Background: The transcriptional control of various cell types, especially in the development or functioning of immune system cells involved in either promoting or inhibiting the immune response against cancer, is significantly influenced by DNA or RNA methylation. Multifaceted interconnections exist between immunological or cancer cell populations in the tumor's microenvironment (TME). TME alters the fluctuating DNA (as well as RNA) methylation sequences in these immunological cells to change their development into pro- or anti-cancer cell categories (such as T cells, which are regulatory, for instance). Objective: This review highlights the impact of DNA and RNA methylation on myeloid and lymphoid cells, unraveling their intricate

الخلفية: العقدية المقيحة المعروفة أيضًا باسم ""(GAS) هي احدى مسببات الأمراض ذات الأهمية الصحية العامة، حيث تصيب 18.1 مليون شخص في جميع أنحاء العالم وتقتل 500000 شخص كل عام. الهدف: حددت هذه المراجعة المقالات المنشورة حول عوامل الخطر واستراتيجيات الوقاية والسيطرة لأمراض المكورات العقدية. المواد والأساليب: تم إجراء بحث منهجي لتحديد الأوراق المنشورة على قواعد البيانات الإلكترونية Web of Science و PubMed و Scopus و Google Scholar في مح

Mannich base is a versatile compound that can be easily modified to introduce different functional groups, allowing for the creation diverse selection of items with varying features. Additionally, the Mannich reaction is a valuable tool in organic synthesis, due to the fact it provides an effortless and efficient approach for synthesizing C-N bonds. Overall, The Mannich base and even its derivatives are essential in many aspects of chemistry and its complexes are in the pharmaceutical industry. Studies have revealed that it shows good anti-cancer, anti-mycobacterial, remarkable anti-HIV, anti-tubercular, anti-convulsant, anti-fungal, antiviral, antitumor, cytotoxic activities and in industrial applications such as in the creation of polymer

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.

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

Early detection of brain tumors is critical for enhancing treatment options and extending patient survival. Magnetic resonance imaging (MRI) scanning gives more detailed information, such as greater contrast and clarity than any other scanning method. Manually dividing brain tumors from many MRI images collected in clinical practice for cancer diagnosis is a tough and time-consuming task. Tumors and MRI scans of the brain can be discovered using algorithms and machine learning technologies, making the process easier for doctors because MRI images can appear healthy when the person may have a tumor or be malignant. Recently, deep learning techniques based on deep convolutional neural networks have been used to analyze med