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Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS
In this paper 13 elements, both physiological and causing toxic effects, were determined by inductively coupled plasma mass spectrometry in roots of 26 species of herbs used in Traditional Chinese Medicine. The herbs were purchased from online shop in two batches 1 year apart to verify the variabili...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526606/ https://www.ncbi.nlm.nih.gov/pubmed/34667188 http://dx.doi.org/10.1038/s41598-021-00019-w |
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author | Sajnóg, Adam Koko, Elwira Kayzer, Dariusz Barałkiewicz, Danuta |
author_facet | Sajnóg, Adam Koko, Elwira Kayzer, Dariusz Barałkiewicz, Danuta |
author_sort | Sajnóg, Adam |
collection | PubMed |
description | In this paper 13 elements, both physiological and causing toxic effects, were determined by inductively coupled plasma mass spectrometry in roots of 26 species of herbs used in Traditional Chinese Medicine. The herbs were purchased from online shop in two batches 1 year apart to verify the variability of elemental content in time. The multivariate statistical methods—multiple regression, canonical variates and interaction effect analysis—were applied to interpret the data and to show the relationships between elements and two batches of herb roots. The maximum permissible concentration of Cd (0.3 mg kg(−1)) was exceeded in 7 herb roots which makes 13% of all specimens. The multiple regression analysis revealed the significant relationships between elements: Mg with Sr; V with Pb, As and Ba; Mn with Pb; Fe with As and Ba; Co with Ni and Sr, Cu with Pb, Cd and As; Zn with Pb, Cd, As and Ba. The canonical variates analysis showed that the statistical inference should not be based solely on the type of herb or number of batch because of the underlying interaction effects between those two variables that may be a source of variability of the content of determined elements. |
format | Online Article Text |
id | pubmed-8526606 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-85266062021-10-20 Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS Sajnóg, Adam Koko, Elwira Kayzer, Dariusz Barałkiewicz, Danuta Sci Rep Article In this paper 13 elements, both physiological and causing toxic effects, were determined by inductively coupled plasma mass spectrometry in roots of 26 species of herbs used in Traditional Chinese Medicine. The herbs were purchased from online shop in two batches 1 year apart to verify the variability of elemental content in time. The multivariate statistical methods—multiple regression, canonical variates and interaction effect analysis—were applied to interpret the data and to show the relationships between elements and two batches of herb roots. The maximum permissible concentration of Cd (0.3 mg kg(−1)) was exceeded in 7 herb roots which makes 13% of all specimens. The multiple regression analysis revealed the significant relationships between elements: Mg with Sr; V with Pb, As and Ba; Mn with Pb; Fe with As and Ba; Co with Ni and Sr, Cu with Pb, Cd and As; Zn with Pb, Cd, As and Ba. The canonical variates analysis showed that the statistical inference should not be based solely on the type of herb or number of batch because of the underlying interaction effects between those two variables that may be a source of variability of the content of determined elements. Nature Publishing Group UK 2021-10-19 /pmc/articles/PMC8526606/ /pubmed/34667188 http://dx.doi.org/10.1038/s41598-021-00019-w Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Article Sajnóg, Adam Koko, Elwira Kayzer, Dariusz Barałkiewicz, Danuta Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS |
title | Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS |
title_full | Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS |
title_fullStr | Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS |
title_full_unstemmed | Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS |
title_short | Chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by ICP-MS |
title_sort | chemometric approach to find relationships between physiological elements and elements causing toxic effects in herb roots by icp-ms |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8526606/ https://www.ncbi.nlm.nih.gov/pubmed/34667188 http://dx.doi.org/10.1038/s41598-021-00019-w |
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