Background: Euonymus japonicus is one species of celastraceous family used as a decorative plant and in traditional Chinese medicine. The lack of information about the main active constituents and the possible biological activities of Iraqi Euonymus japonicus leaves is considered a motivation to start this in vitro study

Objectives: to identify the phytochemical components and to evaluate antioxidant and antimicrobial activities

 Material and Methods: The chemical composition of Iraqi Euonymus japonicus leaves was identified and analyzed using the Reversed-Phase High-Performance Liquid Chromatography approach and the antioxidant properti

Global concerns are rising due to complications associated with the use of chemical agents and antibiotic resistance. Consequently, research focus has shifted towards the quest for effective agents of biological origin. The aim of the present study was to assess the antioxidant and antimicrobial potentials of aqueous and organic extracts derived from various parts of Alcea kurdica. Different parts of A. kurdica were obtained and prepared into leaf, flower and root powders. The powders were extracted with aqueous and organic solvents. The antimicrobial activity of these extracts was assessed against bacterial pathogens using the agar well-diffusion assay. Additionally, the antioxidant effects of the extracts were evaluated using the

Background : the major focus of respiratory cytology is the diagnosis of lung cancer , carcinoma of the lung is now reported to be the most commonly diagnosed non- Cutaneous malignancy in the world. Iraq has faced the increase in incidence of this lethal type of cancer. Sputum cytology is a convenient method of screening and diagnosing primary epithelial tumor of the lung which is of many types include fresh smear ,Sacccomanno smear, and mailing container method.
Methods : Sputum cytological study was done on 50 patients suspected to have pulmonary carcinoma prepared by fresh smear method ,Saccomanno method ,and mailing container
method.One, two,or three samples taken from each patient.Slides were prepared

Metal and metal oxide NPs have shown to be perfectly synthesized by using plant extracts with high efficiency, low cost and low toxicity. Our goal was to synthesize ZnO NPs by using an extract of pomegranate seeds and investigate the anticorrosion, antimicrobial and antioxidant properties of the synthesized ZnO NPs. The results have shown that the use of pomegranate in the green synthesis of ZnO NPs gave a good yield, with a low cost and non-toxic approach. The electrophoretic deposition (EPD) was used to coat stainless steel (S.S) by synthesized ZnO NPs in an alcoholic solution at room temperature producing a good coating against corrosion. The corrosion properties were investigated in a saline solution and a temperature range of (293–32

The antioxidant and antibacterial activities of ethanolic extract and phenolic compounds extract of Lemon balm (Melissa officinalis) and Oregano (Oreganum vulgare) plants were studied; the phenolic content and the relationship between these compounds and the above activities were also investigated. The results showed that the Lemon balm had the highest phenolic content (56.5% mg g) and the phenolic content of Oregano was twice lower than Lemon balm. Lemon balm has the highest antioxidant activity which causes lipid peroxidation inhibition activity of linoleic acid (90.5%), this activity was more than ?-tocopherole antioxidant activity (79.3 %). It was found that the main source of antioxidant activity o

In this research, the concentration of radon gas has been calculated in the classrooms of schools in Diyala Governorate by using the nuclear track detector (CR-39), which was one of the organic solid-state nuclear detectors (SSNTDs). After calculating the radon gas concentration, the lung cancer cases were calculated. The results showed that the lowest value was found in (Alshumue) school (4.753) people. In contrast, the highest value was found in (Habhib) school (20.421). The average values of lung cancer cases in Diyala governorate were equal to (9.319) per person. The results showed that the number of lung cancer cases per year per million persons in Diyala Governorate schools was below the allowed limit from (ICRP) agency (170-230) p

Lung cancer, similar to other cancer types, results from genetic changes. However, it is considered as more threatening due to the spread of the smoking habit, a major risk factor of the disease. Scientists have been collecting and analyzing the biological data for a long time, in attempts to find methods to predict cancer before it occurs. Analysis of these data requires the use of artificial intelligence algorithms and neural network approaches. In this paper, one of the deep neural networks was used, that is the enhancer Deep Belief Network (DBN), which is constructed from two Restricted Boltzmann Machines (RBM). The visible nodes for the first RBM are 13 nodes and 8 nodes in each hidden layer for the two RBMs. The enhancer DBN was tr

     Thyme essential oil (TEO) was extracted from dried leaves of Thymus vulgaris. The air-dried aerial parts of the plant produced 1.0% yield of TEO. The detection of this essential oil’s compounds was performed by GC-MASS. The cytotoxic activity of TEO was evaluated against two human cancer cell lines, namely HeLa (human epithelial cervical cancer) and MCF-7 (human breast carcinoma). Cells grown in 96 multi-well plates were treated with six concentrations of EO (6.25, 12.5, 25, 50, 100, 200 ppm) and incubated at 37 °C for 72 hrs. Cancer cell lines elicited various degrees of sensitivity to the cytotoxic effect of essential oil. The TEO exhibited significant differences (p≤ 0.01) between the effects of

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

Toxicity with advanced glycation end products (AGEs) is a major problem in uremic patients. Treatment with peritoneal dialysis (PD) exacerbates AGE formation as a result of bioincompatibility of the conventional peritoneal dialysis fluid (PDF). The presence of glucose degradation products (GDPs) in PDF is the main cause of its bioincompatibility. Carnosine is an endogenous dipeptide with a powerful antiglycation/antioxidant activity. In an attempt to improve PDF biocompatibility, we evaluated the effect of carnosine in human peritoneal mesothelial cells (HPMC) incubated with PDF or GDPs in vitro. Methods: HPMC were incubated for short or prolonged time with PDF in the presence or absence of carnosine. Similarly, HPMC were incubated in the s