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bsj-3639
Investigation of the Biochemical and Ultrastructural Mechanisms Underlying the Antimicrobial Activity of Mimusops spp. Extracts: Antimicrobial activity of Mimusops spp.
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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.

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Publication Date
Sun Dec 03 2017
Journal Name
Baghdad Science Journal
Network Self-Fault Management Based on Multi-Intelligent Agents and Windows Management Instrumentation (WMI)
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This paper proposed a new method for network self-fault management (NSFM) based on two technologies: intelligent agent to automate fault management tasks, and Windows Management Instrumentations (WMI) to identify the fault faster when resources are independent (different type of devices). The proposed network self-fault management reduced the load of network traffic by reducing the request and response between the server and client, which achieves less downtime for each node in state of fault occurring in the client. The performance of the proposed system is measured by three measures: efficiency, availability, and reliability. A high efficiency average is obtained depending on the faults occurred in the system which reaches to

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Publication Date
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Mon Dec 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Estimation Mean Wind Speed in Iraq By Using Parametric And Nonparametric Linear Mixed Models
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In this research, the one of the most important model and widely used in many and applications is linear mixed model, which widely used to analysis the longitudinal data that characterized by the repeated measures form .where estimating linear mixed model by using two methods (parametric and nonparametric) and used to estimate the conditional mean and marginal mean in linear mixed model ,A comparison between number of models is made to get the best model that will represent the mean wind speed in Iraq.The application is concerned with 8 meteorological stations in Iraq that we selected randomly and   then we take a monthly data about wind speed over ten years Then average it over each month in corresponding year, so we g

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Publication Date
Tue Feb 18 2025
Journal Name
Iranian Journal Of Science
Exploring Neimark-Sacker Bifurcation and Chaos Control in a Tri-species Discrete-Time Model
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Publication Date
Sat Jan 07 2023
Journal Name
Journal Of Advanced Pharmacy Education And Research
Fimasartan attenuates edema and systemic changes in egg albumin-induced paw inflammation in rats
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Angiotensin receptor blockers are well known for their therapeutic efficacy and fimasartan has been used safely and efficiently since 2010 in the treatment of hypertension. The study aimed to examine the anti-inflammatory effect of fimasartan in egg albumin-induced inflammation in rats. Rats were treated with diclofenac (25 mg/kg, intraperitoneally) or fimasartan at two different doses (3 or 10 mg/kg, intraperitoneally). The increase in the thickness of the paw was considered to be edema, which was measured using a vernier caliper. Serum was collected to analyze the systemic production of the inflammatory mediators TNF-α, and IL-6. The results showed that fimasartan in both doses significantly reduced edema in inflamed rat paws and produce

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Publication Date
Sun Jun 20 2021
Journal Name
Baghdad Science Journal
A Comprehensive Review on Medical Image Steganography Based on LSB Technique and Potential Challenges
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The rapid development of telemedicine services and the requirements for exchanging medical information between physicians, consultants, and health institutions have made the protection of patients’ information an important priority for any future e-health system. The protection of medical information, including the cover (i.e. medical image), has a specificity that slightly differs from the requirements for protecting other information. It is necessary to preserve the cover greatly due to its importance on the reception side as medical staff use this information to provide a diagnosis to save a patient's life. If the cover is tampered with, this leads to failure in achieving the goal of telemedicine. Therefore, this work provides an in

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Publication Date
Thu Feb 09 2023
Journal Name
Artificial Intelligence Review
Community detection model for dynamic networks based on hidden Markov model and evolutionary algorithm
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Finding communities of connected individuals in complex networks is challenging, yet crucial for understanding different real-world societies and their interactions. Recently attention has turned to discover the dynamics of such communities. However, detecting accurate community structures that evolve over time adds additional challenges. Almost all the state-of-the-art algorithms are designed based on seemingly the same principle while treating the problem as a coupled optimization model to simultaneously identify community structures and their evolution over time. Unlike all these studies, the current work aims to individually consider this three measures, i.e. intra-community score, inter-community score, and evolution of community over

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Publication Date
Wed Feb 01 2023
Journal Name
Baghdad Science Journal
Breast Cancer MRI Classification Based on Fractional Entropy Image Enhancement and Deep Feature Extraction
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Disease diagnosis with computer-aided methods has been extensively studied and applied in diagnosing and monitoring of several chronic diseases. Early detection and risk assessment of breast diseases based on clinical data is helpful for doctors to make early diagnosis and monitor the disease progression. The purpose of this study is to exploit the Convolutional Neural Network (CNN) in discriminating breast MRI scans into pathological and healthy. In this study, a fully automated and efficient deep features extraction algorithm that exploits the spatial information obtained from both T2W-TSE and STIR MRI sequences to discriminate between pathological and healthy breast MRI scans. The breast MRI scans are preprocessed prior to the feature

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Publication Date
Sat Jan 01 2022
Journal Name
Journal Of Petroleum Science And Engineering
Depositional environment, seismic stratigraphy, and Sr-isotope geochronology, Bangestan reservoir, Ahwaz oilfield, SW Iran
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The Bangestan reservoir, which occurs in the Ahwaz oilfield, consists of the middle Cretaceous limestone Ilam and Sarvak Formations that were deposited in the Zagros Basin. The reservoir is divided into ten Zones (A to J) formed in the upper Albian-Santonian and contains considerable hydrocarbon accumulations. The limestones were deposited on an extensive shallow carbonate platform on a passive margin and are dominated by rudist biostrome and grainstone facies. Paleogeographical changes mean that identification of the facies is complex. Seismic stratigraphy and isotopic data are used to better understand the structural and geological setting and develop an understanding of the sedimentary environment. The results show that the rudist biostr

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Publication Date
Sun Oct 01 2023
Journal Name
Minerva Dental And Oral Science
Salivary interleukin-1β as a biomarker to differentiate between periodontal health, gingivitis, and periodontitis
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