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Glioblastoma

Overview of attention for book
Cover of 'Glioblastoma'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 Whole Genome Sequencing-Based Discovery of Structural Variants in Glioblastoma
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    Chapter 2 Whole Genome DNA Methylation Analysis of Human Glioblastoma Using Illumina BeadArrays
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    Chapter 3 Establishing Primary Human Glioblastoma Adherent Cultures from Operative Specimens
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    Chapter 4 Establishing Primary Human Glioblastoma Tumorsphere Cultures from Operative Specimens
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    Chapter 5 Isolation of Glioblastoma Stem Cells with Flow Cytometry
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    Chapter 6 Lentiviral Transduction of Primary Human Glioblastoma Cultures
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    Chapter 7 Selective Targeting of CD133-Expressing Glioblastoma Stem Cells Using Lentiviral Vectors
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    Chapter 8 Intracellular pH Measurements in Glioblastoma Cells Using the pH-Sensitive Dye BCECF
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    Chapter 9 Induction and Assessment of Hypoxia in Glioblastoma Cells In Vitro
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    Chapter 10 Metabolomic Analysis of Glioma Cells Using Nanoflow Liquid Chromatography–Tandem Mass Spectrometry
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    Chapter 11 Sample Preparation for Relative Quantitation of Proteins Using Tandem Mass Tags (TMT) and Mass Spectrometry (MS)
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    Chapter 12 Single-Cell RNA Sequencing of Glioblastoma Cells
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    Chapter 13 Evaluation of Radioresponse and Radiosensitizers in Glioblastoma Organotypic Cultures
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    Chapter 14 Orthotopic Patient-Derived Glioblastoma Xenografts in Mice
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    Chapter 15 Bioluminescent In Vivo Imaging of Orthotopic Glioblastoma Xenografts in Mice
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    Chapter 16 Evaluation of Vascularity, Blood Perfusion, and Oxygen Tension in Tumor Xenografts with Fluorescent Microscopy
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    Chapter 17 Probing Glioblastoma Tissue Heterogeneity with Laser Capture Microdissection
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    Chapter 18 Flow Cytometric Identification of Tumor-Infiltrating Lymphocytes from Glioblastoma
  20. Altmetric Badge
    Chapter 19 Modeling Glioma with Human Embryonic Stem Cell-Derived Neural Lineages
Attention for Chapter 10: Metabolomic Analysis of Glioma Cells Using Nanoflow Liquid Chromatography–Tandem Mass Spectrometry
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Chapter title
Metabolomic Analysis of Glioma Cells Using Nanoflow Liquid Chromatography–Tandem Mass Spectrometry
Chapter number 10
Book title
Glioblastoma
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7659-1_10
Pubmed ID
29392696
Book ISBNs
978-1-4939-7658-4, 978-1-4939-7659-1
Authors

Jingjing Deng, Guoan Zhang, Thomas A. Neubert

Abstract

Mass spectrometry (MS)-based techniques have been finding utility as sensitive, high throughput metabolite analysis tools for complex biological samples. We describe here a nanoflow liquid chromatography-tandem mass spectrometry (nano-LC-MS/MS) system we developed and applied to metabolic profiling of human cells. Metabolites are extracted from cells using methanol, and filtered through a C18 StageTip to remove large particles. Metabolite samples are separated by HPLC at a flow rate of 400-500 nl/min, then analyzed in both positive and negative ion modes in an LTQ-Orbitrap MS. Metabolite identification and differential analysis are performed using commercial or open source software. Protocols outlined in this chapter describe how nano-LC-MS can be applied to investigate metabolic profiling with limited biomass amount.

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X Demographics

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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 36%
Student > Bachelor 2 18%
Student > Doctoral Student 1 9%
Unspecified 1 9%
Lecturer 1 9%
Other 1 9%
Unknown 1 9%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 4 36%
Unspecified 1 9%
Agricultural and Biological Sciences 1 9%
Neuroscience 1 9%
Chemistry 1 9%
Other 0 0%
Unknown 3 27%
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 04 February 2018.
All research outputs
#20,462,806
of 23,020,670 outputs
Outputs from Methods in molecular biology
#9,945
of 13,166 outputs
Outputs of similar age
#378,193
of 442,361 outputs
Outputs of similar age from Methods in molecular biology
#1,193
of 1,498 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,166 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
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We're also able to compare this research output to 1,498 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.

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