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Nucleation and growth of elastin-like peptide fibril multilayers: an<i>in situ</i>atomic force microscopy study

2011· article· en· W2018433474 on OpenAlexaff
Guocheng Yang, Michael K. Y. Wong, Lauren Lin, Christopher M. Yip

Bibliographic record

VenueNanotechnology · 2011
Typearticle
Languageen
FieldMaterials Science
TopicSupramolecular Self-Assembly in Materials
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsFibrilNucleationMaterials scienceIn situElastinContext (archaeology)Supramolecular chemistryAtomic force microscopyCrystallographyHighly oriented pyrolytic graphiteSelf-assemblyBiophysicsPyrolytic carbonNanotechnologyChemistryCrystal structureBiologyScanning tunneling microscope

Abstract

fetched live from OpenAlex

Controlling how molecules assemble into complex supramolecular architectures requires careful consideration of the subtle inter- and intra-molecular interactions that control their association. This is particularly crucial in the context of assembly at interfaces, where both surface chemistry and structure can play a role in directing structure formation. We report here the results of a study into the self-assembly of the elastin-like peptide EP I on structurally modified highly ordered pyrolytic graphite, including the role of spatial confinement on fibril nucleation and the growth of oriented fibril multilayers. In situ atomic force microscopy performed in fluid and at elevated temperature provided direct evidence of frustrated fibril nuclei and oriented growth of independent fibril domains. These results portend the application of this in situ strategy for studies of the nucleation and growth mechanisms of other fibril- and amyloid-forming proteins.

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)0.001
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 score0.012
Threshold uncertainty score0.898

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.016
GPT teacher head0.258
Teacher spread0.242 · 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

Citations8
Published2011
Admission routes1
Has abstractyes

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