Bacterial toxins are considered to be virulence factors due to the fact that they interfere with the normal processes of the host cell in which they are found. The interplay between the infectious processes of bacteria and the immune system is what causes this impact. In this discussion, we are going to focus on bacterial toxins that act in the extracellular environment, especially on those that impair the activity of macrophages and neutrophils. These toxins are of particular interest since they may be found in a wide variety of bacteria. We will be concentrating our efforts, in particular, on the toxins that are generated by Gram-positive and Gram-negative bacteria. These toxins are able to interact with and have an effect on the many different types of immune cells. We utilize the Shiga toxin, cholera toxin (CT), and pertussis toxin as examples of Gram-negative toxins (PT). As examples of Gram Positive toxins, we use Alpha toxin, anthrax toxin, and botulinum toxin (BONT). In total, we look at six different types of bacterial toxins. According to the findings of the study, Shiga toxins, which are associated with the production of cytokines, chemokines, and macrophages, might thus result in post-translational modification. The cholera toxin induced a mucosal response that was mediated by secretory IgA, whereas the pertussis toxin inhibited the migration of macrophages and interacted with phagocytosis. The process by which cells take in and digest foreign material is called phagocytosis. It was revealed that S. aureus bacteremia led to an increase in the number of Th17 cells, while at the same time alpha-toxin led to a decrease in the number of Th1 cells. The anthrax toxin inhibits the synthesis of cytokines and chemokines, both of which are involved in the inflammatory response. This, in turn, causes the death of macrophages by necrosis and apoptosis. When being treated with BoNT, it was found that cells produced elevated amounts of TNF and NO in a dose-dependent way. This was determined after the cells were exposed to BoNT. This was the conclusion reached.
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The recent advancements in security approaches have significantly increased the ability to identify and mitigate any type of threat or attack in any network infrastructure, such as a software-defined network (SDN), and protect the internet security architecture against a variety of threats or attacks. Machine learning (ML) and deep learning (DL) are among the most popular techniques for preventing distributed denial-of-service (DDoS) attacks on any kind of network. The objective of this systematic review is to identify, evaluate, and discuss new efforts on ML/DL-based DDoS attack detection strategies in SDN networks. To reach our objective, we conducted a systematic review in which we looked for publications that used ML/DL approach
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Rotational Piezoelectric Energy Harvesting (RPZTEH) is widely used due to mechanical rotational input power availability in industrial and natural environments. This paper reviews the recent studies and research in RPZTEH based on its excitation elements and design and their influence on performance. It presents different groups for comparison according to their mechanical inputs and applications, such as fluid (air or water) movement, human motion, rotational vehicle tires, and other rotational operational principal including gears. The work emphasises the discussion of different types of excitations elements, such as mass weight, magnetic force, gravity force, centrifugal force, gears teeth, and impact force, to show their effect
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The provision of safe water for people is a human right; historically, a major number of people depend on groundwater as a source of water for their needs, such as agricultural, industrial or human activities. Water resources have recently been affected by organic and/or inorganic contaminants as a result of population growth and increased anthropogenic activity, soil leaching and pollution. Water resource remediation has become a serious environmental concern, since it has a direct impact on many aspects of people’s lives. For decades, the pump-and-treat method has been considered the predominant treatment process for the remediation of contaminated groundwater with organic and inorganic contaminants. On the other side, this tech
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Previous studies on the synthesis and characterization of metal chelates with uracil by elemental analysis, conductivity, IR, UV-Vis, NMR spectroscopy, and thermal analysis were covered in this review article. Reviewing these studies, we found that uracil can be coordinated through the electron pair on the N1, N3, O2, or O4 atoms. If the uracil was a mono-dentate ligand, it will be coordinated by one of the following atoms: N1, N3 or O2. But if the uracil was bi-dentate ligand, it will be coordinated by atoms N1 and O2, N3 and O2 or N3 and O4. However, when uracil forms complexes in the form of polymers, coordination occurs through the following atoms: N1 and N3 or N1 and O4.
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A substantial portion of today’s multimedia data exists in the form of unstructured text. However, the unstructured nature of text poses a significant task in meeting users’ information requirements. Text classification (TC) has been extensively employed in text mining to facilitate multimedia data processing. However, accurately categorizing texts becomes challenging due to the increasing presence of non-informative features within the corpus. Several reviews on TC, encompassing various feature selection (FS) approaches to eliminate non-informative features, have been previously published. However, these reviews do not adequately cover the recently explored approaches to TC problem-solving utilizing FS, such as optimization techniques.
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Recent years have witnessed an increase in the use of composite coatings for numerous applications, including aerospace, aircraft, and maritime vessels. These materials owe this popularity surge to the superior strength, weight, stiffness, and electrical insulation they exhibit over conventional substances, such as metals. The growing demand for such materials is accompanied by the inevitable need for fast, accurate, and affordable nondestructive testing techniques to reveal any possible defects within the coatings or any defects under coating. However, typical nondestructive testing (NDT) techniques such as ultrasonic testing (UT), infrared thermography (IRT), eddy current testing (ECT), and laser shearography (LS) have failed to p
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To date, comprehensive reviews and discussions of the strengths and limitations of Remote Sensing (RS) standalone and combination approaches, and Deep Learning (DL)-based RS datasets in archaeology have been limited. The objective of this paper is, therefore, to review and critically discuss existing studies that have applied these advanced approaches in archaeology, with a specific focus on digital preservation and object detection. RS standalone approaches including range-based and image-based modelling (e.g., laser scanning and SfM photogrammetry) have several disadvantages in terms of spatial resolution, penetrations, textures, colours, and accuracy. These limitations have led some archaeological studies to fuse/integrate multip
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