Objective: To evaluate two kinds of extraction (aqueous and ethanolic) for coriander using seeds, leaves and stems and
studying their antibacterial activity against nine different microorganisms.
Methodology: Coriander was selected to carry out this study. Seeds, leaves and stems were collected from local markets in
Baghdad then dried in shade for at least 10 days and grinded to fine powder. Aqueous hot extracts for 1hr. at (50
c) and
cold extracts for 24 hrs at (4
c) were performed by using seeds, leaves and stems then studied antibacterial effect against
nine different microorganisms by using well diffusion technique. Cold aqueous extracts of coriander seeds for 48 hrs. and
72 hrs and ethanolic extraction for 48hrs of seed, leaves and stems also performed.
Results: This study showed that hot aqueous extracts for 1hr. to all parts of coriander indicated no antibacterial activity,
while cold aqueous extract for 24hrs of coriander seeds had inhibitory effect for some tested bacteria, but leaves and stems
had not. Cold aqueous extract of seeds for 48hrs showed antibacterial activity for all tested bacteria but in 72hrs there was
no inhibitory effect. On the other hand, ethanolic extracts of seeds, leaves and stems for 48hrs had antibacterial activity and
the highest values for inhibition zone shown in Klebsiella pneumoniae and Proteus mirabilis.
Recommendations: The study recommends using coriander seeds extract as alternative medical therapy for
microorganisms which may resist conventional treatment. This study is a first step for further studies. It is necessary to use
various extraction methods to give active materials with high percentage, although different organic solvents to be used
with coriander plant to obtain extracts used for testing different kinds of microorganisms which have highly resistance to
conventional treatment.
The cytotoxic effect of catechol was examined in two human cancer cell lines, Epidermoid larynx carcinoma (Hep- 2), Cerebral glioblastoma multiforme (AMGM-5) and Murine mammary adenocarcinomacell (AMN3) treated with half concentrations of catechol (1000, 500, 250, 125, 62.5 and 32.25 μM) for 72 hr. The get hold of results showed catechol have a toxic effect of the cell viability of three types of cell lines after 72h of exposure, the toxicity was dependent on catechol concentrations and/or autoxidation for quinines formation, there were a marked decreased of cell viability in a dose dependent manner in all cell line types. Inhibition concentration of catechol for 50% of cell viability (IC50) were calculated, they were at 581.5 μM, 478 μM
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Digression is analyzed to enable management control centers of authority.
Assessment process significance is closely related by setting definite categories to evaluate the economic activity to know the ability to achieves aims.
This study concentrated on the most important categories that used to evaluate company understudy with ather categories suggested to complete assessment process.
This study is in
... Show MoreTill now, isatin derivatives have received a lot of interest in organic and medicinal chemistry due to their significant biological and pharmacological activities. Schiff’s and Mannich bases of isatins are an effective group of heterocyclic derivatives that play a significant role in medicinal chemistry as antimicrobial agents. In light of these facts, new Schiff bases and Mannich bases of isatin were synthesized. The monomer Mannich bases; 3(a-e) have been synthesized by reacting isatin with different secondary amines, piperidine, morpholine, and pyrrolidine, dimethylamine, diphenylamine, separately, and formaldehyde, while the dimer (5) formed by using piperazine and formaldehyde which then react separately with Phenylhydrazine
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... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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