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Roadblocks for integration of novel biomarker concepts into clinical routine: the peptoid approach

Overview of attention for article published in Alzheimer's Research & Therapy, April 2014
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Title
Roadblocks for integration of novel biomarker concepts into clinical routine: the peptoid approach
Published in
Alzheimer's Research & Therapy, April 2014
DOI 10.1186/alzrt253
Pubmed ID
Authors

Hugo Vanderstichele, Thomas Kodadek

Abstract

In the field of Alzheimer's disease, the development of novel biomarker assays is critically needed to improve the early diagnosis of the disease, to estimate the risk of developing the disease, to predict the rate of cognitive decline, and to monitor the response or effectiveness of a therapy. The molecular mechanisms of the disease are becoming more evident. This basic knowledge has yet to be translated into novel biomarker tools with a clinical value for general use by the community. There is therefore high interest in evaluating new technological approaches beside the classical immunoassay approach. The present paper discusses the hypothesis that there might be an adaptive immune response, unique to Alzheimer's disease, which can be visualized by the presence in body fluids of antibodies against specific analytes. Current technologies to identify such antibodies are reviewed. In addition, the major challenges to transfer discovery results of the novel antibody-based biomarker assays to a clinically relevant test will be discussed.

Mendeley readers

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 %
United States 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 24%
Student > Ph. D. Student 3 18%
Student > Doctoral Student 2 12%
Student > Bachelor 2 12%
Student > Master 2 12%
Other 3 18%
Unknown 1 6%
Readers by discipline Count As %
Agricultural and Biological Sciences 5 29%
Chemistry 4 24%
Psychology 3 18%
Biochemistry, Genetics and Molecular Biology 2 12%
Mathematics 1 6%
Other 1 6%
Unknown 1 6%