR, X-ray photoelectron spectroscopy, and water contact angle results confirmed the successful attachment of the polymer linkers and peptides. Peptide grafting density was quantified by means of (125)I radiolabeling. Maximum surface peptide grafting density on dendrimer-modified surfaces was twofold greater than the maximum peptide grafting density achieved via the PEO linker. However, vascular endothelial cell adhesion was significantly greater on surfaces modified with the PEO linker, presumably due to the highly flexible PEO spacer making the peptide more accessible for binding with the cell surface receptors. These results suggest that, although peptide surface density may be important, optimizing surface density may not be sufficient for improving biological interactions.

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 categoriesMeta-epidemiology (narrow), Insufficient 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 score0.020
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.019
GPT teacher head0.237
Teacher spread0.218 · 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.

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
Published2008
Admission routes1
Has abstractyes

Explore more

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