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Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays

Overview of attention for article published in Archives of Toxicology, November 2017
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  • Good Attention Score compared to outputs of the same age (69th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

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Citations

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50 Mendeley
Title
Prediction of metabolism-induced hepatotoxicity on three-dimensional hepatic cell culture and enzyme microarrays
Published in
Archives of Toxicology, November 2017
DOI 10.1007/s00204-017-2126-3
Pubmed ID
Authors

Kyeong-Nam Yu, Sashi Nadanaciva, Payal Rana, Dong Woo Lee, Bosung Ku, Alexander D. Roth, Jonathan S. Dordick, Yvonne Will, Moo-Yeal Lee

Abstract

Human liver contains various oxidative and conjugative enzymes that can convert nontoxic parent compounds to toxic metabolites or, conversely, toxic parent compounds to nontoxic metabolites. Unlike primary hepatocytes, which contain myriad drug-metabolizing enzymes (DMEs), but are difficult to culture and maintain physiological levels of DMEs, immortalized hepatic cell lines used in predictive toxicity assays are easy to culture, but lack the ability to metabolize compounds. To address this limitation and predict metabolism-induced hepatotoxicity in high-throughput, we developed an advanced miniaturized three-dimensional (3D) cell culture array (DataChip 2.0) and an advanced metabolizing enzyme microarray (MetaChip 2.0). The DataChip is a functionalized micropillar chip that supports the Hep3B human hepatoma cell line in a 3D microarray format. The MetaChip is a microwell chip containing immobilized DMEs found in the human liver. As a proof of concept for generating compound metabolites in situ on the chip and rapidly assessing their toxicity, 22 model compounds were dispensed into the MetaChip and sandwiched with the DataChip. The IC50 values obtained from the chip platform were correlated with rat LD50 values, human C max values, and drug-induced liver injury categories to predict adverse drug reactions in vivo. As a result, the platform had 100% sensitivity, 86% specificity, and 93% overall predictivity at optimum cutoffs of IC50 and C max values. Therefore, the DataChip/MetaChip platform could be used as a high-throughput, early stage, microscale alternative to conventional in vitro multi-well plate platforms and provide a rapid and inexpensive assessment of metabolism-induced toxicity at early phases of drug development.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 50 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 50 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 26%
Researcher 8 16%
Student > Bachelor 4 8%
Student > Doctoral Student 4 8%
Student > Postgraduate 3 6%
Other 7 14%
Unknown 11 22%
Readers by discipline Count As %
Engineering 9 18%
Pharmacology, Toxicology and Pharmaceutical Science 7 14%
Biochemistry, Genetics and Molecular Biology 6 12%
Medicine and Dentistry 3 6%
Immunology and Microbiology 2 4%
Other 9 18%
Unknown 14 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 03 October 2023.
All research outputs
#7,068,056
of 24,580,204 outputs
Outputs from Archives of Toxicology
#939
of 2,796 outputs
Outputs of similar age
#132,343
of 447,817 outputs
Outputs of similar age from Archives of Toxicology
#7
of 28 outputs
Altmetric has tracked 24,580,204 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 2,796 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.4. This one has gotten more attention than average, scoring higher than 64% of its peers.
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 447,817 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 69% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.