↓ Skip to main content

A direct solid sampling analysis method for the detection of silver nanoparticles in biological matrices

Overview of attention for article published in Analytical & Bioanalytical Chemistry, October 2015
Altmetric Badge

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
14 Dimensions

Readers on

mendeley
27 Mendeley
Title
A direct solid sampling analysis method for the detection of silver nanoparticles in biological matrices
Published in
Analytical & Bioanalytical Chemistry, October 2015
DOI 10.1007/s00216-015-9108-1
Pubmed ID
Authors

Nadine S. Feichtmeier, Nadine Ruchter, Sonja Zimmermann, Bernd Sures, Kerstin Leopold

Abstract

Engineered silver nanoparticles (AgNPs) are implemented in food contact materials due to their powerful antimicrobial properties and so may enter the human food chain. Hence, it is desirable to develop easy, sensitive and fast analytical screening methods for the determination of AgNPs in complex biological matrices. This study describes such a method using solid sampling high-resolution continuum source graphite furnace atomic absorption spectrometry (GFAAS). A recently reported novel evaluation strategy uses the atomization delay of the respective GFAAS signal as significant indicator for AgNPs and thereby allows discrimination of AgNPs from ionic silver (Ag(+)) in the samples without elaborate sample pre-treatment. This approach was further developed and applied to a variety of biological samples. Its suitability was approved by investigation of eight different food samples (parsley, apple, pepper, cheese, onion, pasta, maize meal and wheat flour) spiked with ionic silver or AgNPs. Furthermore, the migration of AgNPs from silver-impregnated polypropylene food storage boxes to fresh pepper was observed and a mussel sample obtained from a laboratory exposure study with silver was investigated. The differences in the atomization delays (Δt ad) between silver ions and 20-nm AgNPs vary in a range from -2.01 ± 1.38 s for maize meal to +2.06 ± 1.08 s for mussel tissue. However, the differences were significant in all investigated matrices and so indicative of the presence/absence of AgNPs. Moreover, investigation of model matrices (cellulose, gelatine and water) gives the first indication of matrix-dependent trends. Reproducibility and homogeneity tests confirm the applicability of the method. Graphical Abstract Direct detection of silver nanoparticles in biological samples.

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

Geographical breakdown

Country Count As %
Germany 1 4%
Unknown 26 96%

Demographic breakdown

Readers by professional status Count As %
Unspecified 5 19%
Student > Ph. D. Student 4 15%
Student > Doctoral Student 4 15%
Student > Master 4 15%
Researcher 4 15%
Other 6 22%
Readers by discipline Count As %
Chemistry 8 30%
Unspecified 6 22%
Environmental Science 3 11%
Agricultural and Biological Sciences 2 7%
Earth and Planetary Sciences 1 4%
Other 7 26%

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 21 October 2015.
All research outputs
#10,841,657
of 12,230,555 outputs
Outputs from Analytical & Bioanalytical Chemistry
#3,545
of 4,657 outputs
Outputs of similar age
#209,254
of 254,899 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#67
of 162 outputs
Altmetric has tracked 12,230,555 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,657 research outputs from this source. They receive a mean Attention Score of 2.4. This one is in the 1st percentile – i.e., 1% 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 254,899 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 162 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.