Reliable and precise Zn isotopic analysis of biological matrices using a fully automated dual-column purification procedure.

IF 3.8 2区 化学 Q1 BIOCHEMICAL RESEARCH METHODS Analytical and Bioanalytical Chemistry Pub Date : 2025-02-01 Epub Date: 2024-12-23 DOI:10.1007/s00216-024-05702-1
Anika Retzmann, Kerri A Miller, Fwziah Ali Abdalali Mohamed, Michael E Wieser
{"title":"Reliable and precise Zn isotopic analysis of biological matrices using a fully automated dual-column purification procedure.","authors":"Anika Retzmann, Kerri A Miller, Fwziah Ali Abdalali Mohamed, Michael E Wieser","doi":"10.1007/s00216-024-05702-1","DOIUrl":null,"url":null,"abstract":"<p><p>A fully automated dual-column purification procedure for Zn from biological samples, designed for subsequent Zn isotopic analysis, is presented that utilizes the prepFAST MC™ system (Elemental Scientific), DGA resin (TrisKem International), and TK201 resin (TrisKem International). The procedure developed enables the unattended processing of 20 samples per day and is characterized by low and reproduceable blanks (< 1.5 ng), no carry-over or memory effect, high reusability (> 50 times), high Zn yields 100.1% ± 5.3% (2 SD, N = 22), and strong robustness to matrix variations across biological samples (bone, liver, hair, blood). Additionally, Zn isotopic analysis using MC-ICP-MS showed no significant on-column fractionation. The measured δ<sup>66</sup>Zn/<sup>64</sup>Zn<sub>IRMM</sub> values for NIST SRM 1400 (0.67‰ ± 0.07‰, U, k = 2), NIST SRM 1486 (0.91‰ ± 0.06‰, U, k = 2), NIST SRM 1577c (- 0.45‰ ± 0.05‰, U, k = 2), ERM-DB001 (- 0.35‰ ± 0.05‰, U, k = 2), GBW09101 (- 0.32‰ ± 0.08‰, U, k = 2), and SeroNorm whole blood L-3 (-0.15 ‰ ± 0.05 ‰, U, k = 2) are consistent with published values. The procedure developed makes Zn, an analytically challenging isotope system, more accessible, feasible, and reliable for a broader range of users while enabling high sample throughput.</p>","PeriodicalId":462,"journal":{"name":"Analytical and Bioanalytical Chemistry","volume":" ","pages":"835-846"},"PeriodicalIF":3.8000,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Analytical and Bioanalytical Chemistry","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1007/s00216-024-05702-1","RegionNum":2,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/12/23 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"BIOCHEMICAL RESEARCH METHODS","Score":null,"Total":0}
引用次数: 0

Abstract

A fully automated dual-column purification procedure for Zn from biological samples, designed for subsequent Zn isotopic analysis, is presented that utilizes the prepFAST MC™ system (Elemental Scientific), DGA resin (TrisKem International), and TK201 resin (TrisKem International). The procedure developed enables the unattended processing of 20 samples per day and is characterized by low and reproduceable blanks (< 1.5 ng), no carry-over or memory effect, high reusability (> 50 times), high Zn yields 100.1% ± 5.3% (2 SD, N = 22), and strong robustness to matrix variations across biological samples (bone, liver, hair, blood). Additionally, Zn isotopic analysis using MC-ICP-MS showed no significant on-column fractionation. The measured δ66Zn/64ZnIRMM values for NIST SRM 1400 (0.67‰ ± 0.07‰, U, k = 2), NIST SRM 1486 (0.91‰ ± 0.06‰, U, k = 2), NIST SRM 1577c (- 0.45‰ ± 0.05‰, U, k = 2), ERM-DB001 (- 0.35‰ ± 0.05‰, U, k = 2), GBW09101 (- 0.32‰ ± 0.08‰, U, k = 2), and SeroNorm whole blood L-3 (-0.15 ‰ ± 0.05 ‰, U, k = 2) are consistent with published values. The procedure developed makes Zn, an analytically challenging isotope system, more accessible, feasible, and reliable for a broader range of users while enabling high sample throughput.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
可靠和精确的锌同位素分析生物基质使用全自动双柱纯化程序。
采用prepFAST MC™系统(Elemental Scientific)、DGA树脂(TrisKem International)和TK201树脂(TrisKem International),为后续Zn同位素分析设计了一种全自动双柱纯化生物样品Zn的程序。所开发的程序每天可实现20个样品的无人处理,其特点是低且可重复的空白(50次),高锌收率100.1%±5.3% (2 SD, N = 22),对生物样品(骨骼,肝脏,头发,血液)的基质变化具有很强的稳健性。此外,使用MC-ICP-MS进行Zn同位素分析没有发现明显的柱上分馏。NIST SRM 1400(0.67‰±0.07‰,U, k = 2)、NIST SRM 1486(0.91‰±0.06‰,U, k = 2)、NIST SRM 1577c(- 0.45‰±0.05‰,U, k = 2)、ERM-DB001(- 0.35‰±0.05‰,U, k = 2)、GBW09101(- 0.32‰±0.08‰,U, k = 2)和SeroNorm全血L-3(-0.15‰±0.05‰,U, k = 2)的δ66Zn/64ZnIRMM测量值与已发表的值一致。开发的程序使Zn(一种具有分析挑战性的同位素系统)更容易获得、可行和可靠,适用于更广泛的用户,同时实现高样品通量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
CiteScore
8.00
自引率
4.70%
发文量
638
审稿时长
2.1 months
期刊介绍: Analytical and Bioanalytical Chemistry’s mission is the rapid publication of excellent and high-impact research articles on fundamental and applied topics of analytical and bioanalytical measurement science. Its scope is broad, and ranges from novel measurement platforms and their characterization to multidisciplinary approaches that effectively address important scientific problems. The Editors encourage submissions presenting innovative analytical research in concept, instrumentation, methods, and/or applications, including: mass spectrometry, spectroscopy, and electroanalysis; advanced separations; analytical strategies in “-omics” and imaging, bioanalysis, and sampling; miniaturized devices, medical diagnostics, sensors; analytical characterization of nano- and biomaterials; chemometrics and advanced data analysis.
期刊最新文献
My perspective of meaningful research for Analytical and Bioanalytical Chemistry. Quantitative proteome-wide O-glycoproteomics analysis with FragPipe. Carbohydrate Structure Database: current state and recent developments. Glycoscience data content in the NCBI Glycans and PubChem. Navigating the maze of mass spectra: a machine-learning guide to identifying diagnostic ions in O-glycan analysis.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1