Currently, patients with stomach and duodenum diseases should be examined using diagnostic tests for Helicobacter pylori infection. Diagnostic methods available in the arsenal of clinicians make it possible to identify Helicobacter pylori in almost 100% of cases. A competent approach to the selection of a diagnostic test provides high-quality, timely, and economical verification of the pathogen. The paper provides information on the currently available diagnostic procedures for the detection of Helicobacter pylori infection and the results of the diagnosis of helicobacteriosis based on the activity of urease in saliva. The main area of research is the development of an analytical method based on the quantitative determination of ammonia and the detection of amines and aliphatic acids in exhaled air using signals from an array of diverse piezoelectric chemical sensors. Simple data processing algorithms were applied, and qualitative and quantitative decision-making criteria were substantiated. The method of analysis using chemical sensors is characterized by high specificity (96% for ammonia) and sensitivity (90%); it does not require special sample preparation and is indispensable in large-scale studies and personal monitoring and for choosing treatment tactics.

This paper discusses the application of two approaches (direct and inverse) to the identification of volatile substances by means of a gas sensor array in a headspace over nasal mucus swab samples taken from calves with differing degrees of respiratory damage. We propose a unique method to visualize sensor array data for quality analysis, based on the spectra of cross mass sensitivity parameters. The traditional method, which requires an initial sensor array trained on the vapors of the individual substances (database accumulation)—with their further identification in the analyzed bio-samples through the comparison of the analysis results to the database—has shown unsatisfactory performance. The proposed inverse approach is more informative for the pattern recognition of volatile substances in the headspace of mucus samples. The projection of the calculated parameters of the sensor array for individual substances in the principal component space, acquired while processing the sensor array output from nasal swab samples, has allowed us to divide animals into groups according to the clinical diagnosis of their lung condition (healthy respiratory system, bronchitis, or bronchopneumonia). The substances detected in the gas phase of the nasal swab samples (cyclohexanone, butanone-2,4-methyl-2-pentanone) were correlated with the clinical state of the animals, and were consistent with the reference data on disease markers in exhaled air established for destructive organism processes.

Milk and dairy products are included in the list of the Food Security Doctrine and are of paramount importance in the diet of the human population. At the same time, the presence of many macro- and microcomponents in milk, as available sources of carbon and energy, as well as the high activity of water, cause the rapid development of native and pathogen microorganisms in it. The goal of the work was to assess the possibility of using an array of gas chemical sensors based on piezoquartz microbalances with polycomposite coatings to assess the microbiological indicators of milk quality and to compare the microflora of milk samples. Piezosensors with polycomposite coatings with high sensitivity to volatile compounds were obtained. The gas phase of raw milk was analyzed using the sensors; in parallel, the physicochemical and microbiological parameters were determined for these samples, and species identification of the microorganisms was carried out for the isolated microorganisms in milk. The most informative output data of the sensor array for the assessment of microbiological indicators were established. Regression models were constructed to predict the quantity of microorganisms in milk samples based on the informative sensors’ data with an error of no more than 17%. The limit of determination of QMAFAnM in milk was 243 ± 174 CFU/cm³. Ways to improve the accuracy and specificity of the determination of microorganisms in milk samples were proposed.

Deep eutectic solvents (DESs) have unique physical and chemical properties, such as low vapor pressure, ease of synthesis, stability, and non-toxicity. Although they have found application in areas of research such as organic synthesis, electrochemistry, biocatalysis, and the development of biosensors, their use as sensitive coatings for chemical sensors has not been previously considered. This study examines the fundamental principles of generating sensitive coatings for piezoelectric quartz sensors utilizing hydrophilic deep eutectic solvents (choline + polyalcohols). Thin films from DESs with a melting point above 50 °C, including those in the composite coatings with amorphous silicon oxide, have been studied. The sorption characteristics of the coatings were thoroughly examined via piezoelectric quartz microbalance. It has been demonstrated that the limits of detection and determination of volatile organic compounds in aqueous solutions by films based on DESs exhibit lower limits than other polymer coatings. A novel approach is proposed for processing the kinetic curve of the sorption of volatile substances by films based on DES to improve the reliability and detection of volatile compounds in the gas phase above aqueous solutions. The use of DES-based piezoelectric quarts sensors has been demonstrated for assessing microbiological indicators of milk.

The study aimed to assess the possibilities of applying electronic nose device for early diagnosis of postpartum endometritis in cows using secretions. The experiment included four clinically healthy cows, four cows with endometritis. Samples of secretions were obtained on days 1,3,6,8 after analysis of their odours was carried out with MAG-8 device (Russia). As and measuring array, there were used eight sensors based on piezoelectric crystals frequency of 10,0 MHz and film sorbents on electrodes that respond to compounds of C2-C4 alcohols, linear and cyclic ketones, aldehydes, aliphatic amines, and sulfur-containing organic compounds, acids, ammonia. It was found that during the first three days after calving in cows with postpartum endometritis in comparison with healthy animals, the area of the visual response of the sensors was exceeded by 28,4% the content of alcohols, ketones of linear a structure by 5,2-6,0%, aliphatic acids were less by 14,3% and alkyl amines by 9,2%. On 6-8 days after calving, in the clinical manifestation of endometritis, an excess of the “visual imprint” by 6.1 times (p <0.001), a decrease in the content of aliphatic acids by 22.7% (p < 0.05), and an increase in the concentration of sulfur-containing organic compounds - by 4.9%. Therefore, the electronic nose system can distinguish between the composition of the volatile compounds of the cervical postpartum secretions with the normal and pathological course of the postpartum period.