ArticleJournal of biomedical optics2021
Terahertz spectroscopy of diabetic and non-diabetic human blood plasma pellets.
Article in Journal of biomedical optics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- On chip glucose sensing using guided waves at terahertz frequencies.Scientific reports · 2024Article
- Noninvasive Glucose Sensing In Vivo.Sensors (Basel, Switzerland) · 2023Review
- Quantitative evaluation of transdermal drug delivery patches on human skin withBiomedical optics express · 2023Article
- Ultra-High Sensitivity Terahertz Microstructured Fiber Biosensor for Diabetes Mellitus and Coronary Heart Disease Marker Detection.Sensors (Basel, Switzerland) · 2023Article
- Terahertz Asymmetric S-Shaped Complementary Metasurface Biosensor for Glucose Concentration.Biosensors · 2022Article
- Optical Properties of Crystalline Lactose Fluidized with Dilutions of Various Substances in the Terahertz Frequency Range.Pharmaceutics · 2021Article
- Speckle patterns formed by broadband terahertz radiation and their applications for ghost imaging.Scientific reports · 2021Article
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Authors and funding
17 authors.
Funding
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Abstract
significanceThe creation of fundamentally new approaches to storing various biomaterial and estimation parameters, without irreversible loss of any biomaterial, is a pressing challenge in clinical practice. We present a technology for studying samples of diabetic and non-diabetic human blood plasma in the terahertz (THz) frequency range.
aimThe main idea of our study is to propose a method for diagnosis and storing the samples of diabetic and non-diabetic human blood plasma and to study these samples in the THz frequency range. APPROACH: Venous blood from patients with type 2 diabetes mellitus and conditionally healthy participants was collected. To limit the impact of water in the THz spectra, lyophilization of liquid samples and their pressing into a pellet were performed. These pellets were analyzed using THz time-domain spectroscopy. The differentiation between the THz spectral data was conducted using multivariate statistics to classify non-diabetic and diabetic groups' spectra.
resultsWe present the density-normalized absorption and refractive index for diabetic and non-diabetic pellets in the range 0.2 to 1.4 THz. Over the entire THz frequency range, the normalized index of refraction of diabetes pellets exceeds this indicator of non-diabetic pellet on average by 9% to 12%. The non-diabetic and diabetic groups of the THz spectra are spatially separated in the principal component space.
conclusionWe illustrate the potential ability in clinical medicine to construct a predictive rule by supervised learning algorithms after collecting enough experimental data.
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