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Pathway-focused bioassays and transcriptome analysis contribute to a better activity monitoring of complex herbal remedies

Overview of attention for article published in BMC Genomics, February 2013
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Title
Pathway-focused bioassays and transcriptome analysis contribute to a better activity monitoring of complex herbal remedies
Published in
BMC Genomics, February 2013
DOI 10.1186/1471-2164-14-133
Pubmed ID
Authors

Angela Klein, Oliver A Wrulich, Marcel Jenny, Peter Gruber, Kathrin Becker, Dietmar Fuchs, Johanna M Gostner, Florian Überall

Abstract

Transcriptome analysis in combination with pathway-focused bioassays is suggested to be a helpful approach for gaining deeper insights into the complex mechanisms of action of herbal multicomponent preparations in living cells. The polyherbalism based concept of Tibetan and Ayurvedic medicine considers therapeutic efficacy through multi-target effects. A polyherbal Indo-Tibetan preparation, Padma 28, approved by the Swiss drug authorities (Swissmedic Nr. 58436), was applied to a more detailed dissection of mechanism of action in human hepatoma HepG2 cells. Cell-free and cell-based assays were employed to evaluate the antioxidant capacity. Genome-wide expression profiling was done by applying Human Genome U133 Plus 2.0 Affymetrix arrays. Pathway- and network-oriented analysis elucidated the affected biological processes. The results were validated using reporter gene assays and quantitative real-time PCR.

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

Geographical breakdown

Country Count As %
Netherlands 1 4%
Unknown 24 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 7 28%
Researcher 4 16%
Student > Bachelor 2 8%
Other 2 8%
Professor > Associate Professor 2 8%
Other 5 20%
Unknown 3 12%
Readers by discipline Count As %
Agricultural and Biological Sciences 9 36%
Biochemistry, Genetics and Molecular Biology 3 12%
Chemistry 2 8%
Business, Management and Accounting 2 8%
Medicine and Dentistry 2 8%
Other 2 8%
Unknown 5 20%
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 28 February 2013.
All research outputs
#18,331,227
of 22,699,621 outputs
Outputs from BMC Genomics
#8,152
of 10,616 outputs
Outputs of similar age
#146,777
of 192,966 outputs
Outputs of similar age from BMC Genomics
#97
of 138 outputs
Altmetric has tracked 22,699,621 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 10,616 research outputs from this source. They receive a mean Attention Score of 4.7. This one is in the 12th percentile – i.e., 12% 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 192,966 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 12th percentile – i.e., 12% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 138 others from the same source and published within six weeks on either side of this one. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.