Titel |
Biomarkers for Alzheimer’s Disease Drug Development / edited by Robert Perneczky |
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Beteiligt |
Robert Perneczky (Herausgeber) |
Erschienen |
New York, NY: Springer US, Imprint: Humana |
Ausgabe |
2nd ed. 2024 |
Umfang |
Online-Ressource, XIII, 349 p. 51 illus., 49 illus. in color. : online resource. |
Enthält |
Blood-Based Biomarkers for Early Alzheimer’s Disease Diagnosis in Real-World Settings -- Alzheimer’s Disease Prevention and Treatment Based on Population-Based Approaches -- CSF N-Glycomics Using High Throughput UPLC-ESI Techniques in Alzheimer’s Disease -- CSF N-Glycomics Using MALDI MS Techniques -- Optimized Pre-Analytical Handling Protocol for Blood-Based Biomarkers of Alzheimer’s Disease -- Mass Spectrometry-Based Metabolomics Multi-Platform for Alzheimer’s Disease Research -- Analysis of Resting-State Functional Magnetic Resonance Imaging in Alzheimer's Disease -- Diffusion Tensor Imaging in Alzheimer’s Studies -- Magnetic Resonance Spectroscopy (MRS) in Alzheimer’s Disease -- Neuroimaging Methods for MRI Analysis in CSF Biomarkers Studies -- Amyloid PET Imaging: Standard Procedures and Semiquantification -- PET Imaging to Measure Neuroinflammation In Vivo -- Imaging Neuroinflammation: Quantification of Astrocytosis in a Multitracer PET Approach -- High-Throughput Lipidomics and Metabolomics Profiling for Brain Tissue and Biofluid Samples in Neurodegenerative Disorders -- Neuropathological Assessment as an Endpoint in Clinical Trial Design -- Non-Invasive Visualization of Amyloid-Beta Deposits in Alzheimer’s Amyloidosis Mice via Fluorescence Molecular Tomography Using Contrast Agent -- Brain Banking in Dementia Studies -- Speech-Based Digital Biomarkers for Alzheimer’s Research -- cCOG Web-Based Cognitive Assessment Tool -- In Silico Models to Validate Novel Blood-Based Biomarkers |
ISBN |
978-1-0716-3774-6 |
Sprache |
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Land |
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Themengebiet |
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Thema |
Biomarkers. |
DDC-Notation |
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Reihe |
Methods in Molecular Biology ; 2785 |
Persistent Identifier |
urn:nbn:de:101:1-2024030503110237884030 (URN) |
Datensatz-ID |
1322532990 |
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