Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 159

The DOI matches its Crossref record.

Morphology and Persistence Length of Amyloid Fibrils Are Correlated to Peptide Molecular Structure

vandenAkker, Corianne C., Engel, Maarten F. M., Velikov, Krassimir P., Bonn, Mischa, Koenderink, Gijsje H.·2011·Journal of the American Chemical Society

Abstract

The formation of amyloid fibrils is a self-assembly process of peptides or proteins. The superior mechanical properties of these fibrils make them interesting for materials science but constitute a problem in amyloid-related diseases. Amyloid structures tend to be polymorphic, and their structure depends on growth conditions. To understand and control the assembly process, insights into the relation between the mechanical properties and molecular structure are essential. We prepared long, straight as well as short, worm-like β-lactoglobulin amyloid fibrils and determined their morphology and persistence length by atomic force microscopy (AFM) and the molecular conformation using vibrational sum-frequency generation (VSFG) spectroscopy. We show that long fibrils with near-100% β-sheet content have a 40-times higher persistence length than short, worm-like fibrils with β-sheet contents below 80%.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/ja206513r

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 159

Metadata

Authors
vandenAkker, C. C., Engel, M. F. M., Velikov, K. P., Bonn, M., & Koenderink, G. H.
Venue
Journal of the American Chemical Society
Published
2011-10-24
Volume
133
Issue
45
Pages
18030-18033
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W2086994853
Cited by
159
References
0
FWCI
3.09
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Morphology and Persistence Length of Amyloid Fibrils Are Correlated to Peptide Molecular Structure. https://app.cochat.ai/papers/10.1021/ja206513r
The paper
vandenAkker, C. C., Engel, M. F. M., Velikov, K. P., Bonn, M., & Koenderink, G. H. (2011). Morphology and Persistence Length of Amyloid Fibrils Are Correlated to Peptide Molecular Structure. Journal of the American Chemical Society. https://doi.org/10.1021/ja206513r

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.