| 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. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 1 | 2% |
| Unknown | 46 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 7 | 15% |
| Student > Ph. D. Student | 6 | 13% |
| Student > Doctoral Student | 6 | 13% |
| Student > Master | 5 | 11% |
| Professor | 4 | 9% |
| Other | 10 | 21% |
| Unknown | 9 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 12 | 26% |
| Environmental Science | 4 | 9% |
| Nursing and Health Professions | 3 | 6% |
| Agricultural and Biological Sciences | 3 | 6% |
| Immunology and Microbiology | 2 | 4% |
| Other | 10 | 21% |
| Unknown | 13 | 28% |
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.
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#22,760,732
of 25,374,917 outputs
Outputs from Analytical & Bioanalytical Chemistry
#7,542
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Outputs of similar age
#252,729
of 295,284 outputs
Outputs of similar age from Analytical & Bioanalytical Chemistry
#86
of 139 outputs
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