| Title |
Differences in Abundances of Cell-Signalling Proteins in Blood Reveal Novel Biomarkers for Early Detection Of Clinical Alzheimer's Disease
|
|---|---|
| Published in |
PLOS ONE, March 2011
|
| DOI | 10.1371/journal.pone.0017481 |
| Pubmed ID | |
| Authors |
Mateus Rocha de Paula, Martín Gómez Ravetti, Regina Berretta, Pablo Moscato |
| Abstract |
In November 2007 a study published in Nature Medicine proposed a simple test based on the abundance of 18 proteins in blood to predict the onset of clinical symptoms of Alzheimer's Disease (AD) two to six years before these symptoms manifest. Later, another study, published in PLoS ONE, showed that only five proteins (IL-1, IL-3, EGF, TNF- and G-CSF) have overall better prediction accuracy. These classifiers are based on the abundance of 120 proteins. Such values were standardised by a Z-score transformation, which means that their values are relative to the average of all others. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 61 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| France | 1 | 2% |
| Australia | 1 | 2% |
| Unknown | 58 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 16 | 26% |
| Student > Ph. D. Student | 8 | 13% |
| Student > Bachelor | 7 | 11% |
| Other | 6 | 10% |
| Professor > Associate Professor | 4 | 7% |
| Other | 9 | 15% |
| Unknown | 11 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 14 | 23% |
| Agricultural and Biological Sciences | 7 | 11% |
| Biochemistry, Genetics and Molecular Biology | 6 | 10% |
| Computer Science | 3 | 5% |
| Immunology and Microbiology | 3 | 5% |
| Other | 14 | 23% |
| Unknown | 14 | 23% |