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ISOLATION, IDENTIFICATION AND EVALUATION OF LACTIC ACID BACTERIA AS ANTIBACTERIAL ACTIVITY
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Five species of Lactic acid bacteriawere isolated from raw milk, yoghurt, vegetables and pickles, Lactobacillus plantarum, Lactobacillus acidophilus, Lactobacillus brevis, Lactobacillus casei and Lactobacillus bulgaricus isolates were identified by 16S rRNA gene. Evaluate of antimicrobial activity against all the bacterial strains Staphylococcus aureus, Salmonella spp., Pseudomonas fluorescens, Escherichia coli, Bacillus cereus and Bacillus subtilis. It showed that bacteriocin of Lactic acid bacteriamore effective than supernatant of lactic acid bacteria, the results showed that isolatemost efficient isolate belonging to Lactobacillus brevis, the diameter of the inhibition of the bacteriocin of Lactobacillus brevis were 27.7, 26.3 and 25.1 against Escherichia coli, Bacillus ceruse and Staphylococcus aureus, respectively. The optimum result for stability of bacteriocin in pH and temperature was shown and maintained its antibacterial activity against Escherichia coli was pH = 6, temperature below 50ºC.

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Publication Date
Sat Feb 11 2023
Journal Name
Applied Sciences
A Preliminary Study and Implementing Algorithm Using Finite State Automaton for Remote Identification of Drones
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Electronic remote identification (ER-ID) is a new radio frequency (RF) technology that is initiated by the Federal Aviation Authorities (FAA). For security reasons, traffic control, and so on, ER-ID has been applied for drones by the FAA to enable them to transmit their unique identification and location so that unauthorized drones can be identified. The current limitation of the existing ER-ID algorithms is that the application is limited to the Wi-Fi and Bluetooth wireless controllers, which results in a maximum range of 10–20 m for Bluetooth and 50–100 m for Wi-Fi. In this study, a mathematical computing technique based on finite state automaton (FSA) is introduced to expand the range of the ER-ID RF system and reduce the ene

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Publication Date
Sat Jul 01 2017
Journal Name
Journal Of Construction Engineering And Management
Identification, Quantification, and Classification of Potential Safety Risk for Sustainable Construction in the United States
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Publication Date
Sun Mar 06 2016
Journal Name
Baghdad Science Journal
Molecular Identification of Rhizosphere Trichoderma spp. and Their Antagonistic Impact Against Some Plant Pathogenic Fungi
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The main aim of this study was to molecular identification and determine the antagonistic impact of rhizosphere Trichoderma spp. against some phytopathogenic fungi, including (Magnaporthe grisea) pyricularia oryzae, Rhizoctonia solani and Macrophomina phasolina. Four Trichoderma isolates were isolated from rhizosphere soils of the different host plants in different locations of Egyptian governorates. The morphological characterization of isolated Trichoderma as well as using of (ITS1-5.8S-ITS2) ribosomal gene sequence acquisition and data analyses. By comparing the results of DNA sequences of ITS region, the fungi represented one isolate were positively identified as T. asperellum (1 isolate T1) and one as T. longibrachiatum (1 isolate T2)

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Publication Date
Tue Jan 01 2019
Journal Name
Proceedings Of The 5th International Conference On Information Systems Security And Privacy
Identification and Extraction of Digital Forensic Evidence from Multimedia Data Sources using Multi-algorithmic Fusion
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Publication Date
Sun Aug 28 2016
Journal Name
World Journal Of Pharmacy And Pharmaceutical Sciences
AN INSIGHT ON THE IDENTIFICATION OF CANCER STEM CELLS USING NOVEL IMMUNOLOGICAL AND MOLECULAR STRATEGIES
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Cancer stem cells (CSCs) are defined as a population of cells present in tumours, which can undergo self-renewal and differentiation. Identification and isolation of these CSCs using putative surface markers have been a priority of research in cancer. With this background we selected pancreatic normal and tumor cells for this study and passaged them into animal tissue culture medium. Further staining was done using alkaline phosphatase and heamatoxilin staining. Blue to purple colored zones in undifferentiated pluripotent stem cells and clear coloration in the chromatin material indicated pancreatic cells. Further studies on the cell surface marker CD 44 were done using ELISA. For this, the protein was extracted from cultivated normal and t

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Publication Date
Mon Dec 24 2018
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
MOLECULAR IDENTIFICATION AND PHYLOGENETIC-TREE ANALYSIS OF MONIEZIA SPECIES FROM SHEEP IN AL-DIWANIYAH CITY
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    The present study was performed to detect the molecular and the phylogenetic identification of species that belonging to the genus of Moniezia Blanchard, 1891 which affected intestines of sheep in Al-Diwaniyah city, Iraq; fifty intestine samples were sought for the infestation of Moniezia spp. from the city slaughterhouse from 1 October to 30 November 2017, this tapeworm was found to infest the intestines of 13 sheep.

 

    For morphological identify the genus of this tapeworm, eggs from one gravid proglottid of the thirteen worms were examined, polymerase chain reaction (PCR) and the PCR-product-based sequencing were applied on 4 Moniezia tapeworms targeti

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Publication Date
Thu Jun 15 2023
Journal Name
Bionatura
Molecular identification and Phylogenetic-Tree Analysis of Hard Ticks from wild and domestic cat Felidae in Iraq
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A total of 13 samples of domestic cat Felis cattus (Linnaeus, 1758 ) and 9 samples of wild cat Felis chaus furax (de Winton, 1898) of the Felidae Family were trapped and examined to detect the hard ticks. The areas of the collection were: Baghdad, Al-Rashidiya, Tharthar, Nahrawan, AL-Mahmoudiya (middle of Iraq) and AL-Haretha (south of Iraq), Mosul (north of Iraq). The results of the current study revealed that four species belong to two genera of hard ticks: Haemaphysalis sp. (Koch, 1844), Rhipicephalus turanicus (Morel, 1969), Rhipicephalus sanguineus (Neumann, 1904) and Rhipicephalus appendiculatus (Santos, 1955). The rates and the density of infestation were discussed. The current study aimed to clarify the infestation differe

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Publication Date
Mon Apr 07 2025
Journal Name
Al-nahrain Journal For Engineering Sciences
Navigating the Challenges and Opportunities of Tiny Deep Learning and Tiny Machine Learning in Lung Cancer Identification
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Lung cancer is the most common dangerous disease that, if treated late, can lead to death. It is more likely to be treated if successfully discovered at an early stage before it worsens. Distinguishing the size, shape, and location of lymphatic nodes can identify the spread of the disease around these nodes. Thus, identifying lung cancer at the early stage is remarkably helpful for doctors. Lung cancer can be diagnosed successfully by expert doctors; however, their limited experience may lead to misdiagnosis and cause medical issues in patients. In the line of computer-assisted systems, many methods and strategies can be used to predict the cancer malignancy level that plays a significant role to provide precise abnormality detectio

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Publication Date
Sun Dec 01 2019
Journal Name
Journal Of Medicinal And Chemical Sciences
Synthesis and Identification of New 2-Substituted-1,3,4-Oxadiazole Compounds from Creatinine and Study Their Antioxidant Activities
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Scopus
Publication Date
Mon Mar 02 2015
Journal Name
Asian J. Res. Pharm. Sci.
Prevalence of Pathogenic Bacteria from Contaminated Yemeni Currency Notes in Taiz City
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ABSTRACT: Pathogenic bacteria responsible for the causation of many common diseases have been identified on currency notes. The present investigation was carried out on one hundred currency notes of all the denominations (50, 100, 250, 500 and 1000RY), obtained from different occupational mainly bus drivers, hawker street, vegetable vendor, restaurants and butchers and fish seller groups in Taiz city,Yemen. Identification and characterization revealed active participation of the following species of organisms in the ascending order of percentage as E. coli(50.28 %),Staphylococci aureus(14.04 %), Klebsiellaspp(4.39 %),proteus(4.39 %), salmonella(1.25 %), shigella(0.72 %), Coagulase negative staphylococcus(0.60 %), pseudomonas(0.50 %),

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