Radiation treatment response and hypoxia biomarkers revealed by machine learning assisted Raman spectroscopy in tumour cells and xenograft tissues-Reference-Cited by-同舟云学术

Radiation treatment response and hypoxia biomarkers revealed by machine learning assisted Raman spectroscopy in tumour cells and xenograft tissues

Published:2022 Issue:22 Volume:147 Page:5091-5104
ISSN:0003-2654
Container-title:The Analyst
language:en
Short-container-title:Analyst

Author:

Deng Xinchen¹^ORCID,Milligan Kirsty¹^ORCID,Brolo Alexandre²^ORCID,Lum Julian J.³⁴,Andrews Jeffrey L.⁵,Jirasek Andrew¹

Affiliation:

1. Department of Physics, The University of British Columbia – Okanagan campus, Kelowna, Canada V1V 1V7

2. Department of Chemistry, University of Victoria, Victoria, Canada V8P 5C2

3. Department of Biochemistry and Microbiology, University of Victoria, Victoria, Canada V8P 5C2

4. Trev and Joyce Deeley Research Centre, BC Cancer, Victoria, Canada V8R 6V5

5. Department of Statistics, The University of British Columbia – Okanagan campus, Kelowna, Canada V1V 1V7

Abstract

GBR-NMF-RF-SHAP model helped identify a wide range of radiation response biomarkers and hypoxia indicators (e.g., glycogen, lipids, DNA, amino acids) in Raman spectra acquired from H460 human lung cancer cells and H460 xenografts.

Funder

Natural Sciences and Engineering Research Council of Canada

Canadian Institutes of Health Research

Publisher

Royal Society of Chemistry (RSC)

Subject

Electrochemistry,Spectroscopy,Environmental Chemistry,Biochemistry,Analytical Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2022/AN/D2AN01222G

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