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Antibiotic Resistance Protocols

Overview of attention for book
Cover of 'Antibiotic Resistance Protocols'

Table of Contents

  1. Altmetric Badge
    Book Overview
  2. Altmetric Badge
    Chapter 1 Methods for Measuring the Production of Quorum Sensing Signal Molecules
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    Chapter 2 Construction and Use of Staphylococcus aureus Strains to Study Within-Host Infection Dynamics
  4. Altmetric Badge
    Chapter 3 Method for Detecting and Studying Genome-Wide Mutations in Single Living Cells in Real Time
  5. Altmetric Badge
    Chapter 4 Detecting Phenotypically Resistant Mycobacterium tuberculosis Using Wavelength Modulated Raman Spectroscopy
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    Chapter 5 A Flow Cytometry Method for Assessing M. tuberculosis Responses to Antibiotics
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    Chapter 6 Application of Continuous Culture for Assessing Antibiotic Activity Against Mycobacterium tuberculosis
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    Chapter 7 Real-Time Digital Bright Field Technology for Rapid Antibiotic Susceptibility Testing
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    Chapter 8 Enhanced Methodologies for Detecting Phenotypic Resistance in Mycobacteria
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    Chapter 9 Methods to Determine Mutational Trajectories After Experimental Evolution of Antibiotic Resistance
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    Chapter 10 Selection of ESBL-Producing E. coli in a Mouse Intestinal Colonization Model
  12. Altmetric Badge
    Chapter 11 Transcriptional Profiling Mycobacterium tuberculosis from Patient Sputa
  13. Altmetric Badge
    Chapter 12 Direct in Gel Genomic Detection of Antibiotic Resistance Genes in S1 Pulsed Field Electrophoresis Gels
  14. Altmetric Badge
    Chapter 13 Using RT qPCR for Quantifying Mycobacteria marinum from In Vitro and In Vivo Samples
  15. Altmetric Badge
    Chapter 14 Use of Larval Zebrafish Model to Study Within-Host Infection Dynamics
  16. Altmetric Badge
    Chapter 15 A Method to Evaluate Persistent Mycobacterium tuberculosis In Vitro and in the Cornell Mouse Model of Tuberculosis
Attention for Chapter 4: Detecting Phenotypically Resistant Mycobacterium tuberculosis Using Wavelength Modulated Raman Spectroscopy
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (90th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

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14 X users
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1 Google+ user

Citations

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Chapter title
Detecting Phenotypically Resistant Mycobacterium tuberculosis Using Wavelength Modulated Raman Spectroscopy
Chapter number 4
Book title
Antibiotic Resistance Protocols
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7638-6_4
Pubmed ID
29322457
Book ISBNs
978-1-4939-7636-2, 978-1-4939-7638-6
Authors

Vincent O. Baron, Mingzhou Chen, Simon O. Clark, Ann Williams, Kishan Dholakia, Stephen H. Gillespie, Baron, Vincent O., Chen, Mingzhou, Clark, Simon O., Williams, Ann, Dholakia, Kishan, Gillespie, Stephen H.

Abstract

Raman spectroscopy is a non-destructive and label-free technique. Wavelength modulated Raman (WMR) spectroscopy was applied to investigate Mycobacterium tuberculosis cell state, lipid rich (LR) and lipid poor (LP). Compared to LP cells, LR cells can be up to 40 times more resistant to key antibiotic regimens. Using this methodology single lipid rich (LR) from lipid poor (LP) bacteria can be differentiated with both high sensitivity and specificity. It can also be used to investigate experimentally infected frozen tissue sections where both cell types can be differentiated. This methodology could be utilized to study the phenotype of mycobacterial cells in other tissues.

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X Demographics

X Demographics

The data shown below were collected from the profiles of 14 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 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 14 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 36%
Student > Bachelor 2 14%
Researcher 2 14%
Student > Master 2 14%
Other 1 7%
Other 0 0%
Unknown 2 14%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 2 14%
Engineering 2 14%
Immunology and Microbiology 2 14%
Biochemistry, Genetics and Molecular Biology 1 7%
Computer Science 1 7%
Other 2 14%
Unknown 4 29%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 18. 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 25 December 2018.
All research outputs
#1,776,054
of 23,128,387 outputs
Outputs from Methods in molecular biology
#248
of 13,269 outputs
Outputs of similar age
#43,452
of 442,846 outputs
Outputs of similar age from Methods in molecular biology
#14
of 1,499 outputs
Altmetric has tracked 23,128,387 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 13,269 research outputs from this source. They receive a mean Attention Score of 3.4. This one has done particularly well, scoring higher than 98% 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 442,846 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 90% of its contemporaries.
We're also able to compare this research output to 1,499 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.

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