Imperative Requirement Research Articles

Проблемные вопросы прекращения гражданства Российской Федерации вследствие совершения преступления

The article is devoted to problematic issues of termination of Russian citizenship as a result of committing a crime in connection with changes in the legislation on citizenship and law enforcement practice. The article raises the following questions: whether the decision to terminate the citizenship of the Russian Federation of a person who has committed a crime is an imperative requirement of the law; whether such a decision can be made in respect of a person whose criminal record has been expunged or expunged; if so, whether such a decision can be made in respect of persons whose criminal record has been expunged or expunged 10 years ago and more.

Decentralized food safety and authentication on cellulose paper-based analytical platform: A review.

Food safety and authenticity analysis play a pivotal role in guaranteeing food quality, safeguarding public health, and upholding consumer trust. In recent years, significant social progress has presented fresh challenges in the realm of food analysis, underscoring the imperative requirement to devise innovative and expedient approaches for conducting on-site assessments. Consequently, cellulose paper-based devices (PADs) have come into the spotlight due to their characteristics of microchannels and inherent capillary action. This review summarizes the recent advances in cellulose PADs in various food products, comprising various fabrication strategies, detection methods such as mass spectrometry and multi-mode detection, sampling and processing considerations, as well as applications in screening food safety factors and assessing food authenticity developed in the past 3 years. According to the above studies, cellulose PADs face challenges such as limited sample processing, inadequate multiplexing capabilities, and the requirement for workflow integration, while emerging innovations, comprising the use of simplified sample pretreatment techniques, the integration of advanced nanomaterials, and advanced instruments such as portable mass spectrometer and the innovation of multimodal detection methods, offer potential solutions and are highlighted as promising directions. This review underscores the significant potential of cellulose PADs in facilitating decentralized, cost-effective, and simplified testing methodologies to maintain food safety standards. With the progression of interdisciplinary research, cellulose PADs are expected to become essential platforms for on-site food safety and authentication analysis, thereby significantly enhancing global food safety for consumers.

Impact of irrigation systems on water saving and yield of greenhouse and open field cucumber production in Saudi Arabia

Water resources worldwide are limited, especially in desert areas like Saudi Arabia. Therefore, the rational and sustainable management of irrigation water supply is an imperative requirement. This research aimed to assess how different irrigation systems, such as partial root-zone drying (PRD) and regulated deficit irrigation (RDI), would affect the growth of cucumber crops. The study specifically focused on comparing the impact of these irrigation techniques when implemented with surface (S) and subsurface (SB) drip irrigation methods. The research was conducted in both controlled environments and open-field settings in central Saudi Arabia. Additionally, the study aimed to promote the adoption of RDI and PRD irrigation systems among Saudi farmers as a means to conserve essential irrigation water resources. The treatments consisted of two groups: the drip irrigation group with a single line (RDI), which includes full irrigation and deficit irrigation, and the group with the (PRD) for the root zone with two lines with the same irrigation ratios as the first group. The productivity of the RDI-S regular drip irrigation treatment was considered 100 % as the control on which the results of all treatments are measured. The results showed that in terms of irrigation technique, the PRD-SB technique had the highest productivity during the winter season in a greenhouse, with an average of 13.8 kg m−2 for all irrigation levels, while the RDI-SB technique had the highest productivity during the summer season, with an average of 16.1 kg m−2. Regarding irrigation level results, the study showed that an irrigation level of 100 % is the highest yield in all irrigation techniques, with a general average of 14.9 kg m−2 for all irrigation techniques during the winter season and 16.4 kg m−2 during the summer. The study showed that irrigation with the PRD-SB system was the most productive in the open field at all irrigation levels, with an average of 7.3 kg m−2. It could be concluded that using PRD and RDI systems for indoor and outdoor cucumber production can save irrigation water in arid regions.

Renewable energy potential in the State of Palestine: Proposals for sustainability

Renewable energy is not only a viable economic choice in Palestine, but it is also an imperative requirement to end the country's current energy crisis, which is particularly acute in the West Bank and Gaza Strip. The main focus of this study, which makes it the most thorough in its sector, is showcasing Palestine's distinct renewable energy potentials (thermal solar, PV, wind, biomass, and hydropower). The System Advisor Model software (SAM) was used to predict the power potentials for a year. The results indicate that Palestine has a significant potential for PV power generation within 1,700 kWh/kWp. Wind energy can see a considerable difference in capacity, with a mean power density in the high mountains of WB of 600 W/m2, a mean power density for all of WB of 300 W/m2, and a relatively low power density for GS of less than 100 W/m2. Options for investments in the high seas and with the nearby Arabic nations were also offered. About 1,717 GWh of energy equivalent comes from biomass resources. It is determined that the best designed system can produce 82 % of the total while only 18 % is purchased from the grid using HOMER to retrieve the optimum on-grid hybrid energy system. Furthermore, only 70.7 % of the energy produced is consumed, with the remainder being sold back to the grid. Therefore, using renewable energy sources in addition to the grid is advised to cut costs and potentially generate income. Reduce reliance on fossil fuels and combat global warming, as well.

Glycomacropeptide: A comprehensive understanding of its major biological characteristics and purification methodologies.

Glycomacropeptide (GMP) is a bioactive peptide derived from whey protein, consisting of 64 amino acids. It is a phenylalanine-free peptide, making it a beneficial dietary option for individuals dealing with phenylketonuria (PKU). PKU is an inherited metabolic disorder characterized by high levels of phenylalanine in the bloodstream, resulting from a deficiency of phenylalanine dehydrogenase in affected individuals. Consequently, patients with PKU require lifelong adherence to a low-phenylalanine diet, wherein a significant portion of their protein intake is typically sourced from a phenylalanine-free amino acid formula. GMP has several nutritional values, numerous bioactivity properties, and therapeutic effects in various inflammatory disorders. Despite all these features, the purification of GMP is an imperative requirement; however, there are no unique methods for achieving this goal. Traditionally, several methods have been used for GMP purification, such as thermal or acid treatment, alcoholic precipitation, ultrafiltration (UF), gel filtration, and membrane separation techniques. However, these methods have poor specificity, and the presence of large amounts of impurities can interfere with the analysis of GMP. More efficient and highly specific GMP purification methods need to be developed. In this review, we have highlighted and summarized the current research progress on the major biological features and purification methodologies associated with GMP, as well as providing an extensive overview of the recent developments in using charged UF membranes for GMP purification and the influential factors.

Smart cost estimation: Empirical case for extra-high voltage transmission towers

Nowadays, electricity has become an integral part of human lives. Most of our daily appliances, tools, and personal belongings are inseparable from electricity. To ensure a proper electricity distribution with an efficient transfer capability, Extra-High Voltage (EHV) transmission towers are needed. To design such a structure, it is of utmost importance to account for the cost of said tower. However, the process to estimate the cost of EHV transmission towers is both time-consuming and strenuous on human labor since a lot of consideration have to be taken. To overcome this, an imperative requirement exists for a prompt, precise, and automated tool to replace the existing manual cost estimation method. This research endeavor aims to craft a tool using support vector regression (SVR) with the capacity to prognosticate construction expenses for projects involving EHV transmission towers. The exploration of pertinent literature has enabled us to amass historical data and delineate the attributes essential for estimating costs linked to EHV transmission tower construction. The investigation delves into a comprehensive dataset spanning the past decade in Taiwan. Within this timeframe, 317 EHV transmission towers were erected between 2009 and 2019. However, 79 of these instances are excluded due to incomplete information, thereby yielding 238 viable datasets (comprising 75 % of the overall total) to underpin the development of the SVR model. By configuring the parameters to C = 0.2 and γ = 0.1, followed by 5-fold cross-validation, the resultant SVR model attains a remarkable prediction accuracy of 97.91 %, on average. As a result, the proposed SVR-based model can effectively and accurately predict the cost of constructing an EHV transmission tower project and reduce the time spent on estimation, thus contributing to the enhancement of the resilience and robustness of the transmission network system.

Abstract P18: RHBDL2 PROMOTES NON-SMALL CELL LUNG CANCER METASTASIS AND OSIMERTINIB RESISTANCE BY ACTIVATING RAS/MEK/ERK SIGNALING PATHWAY THROUGH INTERACTION WITH FGFR

Abstract Non-small cell lung cancer (NSCLC) is a highly malignant form of cancer, distinguished by prompt metastasis, restricted response to chemotherapy, and unfavorable prognosis. As a result, there is an imperative requirement to investigate novel therapeutic approaches for NSCLC. Rhomboid-like protein 2 (RHBDL2) is overexpressed in various tumor cells and is associated with poor prognosis. However, the relevance of RHBDL2 to NSCLC remains unclear. This study aims to investigate the potential role of RHBDL2 as a diagnostic and prognostic biomarker for NSCLC, as well as its biological functions and molecular mechanisms in NSCLC. We found that RHBDL2 was highly expressed in human NSCLC cells and tissues, and was significantly correlated with distant metastasis and poor survival of NSCLC patients. Gain- and loss-of-function assays showed that RHBDL2 could accelerate NSCLC metastasis in vitro and in vivo. KEGG/GO enrichment analysis identified that the function of RHBDL2 was significantly associated with the activity of RAS signaling pathway. RNA-Seq results also suggested that RHBDL2 might be involved in the activation of the RAS/MEK/ERK signaling pathway. ERK1/2 inhibitor Ravoxertinib could partially restore the metastatic ability of NSCLC cells mediated by RHBDL2. CO-IP/MS results suggested that RHBDL2 interacted with FGFR. GST-pulldown assay confirmed the above findings. RHBDL2 could directly interact with FGFR and affect its phosphorylation, and promote NSCLC cell migration by activating the downstream RAS/MEK/ERK signaling pathway. In addition, we also found that RHBDL2 was involved in osimertinib resistance through FGFR/RAS pathway. Our study results indicate that RHBDL2 promotes NSCLC cell migration and osimertinib resistance by interacting with FGFR and thereby activating the RAS/MEK/ERK signaling pathway. Moreover, it can serve as a novel diagnostic and prognostic biomarker for NSCLC patients. Citation Format: Jun Deng, Jia-jia Qin, Neng-ming Lin. RHBDL2 PROMOTES NON-SMALL CELL LUNG CANCER METASTASIS AND OSIMERTINIB RESISTANCE BY ACTIVATING RAS/MEK/ERK SIGNALING PATHWAY THROUGH INTERACTION WITH FGFR [abstract]. In: Proceedings of Frontiers in Cancer Science; 2023 Nov 6-8; Singapore. Philadelphia (PA): AACR; Cancer Res 2024;84(8_Suppl):Abstract nr P18.

Detection of myocardial infarction using Shannon energy envelope, FA-MVEMD and deterministic learning

Myocardial infarction (MI) poses a significant clinical challenge, necessitating expeditious and precise detection to mitigate potentially fatal outcomes. Current MI diagnosis predominantly relies on electrocardiography (ECG); however, it is fraught with limitations, including inter-observer variability and a reliance on expert interpretation. This study introduces an automated MI detection framework that capitalizes on hybrid signal processing methodologies and deterministic learning theory. The initial step involves the extraction of the Shannon energy envelope (SEE) and its derivative from a single-lead ECG. Integration of the SEE into the ECG’s phase portrait provides a means to capture the underlying nonlinear system dynamics. Subsequently, the application of fast and adaptive multivariate empirical mode decomposition (FA-MVEMD) yields discriminative features originating from the most energetically dominant intrinsic mode components (IMFs) within the SEE. Profound dissimilarities are discernible between ECG signals recorded from healthy subjects and those afflicted with MI. In the subsequent phase, deterministic learning theory, implemented through neural networks, is employed to facilitate the classification of ECG signals into two distinct groups. The method’s efficacy is meticulously evaluated using the PTB diagnostic ECG database, resulting in a noteworthy average classification accuracy of 99.21%\\documentclass[12pt]{minimal} \\usepackage{amsmath} \\usepackage{wasysym} \\usepackage{amsfonts} \\usepackage{amssymb} \\usepackage{amsbsy} \\usepackage{mathrsfs} \\usepackage{upgreek} \\setlength{\\oddsidemargin}{-69pt} \\begin{document}$$\\%$$\\end{document} within a tenfold cross-validation framework. In summation, the findings affirm that the proposed features not only complement conventional ECG attributes but also align closely with the underlying dynamics of the ECG system, ultimately fortifying the automatic detection of MI. The imperative requirement for early and accurate MI diagnosis is addressed through our approach, offering a robust and dependable means to fulfill this pivotal clinical need.

Improving automatic segmentation of liver tumor images using a deep learning model

Liver tumors are one of the most aggressive malignancies in the human body. Computer-aided technology and liver interventional surgery are effective in the prediction, identification and management of liver neoplasms. One of the important processes is to accurately grasp the morphological structure of the liver and liver blood vessels. However, accurate identification and segmentation of hepatic blood vessels in CT images poses a formidable challenge. Manually locating and segmenting liver vessels in CT images is time-consuming and impractical. There is an imperative clinical requirement for a precise and effective algorithm to segment liver vessels. In response to this demand, the current paper advocates a liver vessel segmentation approach that employs an enhanced 3D fully convolutional neural network V-Net. The network model improves the basic network structure according to the characteristics of liver vessels. First, a pyramidal convolution block is introduced between the encoder and decoder of the network to improve the network localization ability. Then, multi-resolution deep supervision is introduced in the network, resulting in more robust segmentation. Finally, by fusing feature maps of different resolutions, the overall segmentation result is predicted. Evaluation experiments on public datasets demonstrate that our improved scheme can increase the segmentation ability of existing network models for liver vessels. Compared with the existing work, the experimental outcomes demonstrate that the technique presented in this manuscript has attained superior performance on the Dice Coefficient index, which can promote the treatment of liver tumors.

The economic basis of a tax: the concept and the principle

The subject. The article investigates the legal content of the concept of the economic basis of a tax and the relevant principle. The reason for choosing this subject of investigation lies in the emerging practice of how the statutory principle applies which is set out in article 3(3) of the Russian Tax Code, according to which taxes and levies should have an economic basis. Purpose of the study. The article analyses the existing ideas about the economic basis of taxes, proposes and substantiates the legal definition of the concept, specifies the types of taxable economic benefit and discloses the content of the principle of the economic grounds of a tax.Methodology. The methodological framework comprises a systemic analysis of the provisions of Russian tax legislation, studying the practice of courts and administrative bodies, higher courts and opinions of experts, the historical background and the interrelation between the economic and legal aspects of taxation.Conclusions. The economic basis of a tax should be understood to mean gaining an economic benefit to which tax legislation pegs the emergence of the obligation to pay the tax. Economic benefit should be understood as a positive economic outcome. The article delves into the types of economic benefit, which includes the following: added value, profit, net profit and natural resource royalty. To impose a specific tax, the principle of economic basis of a tax means an imperative requirement for the taxpayer to have relevant economic benefit.

Dynamic Modelling, Process Control, and Monitoring of Selected Biological and Advanced Oxidation Processes for Wastewater Treatment: A Review of Recent Developments.

This review emphasizes the significance of formulating control strategies for biological and advanced oxidation process (AOP)-based wastewater treatment systems. The aim is to guarantee that the effluent quality continuously aligns with environmental regulations while operating costs are minimized. It highlights the significance of understanding the dynamic behaviour of the process in developing effective control schemes. The most common process control strategies in wastewater treatment plants (WWTPs) are explained and listed. It is emphasized that the proper control scheme should be selected based on the process dynamic behaviour and control goal. This study further discusses the challenges associated with the control of wastewater treatment processes, including inadequacies in developed models, the limitations of most control strategies to the simulation stage, the imperative requirement for real-time data, and the financial and technical intricacies associated with implementing advanced controller hardware. It is discussed that the necessity of the availability of real-time data to achieve reliable control can be achieved by implementing proper, accurate hardware sensors in suitable locations of the process or by developing and implementing soft sensors. This study recommends further investigation on available actuators and the criteria for choosing the most appropriate one to achieve robust and reliable control in WWTPs, especially for biological and AOP-based treatment approaches.

Methodological framework for developing pragmatic communication competence in English to students from vocational technical education ISCED 4

The 21st century require certain demands regarding employment on the labor market. An imperative orientation, in this context, is communication. Effective communication is an essential element in any workplace, or the current global context of the labor market requires employees the ability to communicate in a globally used language - English. Employers evaluate not only the language skills of the candidates, but also their ability to adapt to various professional communication situations: to share ideas, ask questions and answer questions appropriately, in other words they evaluate the competence of pragmatic communication in English language - an imperative requirement in the current context for the professional career. Starting from this idea, the professional-technical education has the duty to develop students’ competence of pragmatic communication in English, to be future specialists in various fields. This article presents the methodological framework for training the competence of pragmatic communication in English for students in ISCED 4 vocational technical education, which represents a scientific-didactic construct created out of theories, principles, didactic methods and learning tasks.

A Centennial Exploration of the Communist Party of China's Poverty Alleviation Through Education: A Qualitative Analysis Using NVivo

Over the cause of its ntennial history, the Communist Party of China (CPC) has been committed to the cause of poverty alleviation through education and has made great achievements in poverty reduction. Education as a fundamental means to disrupt the inter-generational transmission of poverty has played a pivotal role in this process. By conducting an extensive analysis utilizing the Nvivo qualitative analysis tool and employing content analysis methodology, this study provides a comprehensive overview of China's historical trajectory in the development of educational theories and practices for poverty alleviation. The research discerns four distinct stages within the past century: (1) the gestation stage, characterized by the implementation of universal compensatory education, (2) the initiation stage, marked by education as a catalyst for trans-formative change, (3) the transformation stage, emphasizing balanced educational development, and (4) the diversification stage, focusing on comprehensive educational development. The tasks and goals of China's education-based poverty alleviation efforts unique at each stage, and its theory and practice also face many severe problems and challenges. Therefore, the continuous enrichment and refinement of China's education-based poverty alleviation theories and practices has become an imperative requirement for meeting the demands of the evolving era.

Combining dynamic and static host intrusion detection features using variational long short-term memory recurrent autoencoder

Despite the many advantages offered by Host Intrusion Detection Systems (HIDS), they are rarely adopted in mainstream cybersecurity strategies. Unlike Network Intrusion Detection Systems, a HIDS is the last layer of defence between potential attacks and the underlying OSs. One of the main reasons behind this is its poor capabilities to adequately protect against zero-day attacks. With the rising number of zero-day exploits and related attacks, this is an increasingly imperative requirement for a modern HIDS. In this paper variational long short-term memory — recurrent autoencoder approach which improves zero-day attack detection is proposed. We have practically implemented our model using TensorFlow and evaluated its performance using benchmark ADFA-LD and UNM datasets. We have also compared the results against those from notable publications in the area.

Clinical Associated Factors of Tile B/C Type of Pelvic Ring Fractures; a Retrospective Cross-sectional study.

Pelvic ring fractures categorized under Tile Categories B and C denote partially and fully unstable fractures, respectively. This study aimed to identify the clinically associated factors of Tile B/C pelvic ring fractures. This retrospective cross-sectional study reviewed medical records from the Emergency Medicine department at Ramathibodi Hospital in Bangkok, Thailand. The study included individuals aged ≥ 15 who experienced accidents from 2012 to 2021. To investigate the associations between the clinical variables and three critical outcomes, including Tile B/C pelvic ring fractures, major vascular injuries, and the necessity for surgical or radiological interventions, multivariable logistic regression analysis was employed. A total of 198 patients were included in the study, among whom 34.8% were diagnosed with Tile B/C pelvic ring fractures. The analysis revealed several significant predictors of Tile B/C fractures, including the presence of pelvic tenderness (adjusted odds ratio [aOR] = 15.25, 95% confidence interval [CI] = 5.86-39.66, p < 0.001), and a shock index (SI) ≥1 (aOR = 4.2, 95% CI = 1.24-14.22, p = 0.021). Moreover, Tile B/C pelvic ring fractures were associated with an increased incidence of major vascular events and the imperative requirement for surgical or radiological interventions. Clinical findings of pelvic tenderness and an SI ≥1 are strong predictive clinical factors associated with Tile B/C pelvic fractures. Early diagnosis, application of an pelvic binder, provision of initial resuscitation, and prompt transportation to a definitive care facility are crucial components of management.

Innovative approaches to solar cell selection under complex intuitionistic fuzzy dynamic settings

&lt;abstract&gt; &lt;p&gt;The need to meet current energy demands while protecting the interests of future generations has driven people to adopt regulatory frameworks that promote the careful use of limited resources. Among these resources, the sun is an everlasting source of energy. Solar energy stands out as a prime example of a renewable and environmentally friendly energy source. An imperative requirement exists for precise and dependable decision-making methods for the selection of the most efficacious solar cell. We aimed to address this particular issue. The theory of complex intuitionistic fuzzy sets (CIFS) adeptly tackles ambiguity, encompassing complex problem formulations characterized by both intuitionistic uncertainty and periodicity. We introduced two aggregation operators: The complex intuitionistic fuzzy dynamic ordered weighted averaging (CIFDOWA) operator and the complex intuitionistic fuzzy dynamic ordered weighted geometric (CIFDOWG) operator. Noteworthy features of these operators were stated, and significant special cases were meticulously outlined. An updated score function was devised to address the deficiencies, identified in the current score function within the context of CIF knowledge. In addition, we devised a methodical strategy for managing multiple attribute decision-making (MADM) problems that involve CIF data by implementing the proposed operators. To demonstrate the efficacy of the formulated algorithm, we presented a numerical example involving the selection of solar cells together with a comparative analysis with several well-established methodologies.&lt;/p&gt; &lt;/abstract&gt;

Exploratory analysis of the knowledge, attitudes and perceptions of healthcare workers about arboviruses in the context of surveillance in the Republic of Guinea.

The escalating risk and contemporary occurrences of arbovirus infections prompt a critical inquiry into the ability of nations to execute efficient surveillance systems capable to detect, prevent and respond to arbovirus outbreaks. Healthcare workers (HCWs) are the major actors in the surveillance of infectious diseases with epidemic potential. The objective of this study was to evaluate the knowledge, attitudes and perceptions of HCWs regarding arboviruses in the public health facilities of Conakry, Guinea. A cross-sectional survey was conducted during the from December 27, 2022, to January 31, 2023, encompassing from public health facilities in Conakry. The data collection process encompassed various aspects, including the characteristics of health facilities, socio-demographic and professional attributes of HCWs, the information received concerning arboviruses and the sources of information, as well as a series of inquiries designed to evaluate their knowledge, attitudes and perceptions. Subsequently, scores were computed for knowledge, attitude and perception. To identify the factors influencing the knowledge, attitudes, and perceptions of HCWs regarding arboviruses, Decision Tree and Inference Conditional Tree models were used. A total of 352 HCWs participated in the study, comprising 219 from national hospitals, 72 from municipal hospitals and 61 from primary health centers. More than half of the respondents (54.3%) had never received information on arboviruses. Only 1% of the respondents had good knowledge about arboviruses, 95.7% had a negative attitude about arboviruses. Moreover, nearly 60% of the respondents had a moderate perception and 24.1% had a good perception. The analysis revealed significant associations between the knowledge and attitudes of respondents concerning arboviruses and their years of professional experience and age. This study highlights the imperative requirement for comprehensive training targeting HCWs to enhance their capacity for early case detection within healthcare facilities. Additionally, there is a crucial need for analogous studies adopting a mixed-methods approach across all healthcare regions in Guinea.

PECULIARITIES OF IMPROVEMENT OF CONDUCTING CLASSES ON «PHISIOLOGY OF ANIMALS» TO STUDENTS, FUTURE DOCTORS OF VETERINARY MEDICINE

The article is about main approaches of improvement of conducting classes on «Phisiology of Animals». The teaching process of this educational component has many features, that is why scientific and pedagogical workers constantly looking for the most effective and necessary methods of giving lessons on it to students of higher education.&#x0D; The science of physiology occupies a prominent place in the training of a doctor of veterinary medicine. Under such circumstances, the students' study of the vital activity of the animal organism and their acquisition of integral and general biological knowledge in the process of studying the educational discipline " Physiology of Animals " is quite important and useful for learning other disciplines.&#x0D; The subject of studying "Physiology of Animals" is the basic regularities of the emergence, formation and regulation of the processes of interaction of a whole organism with the environment, its behavior in different conditions of existence at different stages of growth and development, taking into account the peculiarities and evolution.Studying the fundamental patterns of biological development through the nature of physiological processes provides a foundational basis for the efficient acquisition of specialized technological disciplines and future practical activities related to the organization, breeding, and responsible use of animals in accordance with their physiological needs, as stipulated by the Law of Ukraine 'On the Protection of Animals from Cruelty.'&#x0D; Thus, in the modern stage of higher education development, the presence of diverse educational programs and services allows for obtaining a comprehensive education in veterinary medicine through new approaches to organizing the educational process and subsequently integrating student youth into European educational structures. Under such conditions, higher education in the world tends to constantly improve. This is what prompts certain reforms in veterinary education. At the same time, bringing something new and progressive to the teaching of disciplines that are already taught, in particular to physiology, is an imperative requirement of the time. In view of the above, the teaching of the educational discipline " Physiology of Animals " with the use of the latest technologies is aimed at the ultimate goal - high-quality training of highly qualified specialists.

Participatory antimicrobial stewardship: fostering patient and public engagement to counter antimicrobial resistance.

International governments defined antimicrobial stewardship (AS) as an essential ally against antimicrobial resistance (AMR). Patient and public engagement (PPE) in AS was pointed out as an imperative requirement to be embraced. We discuss PPE state of the art in AS and methodological reflections on how to achieve its effective implementation.

New Thiophenyl-pyrazolyl-thiazole Hybrids as DHFR Inhibitors: Design, Synthesis, Antimicrobial Evaluation, Molecular Modeling, and Biodistribution Studies.

The antibiotic resistance problems constitute a considerable threat to human health worldwide; thus, the discovery of new antimicrobial candidates to conquer this issue is an imperative requirement. From this view, new thiophenyl-pyrazolyl-thiazole hybrids 3-10 were synthesized and screened for their antibacterial efficiency versus Gram - and Gram + bacterial strains compared to the reference drug amoxicillin. It was noticed that the new hybrids displayed significant antibacterial efficacy versus Gram - bacteria, especially against Pseudomonas aeruginosa. Also, all the screened candidates demonstrated a noticeable antifungal effect against Candida albicans (MICs = 3.9-125 μg/mL) relative to fluconazole (MIC = 250 μg/mL). Moreover, the new hybrids were investigated for their antituberculosis potency against Mycobacterium tuberculosis (RCMB 010126). Derivatives 4c, 6b, 8b, 9b, and 10b demonstrated prominent antituberculosis efficiency (MICs = 0.12-1.95 μg/mL) compared with the reference drug isoniazid (MIC = 0.12 μg/mL). The latter derivatives were further assessed for their inhibitory potency versus M. tuberculosis DHFR enzyme. The compounds 4c, 6b and 10b presented a remarkable suppression effect with IC50 values of 4.21, 5.70, and 10.59 μM, respectively, compared to that of trimethoprim (IC50 = 6.23 μM). Furthermore, biodistribution profile using radiolabeling way revealed a perceived uptake of 131I-compound 6b into infection induced models. The docking study for the new hybrids 4c, 6b, 8b, 9b and 10b was performed to illustrate the various binding modes with Mtb DHFR enzyme. In silico ADMET studies for the most potent inhibitors 4c, 6b and 10b were also accomplished to predict their pharmacokinetic and physicochemical features.