Abstract :H.pylori is an important cause of gastric duodenal disease, including gastric ulcers, Mucosa-associated lymphoid tissue (MALT), and gastric carcinoma. biosensors are becoming the most extensively studied discipline because the easy, rapid, low-cost, highly sensitive, and highly selective biosensors contribute to advances in next-generation medicines such as individualized medicine and ultrasensitive point-of-care detection of markers for diseases. Five of ten patients diagnosed with H.pylori ranging in age from 15–85 participated in this research. who [gastritis, duodenitis, duodenal ulcer (DU), and peptic ulcer (PU)] Suspected H.pylori colonies were identified by the presence of urease, catalase, oxidase activity, and PCR. All parameters are fixed: Laser power:40 mW, size of drops:25 μ, Turbidity:0.5. , Multi modes optical fiber, and Coreless optical fiber to construct optical biosensor (Multimode-Coreless-Multimode) optical fibers based on an inline Mach-Zehnder Interferometer. All samples had a sensitivity. Multimode-Coreless-Multimode optical Biosensor: is a rapid and sensitive method for the detection of H.pylori bacteria.
Lactiplantibacillus plantarum, one of lactic acid bacteria (LAB), is found in various foods, including dairy products, meat, and vegetables, and most of these bacteria offer beneficial effects to humans and animals as potential probiotics with broad-spectrum antimicrobial activities. The aim of this study was evaluating the antibacterial efficacy of L. plantarum against some foodborne bacteria isolated from dairy products. This research involved 34 dairy products, including local and imported milk, cheese, and yogurt sold locally in Baghdad province, Iraq, during May 2022. For the isolation of L. plantarum, a special medium called MRS (de Man Rogosa and Sharpe) was applied. Colonie
... Show MoreThe production of polyhydroxyalkanoates PHAs from biopolymer degrading bacteria was examined
This study was aimed to investigate the load of bacterial contaminant in fresh meat with different types of bacteria.One handered and seven samples were collected from different regions of Baghdad . These samples included 37 of fresh beef 70 of fresh sheep meat. All samples were cultured on different selective media to identitfy of contaminated bacteria .The result revealed that The percentage of bacterial isolate from raw sheep meat were, % 23.8of StreptococcusgroupD,29.4 % of Staphylococcus aureus ,14.7 % of E.coli , %4.9of Salmonella spp, ,%3.5 of pseudomonas aeruginosa, %14.7.%14.7 of Proteus spp.% 2.1 of Listeria spp while the raw beef meat content %5.55 of Staphylococcus aureus, %8.14 of streptococcus group D , %5.18 %1.85 of E.coli,
... Show MoreThe antibacterial effect of (Eruca sativa) extract was evaluated by an in vitro study testing the growth of various Gram-Positive and Gram-Negative bacteria . The bactericidal activity of this extract was analyzed by serial dilution in tubes. This study,found that Gram-Negative and Gram-Positive bacteria susceptible to very low eruca concentrations. On the other hand, Gram-positive bacteria were more susceptible than Gram-negative bacteria, the minimal bactericidal concentration of Gram-positive bacteria was 5 mg ml-1 but minimal bactericidal concentration of Gram-negative bacteria was 10 mg ml-1 that mean duble inhibation concentration of Gram-positive bacteria . this study suggest that Eruca sativa leaves have inhibation effect on Gra
... Show MoreEndophytic bacteria produced analogous secondary metabolites of their hosts. Similarly, the ability to generate antioxidants is not an exception. Dragon scales (Pyrrosia piloselloides), an epiphytic plant of the Polypodiaceae family, are frequently overlooked. This research aims to isolate antioxidant-producing bacteria from dragon-scale fern leaves. The antioxidant activities were tested after the extraction procedure using ethanolic extract. Bacteria were characterized and selected as candidates for antioxidant production by screening for the production of total phenolic compounds. Antioxidant levels were determined utilizing the ABTS, FRAP, and DPPH techniques. The preliminary findings of the entire phenolic compound test rev
... Show MoreThis study represents an optical biosensor for early skin cancer detection using cysteine-cupped CdSe/CdS Quantum Dots (QDs). The study optimizes QD synthesis, surface, optical functionalization, and bioconjugation to enhance specificity and sensitivity for early skin cancer cell detection. The research provides insights into QD interactions with skin cancer biomarkers, demonstrating high-contrast, precise cellular imaging. Cysteine-capped CdSe/CdS absorption spectra reveal characteristic peaks for undamaged DNA, while spectral shifts indicate structural changes in skin-cancer-damaged DNA. Additionally, fluorescence spectra show sharp peaks for undamaged DNA and notable shifts and intensity variations when interacting with skin cancer. This
... Show MoreWith the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica
... Show MoreThis research describes a new model inspired by Mobilenetv2 that was trained on a very diverse dataset. The goal is to enable fire detection in open areas to replace physical sensor-based fire detectors and reduce false alarms of fires, to achieve the lowest losses in open areas via deep learning. A diverse fire dataset was created that combines images and videos from several sources. In addition, another self-made data set was taken from the farms of the holy shrine of Al-Hussainiya in the city of Karbala. After that, the model was trained with the collected dataset. The test accuracy of the fire dataset that was trained with the new model reached 98.87%.
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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