In this study, the chamomile flowers (Matricaria recutitaL) which grow in Iraqi Kurdistan region during the seasons of (2008) are collected. The percentage of essential oil was determined by using steam distillation and the extraction of flowers performed with petroleum ether (70-80) ºC and methanol 70% using ultrasonic extraction. Total phenolic compounds were determined from methanol extracts by using Folin-Ciocalteu method. The extracts were evaluated by thin layer chromatography, ultraviolet absorption and the biological activities were evaluated through their antibacterial action against two types of bacteria using hole method. The flowers showed a composition of 0.071% ash, 0.4% essential oil, 3.2% non oily compounds, 4% oil, 1.9% mo

The various properties of the ground and excited electronic states of coumarins 102 using density functional theory (DFT) and time-dependent density functional theory (TDDFT) was calculated by the B3LYP density functional model with 6-31G(d,p) basis set by Gaussian 09 W program. Spectral characteristics of coumarin102 have been probed into by methods of experimental UV-visible, and quantum chemistry. The UV spectrum was measured in methanol. The optimized structures, total energies, electronic states (HOMO- LUMO), energy gap, ionization potentials, electron affinities, chemical potential, global hardness, softness, global electrophilictity, and dipole moment were measured. We find good agreement between experimental data of UV spectrum and

Studies in Iraq that concerned identification of free-living Protozoa (sarcodina) are scarce; so the current study deals with these protozoan communities inhabiting the Tigris River in Baghdad City. Sampling collection stations have been selected at each of AL-Gheraiˈat and AL-Adhamiyah area adjacent to the river. Monthly intervals sampling with three samples were collected from each station from June to September 2020. Total of 23 sarcodina taxa were listed, out of them 5 taxa were new record to the Tigris River in Baghdad: Difflugia urceolata Carter, 1864 (Arcellinida, Difflugiidae), Heleopera perapetricola Leidy, 1879 (Arcellinida, Heleoperidae), Rhaphidiophrys pallida F.E. Schulze, 1874 (Centrohelida, Raphidiophridae), Saccamoeba sp

Theligand4-[5-(2-hydoxy-phenyl)- [1,3,4- thiadiazole-2- ylimino methyl]-1,5-dimethyl -2-phenyl-1,2-dihydro-pyrazol-3-one [HL1] is prepared and characterized. It is reacted with poly(vinyl chloride) (PVC) in THF to form the PVC-L compounds ,PVC-L interacted with ions of transition metals to form PVC-L-MII complexes .All prepared compounds are characterized by FTIR spectroscopy, u.v-visible spectroscopy, C.H.N.S. analysis and some of them by 1HNMR

New complexes of Cu (ll), Ni (ll), Co (ll), and Zn (ll) wi th 2-amino-5-p-Fiouro Phenyl 1, 3, 4-Thiadiazole have been synthesized. The products were isolated, studied and characterized by physical measurements, ie,(Ff-IR), UV-Vis and the melting points were determined. The new Schiff base (L) has been used to prepare some complexes. The prepared complexes were identified and their structural geometry were suggested

Background:SARS-CoV-2 infection has caused a global pandemic that continues to negatively impact human health. A large group of microbial domains including bacteria co-evolved and interacted in complex molecular pathogenesis along with SARS-CoV-2. Evidence suggests that periodontal disease bacteria are involved in COVID-19, and are associated with chronic inflammatory systemic diseases. This study was performed to investigate the association between bacterial loads of Porphyromonas gingivalis and pathogenesis of SARS-CoV-2 infection. Fifty patients with confirmed COVID-19 by reverse transcriptase-polymerase chain reaction, their age ranges between 20-76 years, and 35 healthy volunteers (matched accordingly with age and sex to th

In accordance with epidemic COVID-19, the elevated infection rates, disinfectant overuse and antibiotic misuse what led to immune suppression in most of the population in addition to genotypic and phenotypic alterations in the microorganisms, so a great need to reevaluate the genetic determinants that responsible for bacterial community (biofilm) has been raised. A total of 250 clinical specimens were obtained from patients in Baghdad hospitals and streaked on Mannitol salt agar medium. The results revealed that 156 isolates appeared as round yellow colonies, indicating that they were mostly identified as Staphylococcus aureus from 250 specimens. The antibiotic resistance pattern of the isolates for methicillin 37.17% (n=58), Amoxic

Breast cancer is the most repeatedly detected cancer category and the second reason cause of cancer-linked deaths among women worldwide. Tumor bio-indictor is a term utilized to describe possible indicators for carcinoma diagnosis, development and progression. The goal of this study is to evaluate part of some cytokines and biomarkers for both serum and saliva samples in breast cancer then estimate their potential value in the early diagnosis of breast cancer by doing more researches in saliva, and utilizing saliva instead of blood (serum and plasma) in sample collection from patients. Serum and salivary samples were taken from 72 patients with breast cancer and 45 healthy controls, in order to investigate the following

Background: Diabetic patients have been reported to be more susceptible to gingivitis and periodontitis than healthy subjects. Many intracellular enzymes like (alkaline phosphatase- (ALP), aspartate aminotransferase- (AST) and alanine aminotransferase- (ALT) that are released outside cells into the gingival crevicular fluid (GCF) and saliva after destruction of periodontal tissue during periodontitis. This study was conducted to determine the periodontal health status and the levels of salivary enzymes (ALP, AST and ALT) of the study and control groups and to correlate the levels of these enzymes with clinical periodontal parameters in each study group. Subjects, Materials and Methods: One hundred subjects were enrolled in the study, with a

Various theories have been proposed since in last century to predict the first sighting of a new crescent moon. None of them uses the concept of machine and deep learning to process, interpret and simulate patterns hidden in databases. Many of these theories use interpolation and extrapolation techniques to identify sighting regions through such data. In this study, a pattern recognizer artificial neural network was trained to distinguish between visibility regions. Essential parameters of crescent moon sighting were collected from moon sight datasets and used to build an intelligent system of pattern recognition to predict the crescent sight conditions. The proposed ANN learned the datasets with an accuracy of more than 72% in comp