The study aimed to evaluate the antimicrobial activity using different concentrations of aqueous and alcoholic extracts of dried lemongrass leaves. Chemical phytochemical tests were performed for aqueous and alcoholic extracts of lemongrass. Antimicrobials activity was tested using agar disc diffusion method against Escherichia coli and Staphylococcus aureus. The results of the study showed that the aqueous extract of dried lemon leaves was highly effective (P≤0.05) against S. aureus, as the inhibition diameter was 22 mm for 50 dilution, while the inhibition diameter decreased to 15 mm for concentration 100. As for the alcoholic extract only, the diameter of inhibition decreased significantly (P≤0.05) as it was 16 mm for 50 dilution, and the diameter of inhibition decreased significantly (P≤0.05) to 8 mm for concentration 100 for S. aureus as well. The results of the study also showed that the effect of the alcoholic extract of lemongrass against E. coli was high, as the inhibition diameter was 20 mm for dilution 50, and a significant decrease (P≤0.05) fell to 12 mm for concentration 100. While the results of the study showed that the effect of alcoholic extract of lemongrass against E. coli the diameter of the inhibition was 14 mm for the dilution of 50, and it decreased significantly (P≤0.05) to zero for the concentration of 100. From all of that, we conclude that both the aqueous and alcoholic extract.
Sensibly highlighting the hidden structures of many real-world networks has attracted growing interest and triggered a vast array of techniques on what is called nowadays community detection (CD) problem. Non-deterministic metaheuristics are proved to competitively transcending the limits of the counterpart deterministic heuristics in solving community detection problem. Despite the increasing interest, most of the existing metaheuristic based community detection (MCD) algorithms reflect one traditional language. Generally, they tend to explicitly project some features of real communities into different definitions of single or multi-objective optimization functions. The design of other operators, however, remains canonical lacking any inte
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Abstract Background: Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Identifying novel biomarkers is critical for improving diagnosis, prognosis, and treatment strategies. This study investigates the serum levels of kisspeptin-1 (KISS1), its receptor (KISS1R), growth differentiation factor 15 (GDF15), and carcinoembryonic antigen (CEA) in Iraqi CRC patients. Objectives: Explore associations between serum levels of Kiss1, Kiss1R, GDF, and CEA and disease progression in Iraqi patients with CRC. Methods: A case-control study was conducted, including 72 CRC patients and 36 healthy controls. Patients were stratified into non-metastatic and metastatic groups. Serum biomarker levels were measured using enzyme-link
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Breast cancer (BC) is one of the most frequently observed malignancy in females worldwide. Today, tamoxifen (TAM) is considered as the highly effective therapy for treatment of breast tumors. Oxidative stress has implicated strongly in the pathophysiology of malignancies. This study aimed to investigate the changes in the levels of oxidants and antioxidants in patients with newly diagnosed and TAM-treated BC. Sixty newly diagnosed and 60 TAM-treated women with BC and 50 healthy volunteers were included in this study. Parameters including total oxidant capacity (TOC), total antioxidant capacity (TAC), and catalase (CAT) activity were determined before and after treatment with TAM. The serum levels of TOC and oxidative stress index (OSI) were
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While conservative access preparations could increase fracture resistance of endodontically treated teeth, it may influence the shape of the prepared root canal. The aim of this study was to compare the prepared canal transportation and centering ability after continuous rotation or reciprocation instrumentation in teeth accessed through traditional or conservative endodontic cavities by using cone-beam computed tomography (CBCT).
Forty extracted intact, matured, and 2-rooted human maxillary first premolars were selected for this
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Software-defined networks (SDN) have a centralized control architecture that makes them a tempting target for cyber attackers. One of the major threats is distributed denial of service (DDoS) attacks. It aims to exhaust network resources to make its services unavailable to legitimate users. DDoS attack detection based on machine learning algorithms is considered one of the most used techniques in SDN security. In this paper, four machine learning techniques (Random Forest, K-nearest neighbors, Naive Bayes, and Logistic Regression) have been tested to detect DDoS attacks. Also, a mitigation technique has been used to eliminate the attack effect on SDN. RF and KNN were selected because of their high accuracy results. Three types of ne
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حضرت معقدات كل من الفنادايل, الخارصين, النحاس والكادميوم بتكافؤهم الثنائي والذهب بتكافؤه الثلاثي بأستخدام صبغة ازوجديدة (6،4،2-ثلاثي هيدروكسي-3-((3-هيدروكسي فنيل) ثنائي زينيل ) فنيل ) ايثان-1-اون المحضرة من ملح الديازونيوم مع ٦,٤,٢- ثلاثي هيدروكسي اسيتوفينون بعد عزل (E)-1-(2,4,6-trihydroxy-3-((3-hydroxyphenyl)diazenyl)phenyl)ethan-1-one تم تشخيصها بواسطة الطرق الطيفية المتاحة والتقنيات التشخيصية لكل من التحليل الدقيق للعناصرواطياف كل من ال
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