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Protocol for the Preparation of Stimuli-Responsive Gold Nanoparticles Capped with Elastin-Based Pentapeptides

2013· article· en· W78948126 on OpenAlexfundno aff
Vincent Lemieux, P. Hans H. M. Adams, Jan C. M. van Hest

Bibliographic record

VenueMethods in molecular biology · 2013
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsnot available
FundersFonds Québécois de la Recherche sur la Nature et les Technologies
KeywordsPentapeptide repeatColloidal goldNanoparticleNanotechnologyLigand (biochemistry)Materials scienceDrug deliveryCombinatorial chemistryChemistryBiophysicsPeptideReceptorBiochemistryBiology

Abstract

fetched live from OpenAlex

Stimuli-responsive materials are playing an increasingly important role in a wide range of applications such as drug delivery, diagnostics, sensors, and tissue engineering. Among them, gold nanoparticles responding to changes in their surrounding environment are of particular interest due to their size-related optical properties. Here, we present a novel strategy for the preparation of gold nanoparticles exhibiting a stimuli-responsive behavior. We rely on the use of a ligand consisting of only a single repeat of the elastin-based pentapeptide VPGVG. In this contribution, we describe a protocol for the solid-phase peptide synthesis of thiol-terminated VPGVG ligand, and for the preparation of gold nanoparticles covered with the pentapeptide through a ligand-exchange reaction.

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)0.002
metaresearch head score (Gemma)0.001
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: Methods · Consensus signal: Methods
Teacher disagreement score0.297
Threshold uncertainty score0.564

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
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 head0.042
GPT teacher head0.435
Teacher spread0.393 · 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
GenreMethods

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

Citations2
Published2013
Admission routes1
Has abstractyes

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