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Developments in cell biology for quantitative immunoelectron microscopy based on thin sections: a review

Overview of attention for article published in Histochemistry & Cell Biology, June 2008
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  • Good Attention Score compared to outputs of the same age (66th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

Mentioned by

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1 Wikipedia page

Citations

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33 Dimensions

Readers on

mendeley
43 Mendeley
Title
Developments in cell biology for quantitative immunoelectron microscopy based on thin sections: a review
Published in
Histochemistry & Cell Biology, June 2008
DOI 10.1007/s00418-008-0451-6
Pubmed ID
Authors

Terry M. Mayhew, John M. Lucocq

Abstract

Quantitative immunoelectron microscopy uses ultrathin sections and gold particle labelling to determine distributions of molecules across cell compartments. Here, we review a portfolio of new methods for comparing labelling distributions between different compartments in one study group (method 1) and between the same compartments in two or more groups (method 2). Specimen samples are selected unbiasedly and then observed and expected distributions of gold particles are estimated and compared by appropriate statistical procedures. The methods can be used to analyse gold label distributed between volume-occupying (organelle) and surface-occupying (membrane) compartments, but in method 1, membranes must be treated as organelles. With method 1, gold counts are combined with stereological estimators of compartment size to determine labelling density (LD). For volume-occupiers, LD can be expressed simply as golds per test point and, for surface-occupiers, as golds per test line intersection. Expected distributions are generated by randomly assigning gold particles to compartments and expressing observed/expected counts as a relative labelling index (RLI). Preferentially-labelled compartments are identified from their RLI values and by Chi-squared analysis of observed and expected distributions. For method 2, the raw gold particle counts distributed between compartments are simply compared across groups by contingency table and Chi-squared analysis. This identifies the main compartments responsible for the differences between group distributions. Finally, we discuss labelling efficiency (the number of gold particles per target molecule) and describe how it can be estimated for volume- or surface-occupiers by combining stereological data with biochemical determinations.

Mendeley readers

The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
South Africa 1 2%
United Kingdom 1 2%
Unknown 41 95%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 23%
Student > Ph. D. Student 9 21%
Student > Bachelor 7 16%
Student > Master 3 7%
Professor > Associate Professor 3 7%
Other 11 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 56%
Medicine and Dentistry 4 9%
Chemistry 3 7%
Biochemistry, Genetics and Molecular Biology 3 7%
Unspecified 2 5%
Other 7 16%

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 13 April 2009.
All research outputs
#3,497,482
of 12,217,320 outputs
Outputs from Histochemistry & Cell Biology
#106
of 588 outputs
Outputs of similar age
#80,553
of 272,438 outputs
Outputs of similar age from Histochemistry & Cell Biology
#2
of 10 outputs
Altmetric has tracked 12,217,320 research outputs across all sources so far. This one is in the 49th percentile – i.e., 49% of other outputs scored the same or lower than it.
So far Altmetric has tracked 588 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 45th percentile – i.e., 45% 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 272,438 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 66% of its contemporaries.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one. This one has scored higher than 8 of them.