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Viability characterization of Taxus chinensis plant cell suspension cultures by rapid colorimetric- and image analysis-based techniques

Overview of attention for article published in Bioprocess and Biosystems Engineering, March 2014
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Title
Viability characterization of Taxus chinensis plant cell suspension cultures by rapid colorimetric- and image analysis-based techniques
Published in
Bioprocess and Biosystems Engineering, March 2014
DOI 10.1007/s00449-014-1153-1
Pubmed ID
Authors

Thomas Wucherpfennig, Annika Schulz, Jaime Arturo Pimentel, Gabriel Corkidi, Dominik Sieblitz, Matthias Pump, Gilbert Gorr, Kai Schütte, Christoph Wittmann, Rainer Krull

Abstract

For the commercially established process of paclitaxel production with Taxus chinensis plant cell culture, the size of plant cell aggregates and phenotypic changes in coloration during cultivation have long been acknowledged as intangible parameters. So far, the variability of aggregates and coloration of cells are challenging parameters for any viability assay. The aim of this study was to investigate simple and non-toxic methods for viability determination of Taxus cultures in order to provide a practicable, rapid, robust and reproducible way to sample large amounts of material. A further goal was to examine whether Taxus aggregate cell coloration is related to general cell viability and might be exploited by microscopy and image analysis to gain easy access to general cell viability. The Alamar Blue assay was found to be exceptionally eligible for viability estimation. Moreover, aggregate coloration, as a morphologic attribute, was quantified by image analysis and found to be a good and traceable indicator of T. chinensis viability.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 6 26%
Student > Ph. D. Student 4 17%
Student > Master 3 13%
Researcher 3 13%
Professor 2 9%
Other 3 13%
Unknown 2 9%
Readers by discipline Count As %
Agricultural and Biological Sciences 12 52%
Engineering 3 13%
Biochemistry, Genetics and Molecular Biology 3 13%
Chemical Engineering 1 4%
Unknown 4 17%
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 25 March 2014.
All research outputs
#22,830,981
of 25,457,297 outputs
Outputs from Bioprocess and Biosystems Engineering
#8
of 8 outputs
Outputs of similar age
#206,980
of 237,555 outputs
Outputs of similar age from Bioprocess and Biosystems Engineering
#2
of 2 outputs
Altmetric has tracked 25,457,297 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8 research outputs from this source. They receive a mean Attention Score of 2.2. This one scored the same or higher as 0 of them.
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