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Digitized data is presented based on the 1966 and 1972 seminal papers by R. J. Bell and P. Dean, which in turn are based on a physical ball and stick model of vitreous silica. The original Bell and Dean paper supports the random network theory for glass structure proposed by Zachariasen in 1932. The data were collected and digitized by verifying the data set in the Appendix of the Bell and Dean paper. One error in location was corrected. The dataset provides a convenient method to determine specific information about bond locations and angles of silica and oxygen atoms if researchers want to test theories of glass structure or fracture in amorphous materials.

Abstract Background Pathomics facilitates automated, reproducible and precise histopathology analysis and morphological phenotyping. Similar to molecular omics, pathomics datasets are high-dimensional, but also face large outlier variability and inherent data missingness, making quick and comprehensible data analysis challenging. To facilitate pathomics data analysis and interpretation as well as support a broad implementation we developed tRigon (Toolbox foR InteGrative (path-)Omics data aNalysis), a Shiny application for fast, comprehensive and reproducible pathomics analysis. Results tRigon is available via the CRAN repository ( https://cran.r-project.org/web/packages/tRigon ) with its source code available on GitLab ( https://git-ce.rwth-aachen.de/labooratory-ai/trigon ). The tRigon package can be installed locally and its application can be executed from the R console via the command ‘tRigon::run_tRigon()’. Alternatively, the application is hosted online and can be accessed at https://labooratory.shinyapps.io/tRigon . We show fast computation of small, medium and large datasets in a low- and high-performance hardware setting, indicating broad applicability of tRigon. Conclusions tRigon allows researchers without coding abilities to perform exploratory feature analyses of pathomics and non-pathomics datasets on their own using a variety of hardware.

Abstract Although clinical applications represent the next challenge in single-cell genomics and digital pathology, we still lack computational methods to analyze single-cell or pathomics data to find sample-level trajectories or clusters associated with diseases. This remains challenging as single-cell/pathomics data are multi-scale, i.e., a sample is represented by clusters of cells/structures, and samples cannot be easily compared with each other. Here we propose PatIent Level analysis with Optimal Transport (PILOT). PILOT uses optimal transport to compute the Wasserstein distance between two individual single-cell samples. This allows us to perform unsupervised analysis at the sample level and uncover trajectories or cellular clusters associated with disease progression. We evaluate PILOT and competing approaches in single-cell genomics or pathomics studies involving various human diseases with up to 600 samples/patients and millions of cells or tissue structures. Our results demonstrate that PILOT detects disease-associated samples from large and complex single-cell or pathomics data. Moreover, PILOT provides a statistical approach to find changes in cell populations, gene expression, and tissue structures related to the trajectories or clusters supporting interpretation of predictions.

Relevance. Related to the need to carry out environmental protection measures in potash mining areas exposed to the environmental consequences of the impact of multi-tonnage salt waste. Aim. To summarise and analyse the geography of potash mining operations, the environmental impact of these operations, and potash waste management practices. Object. Potash mining waste. Methods. Theoretical and logical analysis of the data. Results. The research considers the geographical distribution of potash deposits and presents the characteristics of potash mining waste using the example of the Verkhnekamskoe Potash Deposit. The paper provides both domestic and foreign analyses of ecological consequences of waste storage on the day surface. Several options for potash mining waste management are analysed. For the management of clay-salt slurry, the most effective approach is its injection into underground horizons, which includes the use of saturated solutions as a fertiliser component, as a part of a product in construction, and in the oil industry. A more comprehensive approach to halite waste management is needed. Waste disposal to waste dumps is relevant due to the presence of mined-out areas on the territory of long-operating enterprises. Reclamation of the salt dump will help to isolate it from atmospheric precipitation, thereby reducing the inflow of saturated water into the environment. Utilising waste for production of construction materials is the most economically and environmentally favourable option. Extracting valuable components, producing fertilisers, concentrates, etc. from waste is the least practical approach due to the ecological and economic expenses involved in acquiring extraction equipment and the repeated generation of waste. The most challenging aspect of reducing waste generation in terms of technology lies in improving mining operations and implementing selective mining.

Randomized clinical trials (RCTs) are the gold standard of evidence-based medicine. However, it is no less evident that real practice presents many new and important questions that are difficult to answer in the RCT. To what extent does the real patient meet the criteria for inclusion in the study? What are the efficacy and safety of the drug in comorbid and elderly patients? How deviations from the treatment regimen affect safety, etc. The introduction of innovative oncology approaches is disproportionately faster than in other fields. That is why a balanced analysis of the effects of innovation in real-world practice is relevant. Regulatory authorities are aware of this and demonstrate a willingness to consider and actively support real-world evidence research as part of drug applications, which is a powerful incentive for developing this area. The purpose of the article is to analyze the regulatory approaches in the United States and Europe to real-world studies when considering drug applications and to discuss the experience of organizing an observational study of the effectiveness of individual drugs for the treatment of oncological diseases in Moscow as a unique example of interaction between regulatory authorities and the expert community of oncologists.

The Banff Digital Pathology Working Group (DPWG) was established with the goal to establish a digital pathology repository; develop, validate, and share models for image analysis; and foster collaborations using regular videoconferencing. During the calls, a variety of artificial intelligence (AI)-based support systems for transplantation pathology were presented. Potential collaborations in a competition/trial on AI applied to kidney transplant specimens, including the DIAGGRAFT challenge (staining of biopsies at multiple institutions, pathologists’ visual assessment, and development and validation of new and pre-existing Banff scoring algorithms), were also discussed. To determine the next steps, a survey was conducted, primarily focusing on the feasibility of establishing a digital pathology repository and identifying potential hosts. Sixteen of the 35 respondents (46%) had access to a server hosting a digital pathology repository, with 2 respondents that could serve as a potential host at no cost to the DPWG. The 16 digital pathology repositories collected specimens from various organs, with the largest constituent being kidney (n = 12,870 specimens). A DPWG pilot digital pathology repository was established, and there are plans for a competition/trial with the DIAGGRAFT project. Utilizing existing resources and previously established models, the Banff DPWG is establishing new resources for the Banff community.

The selection technique of diagnostic parameters for the creation of fault detection system of autonomous electric power sources based on gasoline and diesel engines is given in the paper. An analysis of the design features for autonomous electric power sources based on internal combustion engines, which are the most common on the Ukrainian market, was carried out. Thanks to this, a logical model of the research object, which establishes the relation between the main structural elements of the system and determines the possible states of the system, was developed. The effect of fault state initiation for each element on the other system elements was analyzed. An informative criterion – Shannon information entropy is proposed to determine the finite number of diagnostic parameters among the infinite number of possible combinations for physical parameters that characterize the system. The equal-probable cases of exit from operational state of each system elements are considered. The residual entropies of the system at the fault state for one of the autonomous power sources assembly are determined, having applied the concept of Shannon information entropy. The residual entropy value is the informative criterion. The application of this criterion allowed to determine the system elements that most effectively reduce the system uncertainty degree. Based on the residual entropy values, the system assemblies, the state of which should be primarily monitored by diagnostic system, are selected. The diagnostic parameters are determined for such elements, and the ways to obtain them are given

In Russia, the number of beef cattle until recently was concentrated mainly in Kalmykia and adjacent regions. However, the lack of purposeful breeding has led to the fact that the purebred livestock of Kalmyk meat breed has significantly decreased and lost its unique qualities. Introduction of embryo transfer biotechnology can solve the problem of restoring breed qualities under the condition of accelerated reproduction of genotyped livestock. The aim of the research was to study Kalmyk breed response to polyovulation considering further increase in transferrable embryo productivity - the main indicator specific to each breed. As the formation of the breed took place in pasture conditions with a pronounced seasonal sexual cycle, there were doubts about the possibility of using embryo transfer technology in any season. The experiments were carried out on Kalmyk cows at Kalmytskoye farm in 2010 and at the Regional Research and Production Center for Reproduction of Farm Animals, Kalmyk State University, in 2022. The results of the study showed that it was better to synchronize sexual hunting using prostaglandins after 3-4 months after calving (May-October). According to the results of immunogenetic testing, 10 breeding cows and 2 breeding bulls were selected as donors. In September-October, in order to test the embryo transfer method in nomadic animal husbandry, the first work was carried out to stimulate poliovulation and obtain embryos from 3 donor cows. A total of 23 embryos and eggs were obtained, 10 of which were suitable for transplantation. Transferrable embryos were frozen on a ZEM-4 software freezer after equilibration in 1.5 M ethylene glycol cryoprotector solution.

Pathology diagnostics still rely on tissue morphology assessment by trained experts. Here, the authors perform deep-learning-based segmentation followed by large-scale feature extraction of histological images, i.e., next-generation morphometry, to enable outcome-relevant and disease-specific pathomics analysis of non-tumor kidney pathology.

Introduction. The relevance of the study of steppe phytocenoses is caused by the unsatisfactory state of natural grass stands, namely a low level of biodiversity and a high degree of degradation. The aim of the work is to determine the features of the connection of the Earth remote sensing data with the state and degree of degradation of natural grass stands in unstable moistening zone and arid zone of the Stavropol Territory. The Earth remote sensing data with certain temporal and spatial resolutions make it possible to carry out almost continuous monitoring of the state of natural grass stands. Materials and Methods. The study of steppe phytocenoses was carried out in 2016–2020 on the ground at discount areas (100 m2) according to the requirements of methods generally accepted in phytocenology. Vegetation condition was assessed using the Earth remote sensing data based on the values of the Normalized Difference Vegetation Index. According to the satellite data, Normalized Difference Vegetation Index cartograms were constructed for each point of the study. Results. The proportion of polygons with a high degree of degradation is 18.8% of research objects located in the zone of unstable moistening and the proportion of polygons with an average degree of degradation is 37.5%, while in the arid zone 70.6 and 23.5%, respectively. In the zone of unstable moistening, the highest coefficients of rank correlation between the degradation degree and the area occupied by herbaceous vegetation with a certain value of the vegetation index are observed in the case if Normalized Difference Vegetation Index is in the range of 0.0–0.4, and in the arid zone 0.0–0.3 (at 0.01 significance level). Discussion and Conclusion. When using the Earth remote sensing data to assess the degree of degradation of steppe ecosystems of the Stavropol Territory, it is necessary to use regression models specific to various soil and climatic conditions.

Artificial Intelligence can support diagnostic workflows in oncology, but they are vulnerable to adversarial attacks. Here, the authors show that convolutional neural networks are highly susceptible to white- and black-box adversarial attacks in clinically relevant classification tasks.

The relevance of the research stems from the need to study the radioactive load in the zone of influence of mining objects. Objective: assessment of specific activity of natural radionuclides 226Ra, 232Th and 40K in depositing media and analysis of their spatial distribution, as well as measurement of K+ content in snow cover. Objects: soils, bottom sediments, snow. Methods. Measurements of specific activity of natural radionuclides (40K, 226Ra, 232Th) in samples of soils and bottom sediments were performed using MULTIRAD scintillation gamma spectrometer MKS-01A (Russia). Gamma-spectra were processed using programs included in the Progress package. K+ was determined in melted water by capillary electrophoresis on KAB «Kapel 104». Results. The specific activity 40K for the majority of investigated soil samples on the territory of the Verkhnekamskoe salt deposit does not exceed average world values, for samples of bottom sediments – for other territories with anthropogenic influence. In the immediate vicinity of the potassium enterprise, increased K+ content in the snow cover is observed due to the wind regime of the territory. Migration of the investigated radionuclides is limited to the zone of 2 km, K+ ions – to the zone of 3 km. The maximum activities of 226Ra and 232Th in the investigated soil samples are significantly lower than the world average values. Zones with a ratio of 232Th/226Ra activity values

Nucleophilic substitution reactions between 1,2,3-triazole and dibromomethane or 1,2-dirbomoethane in a superbasic medium potassium hydroxide–dimethyl sulfoxide gave mixtures of the isomeric bis(1,2,3-triazolyl)alkanes, in which (1,2,3-triazol-1-yl)(1,2,3-triazol-2-yl)alkanes and bis(1,2,3-triazol-2-yl)alkanes were the dominating products, while bis(triazol-1-yl)alkanes were detected only in trace amounts. The same products could also be obtained under solvent-free conditions in a neat reaction mixture. The proposed methods are economically feasible, do not require using toxic solvents or catalysts, and make the (1,2,3-triazol-2-yl)-derivatives, inaccessible by alkyne-azide cycloaddition (click) reactions, readily available.

The new phase Ba5In2Al2Zr0.9Nb0.1O13.05 with hexagonal perovskite structure was obtained. The substitution of Zr4+ by smaller Nb5+ was accompanied by the incorporation of the oxygen interstitials and did not lead to a significant change in the lattice parameters. It was established that the investigated sample was capable for water incorporation from the gas phase, the hydration degree value was 0.24 mol H2O. IR-spectroscopy analysis defined the presence of OH−-groups with different thermal stability, which participate in different hydrogen bonds. The new phase Ba5In2Al2Zr0.9Nb0.1O13.05 demonstrates the predominant protonic conductivity at pH2O = 2·10−2 atm and Т600 °C.

Summary: Background: HIV-infection is known to aggravate the course of many infectious diseases, including COVID-19. International guidance recommends vaccination of HIV+ individuals against SARS-CoV-2. There is a paucity of data on epidemiological efficacy assessment of COVID-19 vaccines among HIV+. This paper provides a preliminary assessment of Sputnik V vaccine effectiveness in HIV+ patients on antiretroviral therapy (ART). Methods: We performed a retrospective cohort study to assess the effectiveness of the standard Sputnik V vaccination regimen in 24,423 HIV+ Moscow residents during spring - summer 2021, that included dominance of delta variant, with estimation of hospitalization and severe illness rates in vaccinated and unvaccinated patients. Data were extracted from the Moscow anti-COVID-19 vaccination and COVID-19 incidence Registries. Findings: The data obtained indicate that Sputnik V epidemiological efficiency in the entire cohort of HIV+ on ART was 76·33%; in HIV+ with CD4+ ≥ 350 cells/µl, vaccine efficiency was 79·42%, avoiding hospitalization in 90·12% cases and protecting from the development of moderate or severe disease in 97·06%. For delta variant in this group the efficiency was 65·35%, avoiding the need for hospitalization in 75·77% cases and protecting from the development of moderate or severe disease in 93·05% of patients. There was a trend, although not statistically significant, of declining vaccine efficiency in immune-compromised individuals (CD4+ < 350 cells/µl). Interpretation: The study suggested epidemiological efficiency of immunization with Sputnik V in HIV+ ART-treated patients for the original and delta SARS-CoV-2 variants. Funding: Ministry of Health of Russia and Moscow Healthcare Department.

Background: The fast acquisition process of frozen sections allows surgeons to wait for histological findings during the interventions to base intrasurgical decisions on the outcome of the histology. Compared with paraffin sections, however, the quality of frozen sections is often strongly reduced, leading to a lower diagnostic accuracy. Deep neural networks are capable of modifying specific characteristics of digital histological images. Particularly, generative adversarial networks proved to be effective tools to learn about translation between two modalities, based on two unconnected data sets only. The positive effects of such deep learning-based image optimization on computer-aided diagnosis have already been shown. However, since fully automated diagnosis is controversial, the application of enhanced images for visual clinical assessment is currently probably of even higher relevance. Methods: Three different deep learning-based generative adversarial networks were investigated. The methods were used to translate frozen sections into virtual paraffin sections. Overall, 40 frozen sections were processed. For training, 40 further paraffin sections were available. We investigated how pathologists assess the quality of the different image translation approaches and whether experts are able to distinguish between virtual and real digital pathology. Results: Pathologists' detection accuracy of virtual paraffin sections (from pairs consisting of a frozen and a paraffin section) was between 0.62 and 0.97. Overall, in 59% of images, the virtual section was assessed as more appropriate for a diagnosis. In 53% of images, the deep learning approach was preferred to conventional stain normalization (SN). Conclusion: Overall, expert assessment indicated slightly improved visual properties of converted images and a high similarity to real paraffin sections. The observed high variability showed clear differences in personal preferences.

Background: Considerable inter- and intra-laboratory stain variability exists in pathology, representing a challenge in development and application of deep learning (DL) approaches. Since tackling all sources of stain variability with manual annotation is not feasible, we here investigated and compared unsupervised DL approaches to reduce the consequences of stain variability in kidney pathology. Methods: We aimed to improve the applicability of a pretrained DL segmentation model to 3 external multi-centric cohorts with large stain variability. In contrast to the traditional approach of training generative adversarial networks (GAN) for stain normalization, we here propose to tackle stain variability by data augmentation. We augment the training data of the pretrained model by the stain variability using CycleGANs and then retrain the model on the stain-augmented dataset. We compared the performance of i/ the unmodified pretrained segmentation model with ii/ CycleGAN-based stain normalization, iii/ a feature-preserving modification to ii/ for improved normalization, and iv/ the proposed stain-augmented model. Results: The proposed stain-augmented model showed highest mean segmentation accuracy in all external cohorts and maintained comparable performance on the training cohort. However, the increase in performance was only marginal compared to the pretrained model. CycleGAN-based stain normalization suffered from encoded imperceptible information into the normalizations that confused the pretrained model and thus resulted in slightly worse performance. Conclusions: Our findings suggest that stain variability can be tackled more effectively by augmenting data by it than by following the commonly used approach of normalizing the stain. However, the applicability of this approach providing only a rather slight performance increase has to be weighted against an additional carbon footprint.

The well-known fluorophore, namely 1,3,6,8-tetrakis[(trimethylsilyl)ethynyl]pyrene, has been studied profoundly as a fluorescent sensor toward nitroaromatic compounds in solutions and vapor phase. Three prototypes of fluorescent materials for vapor sensing were prepared via electrospinning and drop-casting onto the melamine formaldehyde foam with the fluorophore as a pure solid or as a dopant in the polystyrene matrix. It has been shown that this fluorophore and solid fluorescent materials based on it have high detection limits toward nitroaromatic compounds within the range of 10−8 to 10−9 M in acetonitrile solution and within the up to ppb range in the vapor phase. The model, expanding on Frisch’s permeation model, was utilized to characterize the fluorescence response of materials relative to vapor concentration and duration of exposure to vapor. All prototypes can be used as sensor materials exhibiting a good sensitivity and selectivity for the original hand-made sniffer for detecting nitro-containing explosives in the vapor phase for real-time application.

The search for new magnetocaloric materials for application in magnetic refrigerants is highly motivated by high efficiency, reliability, and environmental safety. The values of the magnetocaloric effect MCE and the refrigerant capacity RC for the equiatomic GdRuSi compound were determined to be MCE = 10.7 and 4.94 J/kgK and RC = 336 and 92 J/kg with a change in the field of 0–50 and 0–17 kOe, respectively. These high values of MCE and RC for GdRuSi appear in the region of nitrogen liquefaction temperature of 77.4 K, due to which the compound can be useful in practice. The densities of states and magnetic moments of GdRuSi were calculated theoretically, taking into account strong electron correlations in the 4f Gd shell. The total magnetic moment of GdRuSi was found to be composed of the Gd moment only with the value calculated in very good agreement with the experimental one.

The evolution of a nanostructured state of palladium—lead membrane alloys during their interaction with hydrogen was studied using precision X-ray diffraction with synchrotron radiation (SR) and scanning electron microscopy (SEM) with energy-dispersive X-ray spectroscopy (EDXS). The importance of this topic is due to the need and demand for improving the performance characteristics of dense metal diffusion filters for high purity hydrogen separation processes. Palladium-based membrane filters with lead concentrations of 5 and 20 wt.% were prepared via electric arc melting from high purity metals (99.95%). The thickness of the filters was 50 μm. Hydrogenation was carried out from a gas medium at 573 K and the pressure of 16 atm. within 150 min. The focus of the study is on the structural state of diffusion filter membranes depending on the content of the palladium-alloying element—lead—and on analysis of the substructure of alloys before and 5300 h relaxation after hydrogenation is carried out. Specific features of the surface morphology and the structure of the membrane filters depending on the concentration of lead in the alloys are determined. The formation and development of deformation processes in metal systems upon the hydrogenation is shown. The establishment of peculiarities of hydrogen interaction with metals will contribute to obtaining new potentially important characteristics of membrane filters.

The aim of our research was to study the endosphere of four halophytic plants: Salicornia europaea L., Salsola australis (R.Br.), Bassia sedoides (Pall.) and Kochia prostrata (L.) Schrad. from arid and saline areas of the Stavropol Territory, Russia. In total, 28 endophyte strains were isolated from the roots and stems of these halophytic plants. Most of the isolates (23 out of 28) were identified as Bacillus sp. while others belonged to the genera Oceanobacillus, Paenibacillus, Pantoea, Alcaligenes and Myroides. Three strains of Bacillus sp. (Se5R, Se1-1R, and Se1-3S), isolated from the S. europaea were capable of growth at 55 °C and in 10% of NaCl. Strains Se1-4S, Kp20-2S, and Bs11-2S Bacillus sp. (isolated from the S. australis, K. prostrata and B. sedoides, respectively) demonstrated strong plant growth promoting activity: 85–265% over control lettuce plants and a high degree of growth suppression (59.1–81.2%) of pathogenic fungi Fusarium oxysporum, Bipolaris sorokiniana and Rhizoctonia solani. Selected strains can be promising candidates for the development of bioinoculants to facilitate salt soil phytoremediation and be beneficial for mitigating the salt stress to the plants growing in salt-affected habitats.

Five random copolymers comprising styrene and styrene with pendant fluorophore moieties, namely pyrene, naphthalene, phenanthrene, and triphenylamine, in molar ratios of 10:1, were synthesized and employed as fluorescent sensors. Their photophysical properties were investigated using absorption and emission spectral analyses in dichloromethane solution and in solid state. All copolymers possessed relative quantum yields up to 0.3 in solution and absolute quantum yields up to 0.93 in solid state, depending on their fluorophore components. Fluorescence studies showed that the emission of these copolymers is highly sensitive towards various nitroaromatic compounds, both in solution and in the vapor phase. The detection limits of these fluorophores for nitroaromatic compounds in dichloromethane solution proved to be in the range of 10−6 to 10−7 mol/L. The sensor materials for new hand-made sniffers based on these fluorophores were prepared by electrospinning and applied for the reliable detection of nitrobenzene vapors at 1 ppm in less than 5 min.

The effect of synthesis conditions on the features of the long- and short-range order of Ln2(WO4)3 (Ln = Gd, Dy, Ho, Yb) powders synthesized via coprecipitation of salts has been studied by a complex of physico-chemical techniques including synchrotron X-ray powder diffraction, X-ray absorption spectroscopy, Raman and infrared spectroscopy, and simultaneous thermal analysis. It was found that crystallization of amorphous precursors begins at 600 °C/3 h and leads to the formation of the monoclinic structure with sp. gr. C12/c1(15) for Ln2(WO4)3 (Ln = Gd, Dy) and with sp. gr. P121/a1(14) for Ln = Yb, whereas crystallization of Ho precursor requires even higher temperature. After annealing at 1000 °C, the P121/a1(14) phase becomes the dominant phase component for all heavy lanthanoid types except for Ln = Gd. It was shown that the Ln (Ln = Dy, Ho, and Yb) tungstates with the P121/a1(14) monoclinic structure correspond to trihydrates Ln2(WO4)3·3H2O formed due to a rapid spontaneous hydration under ambient conditions. It was concluded that the proneness to hydration is due to a specific structure of the P121/a1(14) phase with large voids available to water molecules. Modifications in the local structure of Ln-O coordination shell accompanying the structure type change and hydration are monitored using EXAFS spectroscopy.

Background: There is a need for better strategies to promote burn wound healing and prevent infection. The aim of our study was to develop an easy-to-use placental multipotent mesenchymal stromal cell (MMSC) secretome-based chitosan hydrogel (MSC-Ch-gel) and estimate its antimicrobial and regenerative activity in Staphylococcus aureus-infected burn wounds in rats. Methods: Proteomic studies of the MMSC secretome revealed proteins involved in regeneration, angiogenesis, and defence responses. The MMSC secretome was collected from cultured cells and mixed with water-soluble chitosan to prepare the placental MSC-Ch-gel, which was stored in liquid phase at 4 °C. The wounds of rats with established II-IIIa-degree burns were then infected with S. aureus and externally covered with the MSC-Ch-gel. Three additional rat groups were treated with medical Vaseline oil, the antiseptic drug Miramistin®, or the drug Bepanthen® Plus. Skin wound samples were collected 4 and 8 days after burning for further microbiological and histological analysis. Blood samples were also collected for biochemical analysis. Results: Application of the MSC-Ch-gel cleared the wound of microorganisms (S. aureus wasn’t detected in the washings from the burned areas), decreased inflammation, enhanced re-epithelialisation, and promoted the formation of well-vascularised granulation tissue. Conclusions: MSC-Ch-gel effectively promotes infected wound healing in rats with third-degree burns. Gel preparation can be easily implemented into clinical practice.

The phenolic compounds in the leaves of 12 species of birch trees of the subgenera Neurobetula, Betulenta, and Betula were biochemically profiled using HPTLC. The duration of the vegetation period was found to be significantly related to the content of total phenols (r = 0.74) and flavonoids in leaves (r = 0.65). The correlations for Neurobetula plants were 0.86 and 0.91, respectively. The relationship between the duration of the growing season and the concentration of phenolic compounds in Betula plants was inverse (r =-0.84). A cluster analysis of phytochemical profiles revealed that the studied birch species form groups that coincide with the subgenera proposed by De Jong due to an affinity with the qualitative composition of phenolic compounds. A multiple correlation analysis confirmed the relationship between the qualitative composition of phenolic compounds and the morphological characteristics of the leaves. The results of phytochemical profiling revealed that the qualitative composition of polyphenols in the leaves of 12 birch species is quite specific, allowing the use of individual compounds as additional differential biochemical characters in identifying species and hybrids and studying their potential role in plant adaptation to habitat conditions. Key words: Betula, chemosystematics, introduction, flavonoids, tannins, 1. Introduction The plants of the genus Betula L. play an important role in the flora of the temperate forest zone, as well as the boreal and sub-arctic zones (Furlow [...]