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Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice

Overview of attention for article published in International Journal of Nanomedicine, October 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
1 tweeter
googleplus
1 Google+ user

Citations

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28 Dimensions

Readers on

mendeley
39 Mendeley
Title
Physiologically based pharmacokinetic modeling of zinc oxide nanoparticles and zinc nitrate in mice
Published in
International Journal of Nanomedicine, October 2015
DOI 10.2147/ijn.s86785
Pubmed ID
Authors

Pinpin Lin, Wei-Yu Chen, Yi-Hsien Cheng, Nan-Hung Hsieh, Bo-Chun Wu, Wei-Chun Chou, Chia-Chi Ho, Chung-Min Liao, Jen-Kun Chen

Abstract

Zinc oxide nanoparticles (ZnO NPs) have been widely used in consumer products, therapeutic agents, and drug delivery systems. However, the fate and behavior of ZnO NPs in living organisms are not well described. The purpose of this study was to develop a physiologically based pharmacokinetic model to describe the dynamic interactions of (65)ZnO NPs in mice. We estimated key physicochemical parameters of partition coefficients and excretion or elimination rates, based on our previously published data quantifying the biodistributions of 10 nm and 71 nm (65)ZnO NPs and zinc nitrate ((65)Zn(NO3)2) in various mice tissues. The time-dependent partition coefficients and excretion or elimination rates were used to construct our physiologically based pharmacokinetic model. In general, tissue partition coefficients of (65)ZnO NPs were greater than those of (65)Zn(NO3)2, particularly the lung partition coefficient of 10 nm (65)ZnO NPs. Sensitivity analysis revealed that 71 nm (65)ZnO NPs and (65)Zn(NO3)2 were sensitive to excretion and elimination rates in the liver and gastrointestinal tract. Although the partition coefficient of the brain was relative low, it increased time-dependently for (65)ZnO NPs and (65)Zn(NO3)2. The simulation of (65)Zn(NO3)2 was well fitted with the experimental data. However, replacing partition coefficients of (65)ZnO NPs with those of (65)Zn(NO3)2 after day 7 greatly improved the fitness of simulation, suggesting that ZnO NPs might decompose to zinc ion after day 7. In this study, we successfully established a potentially predictive dynamic model for slowly decomposed NPs. More caution is suggested for exposure to (65)ZnO NPs <10 nm because those small (65)ZnO NPs tend to accumulate in the body for a relatively longer time than 71 nm (65)ZnO NPs and (65)Zn(NO3)2 do.

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 39 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 1 3%
Unknown 38 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 11 28%
Researcher 7 18%
Student > Master 6 15%
Student > Doctoral Student 5 13%
Student > Postgraduate 3 8%
Other 4 10%
Unknown 3 8%
Readers by discipline Count As %
Pharmacology, Toxicology and Pharmaceutical Science 10 26%
Environmental Science 5 13%
Medicine and Dentistry 4 10%
Agricultural and Biological Sciences 4 10%
Biochemistry, Genetics and Molecular Biology 3 8%
Other 9 23%
Unknown 4 10%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 07 October 2015.
All research outputs
#2,567,203
of 6,264,458 outputs
Outputs from International Journal of Nanomedicine
#457
of 1,543 outputs
Outputs of similar age
#85,740
of 194,327 outputs
Outputs of similar age from International Journal of Nanomedicine
#67
of 146 outputs
Altmetric has tracked 6,264,458 research outputs across all sources so far. This one has received more attention than most of these and is in the 56th percentile.
So far Altmetric has tracked 1,543 research outputs from this source. They receive a mean Attention Score of 2.1. This one has gotten more attention than average, scoring higher than 62% 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 194,327 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 52% of its contemporaries.
We're also able to compare this research output to 146 others from the same source and published within six weeks on either side of this one. This one is in the 40th percentile – i.e., 40% of its contemporaries scored the same or lower than it.