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Serum/Plasma Proteomics

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Cover of 'Serum/Plasma Proteomics'

Table of Contents

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    Book Overview
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    Chapter 1 Direct Assessment of Plasma/Serum Sample Quality for Proteomics Biomarker Investigation
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    Chapter 2 A Protocol for the Preparation of Cryoprecipitate and Cryo-depleted Plasma for Proteomic Studies
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    Chapter 3 Preparation of Platelet Concentrates for Research and Transfusion Purposes
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    Chapter 4 Bead-Based and Multiplexed Immunoassays for Protein Profiling via Sequential Affinity Capture
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    Chapter 5 Affinity Proteomics for Fast, Sensitive, Quantitative Analysis of Proteins in Plasma
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    Chapter 6 Characterization of the Low-Molecular-Weight Human Plasma Peptidome
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    Chapter 7 In-Depth, Reproducible Analysis of Human Plasma Using IgY 14 and SuperMix Immunodepletion
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    Chapter 8 Low-Molecular-Weight Plasma Proteome Analysis Using Top-Down Mass Spectrometry
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    Chapter 9 Identification of Post-Translational Modifications from Serum/Plasma by Immunoaffinity Enrichment and LC-MS/MS Analysis Without Depletion of Abundant Proteins
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    Chapter 10 Identification of Core-Fucosylated Glycoproteome in Human Plasma
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    Chapter 11 Proteomic Analysis of Blood Extracellular Vesicles in Cardiovascular Disease by LC-MS/MS Analysis
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    Chapter 12 Targeted Approach for Proteomic Analysis of a Hidden Membrane Protein
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    Chapter 13 Red Blood Cells in Clinical Proteomics
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    Chapter 14 High-Throughput Quantitative Lipidomics Analysis of Nonesterified Fatty Acids in Plasma by LC-MS
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    Chapter 15 Simultaneous Enrichment of Plasma Extracellular Vesicles and Glycoproteome for Studying Disease Biomarkers
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    Chapter 16 Lipidomics of Human Blood Plasma by High-Resolution Shotgun Mass Spectrometry
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    Chapter 17 Proteomics Analysis of Circulating Serum Exosomes
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    Chapter 18 High-Density Serum/Plasma Reverse Phase Protein Arrays
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    Chapter 19 Antibody Colocalization Microarray for Cross-Reactivity-Free Multiplexed Protein Analysis
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    Chapter 20 Surface Profiling of Extracellular Vesicles from Plasma or Ascites Fluid Using DotScan Antibody Microarrays
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    Chapter 21 Serum Profiling for Identification of Autoantibody Signatures in Diseases Using Protein Microarrays
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    Chapter 22 Quantitative Comparisons of Large Numbers of Human Plasma Samples Using TMT10plex Labeling
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    Chapter 23 Efficient Quantitative Comparisons of Plasma Proteomes Using Label-Free Analysis with MaxQuant
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    Chapter 24 Blood and Plasma Proteomics: Targeted Quantitation and Posttranslational Redox Modifications
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    Chapter 25 SWATH Mass Spectrometry for Proteomics of Non-Depleted Plasma
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    Chapter 26 Shotgun and Targeted Plasma Proteomics to Predict Prognosis of Non-Small Cell Lung Cancer
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    Chapter 27 High-Throughput Parallel Proteomic Sample Preparation Using 96-Well Polyvinylidene Fluoride (PVDF) Membranes and C18 Purification Plates
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    Chapter 28 Targeted Quantification of the Glycated Peptides of Human Serum Albumin
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    Chapter 29 Absolute Quantification of Middle- to High-Abundant Plasma Proteins via Targeted Proteomics
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    Chapter 30 A Highly Automated Shotgun Proteomic Workflow: Clinical Scale and Robustness for Biomarker Discovery in Blood
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    Chapter 31 Mass Spectrometry-Based Serum Proteomics for Biomarker Discovery and Validation
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    Chapter 32 Metabolomics Toward Biomarker Discovery
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    Chapter 33 Plasma Biomarker Identification and Quantification by Microparticle Proteomics
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    Chapter 34 Bronchoalveolar Lavage: Quantitative Mass Spectrometry-Based Proteomics Analysis in Lung Diseases
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    Chapter 35 Protein Multiplexed Immunoassay Analysis with R
Attention for Chapter 3: Preparation of Platelet Concentrates for Research and Transfusion Purposes
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Chapter title
Preparation of Platelet Concentrates for Research and Transfusion Purposes
Chapter number 3
Book title
Serum/Plasma Proteomics
Published in
Methods in molecular biology, July 2017
DOI 10.1007/978-1-4939-7057-5_3
Pubmed ID
Book ISBNs
978-1-4939-7056-8, 978-1-4939-7057-5
Authors

David W. Greening Ph.D., Richard J. Simpson, Rosemary L. Sparrow Ph.D., David W. Greening, Rosemary L. Sparrow, Greening, David W., Simpson, Richard J., Sparrow, Rosemary L.

Editors

David W. Greening, Richard J. Simpson

Abstract

Platelets are specialized cellular elements of the blood that play central roles in physiologic and pathologic processes of hemostasis, wound healing, host defense, thrombosis, inflammation, and tumor metastasis. Activation of platelets is crucial for platelet function that includes a complex interplay of adhesion, signaling molecules, and release of bioactive factors. Transfusion of platelet concentrates is an important treatment component for thrombocytopenia and bleeding. Recent progress in high-throughput mRNA and protein profiling techniques has advanced the understanding of platelet biological functions toward identifying novel platelet-expressed and secreted proteins, analyzing functional changes between normal and pathologic states, and determining the effects of processing and storage on platelet concentrates for transfusion. It is important to understand the different standard methods of platelet preparation and how they differ from the perspective for use as research samples in clinical chemistry. Two simple methods are described here for the preparation of research-scale platelet samples from whole blood, and detailed notes are provided about the methods used for the preparation of platelet concentrates for transfusion.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 21 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 14%
Student > Ph. D. Student 3 14%
Other 2 10%
Student > Bachelor 2 10%
Student > Postgraduate 2 10%
Other 2 10%
Unknown 7 33%
Readers by discipline Count As %
Medicine and Dentistry 4 19%
Agricultural and Biological Sciences 2 10%
Social Sciences 2 10%
Computer Science 1 5%
Veterinary Science and Veterinary Medicine 1 5%
Other 2 10%
Unknown 9 43%