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 role in immune response orchestration within both oncological and non-oncological milieus. Deciphering this complex transcriptional regulation holds promise for identifying and demonstrating therapeutic avenues that take advantage of the modulation of DNA and RNA methylation with the goal of alleviating the number of cancer-related morbidity and mortality cases. Conclusion: While more research is required towards fully understanding the effectiveness of epigenetic-based treatments aimed at tumor as well as immune cell populations, there is compelling proof that indicates that they will be successful in slowing the advancement of malignancy as well as lowering cancer-related complications as well fatalities.
Background: Tumor necrosis factor-alpha (TNF-α) and interleukins play important roles in the pathogenesis of rheumatoid arthritis (RA). Genetic research has been employed to find many of the missing connections between genetic risk variations and causal genetic components. Objective: The goal of this study is to look at the genetic variations of TNF-α and interleukins in Iraqi RA patients and see how they relate to disease severity or response to biological therapy. Method: Using specific keywords, the authors conducted a systematic and comprehensive search to identify relevant Iraqi studies examining the genetic variations of TNF-α and interleukins in Iraqi RA patients and how they relate to disease severity or response to biolo
... Show MoreGenetic polymorphisms of genes whose products are responsible for activities, such as xenobiotic metabolism, mutagen detoxification and DNA-repair, have been predicted to be associated with the risk of developing lung cancer (LC). The association of LC with tobacco smoking has been extensively investigated, but no studies have focused on the Arab ethnic- ity. Previously, we examined the association between genetic polymorphisms among Phase I and Phase II metabolism genes and the risk of LC. Here, we extend the data by examining the correlation of OGG1 Ser326Cys combined with CYP1A1 (Ile462Val and MspI) and GSTP1 (Ile105Val and Ala103Val) polymorphisms with the risk of LC. Polymerase chain reaction- restriction fragment length polymorphism (
... Show MoreThe effect of Low-Level Laser (LLL) provided by green semiconductor laser with an emission wavelength of 532 nm on of human blood of people with brain and prostate cancer has been investigated. The effect of LLL on white blood cell (WBC), NEUT, LYMPH and MONO have been considered. Platelet count (PLT) has also been considered in this work. 2 ml of blood sample were irradiating by a green laser of the dose of 4.8 J/cm2. The results suggest a potential effect of LLL on WBC, PLT, NEUT, LYMPH, and MONO of people with brain and prostate cancer Key words: white blood cell , platelet , low-level laser therapy
في هذا البحث تم تحضير المركبات المعدنية الجديدة لأيونات البلاتين (الرباعي) و الذهب (الثلاثي) مع ليكاند قاعدة مانخ جديد مشتق من السيبروفلوكساسين . تم استخدام المعقدات بعد ذلك كمصدر لتحضير جزيئات عن طريق ترسيب المعقدات على مسام دقائق السيليكا النانوية. Si/Au2O3 Si/PtO2 تم تشخيص الليكاند و معقداته
... Show MoreThyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise
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