Antibiotic resistance is the major growing threat facing the pharmacological treatment of bacterial infections. Therefore, bioprospecting the medicinal plants could provide potential sources for antimicrobial agents. Mimusops, the biggest and widely distributed plant genus of family Sapotaceae, is used in traditional medicines due to its promising pharmacological activities. This study was conducted to elucidate the antimicrobial effect of three unexplored Mimusops spp. (M. kummel, M. laurifolia and M. zeyheri). Furthermore, the mechanisms underlying such antibacterial activity were studied. The Mimusops leaf extracts revealed significant antibacterial activities against the five tested bacterial strains with a maximum inhibition zone diameter of 22.0 mm against B. subtilis compared with standard antibiotic ciprofloxacin. The minimal inhibitory and bactericidal concentration values against tested Gram-positive and Gram-negative bacterial strains ranged from 3.15-12.5 µg/ml. However, weak antifungal effect was recorded against Candida albicans with MIC value ˃25 µg/ml. The 1, 1-diphenyl-2-picrylhydrazyl (DPPH) assay showed that M. caffra was the best antioxidant (IC50=14.75±0.028 µg/ml), while M. laurifolia was the least one (IC50=34.22±0.014 µg/ml). The phenolics in plant leaves extracts were identified and quantified by high performance liquid chromatography (HPLC) which revealed the presence of seven phenolic acids and four flavonoids. The abundant phenolic compounds were rutin (5.216±0.067 mg/g dried wt.) and gallic acid (0.296±0.068 mg/g) followed by myricetin (0.317±0.091 mg/g) then kaempferol (0.113±0.049 mg/g) as flavonoids. The antibacterial mechanism of M. laurifolia extract, as a representative species, induces ultrastructural changes in the model bacterium Staphylococcus aureus with cell wall and plasma membrane lysis as revealed by transmission electron microscopy. Overall, Mimusops species (M. laurifolia, M. kummel and M. zeyheri) are promising natural alternative sources for antimicrobial agents.
Moderately, advanced national election technologies have improved political systems. As electronic voting (e-voting) systems advance, security threats like impersonation, ballot tampering, and result manipulation increase. These challenges are addressed through a review covering biometric authentication, watermarking, and blockchain technologies, each of which plays a crucial role in improving the security of e-voting systems. More precisely, the biometric authentication is being examined due to its ability in identify the voters and reducing the risks of impersonation. The study also explores the blockchain technology to decentralize the elections, enhance the transparency and ensure the prevention of any unauthorized alteration or
... Show MoreRecent studies have revealed some conflicting results about the health effects of caffeine. These studies are inconsistent in terms of design and population and source of consumed caffeine. In the current study, we aimed to evaluate the possible health effects of dietary caffeine intake among overweight and obese individuals.
In this cross-sectional study, 488 apparently healthy individuals with overweight and obesity were participated. Dietary intake was assessed by a Food Frequency Questionnaire (FFQ) and
My research to study the processes of the creation of shapes and encrypt any encryption in design forms and contents of computer technology as the creative property of definable and renewal, change and transformation process of transformative theme of shape, form and content encryption process in textile designs lets us know the meaning or substance which may be invisible to the encryption in the digital design of fabrics is a recruitment ideas modern and refined through a technique to accomplish the work of a beautiful audiences with novelty and innovation. The search includes four chapters:1Chapter I deal with the problem of research and its current research (form and content encryption with digital designs in women's contemporary fabr
... Show MoreIntroduction: Cutaneous leishmaniasis (CL) is a common protozoan disease in Iraq characterized by localized ulcers, primarily on exposed skin. This study aimed to investigate the hematological parameters of infected patients using a complete blood count (CBC) in the endemic area of Diyala Governorate, northeast of Baghdad. This has been studied in newly diagnosed, untreated individuals and patients receiving sodium antimony gluconate. Methodology: Hematological screening was performed on blood samples from 161 patients with microscopically diagnosed cutaneous leishmaniasis before and after treatment. Anti-Leishmania IgG was also assessed by ELISA in seropositive and seronegative subjects. Results: The newly diagnosed, untreated pati
... Show MoreThe evolution of the Internet of things (IoT) led to connect billions of heterogeneous physical devices together to improve the quality of human life by collecting data from their environment. However, there is a need to store huge data in big storage and high computational capabilities. Cloud computing can be used to store big data. The data of IoT devices is transferred using two types of protocols: Message Queuing Telemetry Transport (MQTT) and Hypertext Transfer Protocol (HTTP). This paper aims to make a high performance and more reliable system through efficient use of resources. Thus, load balancing in cloud computing is used to dynamically distribute the workload across nodes to avoid overloading any individual r
... Show MoreIn information security, fingerprint verification is one of the most common recent approaches for verifying human identity through a distinctive pattern. The verification process works by comparing a pair of fingerprint templates and identifying the similarity/matching among them. Several research studies have utilized different techniques for the matching process such as fuzzy vault and image filtering approaches. Yet, these approaches are still suffering from the imprecise articulation of the biometrics’ interesting patterns. The emergence of deep learning architectures such as the Convolutional Neural Network (CNN) has been extensively used for image processing and object detection tasks and showed an outstanding performance compare
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