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author:

Dan, Ouyang (Dan, Ouyang.) [1] | Wang, Chuanzhe (Wang, Chuanzhe.) [2] | Zhong, Chao (Zhong, Chao.) [3] | Lin, Juan (Lin, Juan.) [4] | Xu, Gang (Xu, Gang.) [5] | Wang, Guane (Wang, Guane.) [6] | Lin, Zian (Lin, Zian.) [7] (Scholars:林子俺)

Indexed by:

EI Scopus SCIE

Abstract:

Metabolic analysis in biofluids based on laser desorption/ionization mass spectrometry (LDI-MS), featuring rapidity, simplicity, small sample volume and high throughput, is expected to be a powerful diagnostic tool. Nevertheless, the signals of most metabolic biomarkers obtained by matrix-assisted LDI-MS are too limited to achieve a highly accurate diagnosis due to serious background interference. To address this issue, nanomaterials have been frequently adopted in LDI-MS as substrates. However, the "trial and error" approach still dominates the development of new substrates. Therefore, rational design of novel LDI-MS substrates showing high desorption/ionization efficiency and no background interference is extremely desired. Herein, four few-layered organic metal chalcogenides (OMCs) were precisely designed and for the first time investigated as substrates in LDI-MS, which allowed a favorable internal energy and charge transfer by changing the functional groups of organic ligands and metal nodes. As a result, the optimized OMC-assisted platform satisfyingly enhanced the mass signal by approximate to 10 000 fold in detecting typical metabolites and successfully detected different saccharides. In addition, a high accuracy diagnosis of central precocious puberty (CPP) with potential biomarkers of 12 metabolites was realized. This work is not only expected to provide a universal detection tool for large-scale clinical diagnosis, but also provides an idea for the design and selection of LDI-MS substrates. Cu(SPh-COOH) was precisely designed and for the first time investigated as a LDI-MS substrate with enhanced energy transfer and ionization efficiency. A high-accuracy metabolic molecular diagnosis of CPP was achieved using the Cu(SPh-COOH)-assisted LDI-MS platform.

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Community:

  • [ 1 ] [Dan, Ouyang]Fuzhou Univ, Coll Chem, Fujian Prov Key Lab Anal & Detect Technol Food Saf, Minist Educ,Key Lab Analyt Sci Food Safety & Biol, Fuzhou 350108, Fujian, Peoples R China
  • [ 2 ] [Zhong, Chao]Fuzhou Univ, Coll Chem, Fujian Prov Key Lab Anal & Detect Technol Food Saf, Minist Educ,Key Lab Analyt Sci Food Safety & Biol, Fuzhou 350108, Fujian, Peoples R China
  • [ 3 ] [Lin, Zian]Fuzhou Univ, Coll Chem, Fujian Prov Key Lab Anal & Detect Technol Food Saf, Minist Educ,Key Lab Analyt Sci Food Safety & Biol, Fuzhou 350108, Fujian, Peoples R China
  • [ 4 ] [Wang, Chuanzhe]Chinese Acad Sci, Fujian Inst Res Struct Matter, State Key Lab Struct Chem, Fuzhou 350002, Fujian, Peoples R China
  • [ 5 ] [Xu, Gang]Chinese Acad Sci, Fujian Inst Res Struct Matter, State Key Lab Struct Chem, Fuzhou 350002, Fujian, Peoples R China
  • [ 6 ] [Wang, Guane]Chinese Acad Sci, Fujian Inst Res Struct Matter, State Key Lab Struct Chem, Fuzhou 350002, Fujian, Peoples R China
  • [ 7 ] [Lin, Juan]Fujian Prov Govt Hosp, Dept Cardiol, Fuzhou 350003, Peoples R China

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Source :

CHEMICAL SCIENCE

ISSN: 2041-6520

Year: 2023

Issue: 1

Volume: 15

Page: 278-284

7 . 6

JCR@2023

7 . 6 0 0

JCR@2023

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 5

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 0

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