Peptide Self-Assembly
Humana Press
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Mendeley readers
Attention Score in Context
| Chapter title |
Discriminating Strains of Self-Propagating Protein Aggregates Using a Conformational Stability Assay
|
|---|---|
| Book title |
Peptide Self-Assembly
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7811-3_22 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7809-0, 978-1-4939-7811-3
|
| Authors |
Heather H. C. Lau, Angus Lau, Joel C. Watts |
| Abstract |
Prions and other self-propagating protein aggregates can exist as distinct strains, which are thought to represent different conformations of aggregates. There is growing evidence that protein aggregate strains may be important for understanding the biology of common neurodegenerative disorders, such as Alzheimer's disease and Parkinson's disease. While methodology for discriminating prion strains is in widespread use, there is a paucity of tools for comparing the conformational properties of aggregates composed of β-amyloid (Aβ) peptide or α-synuclein protein, particularly when present in complex samples such as brain extracts. The conformational stability assay (CSA) is a simple technique that measures the relative resistance of protein aggregates to chemical denaturation. While originally developed to differentiate prion strains, the CSA has since been adapted for use with other protein aggregates. Here, we describe the CSA in detail and outline its utility for distinguishing prion strains as well as unique conformational states of Aβ and α-synuclein aggregates. |
Mendeley readers
The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 17 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 4 | 24% |
| Student > Ph. D. Student | 3 | 18% |
| Researcher | 2 | 12% |
| Student > Master | 2 | 12% |
| Other | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 5 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Neuroscience | 5 | 29% |
| Agricultural and Biological Sciences | 2 | 12% |
| Biochemistry, Genetics and Molecular Biology | 2 | 12% |
| Medicine and Dentistry | 2 | 12% |
| Psychology | 1 | 6% |
| Other | 0 | 0% |
| Unknown | 5 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 18 May 2018.
All research outputs
#4,233,076
of 23,057,470 outputs
Outputs from Methods in molecular biology
#1,139
of 13,196 outputs
Outputs of similar age
#92,850
of 442,487 outputs
Outputs of similar age from Methods in molecular biology
#95
of 1,499 outputs
Altmetric has tracked 23,057,470 research outputs across all sources so far. Compared to these this one has done well and is in the 80th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,196 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,487 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 92% of its contemporaries.