Characteristics Of Different Types Research Articles

A case series of dermatopathological features in different types of morphea and their clinical correlates.

The dermatopathological features in morphea (localized scleroderma) and their clinicopathologic correlations are not well described in the literature. To describe dermatopathological changes of different types of morphea and to investigate the association between clinical and histopathological features. A total of 18 cases of morphea who attended our tertiary care center in the last four years were evaluated. We noted clinical characteristics of all patients and dermatopathological changes like the pattern of sclerosis, degree of inflammation, cell types and all epidermal-dermal, and appendageal changes. Clinicopathological correlation was performed to interpret the clinical significance of dermatopathological changes in various types of morphea. Morphea was most commonly noted in the third decade and females. A circumscribed plaque was the most common clinical presentation. Full-thickness pattern of sclerosis was significantly associated with various clinical outcomes. Basal pigmentation and a reduced number of appendages were noted in more than 80% of patients. All patients had various grades of inflammation. Severe and moderate-grade inflammation with eosinophils and plasma cells was associated with pruritus and/or pain. The limitations are small sample size and single-centered case series. The dermatopathological examination of morphea may help in better monitoring and treatment of patients, including patterns of sclerosis and grades of inflammation, and cell types in skin pathology reports will aid in proper and better clinical management.

Dermoscopy as a novel tool to examine and assess treatment response of acne scars: A pilot study in an Indian population

Objectives: Acne scars are common and have limited methods of evaluation. They occur due to decreased collagen (atrophic, rolling, icepick, boxcar, and linear) or increased collagen (hypertrophic and keloidal). There are very few studies concerning the evaluation and treatment methodology of acne scars by dermoscopy. The primary aim of the study was to observe the dermoscopic features of different types of acne scars. The secondary aim was to evaluate the role of dermoscopy in the assessment of response to treatment. Material and Methods: Thirty consenting patients with post-acne scars were enrolled for the study in a tertiary care dermatology center. Detailed history and clinical examination data were recorded followed by dermoscopic evaluation at presentation. Consequently, the standard treatment modality was chosen depending on the type of acne scars, and the procedure was done at monthly intervals. Dermoscopy was repeated at a frequency of 6 months. Concurrently, histopathological evaluation for collagen and elastin was performed in a case of deep atrophic scar. Result: Initial dermoscopy showed a poorly defined pseudo reticular network on the face and diffuse pigmentation interrupted by adnexal openings. Ice pick scars appeared as comedo-like openings along with an accentuated perifollicular pigmented network and vascular structures. Rolling scars showed valley-like areas with sloping edges and a marginal rim of pigmentation. Boxcar scars had characteristic cup-shaped depressions with a hyperpigmented rim and dilution of central pigmentation. On sequential dermoscopy following treatment, a decrease in perifollicular pigmentation, and a granular pigment network was seen. There was considerable curtailment of size and depth of acne scars. Further, an increase in the hair follicle density was observed following treatment. Scars of shorter duration showed better response compared to scars of longer duration. In histopathology, increased collagen deposition and early elastogenesis were observed. Conclusion: Treatment is more effective in cases of acne scars of shorter duration. Dermoscopy may be a valuable tool in the assessment of acne scars and their response to treatment.

Multi-objective classification prediction method for coal gangue based on image feature extraction

ABSTRACT Coal gangue is a solid waste discharged during the coal production process, consisting of rocks and minerals, and is a nonmetal mineral resource with attributes suitable for comprehensive utilization. This study explores the pre-classification issue of coal gangue comprehensive utilization through image recognition methods. Initially, coal gangue was categorized into four types – Residual coal, Gray gangue, Red gangue, and White gangue-based on its appearance, chemical composition, phase composition, and usage characteristics. Subsequently, the color features, texture features, and shape features of different types of coal gangue were analyzed using box plots, correlation coefficients, and cluster analysis. Finally, by comprehensively considering color, texture, and shape features, and by simplifying highly correlated variables, a support vector machine was employed for classification prediction. The overall recognition accuracy rate for multi-target classification reached 89%.

Biomechanical study of knee joint based on coronal plane alignment of the knee

To establish a finite element model of the knee joint based on coronal plane alignment of the knee (CPAK) typing method, and analyze the biomechanical characteristics of different types of knee joints. The finite element models of the knee joint were established based on CT scan data of 6 healthy volunteers. There were 5 males and 1 female with an average age of 24.2 years (range, 23-25 years). There were 3 left knees and 3 right knees. According to the CPAK typing method, the knees were rated as types Ⅰ to Ⅵ. Under the same material properties, boundary conditions, and axial loading, biomechanical simulations were performed on the finite element model of the knee joint. Based on the Von Mises stress nephogram and displacement nephogram, the peak stresses of the meniscus, femoral cartilage, and tibial cartilage, and the displacement of the meniscus were compared among different types of knee joints. The constructed finite element model of the knee joint was verified to be effective, and the stress and displacement results were consistent with previous literature. Under the axial load of 1 000 N, the stress nephogram showed that the stress distribution of the medial and lateral meniscus and tibial cartilage of CPAK type Ⅲ knee joint was the most uneven. The peak stresses of the lateral meniscus and tibial cartilage were 9.969 6 MPa and 2.602 7 MPa, which were 173% and 165% of the medial side, respectively. The difference of peak stress between the medial and lateral femoral cartilage was the largest in type Ⅳ knee joint, and the medial was 221% of the lateral. The displacement nephogram showed that the displacement of the medial meniscus was greater than that of the lateral meniscus except for types Ⅲ and Ⅵ knee joints. The difference between medial and lateral meniscus displacement of type Ⅲ knee joint was the largest, the lateral was 170% of the medial. In the same type of joint line obliquity (JLO), the medial and lateral stress distribution of the knee was more uniform in varus and neutral positions than in valgus position. At the same time, the distal vertex of JLO subgroup can help to reduce the uneven medial and lateral stress distribution of varus knee, but increase the uneven distribution of valgus knee.

Impact of Urban Functional Dynamics on Surface Temperature: A Case Study of Chengdu

With global warming and rapid urban development, the urban surface temperature in summer has been increasing, seriously affecting people’s work and life. The formation and changes in surface temperature are directly related to material surroundings and spatial functions. Urban construction has led to an increase in POIs (points of interest), and the POI represents the functional activity within the space to a certain extent. Therefore, this paper attempts to reproduce the process of the urban internal function development of Chengdu according to the distribution characteristics of different types of points of interest. It also delves into the influence of internal spatial functions on surface temperature in Chengdu. The results show that the surface heat values for all types of functions show a significant increase from 2009 to 2022. The rate of increase is particularly pronounced for public transportation, with temperatures increasing by an average of 0.317 °C per year. In addition, there are differences in the thermal contribution values of different functions. The residential and commercial functions have the most significant impact on surface temperature, with both accounting for more than 0.45 of all functional contribution values. Public transportation has a small thermal contribution value but shows a trend of doubling growth. The findings will provide some insights into the design of cooling in future urban planning.

Multi-Channel Fusion Decision-Making Online Detection Network for Surface Defects in Automotive Pipelines Based on Transfer Learning VGG16 Network.

Although approaches for the online surface detection of automotive pipelines exist, low defect area rates, small-sample and long-tailed data, and the difficulty of detection due to the variable morphology of defects are three major problems faced when using such methods. In order to solve these problems, this study combines traditional visual detection methods and deep neural network technology to propose a transfer learning multi-channel fusion decision network without significantly increasing the number of network layers or the structural complexity. Each channel of the network is designed according to the characteristics of different types of defects. Dynamic weights are assigned to achieve decision-level fusion through the use of a matrix of indicators to evaluate the performance of each channel's recognition ability. In order to improve the detection efficiency and reduce the amount of data transmission and processing, an improved ROI detection algorithm for surface defects is proposed. It can enable the rapid screening of target surfaces for the high-quality and rapid acquisition of surface defect images. On an automotive pipeline surface defect dataset, the detection accuracy of the multi-channel fusion decision network with transfer learning was 97.78% and its detection speed was 153.8 FPS. The experimental results indicate that the multi-channel fusion decision network could simultaneously take into account the needs for real-time detection and accuracy, synthesize the advantages of different network structures, and avoid the limitations of single-channel networks.

Nondestructive Detection of Osmotic Damage in GFRP Boat Hulls Using Active Infrared Thermography Methods

This article presents the application of infrared thermography as a nondestructive testing method (NDT) for detecting osmotic damage in glass-fiber-reinforced polymer (GFRP) and glass-reinforced polymer (GRP) boat hull structures. The aim of the conducted experiments is to explore the possibilities of applying active infrared thermography to real structures and to establish a procedure capable of filtering out anomalies caused by various thermal influences, such as thermal reflections from surrounding objects, geometry effects, and heat flow variations on the observed object. The methods used for post-processing IR signals include lock-in thermography (LT), pulse thermography (PT), pulse phase thermography (PPT), and gradient pulse phase thermography (GT). The practical application and advantages and disadvantages of infrared thermography in identifying osmotic damage in GFRP and GRP boat hulls will be illustrated through three case studies. Each case study is based on specific conditions and characteristics of different types of osmotic damage, enabling a thorough analysis of the effectiveness of the method in detecting and assessing the severity of the damage. The post-processed thermal images enable a clearer distinction between damaged and undamaged zones, improving the robustness of detection under realistic field conditions.

СИНТЕЗ СЛОВЕСНО-ХУДОЖЕСТВЕННЫХ ЖАНРОВ И ИСКУССТВ В ТВОРЧЕСТВЕ МИХАИЛА МАТУСОВСКОГО

The article is devoted to the versatility of the creative heritage of M. L. Matusovsky, known to the general public mainly as the author of the lyrics to many popular songs today (“Where does the Motherland begin?”, “At a nameless height”, “School Waltz”, etc.). In order to create a more complete idea of what types of art and their forms Matusovsky showed himself in – with the obvious predominance in his heritage of a wide range of verbal creativity, journalistic and literary-artistic – we review a) verbal-artistic works, which, in addition to lyrical poems, are presented in his literary discourse: ballad, poem, memoir prose; b) cinematographic works – documentaries in the creation of which Matusovsky took part (mainly in several guises). The main attention is paid to the consideration of the features of the documentary film, where M. L. Matusovsky is one of the screenwriters, as well as the author of the poetic text – the film poem “What are you thinking about, Soldier?” (1963). It was in this documentary-fiction film, which belongs to one of the a priori syncretic arts – cinema, that the artist’s desire to unite in the created work various methods of aesthetic understanding of the world, characteristic of different types of art: cinematic, musical, literary and artistic, was most manifested. as a result, it made it possible to more fully and diversifiedly embody the author’s figurative and value concept in the art product, and to implement the influencing function as efficiently as possible.

Microbiota in tumors: new factor influencing cancer development.

Tumor microbiota research is a new field in oncology. With the advancement of high-throughput sequencing, there is growing evidence that a microbial community exists within tumor tissue. How these bacteria access tumor cells varies, including through the invasion of mucous membranes, the bloodstream, or the gut-organ axis. Previous literature has shown that microbes promote the development and progression of cancer through various mechanisms, such as affecting the host's immune system, promoting inflammation, regulating metabolism, and activating invasion and transfer. The study of the tumor microbiota offers a new perspective for the diagnosis and treatment of cancer, and it holds the potential for the development of new diagnostic tools and therapies. The role of the tumor microbiota in the pathogenesis of cancer is becoming increasingly evident, and future research will continue to uncover the specific mechanisms of action of these microbes, potentially shedding light on new strategies and methods for cancer prevention and therapy. This article reviews the latest advancements in this field, including how intratumor microbes migrate, their carcinogenic mechanisms, and the characteristics of different types of tumor microbes as well as the application of relevant methods in tumor microbiota research and the clinical values of targeting tumor microbes in cancer therapy.

Neutron-Image Super-Resolution based on Convolutional Neural Networks and Novel Parallel Transformer

Enhancing the resolution of neutron imaging can be achieved by upgrading the hardware components of the neutron imaging system, including employing more potent neutron source systems, utilizing high-resolution detectors, and implementing superior collimation techniques. However, such improvements are frequently constrained by challenges such as high cost and limited flexibility. In this paper, a flexible and efficient single-neutron-image super-resolution network is proposed for neutron image super-resolution. We propose a novel multi-scale feature extraction network, which can extract features deeply by fusing features of different types and levels. In order to learn more context information, a novel parallel Transformer is proposed to overcome the long dependency problem of sequences. A high-frequency information enhancement network is proposed to enhance the high-frequency information of neutron image in order to address the blur problem. Quantitative and qualitative analyses of benchmark datasets and real neutron images show that the proposed network performs better on Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index (SSIM) than bicubic interpolation and other methods, and reconstructs high-resolution neutron images that are more consistent with human visual perception, highlighting its application potential in neutron images quality enhancement.

Testing relationships between multiple regional features and biogeographic processes of speciation, extinction, and dispersal.

The spatial and environmental features of regions where clades are evolving are expected to impact biogeographic processes such as speciation, extinction, and dispersal. Any number of regional features (such as elevation, distance, area, etc.) may be directly or indirectly related to these processes. For example, it may be that distances or differences in elevation or both may limit dispersal rates. However, it is difficult to disentangle which features are most strongly related to rates of different processes. Here, we present an extensible Multi-feature Feature-Informed GeoSSE (MultiFIG) model that allows for the simultaneous investigation of any number of regional features. MultiFIG provides a conceptual framework for incorporating large numbers of features of different types, including categorical, quantitative, within-region, and between-region features, along with a mathematical framework for translating those features into biogeographic rates for statistical hypothesis testing. Using traditional Bayesian parameter estimation and reversible-jump Markov chain Monte Carlo, MultiFIG allows for the exploration of models with different numbers and combinations of feature-effect parameters, and generates estimates for the strengths of relationships between each regional feature and core process. We validate this model with a simulation study covering a range of scenarios with different numbers of regions, tree sizes, and feature values. We also demonstrate the application of MultiFIG with an empirical case study of the South American lizard genus Liolaemus, investigating sixteen regional features related to area, distance, and elevation. Our results show two important feature-process relationships: a negative distance/dispersal relationship, and a negative area/extinction relationship. Interestingly, although speciation rates were found to be higher in Andean versus non-Andean regions, the model did not assign significance to Andean- or elevation-related parameters. These results highlight the need to consider multiple regional features in biogeographic hypothesis testing.

HS-SPME-GC-MS combined with relative odor activity value identify the key aroma components of flowery and fruity aroma in different types of GABA tea

Anaerobic processing is a crucial factor influencing the formation of flavor quality in Gamma-aminobutyric acid (GABA) tea. In this study, headspace solid-phase microextraction combined with gas chromatography and mass spectrometry was employed to explore the flavor characteristics of different types of GABA tea. We utilized multivariate analyses to identify at least 146 volatile components (VOCs) across 12 functional groups in the GABA tea samples via principal component analysis (PCA). At least 40 differential VOCs were screened from the GABA tea samples via orthogonal partial least squares-discriminant analysis. Subsequently, a minimum of four VOCs were identified in the GABA tea samples via the Pearson correlation coefficient combined with relative odor activity values as potential markers for flowery and fruity aromas, clarifying the impact of the VOCs on these characteristics. The results of this study provide a theoretical basis for understanding the formation of flowery and fruity flavor characteristics in GABA tea.

Numerical Simulation Study on the Stable Combustion of a 660 MW Supercritical Unit Boiler at Ultra-Low Load

To investigate the safe, stable, and economically viable operation of a boiler under ultra-low-load conditions during the deep peaking process of coal-fired units, a numerical simulation study was conducted on a 660 MW front- and rear-wall hedge cyclone burner boiler. The current research on low load conditions is limited to achieving stable combustion by adjusting the operating parameters, and few effective boiler operating parameter predictions are given for very low-load conditions, i.e., below 20%. Various burner operation modes under ultra-low load conditions were analyzed using computational fluid dynamics (CFDs) methods; this operation was successfully tested with six types of pulverized coal combustion in this paper, and fitting models for outlet flue gas temperature and NOx emissions were derived based on the combustion characteristics of different types of pulverized coal. The results indicate that under 20% ultra-low-load conditions, the use of lower burners leads to a uniform temperature distribution within the furnace, achieving a minimum NOx emission of 112 ppm and a flue gas temperature of 743 K. Coal type 3, with the highest carbon content and a calorific value of 22,440 kJ/kg, has the highest average section temperature of 1435.76 K. In contrast, coal type 1 has a higher nitrogen content, with a maximum cross-sectional average NOx concentration of 865.90 ppm and an exit NOx emission concentration of 800 ppm. The overall lower NOx emissions of coal type 3 are primarily attributed to its reduced nitrogen content and increased oxygen content, which enhance pulverized coal combustion and suppress NOx formation. The fitting models accurately capture the influence of pulverized coal composition on outlet flue gas temperature and NOx emissions. This control strategy can be extended to the stable combustion of many kinds of coal. For validation, the fitting error bar for the predicted outlet flue gas temperature based on the elemental composition of coal type 6 was 8.09%, whereas the fitting error bar for the outlet NOx emissions was only 1.45%.

Clinical analysis of 1,038 cases of odontogenic jawbone cysts

BackgroundThis study aims to analyse the clinical characteristics of different types of odontogenic jawbone cysts (OJCs) and to provide a theoretical basis for prevention and clinical treatment.MethodsData from 1,038 patients with OJCs were collected, and relevant information, such as sex, age, clinical symptoms and signs, imaging data, number of lesions, lesion location, pathological diagnosis, clinical treatment and prognosis, was statistically analysed.ResultsAccording to the World Health Organization (WHO) classification of OJCs in 2022, the highest incidence rate was observed for radicular cysts (RCs), accounting for 58.96% of the total number of cases, followed by dentigerous cysts (DCs), accounting for approximately 23.22% of cases. lateral periodontal cysts (LPCs) and calcifying odontogenic cysts (COCs) comprised the lowest number of cases. The age distribution of patients was between 4 and 89 years, and the high incidence age group was youth and middle age, accounting for 66.67% of the total number of cases. The male-to-female ratio of patients was 1.51:1, and there was a statistically significant difference between the sexes(p < 0.05).In terms of the site of incidence, odontogenic keratocysts (OKCs) were prevalent in the mandibular molar region. In addition, mandibular ramus, inflammatory collateral cysts (ICCs) and dentigerous cysts (DCs) were more common in the mandibular third molar, and radicular cysts (RCs) and calcifying odontogenic cysts (COCs) were prevalent in the maxillary anterior region. On imaging, 955 (92.0%) lesions were solitary, and 83 (8.0%) were multiple. The treatment included four types of surgery, including simple curettage, marsupialization, marsupialization followed by secondary curettage, and partial resection of the jaw, and a total of 921 patients were followed up, with a recurrence rate of 2.82%.ConclusionsOJCs are more common in males than in females, and a statistically significant difference is observed in the most prevalent types of cysts occurring at different ages and in various regions of the jawbone (p < 0.05). Early diagnosis should be made with the help of X-rays, age, location, and clinical symptoms. In addition, appropriate treatment methods should be selected, and long-term follow-up observation is needed.

Analysis and Fuzzy Neural Networks‐Based Inertia Coefficient Adjustment Strategy of Power Converters

ABSTRACTWith the development of new energy generation technology and power electronic technology, power electronic equipment occupies an increasing proportion of the power system, and its control flexibility makes the power system complicated, bringing problems such as low inertia, low damping, high harmonics, low reliability, and weak anti‐interference ability. Especially the influence of converter on inertia of power system, even causing excessive frequency fluctuations, leading to the collapse of the power system. In view of the inertia problem of converters, this article starts with the principle of converters and analyzes the inertia transmission characteristics of different types of converters in power systems by three types of control strategies. Based on the influence of the inertia parameters of converters on system frequency and power, a converter inertia target function is established, and a neural network adaptive adjustment strategy for converter inertia coefficient is proposed to achieve self‐adaptive optimization of converter output power and system frequency. The corresponding converter model is established, and the simulation circuit and control model are built by Simulink to verify the inertia transfer characteristics. The simulation results show the correctness of the relevant theories and provide theoretical support for the inertia design of high‐proportion power electronic systems.

How do urban green space attributes affect visitation and satisfaction? An empirical study based on multisource data

Urban green spaces (UGSs) are major settings of human–nature interaction and important to public well-being. Visitation and satisfaction are indicators that reflect the utilization degree of and feedback regarding UGSs. The focus of this study is to analyze the visitation and satisfaction characteristics of different types of UGSs, analyze the dominant factors affecting these indicators, and rank their importance to provide strategies for improving management. Here, 50 typical UGSs in Shanghai are selected. All-subset regression, hierarchical partitioning analysis and other methods are comprehensively used to explore the influencing factors. The results are as follows: 1) Comprehensive parks have the highest visitation rates, whereas community parks have the lowest visitation rates but the highest satisfaction rates. 2) UGS size has the greatest influence on visitation, followed by connectivity, building shape index, and edge density, with contributions of 69.35 %, 16.40 %, 8.50 %, and 5.75 %, respectively. 3) Transportation facility density and edge density have the greatest influences on satisfaction, with contributions of 51.49 % and 48.51 %, respectively. In this study, the applicability of using multisource data to analyze UGS attributes and their factors affecting visitation and satisfaction are demonstrated. Targeted strategies for constructing UGSs will help authorities plan and manage UGSs effectively.

Switch monitoring algorithm for 220 kV terminal substation startup process based on multi time scale graph model

The switch monitoring in the startup process of 220 kV terminal substation is a dynamic and changeable process, which has obvious characteristics of diversified scales in time, so as to solve the problem of switch monitoring under multivariable and multi-scale interference. The switch monitoring framework for the startup process of 220KV terminal substation is built. The process layer uses the graphic configuration software and combines the internal and external models of the substation to build the objective function for the generation of the substation graphic model. The particle swarm optimization algorithm is used to solve it to generate the optimal substation graphic model. Through the online monitoring device, the signals such as sensors, normally open and normally closed contacts are collected in real time, and the status of the switchgear is obtained through processing, the reduced half trapezoidal cloud model multivariable multi-scale sample entropy similarity tolerance criterion is used for softening treatment, and the multivariable multi-scale cloud sample entropy is determined to achieve the extraction of multiple time scale switch fault feature vectors, which are used as the input of the SE-DSCNN fault diagnosis model. Combined with the substation diagram, the switch fault identification during the startup process of the substation is realized, and the fault switch position is located. The experimental results show that the algorithm can accurately generate the substation model, which includes all the equipment in the substation, accurately describes the connection relationship and operation status of the equipment, and has high accuracy, integrity and aesthetics; The algorithm can effectively extract and analyze the MMCES entropy characteristics of different types of switch faults; The algorithm can realize the switch monitoring during the startup of substation C, and determine the fault switch and fault location.

Construction and Empirical Research of an Evaluation System for High-Quality Development of Small Towns in Guangxi Under the New Development Concept

The high-quality development of small towns in Guangxi is crucial for regional economic balance and sustainable development. This research conducts an in-depth exploration and systematic construction and validation analysis of the high-quality development of small towns in Guangxi. Guided by the new development concepts of innovation, coordination, green, openness, and sharing, a comprehensive evaluation system is established to assess the development levels of 70 small towns from 2005 to 2022. The research findings are as follows: 1. The analysis revealed significant growth in these dimensions over the study period, highlighting the unique characteristics of different types of small towns. 2. It was observed that small towns in southeastern Guangxi generally demonstrated higher development levels, while those in the northwestern regions exhibited considerable disparities, indicating regional imbalances. 3. The overall gap in the high-quality development level of small towns is gradually narrowing, but the difference is still relatively significant. 4. The findings underscore the advantages of the evaluation system developed, which effectively captures the multidimensional nature of high-quality development and serves as a robust framework for future research.

Study of functional properties of different bifurcation types of the splenic vasculature

Background. The study using numerical modeling of functional properties (conductive, distributive, pillar) of digital models of 4 types of bifurcations of the intraorgan arterial vasculature is a valuable tool to find its morphometric reference and subsequently the criterion of normality.Aim: To establish the functional properties of different types of splenic arterial bifurcations through their numerical modeling based on morphometry results.Material and Methods. Modelling was carried out on the basis of previously obtained morphometric characteristics of different types of splenic arterial bifurcations: type 1, the diameter of the parent (proximal) segment (D) is not equal to the diameters of the larger (dmax) and smaller (dmin) subsidiary branches (distal segments) D ≠ dmax ≠ dmin; type 2, D = dmax, D ≠ dmin; type 3, D ≠ dmax, dmin = dmax; type 4, D = dmax = dmin. The ANSYS Student computer software was used to calculate the values of splenic arterial bifurcation indices characterizing the conductive and support functions, and the Vasculograph computer software was used to calculate the distribution function.Results. It was found that the value of the bifurcation parameter of splenic arterial bifurcations of different types characterizing: 1) conductive function decreases in the order of type 1 complete asymmetry, type 2 lateral asymmetry, type 4 complete symmetry and type 3 unilateral symmetry; 2) the distributive function decreases in the direction of type 1 complete asymmetry, type 2 lateral asymmetry, type 3 unilateral symmetry, and type 4 complete symmetry 3) the pilar function decreases in the direction of type 1 complete asymmetry, type 2 lateral asymmetry, type 3 unilateral symmetry, and type 4 complete symmetry.Conclusion. The obtained results indicate that different types of splenic arterial bifurcations are oriented to fulfil heterogeneous functions. This should be taken into account when seeking a reference and subsequently a morphometric criterion of splenic vasculature norm, which can be used for radial diagnostics.

PATHOMORPHOLOGICAL AND PATHOHISTOLOGICAL CHARACTERISTICS OF PRIMARY VULVAR CARCINOMA

The purpose of the study was to determine pathomorphological and pathohistological characteristics of primary vulvar carcinoma. Materials, methods, and study design: A retro- and prospective comprehensive morphological study of 117 patients was conducted at Bondar Regional Cancer Research Center (Donetsk) over the period from 2002 to 2019. Out of 117 we identified 44 patients with primary vulvar cancer without previous inflammatory diseases (cancer de novo). The materials were fixed in formalin and examined using standard methods of histological staining and morphometry. Statistical analysis methods were used to process the data. Results and Discussion: The differentiated VIN type occurred in 61.2% of cases, the undifferentiated type – in 37.8%. VIN1 was characterized by basal cell hyperplasia, VIN2 – by abnormal vertical anisomorphy, VIN3 – by significant abnormal cell stratification and differentiation. Cell proliferative activity increased with VIN severity, with the highest mitotic index and nuclear-cytoplasmic ratio in VIN3. In VIN1, a positive reaction to nuclear proliferation antigen was observed in the lower third of the epithelial layer. In VIN2 and VIN3, the positive reaction covered most of the epithelium. Well-differentiated SCC (G1) was characterized by polymorphic cell complexes with a small number of pathological mitoses and apoptosis. Moderately differentiated SCC (G2) had a pronounced inflammatory reaction and necrosis, with disruption of the basement membrane. Poorly differentiated SCC (G3) demonstrated loss of vertical anisomorphy, high mitotic index and presence of tumor emboli in vessels. Conclusions: The study showed significant differences in the morphological and morphometric characteristics of different types of VIN and invasive vulvar carcinoma. The results will help to improve the diagnosis and treatment of primary vulvar cancer, especially in understanding its pathogenesis and prognostic factors.