Apium graveolens has been utilized for a multitude of purposes due to its diverse pharmacological characteristics. On the other hand, little is known about how the fatty acids (saturated and unsaturated) terpenes and steroids found in Iraqi Apium graveolens affect the human cancer cells. The purpose of this study was to examine the effects of Iraqi Apium graveolens petroleum ether extract on the human prostate cancer cell line (PC3). Subsidiary extraction and phytochemical analysis by GC/MS were performed.The dry and fresh aerial parts (leaves and stem) of Apium graveolens were extracted using a Soxhlet device with 70 % ethanol, then fractionated with petroleum ether. Then Gas Chromatography System was used to identify the bioactive

Environmental stress affects the yield of sorghum. This impact can be reduced by seed stimulation technique and determining the appropriate planting date. An experiment was conducted in the spring and fall seasons of 2022. Randomized complete block design with split-plot arrangement in four replications was used. Planting dates (spring season: February 15th, March 1st, 15th, April 1st, 15th; fall season: June 15th, July 1st, 15th, August 1st, 15th) were assigned to the main plots. Seed stimulation treatments (banana peel extract 35% + citric acid 100 mg L-1 and soaking in distilled water only) were applied to the subplots. The interaction treatment of soaking with banana peel extract + citric acid and the planting date of April 15th showed

Most available methods for unit hydrographs (SUH) derivation involve manual, subjective fitting of
a hydrograph through a few data points. The use of probability distributions for the derivation of synthetic
hydrographs had received much attention because of its similarity with unit hydrograph properties. In this
paper, the use of two flexible probability distributions is presented. For each distribution the unknown
parameters were derived in terms of the time to peak(tp), and the peak discharge(Qp). A simple Matlab
program is prepared for calculating these parameters and their validity was checked using comparison
with field data. Application to field data shows that the gamma and lognormal distributions had fit well.<

Background: Studies discussing the correlation between biochemical markers of bone turnover and the diagnosis of osteoporosis in postmenopausal Iraqi women are rare. This study is devoted to find out the significance of serum osteocalcin (OC) and osteopontin (OPN) levels with the incidence of osteoporosis and its major complication (fracture).Objectives: to investigate the significance of bone turnover biochemical markers; serum osteocalcin and serum osteopontin in evaluating osteoporosis for postmenopausal Iraqi women with and without history of vertebral fracture, as well as to explore the relationship of these markers with bone mineral density (BMD).Methods: Fifty seven postmenopausal women whose ages are fifty years old and over, cat

The immune infertility caused by anti-sperm antibodies (ASAs) represented about 10–20% of infertility among the couples. The ASAs interfere with sperm parameters such as sperm motility and sperm ability to penetrate cervical mucus, sperm-oocyte binding, and fertilization and embryo development. Objectives: The present study designed to assess semen analysis, presence of ASAs and DNA fragmentation index as well as correlation within these parameters in normzoospermic Iraqi subjects Patients, Materials, and Methods: A total number of Iraqi subjects (116) with range of age (20-51) years and their mean duration of infertility (4.70 ± 2.77). Seminal fluid for macroscopic and microscopic assessments done according to WHO 2010 criteria. The

<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope