Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning-Reference-Cited by-同舟云学术

Metabolic profiling of murine radiation-induced lung injury with Raman spectroscopy and comparative machine learning

Published:2024 Issue:10 Volume:149 Page:2864-2876
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Wiebe Mitchell¹^ORCID,Milligan Kirsty¹^ORCID,Brewer Joan¹,Fuentes Alejandra M.¹^ORCID,Ali-Adeeb Ramie²,Brolo Alexandre G.²^ORCID,Lum Julian J.³⁴,Andrews Jeffrey L.¹,Haston Christina¹,Jirasek Andrew¹

Affiliation:

1. Department of Computer Science, Mathematics, Physics, and Statistics, The University of British Columbia Okanagan Campus, Kelowna, Canada

2. Department of Chemistry, The University of Victoria, Victoria, Canada

3. Department of Biochemistry and Microbiology, University of Victoria, Victoria, Canada

4. Trev and Joyce Deeley Research Centre, BC Cancer, Victoria, Canada

Abstract

A cohort of control/irradiated mice were metabolically profiled, via Raman spectrocopy, for associations with radiation-induced lung injury (RILI). Machine learning methods revealed disease-associated metabolites.

Funder

Natural Sciences and Engineering Research Council of Canada

Canadian Institutes of Health Research

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/AN/D4AN00152D

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