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Synergistic Antibacterial and Anticancer Effects of a Biohybrid Composed of Zinc Oxide Nanoparticles and <i>Streptococcus Salivarius</i> Bacteriocin
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ABSTRACT<p> Antimicrobial therapies are desperately needed since the threat posed by multidrug‐resistant (MDR) bacteria only grows. Bacteriocins produced by <italic>Streptococcus salivarius</italic> possess promising antibacterial properties, yet their practical application is hindered by low production yield and limited stability. Here, we report the green synthesis of a novel biohybrid by conjugating purified <italic>S. salivarius</italic> bacteriocins with zinc oxide nanoparticles (ZnONPs), aiming to enhance bacteriocin stability and antimicrobial efficacy. The successful creation of well‐dispersed nanohybrids was validated by thorough characterization using x‐ray diffraction (XRD), transmission electron microscopy (TEM), and scanning electron microscopy (SEM), exhibiting predominantly cubic and spherical morphologies with sizes ranging from 8 to 68 nm. The ZnONPs–bacteriocin nanohybrids demonstrated pronounced antibacterial activity against both Gram‐positive and Gram‐negative MDR pathogens, as evidenced by significant inhibition zones, and low values for the minimum bactericidal concentration (MBC) and minimum inhibitory concentration (MIC). In vitro cytotoxicity, assays revealed a dose‐dependent reduction in the viability of both cancerous (A375) and normal (HdFn) cell lines. The nanohybrid displayed greater cytotoxicity toward A375 cells (IC <sub>50</sub> = 121.7 µg/mL) than HdFn cells (IC <sub>50</sub> = 161.6 µg/mL), indicating a degree of selectivity. Collectively, our results demonstrate that green‐synthesized ZnONPs–bacteriocin biohybrids are eco‐friendly and exhibit potent, broad‐spectrum antimicrobial and selective cytotoxic activities, suggesting their significant potential for biomedical applications targeting resistant bacterial infections and malignant cells. </p>
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Publication Date
Sun Nov 01 2020
Journal Name
Journal Of Materials Research And Technology
Immobilization of l-asparaginase on gold nanoparticles for novel drug delivery approach as anti-cancer agent against human breast carcinoma cells
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Publication Date
Fri Dec 01 2023
Journal Name
Baghdad Science Journal
Preparing New Ceramic Membranes from Syrian Zeolite Coated with Silver Nanoparticles to Treatment Wells Water
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As a result of the exacerbation of the problem of water pollution, research was directed towards studying the treatment using ceramic membranes, which proved to be highly effective in treating all water sources. The research aims to study the possibility of preparing a new type of ceramic membranes from Syrian zeolite that was not previously used in this field. In this research, ceramic membranes were prepared from Syrian raw zeolite in several stages. Zeolite sample was characterized, grinded, mixed with boric acid, pressed to form desks, treated thermally according to experiment program, finally coated with silver nanoparticles. Specifications of prepared membranes were determined according to reference methods, effectiveness of prepar

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Publication Date
Sat Apr 01 2017
Journal Name
Applied Energy
Melting enhancement in triplex-tube latent heat energy storage system using nanoparticles-metal foam combination
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Publication Date
Thu Mar 01 2018
Journal Name
Ieee Systems Journal
A Comprehensive Survey of the Current Trends and Extensions for the Proxy Mobile IPv6 Protocol
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Publication Date
Wed Nov 30 2022
Journal Name
مجلة الجامعة العراقية
The competencies of lecturers and their roles in managing E-training workshops, a Pedagogical Pointview
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The aim of the research is to shed light on identifying the extent of the university professor's competencies and their roles in managing and training participants in e-training workshops as a pedagogical point view. The research sample consisted of a group of (30) university professors (lecturers) in the training workshops, in scientific,humanitarian and social disciplines, including (12) a university professor (holding a trainer certificate), , the research methodology is descriptive, and the community is a group of trained participants. (115) participated in (40) e-training workshops organized by the Center for Continuing Education at the University of Baghdad (and the selection of workshops within the researcher's specialization in the

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Publication Date
Sun Jul 05 2026
Journal Name
Journal Of Baghdad College Of Dentistry
A Comparative Immunohistochemical Expression of Cyclin D1 in Keratocystic Odontogenic Tumor, Dentigerous and Radicular Cysts
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Background: Odontogenic cysts include a group of osseodestructive lesions that frequently affect the jaws. Those cysts could derive from odontogenic epithelium and occur in the tooth-bearing regions of the jaws. The aims of this study were to evaluate the immunohistochemical expression of Cyclin D1 in Keratocystic Odontogenic Tumor, Dentigerous cyst and Radicular cyst in epithelium and connective tissue capsule. Materials and Methods: In this study, thirty formalin fixed paraffin embedded tissue blocks of Odontogenic cysts and Tumor, consist of 14 Keratocystic Odontogenic Tumor, 8 dentigerous cysts and 8 radicular cysts were analyzed immunohistochemically for the presence of Cyclin D1 proteins. Results: Strong to moderate expression of Cy

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
A noval SVR estimation of figarch modal and forecasting for white oil data in Iraq
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The purpose of this paper is to model and forecast the white oil during the period (2012-2019) using volatility GARCH-class. After showing that squared returns of white oil have a significant long memory in the volatility, the return series based on fractional GARCH models are estimated and forecasted for the mean and volatility by quasi maximum likelihood QML as a traditional method. While the competition includes machine learning approaches using Support Vector Regression (SVR). Results showed that the best appropriate model among many other models to forecast the volatility, depending on the lowest value of Akaike information criterion and Schwartz information criterion, also the parameters must be significant. In addition, the residuals

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Publication Date
Thu Oct 01 2020
Journal Name
The Asian Efl Journal
The Effect of Flow as a Strategy on EFL Student-teachers' Performance and their Flow
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This study aims at suggesting flow as a strategy for training female EFL student-teachers in the teaching training course and finding out the effect of this strategy on their performance and their flow state. The training course syllabuses will be constructed according to the flow nine factors and the teaching skills. The measurement tools are the student-teacher performance checklist that has already been used by the department of English language and SHORT Flow State Scale (S FSS-2). The study population is represented with the (60) female student-teachers/ fourth stage/ evening studies at theEnglish department /college of education for women/the University of Baghdad. The study is used the experimental design in that (30) of the student-

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Publication Date
Mon Dec 16 2024
Journal Name
Light & Engineering
The Design and Experimental Realization of a Laser-Based Heating System Using Recycled Laser Module
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Laser is a powerful device that has a wide range of applications in fields ranging from materials science and manufacturing to medicine and fibre optic communications. One remarkable

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Publication Date
Wed May 04 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Knee Meniscus Segmentation and Tear Detection Based On Magnitic Resonacis Images: A Review of Literature
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The meniscus has a crucial function in human anatomy, and Magnetic Resonance Imaging (M.R.I.) plays an essential role in meniscus assessment. It is difficult to identify cartilage lesions using typical image processing approaches because the M.R.I. data is so diverse. An M.R.I. data sequence comprises numerous images, and the attributes area we are searching for may differ from each image in the series. Therefore, feature extraction gets more complicated, hence specifically, traditional image processing becomes very complex. In traditional image processing, a human tells a computer what should be there, but a deep learning (D.L.) algorithm extracts the features of what is already there automatically. The surface changes become valuable when

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