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Biophysics of Infection

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Cover of 'Biophysics of Infection'

Table of Contents

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    Book Overview
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    Chapter 1 Biophysics of Infection
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    Chapter 2 Biophysics of Infection
  4. Altmetric Badge
    Chapter 3 Biophysics of Infection
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    Chapter 4 Biophysics of Infection
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    Chapter 5 Evolution of Drug Resistance in Bacteria
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    Chapter 6 Using Biophysics to Monitor the Essential Protonmotive Force in Bacteria.
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    Chapter 7 Biophysics of Infection
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    Chapter 8 Biophysics of Infection
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    Chapter 9 Biophysics of Infection
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    Chapter 10 Bacterial Surfaces: Front Lines in Host-Pathogen Interaction.
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    Chapter 11 Biophysical Approaches to Bacterial Gene Regulation by Riboswitches
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    Chapter 12 Biophysics of Infection
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    Chapter 13 Transcription Regulation and Membrane Stress Management in Enterobacterial Pathogens.
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    Chapter 14 Biophysics of Infection
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    Chapter 15 Biophysics of Infection
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    Chapter 16 Neutron Reflectivity as a Tool for Physics-Based Studies of Model Bacterial Membranes
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    Chapter 17 Mechanisms of Salmonella Typhi Host Restriction.
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    Chapter 18 Biophysics of Infection
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    Chapter 19 Force Spectroscopy in Studying Infection.
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    Chapter 20 Biophysics of Infection
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    Chapter 21 Biophysics of Infection
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    Chapter 22 Erratum to: The Type I Restriction Enzymes as Barriers to Horizontal Gene Transfer: Determination of the DNA Target Sequences Recognised by Livestock-Associated Methicillin-Resistant Staphylococcus aureus Clonal Complexes 133/ST771 and 398
Attention for Chapter 4: Biophysics of Infection
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Chapter title
Biophysics of Infection
Chapter number 4
Book title
Biophysics of Infection
Published in
Advances in experimental medicine and biology, May 2016
DOI 10.1007/978-3-319-32189-9_4
Pubmed ID
Book ISBNs
978-3-31-932187-5, 978-3-31-932189-9
Authors

Alys K Jepson, Jana Schwarz-Linek, Lloyd Ryan, Maxim G Ryadnov, Wilson C K Poon, Alys K. Jepson, Maxim G. Ryadnov, Wilson C. K. Poon

Editors

Mark C. Leake

Abstract

We measured the minimum inhibitory concentration (MIC) of the antimicrobial peptide pexiganan acting on Escherichia coli , and found an intrinsic variability in such measurements. These results led to a detailed study of the effect of pexiganan on the growth curve of E. coli, using a plate reader and manual plating (i.e. time-kill curves). The measured growth curves, together with single-cell observations and peptide depletion assays, suggested that addition of a sub-MIC concentration of pexiganan to a population of this bacterium killed a fraction of the cells, reducing peptide activity during the process, while leaving the remaining cells unaffected. This pharmacodynamic hypothesis suggests a considerable inoculum effect, which we quantified. Our results cast doubt on the use of the MIC as 'a measure of the concentration needed for peptide action' and show how 'coarse-grained' studies at the population level give vital information for the correct planning and interpretation of MIC measurements.

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

Geographical breakdown

Country Count As %
Unknown 34 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 18%
Student > Bachelor 4 12%
Professor 4 12%
Student > Master 3 9%
Unspecified 1 3%
Other 3 9%
Unknown 13 38%
Readers by discipline Count As %
Physics and Astronomy 6 18%
Agricultural and Biological Sciences 4 12%
Biochemistry, Genetics and Molecular Biology 3 9%
Unspecified 1 3%
Pharmacology, Toxicology and Pharmaceutical Science 1 3%
Other 4 12%
Unknown 15 44%
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 05 June 2016.
All research outputs
#18,462,696
of 22,876,619 outputs
Outputs from Advances in experimental medicine and biology
#3,316
of 4,951 outputs
Outputs of similar age
#250,763
of 334,153 outputs
Outputs of similar age from Advances in experimental medicine and biology
#92
of 134 outputs
Altmetric has tracked 22,876,619 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,951 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 19th percentile – i.e., 19% of its peers scored the same or lower than it.
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 334,153 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 134 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.