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Detection of nanoplastics in food by asymmetric flow field-flow fractionation coupled to multi-angle light scattering: possibilities, challenges and analytical limitations

Overview of attention for article published in Analytical & Bioanalytical Chemistry, February 2018
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (64th percentile)
  • High Attention Score compared to outputs of the same age and source (80th percentile)

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1 policy source
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Citations

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242 Mendeley
Title
Detection of nanoplastics in food by asymmetric flow field-flow fractionation coupled to multi-angle light scattering: possibilities, challenges and analytical limitations
Published in
Analytical & Bioanalytical Chemistry, February 2018
DOI 10.1007/s00216-018-0919-8
Pubmed ID
Authors

Manuel Correia, Katrin Loeschner

Abstract

We tested the suitability of asymmetric flow field-flow fractionation (AF4) coupled to multi-angle light scattering (MALS) for detection of nanoplastics in fish. A homogenized fish sample was spiked with 100 nm polystyrene nanoparticles (PSNPs) (1.3 mg/g fish). Two sample preparation strategies were tested: acid digestion and enzymatic digestion with proteinase K. Both procedures were found suitable for degradation of the organic matrix. However, acid digestion resulted in large PSNPs aggregates/agglomerates (> 1 μm). The presence of large particulates was not observed after enzymatic digestion, and consequently it was chosen as a sample preparation method. The results demonstrated that it was possible to use AF4 for separating the PSNPs from the digested fish and to determine their size by MALS. The PSNPs could be easily detected by following their light scattering (LS) signal with a limit of detection of 52 μg/g fish. The AF4-MALS method could also be exploited for another type of nanoplastics in solution, namely polyethylene (PE). However, it was not possible to detect the PE particles in fish, due to the presence of an elevated LS background. Our results demonstrate that an analytical method developed for a certain type of nanoplastics may not be directly applicable to other types of nanoplastics and may require further adjustment. This work describes for the first time the detection of nanoplastics in a food matrix by AF4-MALS. Despite the current limitations, this is a promising methodology for detecting nanoplastics in food and in experimental studies (e.g., toxicity tests, uptake studies). Graphical abstract Basic concept for the detection of nanoplastics in fish by asymmetric flow field-flow fractionation coupled to multi-angle light scattering.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 242 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 242 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 44 18%
Researcher 33 14%
Student > Ph. D. Student 30 12%
Student > Doctoral Student 15 6%
Student > Bachelor 10 4%
Other 32 13%
Unknown 78 32%
Readers by discipline Count As %
Chemistry 54 22%
Environmental Science 28 12%
Engineering 14 6%
Agricultural and Biological Sciences 13 5%
Biochemistry, Genetics and Molecular Biology 9 4%
Other 32 13%
Unknown 92 38%
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 01 January 2022.
All research outputs
#8,264,793
of 25,382,440 outputs
Outputs from Analytical & Bioanalytical Chemistry
#1,976
of 9,619 outputs
Outputs of similar age
#156,254
of 446,116 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#29
of 189 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one has received more attention than most of these and is in the 66th percentile.
So far Altmetric has tracked 9,619 research outputs from this source. They receive a mean Attention Score of 3.1. This one has done well, scoring higher than 77% 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 446,116 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 64% of its contemporaries.
We're also able to compare this research output to 189 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 80% of its contemporaries.