Pathogenetic role and clinical significance of interleukin-1ß in cancer.

In recent years, pro-oncogenic mechanisms of the tumour microenvironment (ТМЕ) have been actively discussed. One of the main cytokines of the TМЕ is interleukin-1 beta (IL-1ß), which exhibits proinflammatory properties. Some studies have shown an association between an increase in IL-1ß levels and tumour progression. The purpose of this review is to analyse the pathogenic mechanisms induced by IL-1ß in the TМЕ, as well as the diagnostic significance of the presence of IL-1ß in patients with cancer and the efficacy of treatment with IL-1ß inhibitors. According to the literature, IL-1ß can induce an increase in tumour angiogenesis due to its effects on the differentiation of epithelial cells, pro-angiogenic molecule secretion and expression of adhesion molecules, thus increasing tumour growth and metastasis. IL-1ß is also involved in the suppression of anti-tumour immune responses. The expression and secretion of IL-1ß has been noted in various types of tumours. In some clinical studies, an elevated level of IL-1ß was found to be associated with low efficacy of anti-cancer therapy and a poor prognosis. In most experimental and clinical studies, the use of IL-1ß inhibitors contributed to a decrease in tumour mass and an increase in the response to anti-tumour drugs.

MASS SPECTROMETRY-BASED TECHNIQUES FOR DIRECT QUANTIFICATION OF HIGH IONIZATION ENERGY ELEMENTS IN SOLID MATERIALS-CHALLENGES AND PERSPECTIVES.

The determination of nonmetals, first of all, the most electronegative ones-nitrogen, oxygen, fluorine, chlorine, and bromine, poses the highest challenge for element analysis. These elements are characterized by high reactivity, volatility, high ionization energy, and the absence of intensive spectral lines in the optical spectral range. Conventional techniques of their quantification include considerable "wet chemistry" stages so the application of these techniques for the solid sample is highly laborious and prone to uncontrollable uncertainties. Additionally, current development in material science and other areas requires the quantification of the elements at lower levels with good sensitivity. Owing to their robustness and flexibility, mass spectrometry techniques provide vast possibilities for the quantification, spatial and isotopic analysis, including the solutions for direct analysis of solids. The current review focuses on the application of major mass spectrometric techniques for the quantification of N, O, F, Cl, and Br in solid samples. The following techniques are mainly considered: thermal ionization mass spectrometry (TIMS), isotope-ratio MS (IRMS), secondary ion MS (SIMS), inductively coupled plasma MS (ICP-MS), and glow discharge MS (GDMS); as the most accessible and widely applied for the purpose. General ionization issues, advantages, limitations, and novel methodological solutions are discussed. © 2020 John Wiley & Sons Ltd.

Volatile Organic Compound Fragmentation in the Afterglow of Pulsed Glow Discharge in Ambient Air.

Glow discharge (GD) source gained an increased level of attention in relation to the analysis of volatile organic compounds (VOCs) since past work showed that this soft ionization method allowed direct analysis of VOCs with minimal fragmentation, however, the issue of fragmentation was not previously studied in detail. The aim of the present work was to investigate the effect of discharge conditions on VOC fragmentation in the system consisting of the cell with pulsed glow discharge and a time-of-flight mass spectrometer. Ionization of VOCs of different classes (hydrocarbons, alcohols, esters, and carboxylic acids) was investigated. A copper cathode with flat geometry was used. VOCs were ionized in the afterglow of short pulse glow discharge in the air. The use of discharge afterglow significantly reduces or eliminates the effects of ionization mechanisms other than Penning process, in particular, electron ionization. This significantly reduced VOC fragmentation and provided rather low limits of detection. Specific cluster formation was observed for alcohols and esters, which may facilitate their identification.

A study of matrix and admixture elements in fluorine-rich ionic conductors by pulsed glow discharge mass spectrometry.

RATIONALE: Dopants in ionic conductors play a crucial role in achieving the required electrochemical properties. A slight variation in their concentration considerably affects the conductivity of crystals and their applicability as ionic conductors and laser materials. To ensure the growth of high-quality fluoride crystals, adequate approaches for the quantification of matrix and admixture/dopant components are required. METHODS: A panel of SrF2 - and GdF3 -doped LaF3 single crystals was investigated. The electrical conductivity of the crystals was measured using impedance spectroscopy in the frequency range 100 Hz-1 MHz to control for crystal quality. Pulsed glow discharge mass spectrometry (GDMS) was used to simultaneously quantify fluorine, strontium, lanthanum, and gadolinium in the crystals. X-ray fluorescence, scanning electron microscopy-energy dispersive X-ray spectroscopy, and arc optical emission spectrometry were used for validation. RESULTS: Quasiperiodic intensity drifts under sputtering of the ionic conductors were observed and attributed to F- redistribution on the sample surface, affecting surface conductivity and sputtering rate. Several sample preparation protocols were tested to address that effect. Full coating of the sample with a layer of silver several micrometers thick provided stable and effective sputtering. The parameters for the GDMS determination of F, Sr, La, and Gd were optimized. The elements' distribution was studied in different parts of the crystals. CONCLUSIONS: An analytical approach to the direct multi-element analysis of fluoride-containing ionic conductors using pulsed GDMS with La1-x-y Srx Gdy F3-x as an example was designed and tested. Instability effects of ionic conductivity were explained and coped with, providing effective and stable sputtering.

Metal-organic frameworks based surface-enhanced Raman spectroscopy technique for ultra-sensitive biomedical trace detection.

Metal-organic frameworks (MOFs) have attracted widespread interest due to their unique and unprecedented advantages in microstructures and properties. Besides, surface-enhanced Raman scattering (SERS) technology has also rapidly developed into a powerful fingerprint spectroscopic technique that can provide rapid, non-invasive, non-destructive, and ultra-sensitive detection, even down to single molecular level. Consequently, a considerable amount of researchers combined MOFs with the SERS technique to further improve the sensing performance and broaden the applications of SERS substrates. Herein, representative synthesis strategies of MOFs to fabricate SERS-active substrates are summarized and their applications in ultra-sensitive biomedical trace detection are also reviewed. Besides, relative barriers, advantages, disadvantages, future trends, and prospects are particularly discussed to give guidance to relevant researchers.

Online breath analysis using metal oxide semiconductor sensors (electronic nose) for diagnosis of lung cancer.

The analysis of exhaled breath is drawing a high degree of interest in the diagnostics of various diseases, including lung cancer. Electronic nose (E-nose) technology is one of the perspective approaches in the field due to its relative simplicity and cost efficiency. The use of an E-nose together with pattern recognition algorithms allow 'breath-prints' to be discriminated. The aim of this study was to develop an efficient online E-nose-based lung cancer diagnostic method via exhaled breath analysis with the use of some statistical classification methods. A developed multisensory system consisting of six metal oxide chemoresistance gas sensors was employed in three temperature regimes. This study involved 118 individuals: 65 in the lung cancer group (cytologically verified) and 53 in the healthy control group. The exhaled breath samples of the volunteers were analysed using the developed E-nose system. The dataset obtained, consisting of the sensor responses, was pre-processed and split into training (70%) and test (30%) subsets. The training data was used to fit the classification models; the test data was used for the estimation of prediction possibility. Logistic regression was found to be an adequate data-processing approach. The performance of the developed method was promising for the screening purposes (sensitivity-95.0%, specificity-100.0%, accuracy-97.2%). This shows the applicability of the gas-sensitive sensor array for the exhaled breath diagnostics. Metal oxide sensors are highly sensitive, low-cost and stable, and their poor sensitivity can be enhanced by integrating them with machine learning algorithms, as can be seen in this study. All experiments were carried out with the permission of the N.N. Petrov Research Institute of Oncology ethics committee no. 15/83 dated March 15, 2017.