Identification of fluoroquinolone-resistant <i>Mycobacterium tuberculosis</i> through high-level data fusion of Raman and laser-induced breakdown spectroscopy-Reference-Cited by-同舟云学术

Identification of fluoroquinolone-resistant Mycobacterium tuberculosis through high-level data fusion of Raman and laser-induced breakdown spectroscopy

Published:2024 Issue: Volume: Page:
ISSN:1759-9660
Container-title:Analytical Methods
language:en
Short-container-title:Anal. Methods

Author:

Jeon Gookseon¹²^ORCID,Kim Soogeun³,Kim Young Jin⁴,Kim Seungmo⁵,Han Kyungmin⁶,Oh Kyunghwan²^ORCID,Lee Hee Joo⁶,Choi Janghee¹

Affiliation:

1. Industrial Transformation Technology Department, Research Institute of Sustainable Development Technology, Korea Institute of Industrial Technology, 89, Yangdaegiro-gil, Ipjang-myeon, Seobuk-gu, Cheonan-Si, Chungcheongnam-do 31056, Republic of Korea

2. Photonic Device Physics Laboratory, Institute of Physics and Applied Physics, Yonsei University, 50, Yonsei-ro, Seodaemun-gu, Seoul 03722, Republic of Korea

3. Advanced Photonics Research Institute (APRI), Gwangju Institute of Science and Technology (GIST), Gwangju 61005, Republic of Korea

4. Department of Laboratory Medicine, Kyung Hee University College of Medicine, Kyung Hee University Hospital, Seoul, Republic of Korea

5. Laboratory Medicine Center, Korean National Tuberculosis Association, The Korean Institute of Tuberculosis, Cheongju, Republic of Korea

6. Clinical Laboratory Medicine Center, Korean National Tuberculosis Association, Seoul, Republic of Korea

Abstract

This study presents a fusion model of Raman and LIBS to diagnose drug-resistant tuberculosis, achieving 98.3% accuracy. Given the rapid measurement capabilities of both techniques, this approach is expected to reduce the diagnosis time.

Funder

Korea Institute of Industrial Technology

National Research Foundation of Korea

Ministry of Science and ICT, South Korea

Publisher

Royal Society of Chemistry (RSC)

Link

http://pubs.rsc.org/en/content/articlepdf/2024/AY/D4AY01331J

Reference57 articles.

1. Global Tuberculosis Report 2022 , https://www.who.int/teams/global-tuberculosis-programme/tb-reports/global-tuberculosis-report-2022 , (accessed July 17, 2023)

2. WHO consolidated guidelines on tuberculosis , https://www.who.int/publications-detail-redirect/9789240048126 , (accessed July 17, 2023)

3. Evolution of drug resistance in Mycobacterium tuberculosis: a review on the molecular determinants of resistance and implications for personalized care

4. Early outcome and safety of bedaquiline-containing regimens for treatment of MDR- and XDR-TB in China: a multicentre study

5. Final treatment outcomes of delamanid-containing regimens in patients with MDR-/XDR-TB in South Korea