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Glioblastoma

Overview of attention for book
Cover of 'Glioblastoma'

Table of Contents

  1. Altmetric Badge
    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
  4. Altmetric Badge
    Chapter 3 Establishing Primary Human Glioblastoma Adherent Cultures from Operative Specimens
  5. Altmetric Badge
    Chapter 4 Establishing Primary Human Glioblastoma Tumorsphere Cultures from Operative Specimens
  6. Altmetric Badge
    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
  12. Altmetric Badge
    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
  18. Altmetric Badge
    Chapter 17 Probing Glioblastoma Tissue Heterogeneity with Laser Capture Microdissection
  19. Altmetric Badge
    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 18: Flow Cytometric Identification of Tumor-Infiltrating Lymphocytes from Glioblastoma
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (69th percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

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Chapter title
Flow Cytometric Identification of Tumor-Infiltrating Lymphocytes from Glioblastoma
Chapter number 18
Book title
Glioblastoma
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7659-1_18
Pubmed ID
Book ISBNs
978-1-4939-7658-4, 978-1-4939-7659-1
Authors

Karolina Woroniecka, Pakawat Chongsathidkiet, Aladine Elsamadicy, Harrison Farber, Xiuyu Cui, Peter E. Fecci, Woroniecka, Karolina, Chongsathidkiet, Pakawat, Elsamadicy, Aladine, Farber, Harrison, Cui, Xiuyu, Fecci, Peter E.

Abstract

We describe an isolation method of tumor-infiltrating lymphocytes (TILs) from glioblastoma tumors for the purpose of analysis by flow cytometry. This protocol is unique from many others in that the use of a selective lymphocyte isolation procedure, such as a Ficoll or Percoll gradient, is not used. We find that staining of TILs and analysis by flow cytometry is not affected by the presence of heterogeneous populations, while other selective isolation procedures can significantly decrease lymphocyte yield from already rare populations.

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

Geographical breakdown

Country Count As %
Unknown 28 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 4 14%
Student > Master 4 14%
Researcher 4 14%
Other 3 11%
Student > Ph. D. Student 2 7%
Other 3 11%
Unknown 8 29%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 7 25%
Medicine and Dentistry 4 14%
Agricultural and Biological Sciences 2 7%
Immunology and Microbiology 2 7%
Nursing and Health Professions 1 4%
Other 0 0%
Unknown 12 43%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 26 March 2020.
All research outputs
#6,491,526
of 23,020,670 outputs
Outputs from Methods in molecular biology
#1,969
of 13,166 outputs
Outputs of similar age
#132,204
of 442,361 outputs
Outputs of similar age from Methods in molecular biology
#180
of 1,498 outputs
Altmetric has tracked 23,020,670 research outputs across all sources so far. This one has received more attention than most of these and is in the 70th percentile.
So far Altmetric has tracked 13,166 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done well, scoring higher than 84% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 442,361 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 69% of its contemporaries.
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 has done well, scoring higher than 87% of its contemporaries.