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Human Fungal Pathogen Identification

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Cover of 'Human Fungal Pathogen Identification'

Table of Contents

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    Book Overview
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    Chapter 1 Current Challenges in the Diagnosis of Fungal Infections.
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    Chapter 2 Human Fungal Pathogen Identification
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    Chapter 3 Current Algorithms in Fungal Diagnosis in the Immunocompromised Host.
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    Chapter 4 Commercial Molecular Tests for Fungal Diagnosis from a Practical Point of View.
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    Chapter 5 Systemic Antifungal Agents: Current Status and Projected Future Developments.
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    Chapter 6 Fungal-Grade Reagents and Materials for Molecular Analysis.
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    Chapter 7 Host-Derived Biomarkers for Risk Assessment of Invasive Fungal Diseases.
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    Chapter 8 Assessment of Immune Responses to Fungal Infections: Identification and Characterization of Immune Cells in the Infected Tissue.
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    Chapter 9 Histopathology.
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    Chapter 10 Culture-Based Techniques.
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    Chapter 11 Serological Approaches.
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    Chapter 12 Isolation of Nucleic Acids for Fungal Diagnosis.
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    Chapter 13 Prerequisites for Control of Contamination in Fungal Diagnosis.
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    Chapter 14 Broad-Spectrum Molecular Detection of Fungal Nucleic Acids by PCR-Based Amplification Techniques.
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    Chapter 15 Genus- and Species-Specific PCR Detection Methods.
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    Chapter 16 Identification of Fungal Pathogens in Tissue Samples from Patients with Proven Invasive Infection by Fluorescence In Situ Hybridization.
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    Chapter 17 Nuclear Magnetic Resonance Spectroscopy-Based Identification of Yeast.
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    Chapter 18 T2 Magnetic Resonance for Fungal Diagnosis.
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    Chapter 19 Fungal Species Identification by MALDI-ToF Mass Spectrometry.
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    Chapter 20 Immunological Identification of Fungal Species.
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    Chapter 21 Human Fungal Pathogen Identification
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    Chapter 22 Microarray Technologies in Fungal Diagnostics.
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    Chapter 23 Molecular Detection of Resistance to Echinocandins.
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    Chapter 24 Molecular Detection of Resistance to Azole Components.
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    Chapter 25 Immune Cell-Supplemented Human Skin Model for Studying Fungal Infections.
Attention for Chapter 14: Broad-Spectrum Molecular Detection of Fungal Nucleic Acids by PCR-Based Amplification Techniques.
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Chapter title
Broad-Spectrum Molecular Detection of Fungal Nucleic Acids by PCR-Based Amplification Techniques.
Chapter number 14
Book title
Human Fungal Pathogen Identification
Published in
Methods in molecular biology, January 2017
DOI 10.1007/978-1-4939-6515-1_14
Pubmed ID
Book ISBNs
978-1-4939-6513-7, 978-1-4939-6515-1
Authors

Stefan Czurda, Thomas Lion M.D., Ph.D., Thomas Lion

Editors

Thomas Lion

Abstract

Over the past decade, the incidence of life-threatening invasive fungal infections has dramatically increased. Infections caused by hitherto rare and emerging fungal pathogens are associated with significant morbidity and mortality among immunocompromised patients. These observations render the coverage of a broad range of clinically relevant fungal pathogens highly important. The so-called panfungal or, perhaps more correctly, broad-range nucleic acid amplification techniques do not only facilitate sensitive detection of all clinically relevant fungal species but are also rapid and can be applied to analyses of any patient specimens. They have therefore become valuable diagnostic tools for sensitive screening of patients at risk of invasive fungal infections. This chapter summarizes the currently available molecular technologies employed in testing of a wide range of fungal pathogens, and provides a detailed workflow for patient screening by broad-spectrum nucleic acid amplification techniques.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 20%
Professor 1 20%
Researcher 1 20%
Student > Postgraduate 1 20%
Student > Master 1 20%
Other 0 0%
Readers by discipline Count As %
Medicine and Dentistry 2 40%
Unspecified 1 20%
Environmental Science 1 20%
Engineering 1 20%