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

Amygdalin (d-Mandelonitrile 6-O-β-d-glucosido-β-d-glucoside) and its semi synthetic product is Laetrile ( also called vitamin B17): a natural cyanogenic glycoside occurring in the seeds of some edible plants, such as bitter almonds and peaches. Early in the 19th century, Amygdalin was first isolated in 1830 by two French chemists, Robiquet and Boutron-Charlard, as active components in various fruit pits and raw nuts. However, the systematized study of vitamin B17 started when chemist Bohn (1802) discovered that a hydrocyanic acid is released during distillation of the water from bitter almonds. The various pharmacological effects of Laetrile include antiatherogenic, activity in renal fibrosis, pulmonary fibrosis, immune regulation, ant

KE Sharquie, AA Noaimi, Journal of the Saudi Society of Dermatology & Dermatologic Surgery, 2012 - Cited by 36

Problem: Cancer is regarded as one of the world's deadliest diseases. Machine learning and its new branch (deep learning) algorithms can facilitate the way of dealing with cancer, especially in the field of cancer prevention and detection. Traditional ways of analyzing cancer data have their limits, and cancer data is growing quickly. This makes it possible for deep learning to move forward with its powerful abilities to analyze and process cancer data. Aims: In the current study, a deep-learning medical support system for the prediction of lung cancer is presented. Methods: The study uses three different deep learning models (EfficientNetB3, ResNet50 and ResNet101) with the transfer learning concept. The three models are trained using a

The main aim of this study was to molecular identification and determine the antagonistic impact of rhizosphere Trichoderma spp. against some phytopathogenic fungi, including (Magnaporthe grisea) pyricularia oryzae, Rhizoctonia solani and Macrophomina phasolina. Four Trichoderma isolates were isolated from rhizosphere soils of the different host plants in different locations of Egyptian governorates. The morphological characterization of isolated Trichoderma as well as using of (ITS1-5.8S-ITS2) ribosomal gene sequence acquisition and data analyses. By comparing the results of DNA sequences of ITS region, the fungi represented one isolate were positively identified as T. asperellum (1 isolate T1) and one as T. longibrachiatum (1 isolate T2)

Spinach, Spinacia oleracea L is a popular vegetable belonging to the family Chenopodiaceae. This study was concerned with extraction of compounds in Iraqi spinach leaves, preliminary phytochemical evaluation, identification of two biological important flavonols, quercetin and kaempferol in spinach leaves and evaluation of the protective effect of aqueous spinach extract on methotrexate (MTX) induced hepatotoxicity in rats. The percentage yield of extraction procedure, identification of spinach by chemical tests and identification of flavonols by thin layer chromatography (TLC) and High performance liquid chromatography (HPLC) were fully described in this study. The results indicate that the percentage of quarce

Over the past few decades, the health benefits are under threat as many commonly used antibiotics have become less and less effective against certain illnesses not only because many of them produce toxic reactions but also due to the emergence of drug-resistant bacteria. The clinical use of a combination of antibiotic therapy for Pseudomonas aeruginosa infections is probably more effective than monotherapy. The present study aims to estimate the antibacterial and antibiofilm activity of Conocarpus erectus leaves extracts against multi-drug resistant P. aeruginosa isolated from different hospitals in Baghdad city. One hundred fifty different clinical specimens were collected from patients from September 2021 to January 2022. All samples were

Purpose: To compare the antibacterial-enhancing efficacy of aloe vera and honey in salicylic acid topical formulations against acne. Method: Six formulations containing 5 % salicylic acid were developed as creams and gels as follows: Formulations S, V and H were creams containing salicylic acid alone (S), salicylic acid with 28 % aloe vera (V), and salicylic acid with 10 % honey (H). Formulations J, M, and B were gels containing salicylic acid alone (J), salicylic acid with aloe vera 20 % (M) and salicylic acid with 12 % honey (B). Each formula was evaluated for colour, odour, pH, viscosity, spreadability, and stability under different temperatures (25, 30, and 60oC) and times (1 hour, 1 day, and 1 week). Furthermore, antibacterial