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Hierarchical imaging: a new concept for targeted imaging of large volumes from cells to tissues

Overview of attention for article published in BMC Molecular and Cell Biology, December 2016
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Title
Hierarchical imaging: a new concept for targeted imaging of large volumes from cells to tissues
Published in
BMC Molecular and Cell Biology, December 2016
DOI 10.1186/s12860-016-0122-8
Pubmed ID
Authors

Irene Wacker, Waldemar Spomer, Andreas Hofmann, Marlene Thaler, Stefan Hillmer, Ulrich Gengenbach, Rasmus R. Schröder

Abstract

Imaging large volumes such as entire cells or small model organisms at nanoscale resolution seemed an unrealistic, rather tedious task so far. Now, technical advances have lead to several electron microscopy (EM) large volume imaging techniques. One is array tomography, where ribbons of ultrathin serial sections are deposited on solid substrates like silicon wafers or glass coverslips. To ensure reliable retrieval of multiple ribbons from the boat of a diamond knife we introduce a substrate holder with 7 axes of translation or rotation specifically designed for that purpose. With this device we are able to deposit hundreds of sections in an ordered way in an area of 22 × 22 mm, the size of a coverslip. Imaging such arrays in a standard wide field fluorescence microscope produces reconstructions with 200 nm lateral resolution and 100 nm (the section thickness) resolution in z. By hierarchical imaging cascades in the scanning electron microscope (SEM), using a new software platform, we can address volumes from single cells to complete organs. In our first example, a cell population isolated from zebrafish spleen, we characterize different cell types according to their organelle inventory by segmenting 3D reconstructions of complete cells imaged with nanoscale resolution. In addition, by screening large numbers of cells at decreased resolution we can define the percentage at which different cell types are present in our preparation. With the second example, the root tip of cress, we illustrate how combining information from intermediate resolution data with high resolution data from selected regions of interest can drastically reduce the amount of data that has to be recorded. By imaging only the interesting parts of a sample considerably less data need to be stored, handled and eventually analysed. Our custom-designed substrate holder allows reproducible generation of section libraries, which can then be imaged in a hierarchical way. We demonstrate, that EM volume data at different levels of resolution can yield comprehensive information, including statistics, morphology and organization of cells and tissue. We predict, that hierarchical imaging will be a first step in tackling the big data issue inevitably connected with volume EM.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 40 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 30%
Student > Bachelor 5 13%
Student > Ph. D. Student 4 10%
Professor 3 8%
Other 2 5%
Other 5 13%
Unknown 9 23%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 15%
Neuroscience 6 15%
Biochemistry, Genetics and Molecular Biology 5 13%
Engineering 3 8%
Medicine and Dentistry 3 8%
Other 5 13%
Unknown 12 30%
Attention Score in Context

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 30 May 2017.
All research outputs
#15,091,901
of 25,374,917 outputs
Outputs from BMC Molecular and Cell Biology
#664
of 1,233 outputs
Outputs of similar age
#222,627
of 419,608 outputs
Outputs of similar age from BMC Molecular and Cell Biology
#2
of 7 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,233 research outputs from this source. They receive a mean Attention Score of 4.0. 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 419,608 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.