Molecular and biological factors in the prognosis of head and neck squamous cell cancer.

The objective of the review is to summarize available literary data on the role and prognostic value of molecular biological markers p53, UBE2C, CD147, STAT3, VEGF in the carcinogenesis of head and neck squamous cell carcinoma (HNSCC). To date, researches have been studying HNSCC molecular and genetic characteristics and obtaining information about new molecular biological markers that have different functional significance in tumor progression. This review presents current data on protein molecules involved in the HNSCC development, as well as in the formation of drug resistance mechanisms in tumors. The considered markers can be used not only for prognosis but also for developing a new approach to treatment, including patients resistant to therapy or recurrent HNSCC. However, the introduction of these markers into practice requires further examination of their functions and larger-scale studies.

Surface Modification of Additively Fabricated Titanium-Based Implants by Means of Bioactive Micro-Arc Oxidation Coatings for Bone Replacement.

In this work, the micro-arc oxidation method is used to fabricate surface-modified complex-structured titanium implant coatings to improve biocompatibility. Depending on the utilized electrolyte solution and micro-arc oxidation process parameters, three different types of coatings (one of them-oxide, another two-calcium phosphates) were obtained, differing in their coating thickness, crystallite phase composition and, thus, with a significantly different biocompatibility. An analytical approach based on X-ray computed tomography utilizing software-aided coating recognition is employed in this work to reveal their structural uniformity. Electrochemical studies prove that the coatings exhibit varying levels of corrosion protection. In vitro and in vivo experiments of the three different micro-arc oxidation coatings prove high biocompatibility towards adult stem cells (investigation of cell adhesion, proliferation and osteogenic differentiation), as well as in vivo biocompatibility (including histological analysis). These results demonstrate superior biological properties compared to unmodified titanium surfaces. The ratio of calcium and phosphorus in coatings, as well as their phase composition, have a great influence on the biological response of the coatings.

Non-Invasive Diagnosis of Malignancies Based on the Analysis of Markers in Exhaled Air.

Novel non-invasive methods for the diagnosis of malignancies should be effective for early diagnosis, reproducible, inexpensive, and independent from the human factor. Our aim was to establish the applicability of the non-invasive method, based on the analysis of air exhaled by patients who are at different stages of oropharyngeal, larynx and lung cancer. The diagnostic device includes semiconductor sensors capable of measuring the concentrations of gas components in exhaled air, with the high sensitivity of 1 ppm. The neural network uses signals from these sensors to perform classification and identify cancer patients. Prior to the diagnostic procedure of the non-invasive method, we clarified the extent and stage of the tumor according to current international standards and recommendations for the diagnosis of malignancies. The statistical dataset for neural network training and method validation included samples from 121 patients with the most common tumor localizations (lungs, oropharyngeal region and larynx). The largest number of cases (21 patients) were lung cancer, while the number of patients with oropharyngeal or laryngeal cancer varied from 1 to 9, depending on tumor localization (oropharyngeal, tongue, oral cavity, larynx and mucosa of the lower jaw). In the case of lung cancer, the parameters of the diagnostic device are determined as follows: sensitivity-95.24%, specificity-76.19%. For oropharyngeal cancer and laryngeal cancer, these parameters were 67.74% and 87.1%, respectively. This non-invasive method could lead to relevant medicinal findings and provide an opportunity for clinical utility and patient benefit upon early diagnosis of malignancies.

Cancer Diagnosis by Neural Network Analysis of Data from Semiconductor Sensors.

"Electronic nose" technology, including technical and software tools to analyze gas mixtures, is promising regarding the diagnosis of malignant neoplasms. This paper presents the research results of breath samples analysis from 59 people, including patients with a confirmed diagnosis of respiratory tract cancer. The research was carried out using a gas analytical system including a sampling device with 14 metal oxide sensors and a computer for data analysis. After digitization and preprocessing, the data were analyzed by a neural network with perceptron architecture. As a result, the accuracy of determining oncological disease was 81.85%, the sensitivity was 90.73%, and the specificity was 61.39%.