Oral cancer is a major health problem in the world, with significant morbidity and mortality rates that are mostly because they are not diagnosed early enough or because the lesions are often not detected at an early stage. Intraoral imaging has become a convenient and non-invasive screening tool, but diagnostic performance is highly reliant on clinician experience, and there is a wide range of heterogeneous imaging conditions across devices and clinical environments. This paper will attempt to overcome these shortcomings by introducing OralLesionNet, a dense multi-scale convolutional neural network (CNN) architecture that can effectively detect oral cancer using intraoral images with a higher degree of domain generalisation. The proposed model incorporates a dense multi-scale backbone to achieve fine-grained textural features, as well as coarse morphological features, to facilitate a better ability to differentiate benign and malignant lesions. The domain generalisation module is included in the training to promote the learning of invariant features to mitigate the performance decline due to inter-centre and device-related variations. The model was tested on a free, publicly available intraoral image dataset of benign and malignant cases that were clinically verified. To obtain a credible assessment, extensive preprocessing, augmentation, and train-validation-test splitting were used. The experimental outcomes indicate that OralLesionNet is more accurate, more precise, more recalls, more F1-score, and more area under the ROC curve (AUC) than baseline CNN, ResNet and DenseNet architectures. Ablation experiments validate the claims that multi-scale design and domain generalisation strategy play an important role in enhancing performance. The sensitivity obtained with the proposed framework is very high; this is very important in screening applications where false negatives should be reduced to a minimum. These results suggest that oral lesion classification can be made more robust and generalizable with dense multi-scale representation and domain-aware learning. OralLesionNet has a good potential of becoming a computer-aided diagnostic support tool that could enhance the ability to detect at earlier stages, minimise the inter-observer variability, and expand the screening to resource-limited settings.

This research work is dedicated to studying the histological layers of arterial vessels and their functional interrelationship with the microcirculatory track (MCT) system. The article analyzes the role of the endothelial layer, smooth muscle cells, and elastic elements within the arterial wall in maintaining hemodynamic stability. Specifically, the mechanisms by which arterioles, acting as "resistive vessels," regulate pressure transformation in microcirculation are histomorphologically substantiated. The findings serve as a theoretical foundation for understanding the morphogenesis of vascular pathologies.

This article presents the results of studies examining changes in toxic hepatitis and proposes methods for correcting this pathology. Methods for correcting these disorders using antioxidants, membrane stabilizers, immunomodulators, coenzymes, and other biologically active substances are proposed. The article also presents the results of using these substances in experimental studies.

In modern medicine, painkillers are widely used in the treatment of diseases and complications of some diseases. According to the World Health Organization, about 30 million people worldwide use painkillers per day. For example, in Malaysia, the consumption of NSAID is 14.2%, of which 4.2% is considered daily consumption. In Iran, it is 14.7% among 35-70-year-olds, and in Saudi Arabia this figure is 14.0%.

The chemical composition of the leaves of Pistacia vera has been studied for the first time. Plant material was successively extracted with chloroform and 70% acetone. The acetone extract was distilled off on a rotary evaporator to an aqueous residue. The aqueous portion was then fractionated with ethyl acetate. Individual compounds were separated by column chromatography and their chemical structure was established by physicochemical (UV, IR, NMR, mass spectroscopy) research methods.

Diabetes mellitus (DM) is one of the foremost medical and social challenges of the 21st century, and diabetic neuropathy (DN) is one of its most common complications, occurring in 50–60% of patients with long-standing disease. The aim of this study is to systematize current data on the pathophysiological mechanisms of DN and to analyze the role of metabolic, vascular, oxidative, inflammatory, and trophic factors in nerve tissue damage. A systematic literature review (2014–2024) was conducted using international and Russian databases (PubMed, Scopus, Web of Science, RSCI, eLIBRARY.RU) with the following keywords: "diabetes mellitus," "diabetic neuropathy," "hyperglycemia," "polyol pathway," "advanced glycation end-products," "oxidative stress," "nerve growth factor," and their Russian equivalents. The pathogenesis of DN involves the activation of the polyol pathway, the accumulation of advanced glycation end products, mitochondrial and endothelial dysfunction, chronic inflammation, and a deficiency of neurotrophic factors, all of which lead to progressive nerve tissue damage. Understanding these mechanisms offers opportunities for early diagnosis, the development of biomarkers, and pathogenetically-based therapy. A comprehensive approach to treatment can slow the progression of this complication and improve patients' quality of life.

At present, congenital deformities of the neck remain one of the actual problems in pediatric orthopedics. Indications for conservative or surgical treatment of these pathologies are determined based on the patient’s age, and staged rehabilitation is carried out after surgery. The study included 58 patients aged from 1 to 18 years who underwent treatment. In cases of congenital muscular torticollis, performing surgical treatment early, starting from the age of 1 year, allowed us to prevent further complications.ик.

The article presents data from the literature concerning current perspectives on the impact of fetal macrosomia on the development of obstetric and perinatal complications. Fetal macrosomia is one of the pressing issues in modern obstetric practice. In recent years, there has been a significant increase in the number of births of infants with high birth weight. This phenomenon has not only medical but also social significance, negatively affecting the health of both the mother and the child.

The aim of this work is to investigate the osmotic dilatation of human erythrocytes with various hypercholesterolemias. stress resistance It is the ability of the cell membrane to maintain its shape under various turgor conditions and to resist hemolysis. Cholesterol level increase erythrocyte membrane lipids the composition changes, that with together osmotic stability reduce possible.