The possibilities of optical methods in the early diagnosis of gliomas

A novel approach based on the Raman and absorption spectroscopy for detection of gliomas molecular markers in brain tissue and blood will be discussed. Using the mice model of the U87 human glioblastoma, we have shown the possibility of glioma development control by a combination of Raman, infrared (IR), and Terahertz (THz) pulsed spectroscopy

Diagnosis of glioma molecular markers by terahertz technologies

This review considers glioma molecular markers in brain tissues and body fluids, shows the pathways of their formation, and describes traditional methods of analysis. The most important optical properties of glioma markers in the terahertz (THz) frequency range are also presented. New metamaterial-based technologies for molecular marker detection at THz frequencies are discussed. A variety of machine learning methods, which allow the marker detection sensitivity and differentiation of healthy and tumor tissues to be improved with the aid of THz tools, are considered. The actual results on the application of THz techniques in the intraoperative diagnosis of brain gliomas are shown. THz technologies’ potential in molecular marker detection and defining the boundaries of the glioma’s tissue is discussed

Study of dry pellets of blood plasma using THz spectroscopy

This work is devoted to the development of a suitable phantom of a biological object for measurements in the THz frequency range and for approbation with various diagnostic methods developed in different THz laboratories. The phantoms were represented as a pellet of human and a laboratory rat blood plasma in the diabetic and the control groups. These objects were analyzed in various laboratories, using THz pulsed spectroscopy and a high-resolution THz spectrometer based on a backward wave oscillator. The components of the dry blood plasma were identified by the detected spectral lines

Malignant and benign thyroid nodule differentiation through the analysis of blood plasma with terahertz spectroscopy

The liquid and lyophilized blood plasma of patients with benign or malignant thyroid nodules and healthy individuals were studied by terahertz (THz) time-domain spectroscopy and machine learning. The blood plasma samples from malignant nodule patients were shown to have higher absorption. The glucose concentration and miRNA-146b level were correlated with the sample’s absorption at 1 THz. A two-stage ensemble algorithm was proposed for the THz spectra analysis. The first stage was based on the Support Vector Machine with a linear kernel to separate healthy and thyroid nodule participants. The second stage included additional data preprocessing by Ornstein-Uhlenbeck kernel Principal Component Analysis to separate benign and malignant thyroid nodule participants. Thus, the distinction of malignant and benign thyroid nodule patients through their lyophilized blood plasma analysis by terahertz time-domain spectroscopy and machine learning was demonstrated

Study of adsorption of the SARS-CoV-2 virus spike protein by vibrational spectroscopy using terahertz metamaterials

Adhesion of the spike protein of the SARS-CoV-2 virus is studied by vibrational spectroscopy using terahertz metamaterials. The features of metastructure absorption upon the deposition of histidine, albumin, and the receptor-binding domain of the spike protein films are investigated. An original technique for quantitative assessment of the efficiency of virus adhesion on the metamaterial surfaces are proposed and experimentally tested

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

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 nondiabetic 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