Terahertz high-resolution spectroscopy of thermal decomposition gas products of diabetic and non-diabetic blood plasma and kidney tissue pellets.

SIGNIFICANCE: One of the modern trends in medical diagnostics is based on metabolomics, an approach allowing determination of metabolites which can be the specific features of disease. High-resolution gas spectroscopy allows investigation of the gas metabolite content of samples of biological origin. We present the elaboration of a method of studying diabetic and non-diabetic biological samples, prepared as pellets, by terahertz (THz) high-resolution spectroscopy. AIM: The main idea of the work is studying the content of thermal decomposition gas products of diabetic and non-diabetic dried blood plasma and kidney tissues for revealing the set of gas-markers that characterized the diabetes by the THz high-resolution spectroscopy method. APPROACH: We present an approach to study the diabetic and non-diabetic blood plasma (human and rats) and kidney tissues (rats), using high-resolution spectroscopy based on the non-stationary effect of THz frequency range. The methods of preparing the blood and kidney tissue samples as pellets and of vaporizing the samples were developed. RESULTS: The measurements of rotational absorption spectra of vapors at heating the pellets prepared from blood and kidney tissue were carried out in 118 to 178 GHz frequency range. The absorption lines appearing in spectra of the sample vapors were detected and identified. The molecular contents of thermal decomposition products differed for non-diabetic and diabetic samples; e.g., main marker is acetone appearing in the diabetic blood (human and rats) and in the diabetic kidney tissue. CONCLUSIONS: Our paper illustrates the potential ability for determining the metabolite content of biological samples for diagnostics and prognosis of diseases for clinical medicine.

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 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.