Raman Spectroscopy Of Human Skin For Kidney Failure Detection

INTRODUCTION

Among the non-communicable diseases, chronic kidney disease stands out as a prevalent condition. According to the World Health Organization, approximately 10% of the global population suffers from this ailment, resulting in millions of annual deaths attributed to kidney pathologies. The failure of the kidneys contributes to disruptions in the body's water, electrolyte, and nitrogen balance, as well as other metabolic disorders. These physiological and pathological characteristics of internal organs have a direct impact on the condition of the skin and its constituent composition. Various biochemical and immunochemical methods of laboratory analysis are applied in studying skin component composition. However, these methods are invasive and require additional reagents. Currently, Raman spectroscopy (RS) has been used in clinical experimental studies to determine skin composition. In skin analysis, RS is used to quantify the content of a specific component in the skin, determine dermal drug delivery, identify biophysical links between vibrational characteristics and specific compositional and chemical changes associated with aging, screen for skin cancer, etc.

METHOD

RS is based on the inelastic scattering of light by polarizable molecules, revealing the vibrational energy levels of the chemical bonds of molecules. The skin tissues for the in vivo analysis were selected using a stratified random sampling method.

Figure 1 The raw spectrum of human skin

The obtained experimental dataset of human skin was analyzed with smart algorithms. When constructing the regression model, the informative spectra bands were defined by analyzing the variable importance in the projection (VIP) distribution. VIP makes it possible to assess the impact of individual variables of the predicate matrix array on the model. The most informative Raman spectral bands were 1315–1330 cm⁻¹ (amide III, δ(CH2) in α-helicx collagen), 1450–1460 cm⁻¹ (δ(CH) in proteins and lipids) and 1700–1800 cm⁻¹ (ν(CO), ν(COO) in lipids and phospholipids). Changes in collagen structure, lipid content, or metabolite concentrations are specific and characteristic biological markers to identify kidney failure.