Raman-based high-resolution detection of 13 CO2 isotopes in human breath

Polishchuk, Anton; Kenzhebayeva, Yuliya; Grigorenko, Konstantin; Popov, E. E.; Vitkin, Vladimir

doi:10.1117/12.2556261

Cited by 3 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The high accuracy of gas analyzers based on Raman spectrometry makes it possible to more accurately determine the 12 CO 2 and 13 CO 2 volume fraction changes in breath samples. Several studies have demonstrated the potential of using Raman spectroscopy for the UBT [29][30][31], but further investigation is needed to improve the detection of changes in the 12 CO 2 and 13 CO 2 volume fraction. In this study, we investigate the accuracy of measurements and the stability of results achieved by using a previously developed Raman gas analyzer [25].…”

Section: Introductionmentioning

confidence: 99%

Raman Spectroscopy for Urea Breath Test

et al. 2023

Self Cite

View full text Add to dashboard Cite

The urea breath test is a non-invasive diagnostic method for Helicobacter pylori infections, which relies on the change in the proportion of 13CO2 in exhaled air. Nondispersive infrared sensors are commonly used for the urea breath test in laboratory equipment, but Raman spectroscopy demonstrated potential for more accurate measurements. The accuracy of the Helicobacter pylori detection via the urea breath test using 13CO2 as a biomarker is affected by measurement errors, including equipment error and δ13C measurement uncertainty. We present a Raman scattering-based gas analyzer capable of δ13C measurements in exhaled air. The technical details of the various measurement conditions have been discussed. Standard gas samples were measured. 12CO2 and 13CO2 calibration coefficients were determined. The Raman spectrum of the exhaled air was measured and the δ13C change (in the process of the urea breath test) was calculated. The total error measured was 6% and does not exceed the limit of 10% that was analytically calculated.

show abstract

Section: Introductionmentioning

confidence: 99%

Raman Spectroscopy for Urea Breath Test

et al. 2023

Self Cite

View full text Add to dashboard Cite

show abstract

Ultrasensitive Raman Gas Spectroscopy for Dinitrogen Sensing at the Parts-per-Billion Level

Merian,

Silva,

Wolf

et al. 2024

Anal. Chem.

View full text Add to dashboard Cite

Raman spectroscopy combined with machine learning algorithms to detect adulterated Suichang native honey

Chen

et al. 2022

Sci Rep

View full text Add to dashboard Cite

Zhejiang Suichang native honey, which is included in the list of China’s National Geographical Indication Agricultural Products Protection Project, is very popular. This study proposes a method of Raman spectroscopy combined with machine learning algorithms to accurately detect low-concentration adulterated Suichang native honey. In this study, the native honey collected by local beekeepers in Suichang was selected for adulteration detection. The spectral data was compressed by Savitzky–Golay smoothing and partial least squares (PLS) in sequence. The PLS features taken for further analysis were selected according to the contribution rate. In this study, three classification modeling methods including support vector machine, probabilistic neural network and convolutional neural network were adopted to correctly classify pure and adulterated honey samples. The total accuracy was 100%, 100% and 99.75% respectively. The research result shows that Raman spectroscopy combined with machine learning algorithms has great potential in accurately detecting adulteration of low-concentration honey.

show abstract

Raman-based high-resolution detection of 13 CO2 isotopes in human breath

Cited by 3 publications

References 0 publications

Raman Spectroscopy for Urea Breath Test

Raman Spectroscopy for Urea Breath Test

Ultrasensitive Raman Gas Spectroscopy for Dinitrogen Sensing at the Parts-per-Billion Level

Raman spectroscopy combined with machine learning algorithms to detect adulterated Suichang native honey

Contact Info

Product

Resources

About