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Imaging Mass Spectrometry

Overview of attention for book
Cover of 'Imaging Mass Spectrometry'

Table of Contents

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    Book Overview
  2. Altmetric Badge
    Chapter 1 “A Future Amalgamation Between the Scientist and the Clinician?”
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    Chapter 2 Fresh Frozen Versus Formalin-Fixed Paraffin Embedded for Mass Spectrometry Imaging
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    Chapter 3 Imaging MS of Rodent Ocular Tissues and the Optic Nerve
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    Chapter 4 MALDI-MSI of Lipids in Human Skin
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    Chapter 5 MALDI-MSI Analysis of Cytological Smears: The Study of Thyroid Cancer
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    Chapter 6 Droplet-Based Liquid Extraction for Spatially-Resolved Microproteomics Analysis of Tissue Sections
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    Chapter 7 DESI Mass Spectrometry Imaging (MSI)
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    Chapter 8 Peptide Imaging: Maximizing Peptide Yield, Optimization of the “Peptide Mass Fingerprint”
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    Chapter 9 MALDI-MS Imaging in the Study of Glomerulonephritis
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    Chapter 10 Hierarchical Cluster Analysis to Aid Diagnostic Image Data Visualization of MS and Other Medical Imaging Modalities
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    Chapter 11 Laser Ablation Inductively Coupled Plasma Mass Spectrometry Imaging of Plant Metabolites
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    Chapter 12 Mass Spectrometry Imaging of Drugs of Abuse in Hair
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    Chapter 13 MALDI Mass Spectrometry Profiling and Imaging Applied to the Analysis of Latent Fingermarks
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    Chapter 14 ToF-SIMS Parallel Imaging MS/MS of Lipid Species in Thin Tissue Sections
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    Chapter 15 Rodent Whole-Body Sectioning and MALDI Mass Spectrometry Imaging
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    Chapter 16 The Future in Disease Models for Mass Spectrometry Imaging, Ethical Issues, and the Way Forward
Attention for Chapter 5: MALDI-MSI Analysis of Cytological Smears: The Study of Thyroid Cancer
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Chapter title
MALDI-MSI Analysis of Cytological Smears: The Study of Thyroid Cancer
Chapter number 5
Book title
Imaging Mass Spectrometry
Published in
Methods in molecular biology, May 2017
DOI 10.1007/978-1-4939-7051-3_5
Pubmed ID
Book ISBNs
978-1-4939-7050-6, 978-1-4939-7051-3
Authors

Niccolò Mosele, Andrew Smith, Manuel Galli, Fabio Pagni, Fulvio Magni, Mosele, Niccolò, Smith, Andrew, Galli, Manuel, Pagni, Fabio, Magni, Fulvio

Editors

Laura M. Cole

Abstract

Fine needle aspiration (FNA) biopsies are the current gold-standard for the preoperative evaluation of thyroid nodules. However, a significant number of them (15-30%) are unable to be affirmatively diagnosed and are given an "indeterminate for malignancy" final report, meaning that the malignant nature of the thyroid nodule remains unknown and the recommended therapeutic approach is total thyroidectomy. Furthermore, cytomorphological evaluation of biopsies taken post-surgery indicates that approximately 80% of nodules within this group of patients are in fact benign, and the total thyroidectomy unwarranted. Therefore, the identification of new possible diagnostic targets that can assist in the preoperative diagnosis of thyroid tumors and reduce the number of unnecessary thyroidectomies is imperative.Matrix-Assisted Laser Desorption/Ionization (MALDI)-Mass Spectrometry Imaging (MSI) has the ability to provide very precise and localized information regarding protein expression in cytological specimens. This enables the detection of cell subpopulations based on their different protein profiles, even within regions that are indistinguishable at the microscopic level, and the feasibility of this approach to investigate FNA specimens has already been highlighted in a number of studies. Here, an overview about the sample preparation procedure for the MALDI-MSI analysis of ex vivo FNA biopsies is provided, highlighting how molecular imaging can be combined with traditional histology to generate protein signatures of the different thyroid lesions, and, ultimately, build classification models that can be potentially used to classify benign and malignant thyroid nodules from a molecular standpoint.

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The data shown below were collected from the profiles of 2 X users 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 20%
Student > Master 2 13%
Researcher 2 13%
Student > Bachelor 1 7%
Other 1 7%
Other 1 7%
Unknown 5 33%
Readers by discipline Count As %
Medicine and Dentistry 3 20%
Pharmacology, Toxicology and Pharmaceutical Science 1 7%
Agricultural and Biological Sciences 1 7%
Biochemistry, Genetics and Molecular Biology 1 7%
Decision Sciences 1 7%
Other 1 7%
Unknown 7 47%
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 01 March 2018.
All research outputs
#15,459,782
of 22,973,051 outputs
Outputs from Methods in molecular biology
#5,379
of 13,147 outputs
Outputs of similar age
#196,408
of 312,881 outputs
Outputs of similar age from Methods in molecular biology
#95
of 250 outputs
Altmetric has tracked 22,973,051 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 13,147 research outputs from this source. They receive a mean Attention Score of 3.4. This one is in the 44th percentile – i.e., 44% of its peers scored the same or lower than it.
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