Terahertz spectroscopy of diabetic and non-diabetic human blood plasma pellets.

Anastasiya A Lykina,Elena G Domracheva,Vladimir A Anfertev,Alina Y Babenko,Mariya B Chernyaeva,Yuri V Kistenev,Maksim M Nazarov,Vladimir L Vaks,Dmitry V Korolev,Ilia A Mustafin,Olga P Cherkasova,Denis A Vrazhnov,Olga A Smolyanskaya,Vladimir V Prischepa,Yulia A Kononova,Alexander P Shkurinov,Maria R Konnikova

doi:10.1117/1.jbo.26.4.043006

Abstract

.Significance: The 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.Aim: The 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.Results: We 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.Conclusion: We illustrate the potential ability in clinical medicine to construct a predictive rule by supervised learning algorithms after collecting enough experimental data.

Highlights

Diabetes mellitus is a disease caused by the deficit or reduced efficiency of endogenous insulin resulting in blood sugar imbalance.[1]
The following tests are used in clinical practice to diagnose diabetes mellitus and monitor patients, for example, determining the level of glucose in venous blood plasma by the enzyme method or in capillary blood by an electrochemical method, as well as determining the level of glycated hemoglobin in whole venous blood by liquid chromatography.[3,4]
Each crystal of pellets contains a certain percentage of lipids, proteins, and fibrinogen—all of them normal or glycated

Summary

Introduction

Diabetes mellitus is a disease caused by the deficit or reduced efficiency of endogenous insulin resulting in blood sugar imbalance.[1] The development of diabetes is associated with impairments in the carbohydrate, protein, and lipid metabolism. It is almost always accompanied by a significant increase of the blood concentrations of glucose, corticosteroid hormones, and some other metabolites.[1] Protein glycation is a non-enzymatic reaction between the carbonyl groups of monosaccharides (e.g., glucose and fructose) and amino groups of proteins (e.g., albumin). The development of methods for determining blood parameters and for storing biological samples will reduce the cost of performing diagnostic tests.[3,4]

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Methods

Conclusion