МЕТОДИ ТА ЗАСОБИ ОБРОБКИ ДАНИХ В СУЧАСНИХ АВТОМАТИЗОВАНИХ СИСТЕМАХ

Introduction. In modern automated systems, data processing is crucial for ensuring efficient and accurate processes. The use of various methods and tools, such as artificial intelligence algorithms, cloud technologies and big data, enables system performance to be optimised and decision-making to be accelerated. These approaches increase productivity, reduce costs, and improve adaptability to changes in the digital environment.Goal. The aim is to analyse the methods and means of data processing in modern automated systems in order to determine their efficiency, application features and impact on process optimisation.Research objectives: The aim is to investigate and evaluate the methods and means of data processing in modern automated systems, with a view to improving their effectiveness. This will involve developing a conceptual model for managing information flows in the context of digital transformation.Research methods. The research employed literature analysis methods to study the theoretical foundations of data processing in modern automated systems. It also used comparison and generalisation methods to determine the efficiency and application features of different approaches. A systematic approach was also employed to evaluate the relationship between data processing methods and their effect on process optimisation.The results. A lack of comprehensive studies covering the synergy of machine learning methods, big data processing, and quantum computing in the context of optimising analytical processes was revealed in the studied subject area, modern standards, and the current state of scientific research in the field of automated data processing systems.This requires the establishment of a conceptual framework and the development of an integrated data processing model that takes into account the volatility of the digital environment and the evolving nature of information technology. The formation of the data processing concept in automated systems is based on a multifactor approach that includes five vector directions of information flow management: analysis of the structure and sources of big data, application of machine learning methods for classification and forecasting, optimization of distributed processing processes, implementation of streaming analytics technologies, and the use of quantum algorithms to improve analytical computations. The developed concept involves creating an adaptive system that enables real-time decision-making based on large volumes of information, considering environmental variability factors and data security. The study of data processing revealed the benefits of an integrated approach combining traditional statistical methods, deep learning algorithms, quantum optimisation models and streaming analytics technologies. A conceptual data management model for automated systems has been developed. Consisting of five interconnected blocks, it provides comprehensive data analysis and processing at various levels of digital infrastructure. These include systemic big data analysis, the application of neural network technologies for classification and forecasting, the implementation of streaming data processing algorithms, the integration of distributed computing systems and the implementation of quantum algorithms for accelerating computation. The proposed model improves the accuracy of analytical forecasts, reduces data processing time and ensures continuous information updates.Conclusions. This study examines modern data processing methods in automated systems, including statistical approaches, machine learning, distributed computing and quantum technologies. The advantages and limitations of each approach are identified, and the importance of integrating them to improve the efficiency and adaptability of such systems is emphasised. Particular attention is paid to the role of automated systems in different sectors, ranging from medicine to industry, and their effect on data-driven decision-making processes. The paper also emphasises the importance of the ethical and security aspects of data processing within the context of digital transformation. The development of a conceptual data management model is feasible and aims to support the evolution of a resilient and secure digital infrastructure.Проблема. У сучасних автоматизованих системах обробка даних відіграє ключову роль у забезпеченні ефективності та точності процесів. Використання різноманітних методів і засобів, таких як алгоритми штучного інтелекту, хмарні технології та великі дані, дозволяє оптимізувати роботу систем та прискорювати прийняття рішень. Завдяки цим підходам досягається підвищена продуктивність, зниження витрат і покращена адаптивність до змін у цифровому середовищі. Однак, не усі методи та підходи демонструють однакову ефективність при обробці таких даних, що обґрунтовує необхідність досліджень з визначення оптимальних методів чи їх поєднання для підвищення якості отриманих даних у результатів їх підготовки для подальшого використання.Мета. Аналіз методів та засобів обробки даних у сучасних автоматизованих системах для визначення їхньої ефективності, особливостей застосування та впливу на оптимізацію процесів.Завдання дослідження. На основі порівняльного аналізу відомих методів обробки масивів даних дослідити їх застосування в сучасних автоматизованих системах та визначити показник ефективності, розробки концептуальної моделі управління інформаційними потоками в умовах цифрової трансформації.Методи дослідження. У процесі дослідження використовувалися методи аналізу літературних джерел для вивчення теоретичних основ обробки даних у сучасних автоматизованих системах, а також методи порівняння та узагальнення для визначення ефективності та особливостей застосування різних підходів. Крім того, застосовувався системний підхід для оцінки взаємозв’язку між методами обробки даних та їхнім впливом на оптимізацію процесів.Результати. Досліджена предметна область, сучасні стандарти та наявний стан наукові праці у сфері автоматизованих систем та обробки даних виявили недостатню кількість та об’єми комплексних досліджень, які б охоплювали синергію методів машинного навчання, обробки великих даних та квантових обчислень у контексті оптимізації аналітичних процесів. Це створює необхідність формування концептуальної основи та розробки інтегрованої моделі обробки даних, що враховує турбулентність цифрового середовища та динаміку розвитку інформаційних технологій. Формування концепції обробки даних у автоматизованих системах базується на багатофакторному підході, що включає п’ять векторних напрямів управління інформаційними потоками: аналіз структури та джерел великих даних, застосування методів машинного навчання для класифікації та прогнозування, оптимізація процесів розподіленої обробки, впровадження технологій потокової аналітики та використання квантових алгоритмів для підвищення продуктивності аналітичних обчислень. Розроблена концепція передбачає створення адаптивної системи, яка дозволяє реалізувати оперативне прийняття рішень на основі великих обсягів інформації з урахуванням факторів змінності середовища та безпеки даних. Дослідження предметної області обробки даних визначило перевагу інтегрованих підходів, що поєднують традиційні статистичні методи, алгоритми глибокого навчання, квантові оптимізаційні моделі та технології потокової аналітики. Сформовано концептуальну модель управління даними в автоматизованих системах, яка містить п’ять блоків, пов’язаних між собою інформаційними потоками та забезпечує всебічний аналіз і обробку інформації на різних рівнях цифрової інфраструктури: системний аналіз великих даних; застосування нейромережевих технологій для класифікації та прогнозування; впровадження алгоритмів потокової обробки даних; інтеграція розподілених обчислювальних систем; імплементація квантових алгоритмів для прискорення обчислень.Висновки. У дослідженні проаналізовано сучасні методи обробки даних в автоматизованих системах, зокрема статистичні підходи, машинне навчання, розподілені обчислення та квантові технології. Визначено переваги й обмеження кожного з підходів, а також підкреслено необхідність їх інтеграції для підвищення ефективності та адаптивності систем. Особлива увага приділена ролі автоматизованих систем у різних сферах –  від медицини до промисловості – та їхньому впливу на прийняття рішень на основі даних. У роботі також наголошено на важливості етичних та безпекових аспектів обробки інформації в умовах цифрової трансформації. Обґрунтовано доцільність створення концептуальної моделі управління даними, яка сприятиме розвитку стійкої та безпечної цифрової інфраструктури

Human mucosal associated invariant T cells detect bacterially infected cells

Control of infection with Mycobacterium tuberculosis (Mtb) requires Th1-type immunity, of which CD8+ T cells play a unique role. High frequency Mtb-reactive CD8+ T cells are present in both Mtb-infected and uninfected humans. We show by limiting dilution analysis that nonclassically restricted CD8+ T cells are universally present, but predominate in Mtbuninfected individuals. Interestingly, these Mtb-reactive cells expressed the Va7.2 T-cell receptor (TCR), were restricted by the nonclassical MHC (HLA-Ib) molecule MR1, and were activated in a transporter associated with antigen processing and presentation (TAP) independent manner. These properties are all characteristics of mucosal associated invariant T cells (MAIT), an "innate" T-cell population of previously unknown function. These MAIT cells also detect cells infected with other bacteria. Direct ex vivo analysis demonstrates that Mtb-reactive MAIT cells are decreased in peripheral blood mononuclear cells (PBMCs) from individuals with active tuberculosis, are enriched in human lung, and respond to Mtb-infected MR1-expressing lung epithelial cells. Overall, these findings suggest a generalized role for MAIT cells in the detection of bacterially infected cells, and potentially in the control of bacterial infection. © 2010 Gold et al

Immunopathogenesis of primary biliary cirrhosis: an old wives' tale

Primary biliary cirrhosis (PBC) is a cholestatic liver disease characterised by the autoimmune destruction of the small intrahepatic bile ducts. The disease has an unpredictable clinical course, but may progress to fibrosis and cirrhosis. Although medical treatment with urseodeoxycholic acid is largely successful, some patients may progress to liver failure requiring liver transplantation. PBC is characterised by the presence of disease specific anti-mitochondrial (AMA) antibodies, which are pathognomonic for PBC development. The disease demonstrates an overwhelming female preponderance and virtually all women with PBC present in middle age. The reasons for this are unknown; however several environmental and immunological factors may be involved. As the immune systems ages, it become less self tolerant, and mounts a weaker response to pathogens, possibly leading to cross reactivity or molecular mimicry. Some individuals display immunological changes which encourage the development of autoimmune disease. Risk factors implicated in PBC include recurrent urinary tract infection in females, as well as an increased prevalence of reproductive complications. These risk factors may work in concert with and possibly even accelerate, immune system ageing, contributing to PBC development. This review will examine the changes that occur in the immune system with ageing, paying particular attention to those changes which contribute to the development of autoimmune disease with increasing age. The review also discusses risk factors which may account for the increased female predominance of PBC, such as recurrent UTI and oestrogens

Individual Human Brain Areas Can Be Identified from Their Characteristic Spectral Activation Fingerprints

The human brain can be parcellated into diverse anatomical areas. We investigated whether rhythmic brain activity in these areas is characteristic and can be used for automatic classification. To this end, resting-state MEG data of 22 healthy adults was analysed. Power spectra of 1-s long data segments for atlas-defined brain areas were clustered into spectral profiles (“fingerprints”), using k-means and Gaussian mixture (GM) modelling. We demonstrate that individual areas can be identified from these spectral profiles with high accuracy. Our results suggest that each brain area engages in different spectral modes that are characteristic for individual areas. Clustering of brain areas according to similarity of spectral profiles reveals well-known brain networks. Furthermore, we demonstrate task-specific modulations of auditory spectral profiles during auditory processing. These findings have important implications for the classification of regional spectral activity and allow for novel approaches in neuroimaging and neurostimulation in health and disease

Human Innate Mycobacterium tuberculosis–Reactive αβTCR+ Thymocytes

The control of Mycobacterium tuberculosis (Mtb) infection is heavily dependent on the adaptive Th1 cellular immune response. Paradoxically, optimal priming of the Th1 response requires activation of priming dendritic cells with Th1 cytokine IFN-γ. At present, the innate cellular mechanisms required for the generation of an optimal Th1 T cell response remain poorly characterized. We hypothesized that innate Mtb-reactive T cells provide an early source of IFN-γ to fully activate Mtb-exposed dendritic cells. Here, we report the identification of a novel population of Mtb-reactive CD4− αβTCR+ innate thymocytes. These cells are present at high frequencies, respond to Mtb-infected cells by producing IFN-γ directly ex vivo, and display characteristics of effector memory T cells. This novel innate population of Mtb-reactive T cells will drive further investigation into the role of these cells in the containment of Mtb following infectious exposure. Furthermore, this is the first demonstration of a human innate pathogen-specific αβTCR+ T cell and is likely to inspire further investigation into innate T cells recognizing other important human pathogens

Proton beam therapy in repeat irradiation of recurrent head and neck tumors: analysis of short-term results

Introduction. Recurrence of head and neck tumors occurs in 50 % of cases and usually has locoregional character. Due to the characteristics of dose distribution, proton beam therapy is a promising treatment option for patients with recurrences of tumors in this location who previously underwent radiation therapy.Aim. To evaluate the effectiveness and tolerability of repeat irradiation using active scanning proton beam therapy in patients with recurrent head and neck tumors who previously underwent radiation therapy.Materials and methods. Between November of 2015 and December of 2020, 40 patients with locoregional recurrence of head and neck tumors underwent treatment using active scanning proton beam therapy at the A. F . Tsyb Medical Radiological Research Center – branch of the National Medical Research Radiological Center. Median cumulative dose of primary irradiation was 64.5 Gy. Median time between primary and repeat irradiation was 35.7 months, mean irradiated volume of the repeat course was 94.5 cm3. Proton beam therapy was performed using standard mode (2 isoGy) and accelerated hypofractionation (2.4 isoGy / 3 isoGy) with mean equivalent cumulative dose of 56.4 Gy (α / β = 10). Radiation toxicity was evaluated using the Radiation Therapy Oncology Group European (RTOG) / Organization for Research and Treatment of Cancer (EORTC) scale.Results. Treatment response was achieved in 34 (85 %) patients: in 17 (42.5 %) patients, stable disease was observed; in 10 (25 %) patients, partial response was observed; and in 7 (17.5 %) patients, complete response was observed. In 6 (15 %) cases, disease progression was diagnosed at first follow-up examination. One- and two-year locoregional control, progression-free survival and overall survival were 58.4 / 19.8; 44.5 / 19.8 and 82.3 / 38.8 % respectively with median follow-up duration of 14.2 months. Median survival was 19.5 months. Grade III and above early radiation toxicity was observed in 3 (7.5 %) patients. In total, 6 (15 %) cases of grade III complications and 2 (5 %) episodes of carotid artery rupture leading to death were observed. Overall frequency of complications of grade III and higher was 20 %.Conclusion. Repeat irradiation using proton beam therapy can be considered an effective and safe treatment method for patients with recurrent head and neck tumors. Dosimetric and radiobiological benefits of proton beams allow to achieve balance between high doses and radiation exposure in previously irradiated tissues

An increased risk of urinary tract infection precedes development of primary biliary cirrhosis

BACKGROUND: Primary Biliary Cirrhosis is known to be associated with Urinary Tract Infections (UTIs), but whether these precede or follow the liver disease is unclear. We have therefore attempted to determine whether UTIs are more common in people with Primary Biliary Cirrhosis (PBC) prior to their diagnosis.METHODS: We conducted a case control study in the General Practice Research Database. All cases of PBC first recorded at least one year after entry to the dataset were selected along with up to 10 controls matched for age, sex. A second unmatched control group who had Chronic Liver Diseases but not PBC were chosen. The main exposures studied were the occurrence of Urinary tract infections and pyelonephritis at least one or at least five years before diagnosis. We also performed an analysis restricted to those younger than 55 at diagnosis, as we hypothesized the relationship to be stronger in the younger age group.RESULTS: PBC is associated with UTI prior to diagnosis, OR 1.50 (CI 1.26-1.78), which was similar 5 years prior to diagnosis and after adjusting for smoking. The strongest relationships were observed in pyelonephritis exposures five years before diagnosis in cases under 55 years: adjusted odds ratios were 2.60 (1.02-6.63) in comparison with matched general population controls and adjusted odds ratios were OR 2.45 (1.02-5.59) in the comparison with chronic liver disease controls.CONCLUSIONS: We found that the association between urosepsis and PBC is specific to this disease and precedes the diagnosis of PBC in a manner not previously observed in human data. This is consistent with a causal relationship.</p

Distal Xq duplication and functional Xq disomy

Distal Xq duplications refer to chromosomal disorders resulting from involvement of the long arm of the X chromosome (Xq). Clinical manifestations widely vary depending on the gender of the patient and on the gene content of the duplicated segment. Prevalence of Xq duplications remains unknown. About 40 cases of Xq28 functional disomy due to cytogenetically visible rearrangements, and about 50 cases of cryptic duplications encompassing the MECP2 gene have been reported. The most frequently reported distal duplications involve the Xq28 segment and yield a recognisable phenotype including distinctive facial features (premature closure of the fontanels or ridged metopic suture, broad face with full cheeks, epicanthal folds, large ears, small and open mouth, ear anomalies, pointed nose, abnormal palate and facial hypotonia), major axial hypotonia, severe developmental delay, severe feeding difficulties, abnormal genitalia and proneness to infections. Xq duplications may be caused either by an intrachromosomal duplication or an unbalanced X/Y or X/autosome translocation. In XY males, structural X disomy always results in functional disomy. In females, failure of X chromosome dosage compensation could result from a variety of mechanisms, including an unfavourable pattern of inactivation, a breakpoint separating an X segment from the X-inactivation centre in cis, or a small ring chromosome. The MECP2 gene in Xq28 is the most important dosage-sensitive gene responsible for the abnormal phenotype in duplications of distal Xq. Diagnosis is based on clinical features and is confirmed by CGH array techniques. Differential diagnoses include Prader-Willi syndrome and Alpha thalassaemia-mental retardation, X linked (ATR-X). The recurrence risk is significant if a structural rearrangement is present in one of the parent, the most frequent situation being that of an intrachromosomal duplication inherited from the mother. Prenatal diagnosis is performed by cytogenetic testing including FISH and/or DNA quantification methods. Management is multi-specialist and only symptomatic, with special attention to prevention of malnutrition and recurrent infections. Educational and rehabilitation support should be offered to all patients

Identification of De Novo Copy Number Variants Associated with Human Disorders of Sexual Development

Disorders of sexual development (DSD), ranging in severity from genital abnormalities to complete sex reversal, are among the most common human birth defects with incidence rates reaching almost 3%. Although causative alterations in key genes controlling gonad development have been identified, the majority of DSD cases remain unexplained. To improve the diagnosis, we screened 116 children born with idiopathic DSD using a clinically validated array-based comparative genomic hybridization platform. 8951 controls without urogenital defects were used to compare with our cohort of affected patients. Clinically relevant imbalances were found in 21.5% of the analyzed patients. Most anomalies (74.2%) evaded detection by the routinely ordered karyotype and were scattered across the genome in gene-enriched subtelomeric loci. Among these defects, confirmed de novo duplication and deletion events were noted on 1p36.33, 9p24.3 and 19q12-q13.11 for ambiguous genitalia, 10p14 and Xq28 for cryptorchidism and 12p13 and 16p11.2 for hypospadias. These variants were significantly associated with genitourinary defects (P = 6.08×10−12). The causality of defects observed in 5p15.3, 9p24.3, 22q12.1 and Xq28 was supported by the presence of overlapping chromosomal rearrangements in several unrelated patients. In addition to known gonad determining genes including SRY and DMRT1, novel candidate genes such as FGFR2, KANK1, ADCY2 and ZEB2 were encompassed. The identification of risk germline rearrangements for urogenital birth defects may impact diagnosis and genetic counseling and contribute to the elucidation of the molecular mechanisms underlying the pathogenesis of human sexual development

HCV+ Hepatocytes Induce Human Regulatory CD4+ T Cells through the Production of TGF-β

Background: Hepatitis C Virus (HCV) is remarkably efficient at establishing persistent infection and is associated with the development of chronic liver disease. Impaired T cell responses facilitate and maintain persistent HCV infection. Importantly, CD4 + regulatory T cells (Tregs) act by dampening antiviral T cell responses in HCV infection. The mechanism for induction and/or expansion of Tregs in HCV is unknown. Methodology/Principal Findings: HCV-expressing hepatocytes were used to determine if hepatocytes are able to induce Tregs. The infected liver environment was modeled by establishing the co-culture of the human hepatoma cell line, Huh7.5, containing the full-length genome of HCV genotype 1a (Huh7.5-FL) with activated CD4 + T cells. The production of IFN-c was diminished following co-culture with Huh7.5-FL as compared to controls. Notably, CD4 + T cells in contact with Huh7.5-FL expressed an increased level of the Treg markers, CD25, Foxp3, CTLA-4 and LAP, and were able to suppress the proliferation of effector T cells. Importantly, HCV + hepatocytes upregulated the production of TGF-b and blockade of TGF-b abrogated Treg phenotype and function. Conclusions/Significance: These results demonstrate that HCV infected hepatocytes are capable of directly inducing Tregs development and may contribute to impaired host T cell responses