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OPEs-ID: A software for non-targeted screening of organophosphate esters based on liquid chromatography-high-resolution mass spectrometry
被引:0
|作者:
Xiong, Yinran
[1
,2
,6
]
Liu, Jinyue
[1
,2
]
Yu, Jing
[1
,2
]
Chen, Da
[3
,4
]
Li, Tiantian
[5
]
Zhou, Fengli
[3
,4
]
Wu, Ting
[1
,2
]
Liu, Xiaotu
[3
,4
]
Du, Yiping
[1
,2
]
机构:
[1] East China Univ Sci & Technol, Sch Chem & Mol Engn, Shanghai 200237, Peoples R China
[2] East China Univ Sci & Technol, Res Ctr Anal & Test, Shanghai 200237, Peoples R China
[3] Jinan Univ, Sch Environm, Guangzhou 510632, Peoples R China
[4] Jinan Univ, Guangdong Key Lab Environm Pollut & Hlth, Guangzhou 510632, Peoples R China
[5] Natl Inst Environm Hlth, Chinese Ctr Dis Control & Prevent, China CDC Key Lab Environm & Populat Hlth, Beijing 100021, Peoples R China
[6] Chongqing Municipal Key Lab Sci Utilizat Tobacco R, Chongqing 400060, Peoples R China
基金:
中国国家自然科学基金;
关键词:
Fragments-dependent screening;
LC-HRMS;
In silico fragmentation;
Isotopic pattern matching;
Organophosphate esters (OPEs);
METABOLITE IDENTIFICATION;
STRUCTURE ELUCIDATION;
WATER;
FRAGMENTATION;
PREDICTION;
PRODUCTS;
RULES;
D O I:
10.1016/j.jhazmat.2023.133275
中图分类号:
X [环境科学、安全科学];
学科分类号:
08 ;
0830 ;
摘要:
Organophosphate esters (OPEs) are widely used as flame retardants and plasticizers, presenting a potential threat to the environment and human health. To date, no automatic software exists for the nontargeted screening of OPEs. In this study, OPEs-ID, a user-friendly software, was developed for the identification of OPEs using liquid chromatography-high-resolution mass spectrometry. The main workflow of OPEs-ID included fragmentsdependent precursor ion screening, elemental composition determination, extracted ion chromatograms (EIC) comparison, and molecular structure identification via MetFrag strategy. A mixture of 17 OPE standards was identified with an identification rate of 100% by OPEs-ID. OPEs-ID demonstrated a rate of 94.1% for correctly ranking within the top 1 candidate in a local database (41.2% in PubChem) for the 17 OPE standards, which remarkably improved the identification when compared to conventional in silico fragmentation algorithms. Using a pooled airborne fine particle sample (PM2.5), OPEs-ID could automatically retrieve 22 valid molecules with structure candidates. The detection frequencies of 9 newly identified OPEs were between 13% and 100% in the 32 PM2.5 samples. Their semi-quantification concentrations were comparable to those of some traditional OPEs. Overall, OPEs-ID offers a powerful tool to significantly enrich our understanding of the OPEs present in the environment.
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页数:9
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