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Adverse outcome pathway development from protein alkylation to liver fibrosis

Overview of attention for article published in Archives of Toxicology, August 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (65th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (53rd percentile)

Mentioned by

policy
1 policy source
facebook
1 Facebook page

Citations

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45 Dimensions

Readers on

mendeley
81 Mendeley
Title
Adverse outcome pathway development from protein alkylation to liver fibrosis
Published in
Archives of Toxicology, August 2016
DOI 10.1007/s00204-016-1814-8
Pubmed ID
Authors

Tomislav Horvat, Brigitte Landesmann, Alfonso Lostia, Mathieu Vinken, Sharon Munn, Maurice Whelan

Abstract

In modern toxicology, substantial efforts are undertaken to develop alternative solutions for in vivo toxicity testing. The adverse outcome pathway (AOP) concept could facilitate knowledge-based safety assessment of chemicals that does not rely exclusively on in vivo toxicity testing. The construction of an AOP is based on understanding toxicological processes at different levels of biological organisation. Here, we present the developed AOP for liver fibrosis and demonstrate a linkage between hepatic injury caused by chemical protein alkylation and the formation of liver fibrosis, supported by coherent and consistent scientific data. This long-term process, in which inflammation, tissue destruction, and repair occur simultaneously, results from the complex interplay between various hepatic cell types, receptors, and signalling pathways. Due to the complexity of the process, an adequate liver fibrosis cell model for in vitro evaluation of a chemical's fibrogenic potential is not yet available. Liver fibrosis poses an important human health issue that is also relevant for regulatory purposes. An AOP described with enough mechanistic detail might support chemical risk assessment by indicating early markers for downstream events and thus facilitating the development of an in vitro testing strategy. With this work, we demonstrate how the AOP framework can support the assembly and coherent display of distributed mechanistic information from the literature to support the use of alternative approaches for prediction of toxicity. This AOP was developed according to the guidance document on developing and assessing AOPs and its supplement, the users' handbook, issued by the Organisation for Economic Co-operation and Development.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 81 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Italy 1 1%
Brazil 1 1%
Unknown 79 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 14 17%
Student > Bachelor 12 15%
Student > Ph. D. Student 11 14%
Other 9 11%
Student > Master 6 7%
Other 10 12%
Unknown 19 23%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 14 17%
Biochemistry, Genetics and Molecular Biology 11 14%
Agricultural and Biological Sciences 8 10%
Medicine and Dentistry 6 7%
Chemistry 6 7%
Other 9 11%
Unknown 27 33%
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 05 April 2017.
All research outputs
#7,277,460
of 22,962,258 outputs
Outputs from Archives of Toxicology
#934
of 2,647 outputs
Outputs of similar age
#115,424
of 344,052 outputs
Outputs of similar age from Archives of Toxicology
#22
of 47 outputs
Altmetric has tracked 22,962,258 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 2,647 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.2. This one has gotten more attention than average, scoring higher than 63% 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 344,052 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 65% of its contemporaries.
We're also able to compare this research output to 47 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.