DNA methylation is one of the main epigenetic mechanisms in cancer development and progression. Aberrant DNA methylation of CpG islands within promoter regions contributes to the dysregulation of various tumor suppressors and oncogenes; this leads to the appearance of malignant features, including rapid proliferation, metastasis, stemness, and drug resistance. The discovery of two important protein families, DNA methyltransferases (DNMTs) and Ten-eleven translocation (TET) dioxygenases, respectively, which are responsible for deregulated transcription of genes that play pivotal roles in tumorigenesis, led to further understanding of DNA methylation-related pathways. But how these enzymes can target specific genes in different malignancies;

Thyroid 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

Water quality planning relies on Biochemical Oxygen Demand BOD. BOD testing takes five days. The Particle Swarm Optimization (PSO) is increasingly used for water resource forecasting. This work designed a PSO technique for estimating everyday BOD at Al-Rustumiya wastewater treatment facility inlet. Al-Rustumiya wastewater treatment plant provided 702 plant-scale data sets during 2012-2022. The PSO model uses the daily data of the water quality parameters, including chemical oxygen demand (COD), chloride (Cl^-), suspended solid (SS), total dissolved solids (TDS), and pH, to determine how each variable affects the daily incoming BOD. PSO and multiple linear regression (MLR) findings are compared, and their perfor

نظرة عامة: تُعرَّف المادة أو العامل الذي يمكن أن يؤثر على الحمض النووي أو الكروموسومات على أنه سم جيني. قد يؤدي تلف الحمض النووي في الخلية الجسدية إلى حدوث طفرة جسدية ، والتي قد تحفز التحول الخبيث ، في حين أن الضرر الذي يلحق بالخلية الجرثومية قد يؤدي إلى تغيير خاصية وراثية (طفرة في السلالة الجرثومية) (سرطان). أحد الأحماض الدهنية الأحادية غير المشبعة الأحادية غير الأساسية هو حمض البالميتوليك. بعد حمض الأوليك

Myelosuppression is a serious disease that is related to the malfunction of blood cells production that leads to cytopenia which is the most serious hematologic toxicity of cancer chemotherapies including cyclophosphamide, which is a strong oxazaphosphorine [a nitrogen mustard alkylating agent] that can be used alone or combined with other chemotherapeutic agents for the treatment of different malignant diseases. It induces severe bone marrow suppression by damaging hematopoietic stem cells through the generation of oxidative stress. Fisetin is a hydrophobic polyphenolic compound with a wide range of pharmacological properties such as antioxidant, anti-inflammatory, antimicrobial, osteoprotective, antidiabetic, and anti-carcinogenic

Erosion and deposition are natural phenomena in many estuaries that can cause morphological changes, leading to navigation and offshore structure problems. Many previous studies have focused on investigating the morphological changes of estuaries depending on different parameters and their combined effects with erosion and deposition processes, such as maximum flow amplitude, waves, currents, tidal flow, storms, rising sea elevation, maximum turbidity, salinity, and bed roughness height as input parameters. These studies are based on field measurements and numerical simulations by using topographic surveys, soil samples, satellite images, geological data, and bathymetric maps with the aid of ArcGIS. Some of these studies examine the

Several stress-strain models were used to predict the strengths of steel fiber reinforced concrete, which are distinctive of the material. However, insufficient research has been done on the influence of hybrid fiber combinations (comprising two or more distinct fibers) on the characteristics of concrete. For this reason, the researchers conducted an experimental program to determine the stress-strain relationship of 30 concrete samples reinforced with two distinct fibers (a hybrid of polyvinyl alcohol and steel fibers), with compressive strengths ranging from 40 to 120 MPa. A total of 80% of the experimental results were used to develop a new empirical stress-strain model, which was accomplished through the application of the parti