Objective: to investigate the antitumor effects of various forms of vitamin B12 in combination with various synergistic vitamins and evaluate the prospects for clinical applications.

Material and methods. Cell lines BT-474 (breast ductal carcinoma) and A549 (lung carcinoma) were used as an in vitro cell model, and transplantable epidermoid Lewis lung carcinoma (LLC) was used as an in vivo animal tumor model. Animal studies of LLC were carried out on 25 male F₁ hybrid mice (age 2.5–3 months, body weight 23–26 g). In silico research was conducted as a systematic computer analysis of 9,326 scientific sources.

Results. In vitro studies on cultures of two human tumor cell lines (BT-474 and A549) confirmed the cytotoxic effect of vitamin B12 (aquacobalamin). It has been shown that vitamin B12 has weak cytotoxic properties in the concentration range of 3.125–200 μg/L (IC50>200 nM), and its hydrophobic derivative (heptamethyl cyanoquacobyric acid ester) significantly reduces the survival of tumor lines. BT-474 and A549 cells at high concentrations (100–200 µg/l, IC50~100 nM). Experimental animals with an in vivo LLС model easily tolerated a drug based on vitamin B12. Exposure to the drug up to the 21^st day of LLС development was accompanied by an increasing tendency to inhibit tumor growth by 10–20% (р=0.059). The results of a systematic in silico review of the literature show that clinical data confirmed the significant antitumor effect of vitamin B12.

Conclusion. The cellular model indicated the antitumor properties of vitamin B12 and its hydrophobic derivative. With subchronic intragastric administration of B12 to tumor-bearing animals, a steady tendency to inhibit the LLС growth was observed. Analysis of clinical data confirmed the feasibility of the antitumor use of vitamin B12 individually and in combination with synergistic vitamins.

Objective: To analyze the legal and ethical aspects of regulating artificial intelligence (AI) in medicine in key jurisdictions (United States, European Union, China, Russia), to identify regulatory gaps, ethical dilemmas and prospects for harmonization of standards.

Material and methods. National and international regulatory documents (GDPR, AI Act, FDA, NMPA), scientific publications, clinical cases and regulatory initiatives (IMDRF, WHO) were reviewed. Methods for comparative legal analysis and systematization of ethical and legal norms were used.

Results. Considerable differences in approaches to AI regulation were identified, including flexibility in the US, the ethical centricity in the EU, centralization in China and an emerging framework in Russia. Key issues were emphasized, such as algorithmic bias, AI transparency, responsibility, and the conflict between innovation and security.

Conclusion. The harmonization of international standards, the introduction of dynamic regulation and the strengthening of interdisciplinary cooperation should be pursued to achieve a balance between innovation and the protection of patients' rights.

Backgrоund. Immunoglobulin A nephropathy (IgA-N) is a common form of chronic glomerulonephritis. Its basis is the accumulation of IgA immune complexes in the glomeruli, associated with impaired glycosylation of the IgA molecule. Exogenous antigens, such as gluten, play an important role in the development of the disease. It has been experimentally confirmed that oral immunization with gluten induces mesangial IgA deposits, and a gluten-free diet can improve the course of nephropathy, indicating the significance of the enterorenal axis in the pathogenesis of IgA-N.

Objective: To study structural changes in renal tissue in IgAN patients and to evaluate the clinical and diagnostic significance of IgA antibodies to deamidated gliadin peptides (anti-DGP IgA) in the blood serum.

Material and methods. The study involved 105 patients aged 18 to 64 years diagnosed with IgAN based on a lifetime nephrobiopsy with morphological examination according to the Oxford classification. Patients were divided into two groups: the main group (n=20) included IgAN patients with detected anti-DGP IgA, and the control group (n=85) included IgAN patients seronegative for anti-DGP IgA, IgA antibodies to tissue transglutaminase, and to endomysium.

Results. When comparing fibrous-sclerotic changes, no statistically significant intergroup differences were obtained. However, a clear trend of predominance of irreversible light-optical changes within the area of the nephrobiopsy specimen was noted in patients of the main group compared to the control group: 82.4% and 56.9%, respectively (p=0.059).

Conclusion. The obtained results reflect a high frequency of irreversible fibrous-sclerotic changes in the nephrobiopsy in patients with IgAN and anti-DGP IgA in the blood serum. Timely detection of anti-DGP IgA can improve the ability to predict the outcome of the disease and optimize therapeutic strategies.

Nitric oxide NO is a signaling molecule involved in numerous physical and pathological processes in biological systems. Highly sensitive sensor materials for measuring NO amounts in vivo in exhaled air and in body fluids (saliva, blood, urine) can be a useful tool in diagnostics and management of patients with bronchopulmonary, cardiovascular, neurological and tumor diseases. Several approaches to measuring NO in biosubstrates (including exhaled air) have been developed: fluorescence/chemiluminescence, electron spin resonance, electrochemical/amperometric (organic and inorganic) and enzymatic/protein sensors. Semiconductors, transition metal nitrides, phthalocyanine complexes, porphyrin and cobalamin derivatives with metals can serve as materials for NO sensors. Creating sensor materials based on vitamin B12 derivatives is an urgent research task in biomedicine. The article systematizes information on using various compounds as materials for NO-sensitive and selective sensors to measure/evaluate NO levels in various biosubstrates.

Objective: Comparative analysis of modern computer programs (smartphone programs – mobile applications) using artificial intelligence (AI) for diagnosis and dynamic monitoring of skin pathologies.

Material and methods. A total of 1,319 publications were identified for AI-powered computer programs using targeted searches in PubMed/MEDLINE and Google Scholar databases, as well as in the eLibrary and CyberLeninka electronic libraries for the period 2016–2025. Using queries focused on AI, convolutional neural networks (CNNs), computer programs (mobile apps), and dermatovenereology, a total of 1,319 publications were identified. After a multi-stage screening based on inclusion/exclusion criteria (including the availability of quantitative performance metrics), 9 key articles with specific descriptions of the computer programs (mobile apps) were selected. A search and subsequent analysis identified 9 computer programs (mobile apps): Google DermAssist, SkinIO, Melanoma Check, Derma Onko Check, SkinVision, Tibot, SkinScan, Aysa, and Skinive, which use AI to diagnose and monitor skin conditions.

Results. Effectiveness of the programs varies: Google DermAssist and Derma Onko Check demonstrated high accuracy (96–97%) and sensitivity (97–98%), while Skinive showed improvement in metrics over time from 2020 to 2021 (maximum sensitivity of 97.9% and specificity of 97.1%). Limitations include dependence on photo image quality, low effectiveness for rare conditions and dark skin tones, and the need for a biopsy to confirm a diagnosis. Mobile apps using CNN demonstrate high sensitivity (87–97.9%), but specificity varies significantly (70–98%), which may increase the number of additional consultations with specialist doctors when using these programs in diagnostics.

Conclusion. AI-based software (mobile apps) offer significant potential for increasing the accessibility and accuracy of skin pathology diagnostics, especially in remote areas and regions with a shortage of dermatovenereologists. Potential developments include integrating software with telemedicine, improving algorithms for diagnosing rare pathologies, and standardizing testing to improve the reproducibility of results.