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Neuroproteomics

Overview of attention for book
Cover of 'Neuroproteomics'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Neuroproteomics Studies: Challenges and Updates
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    Chapter 2 Progress and Potential of Imaging Mass Spectrometry Applied to Biomarker Discovery
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    Chapter 3 Biofluid Proteomics and Biomarkers in Traumatic Brain Injury
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    Chapter 4 Degradomics in Neurotrauma: Profiling Traumatic Brain Injury
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    Chapter 5 Evolving Relevance of Neuroproteomics in Alzheimer’s Disease
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    Chapter 6 Genome to Phenome: A Systems Biology Approach to PTSD Using an Animal Model
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    Chapter 7 Photoaffinity Labeling of Pentameric Ligand-Gated Ion Channels: A Proteomic Approach to Identify Allosteric Modulator Binding Sites
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    Chapter 8 Quantitative Phosphoproteomic Analysis of Brain Tissues
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    Chapter 9 Glycoproteins Enrichment and LC-MS/MS Glycoproteomics in Central Nervous System Applications
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    Chapter 10 A Novel 2-DE-Based Proteomic Analysis to Identify Multiple Substrates for Specific Protease in Neuronal Cells
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    Chapter 11 Neuroproteomic Profiling of Cerebrospinal Fluid (CSF) by Multiplexed Affinity Arrays
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    Chapter 12 Isolation and Proteomic Analysis of Microvesicles and Exosomes from HT22 Cells and Primary Neurons
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    Chapter 13 Combined MALDI Mass Spectrometry Imaging and Parafilm-Assisted Microdissection-Based LC-MS/MS Workflows in the Study of the Brain
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    Chapter 14 De Novo and Uninterrupted SILAC Labeling of Primary Microglia
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    Chapter 15 Spike-In SILAC Approach for Proteomic Analysis of Ex Vivo Microglia
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    Chapter 16 A Proteomic Evaluation of Sympathetic Activity Biomarkers of the Hypothalamus-Pituitary-Adrenal Axis by Western Blotting Technique Following Experimental Traumatic Brain Injury
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    Chapter 17 Efficient and Accurate Algorithm for Cleaved Fragments Prediction (CFPA) in Protein Sequences Dataset Based on Consensus and Its Variants: A Novel Degradomics Prediction Application
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    Chapter 18 Effect of Second-Hand Tobacco Smoke on the Nitration of Brain Proteins: A Systems Biology and Bioinformatics Approach
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    Chapter 19 An Advanced Omic Approach to Identify Co-Regulated Clusters and Transcription Regulation Network with AGCT and SHOE Methods
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    Chapter 20 AutoDock and AutoDockTools for Protein-Ligand Docking: Beta-Site Amyloid Precursor Protein Cleaving Enzyme 1(BACE1) as a Case Study
  22. Altmetric Badge
    Chapter 21 An Integration of Decision Tree and Visual Analysis to Analyze Intracranial Pressure
Attention for Chapter 12: Isolation and Proteomic Analysis of Microvesicles and Exosomes from HT22 Cells and Primary Neurons
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Chapter title
Isolation and Proteomic Analysis of Microvesicles and Exosomes from HT22 Cells and Primary Neurons
Chapter number 12
Book title
Neuroproteomics
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6952-4_12
Pubmed ID
Book ISBNs
978-1-4939-6950-0, 978-1-4939-6952-4, 978-1-4939-6950-0, 978-1-4939-6952-4
Authors

Richard Witas, Dale Chaput, Hirah Khan, Stanley M. Stevens, David Kang, Stanley M. Stevens Jr.

Editors

Firas H. Kobeissy, Stanley M. Stevens, Jr.

Abstract

Exosomes and microvesicles are extracellular vesicles (EVs) released by most cell types. The role of EVs as a method of intercellular communication has led to these vesicles becoming a major area of interest in a variety of scientific fields including neuroscience. Emerging evidence is now demonstrating that the biomolecular composition of EVs, especially exosomes, can play a role in the progression of disease including various neurodegenerative diseases and cancer. In addition to the miRNA profiles of EVs, these vesicles also show interesting changes in protein expression profiles under different physiological and pathological conditions. Characterization of these profiles could prove valuable for both understanding disease pathogenesis and for the discovery of new biomarkers of disease. In this chapter, we describe a protocol for isolation of exosomes and microvesicles from immortalized HT22 cells and primary cortical neurons with sufficient yield and low serum contamination required for downstream analysis and label-free relative quantitation by mass spectrometry.

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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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 30 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 23%
Student > Doctoral Student 6 20%
Student > Bachelor 3 10%
Researcher 3 10%
Professor 3 10%
Other 3 10%
Unknown 5 17%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 27%
Neuroscience 5 17%
Medicine and Dentistry 3 10%
Pharmacology, Toxicology and Pharmaceutical Science 2 7%
Immunology and Microbiology 2 7%
Other 4 13%
Unknown 6 20%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 17 May 2017.
All research outputs
#20,420,242
of 22,971,207 outputs
Outputs from Methods in molecular biology
#9,928
of 13,146 outputs
Outputs of similar age
#356,026
of 421,092 outputs
Outputs of similar age from Methods in molecular biology
#842
of 1,074 outputs
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