LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics-Reference-Cited by-同舟云学术

LAP-MALDI MS coupled with machine learning: an ambient mass spectrometry approach for high-throughput diagnostics

Published:2022 Issue:6 Volume:13 Page:1746-1758
ISSN:2041-6520
Container-title:Chemical Science
language:en
Short-container-title:Chem. Sci.

Author:

Piras Cristian¹²,Hale Oliver J.¹,Reynolds Christopher K.³,Jones A. K. (Barney)³,Taylor Nick⁴,Morris Michael⁵,Cramer Rainer¹^ORCID

Affiliation:

1. Department of Chemistry, University of Reading, Whiteknights, Reading RG6 6DX, UK

2. Department of Health Sciences, "Magna Græcia University" of Catanzaro, Campus Universitario "Salvatore Venuta" Viale Europa, 88100, Catanzaro, Italy

3. School of Agriculture, Policy and Development, University of Reading, Whiteknights, Reading RG6 6EU, UK

4. Veterinary Epidemiology and Economics Research Unit (VEERU), PAN Livestock Services Ltd, School of Agriculture, Policy and Development, University of Reading, Whiteknights, Reading RG6 6EU, UK

5. Waters Corporation, Stamford Avenue, Wilmslow, SK9 4AX, UK

Abstract

LAP-MALDI MS profiling provides rapid, cost-effective large-scale disease analysis as demonstrated by preclinical detection of bovine mastitis and antimicrobial resistance testing using a longitudinal sample collection from a 500-cows dairy herd.

Funder

Biotechnology and Biological Sciences Research Council

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/SC/D1SC05171G

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