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Preparation, Characterization, Antimicrobial and Antitumor Activity of Chitosan Schiff base / PVA / PVP Au, Ag Nanocomposite in Treatment of Breast Cancer Cell Line
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Objective(s): Biocompatibility, non-toxicity, minimal allergenicity, and biodegradability are all characteristics of chitosan. Other biological properties of chitosan have been reported, including antitumor, antimicrobial and antioxidant activities. This research aim is the synthesis of drug compounds by preparation and characterization of polymer chitosan Schiff base and chitosan Schiff base / Poly vinyl alcohol / poly vinyl pyrrolidone Nanocomposite and study applications (anticancer cell line, antimicrobial agents). Methods: Chitosan Schiff base was prepared from the reaction of chitosan with carbonyl group of 4-nitro benzaldehyde. Polymer blend have been prepared by solution casting method. Chitosan Schiff base mixing with PVA and PVP. Green synthesis of AuNPs and AgNPs by onion peals extract as reducing agent. Nanocomposites were prepared by mixing 10 mL of chitosan Schiff base, 5 mL PVA and 5 mL of PVP with 25 mL of two different concentrations (100, 200 ppm) of AuNPs and AgNPs. In vitro bacterial activities polymer blends and Au, Ag nano composites were performed against pathogenic bacteria such as the Acinetobacter baumannii, Staphylococcus aureus, Pseudomonas aeruginosa and Esherichia coli. Cancer cell line (AMJ-13) cell line. Results: The prepared AgNPs and AuNPs were characterized by UV-visible spectroscopy, SEM microscopy and XRD analysis. UV-vis spectrum of AuNPs at 543 nm and AgNPs at 425 nm, particles size of AuNPs 24.74 nm and AgNPs 18.77 nm. The polymer blends and nano composites were characterized by FT-IR, SEM, DSC and TGA. DSC analysis investigated the polymer blend and nano composites shows a good thermal stability for all prepared compounds. The inhibition zone of blend and nanocomposites The Inhibition zone of blend and Nano composites ranging between (8-15) millimetre with concentration of 20 mg. The inhibition rate of blend and Nanocomposites ranging between (1.33 – 77.33) for all compounds. IC 50 of blend and Nanocomposites ranging between (26.04 - 183.56) µg for all compounds. Conclusions: The prepared AgNPs and AuNPs were characterized by UV-visible spectroscopy, SEM microscopy and XRD analysis. UV-vis spectrum of AuNPs at 543 nm and AgNPs at 425 nm, particles size of AuNPs 24.74 nm and AgNPs 18.77 nm. The polymer blends and nano composites were characterized by FT-IR, SEM, DSC and TGA. DSC analysis investigated the polymer blend and nano composites shows a good thermal stability for all prepared compounds. The inhibition zone of blend and nanocomposites The Inhibition zone of blend and Nano composites ranging between (8-15) millimetre with concentration of 20 mg. The inhibition rate of blend and Nanocomposites ranging between (1.33 – 77.33) for all compounds. IC 50 of blend and Nanocomposites ranging between (26.04 - 183.56) µg for all compounds.

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Publication Date
Sun Nov 24 2024
Journal Name
Polymer-plastics Technology And Materials
Li <sub>2</sub> CO <sub>3</sub> as a Modifier for PVA/PVP/PEG Blend Polymer Electrolytes: Effects on Structural Integrity, Electrical Performance, Thermal Behavior and Optical Properties
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Publication Date
Sun Nov 10 2019
Journal Name
Journal Of Engineering And Applied Sciences
Fabrication and Properties of Ag<sub>2</sub>O/Si Heterojunction Solar Cell Pure and Doped (Sb, Sn and Se)
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Publication Date
Fri Sep 30 2022
Journal Name
Journal Of Economics And Administrative Sciences
Distinguishing Shapes of Breast Cancer Masses in Ultrasound Images by Using Logistic Regression Model
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The last few years witnessed great and increasing use in the field of medical image analysis. These tools helped the Radiologists and Doctors to consult while making a particular diagnosis. In this study, we used the relationship between statistical measurements, computer vision, and medical images, along with a logistic regression model to extract breast cancer imaging features. These features were used to tell the difference between the shape of a mass (Fibroid vs. Fatty) by looking at the regions of interest (ROI) of the mass. The final fit of the logistic regression model showed that the most important variables that clearly affect breast cancer shape images are Skewness, Kurtosis, Center of mass, and Angle, with an AUCROC of

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Publication Date
Tue May 01 2018
Journal Name
Journal Of Physics: Conference Series
Synthesis, Characterization and the Corrosion Inhibition Study of Two Schiff Base Ligands Derived From Urea and Thiourea and Their Complexes with Cu(II) and Hg(II) Ions
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Publication Date
Tue Jan 01 2019
Journal Name
Technologies And Materials For Renewable Energy, Environment And Sustainability: Tmrees19gr
I-V characteristics of n-Si /ZnO/Se/MWCNTs nanocomposite solar cell fabricated by solvothermal technique
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Publication Date
Tue Dec 30 2025
Journal Name
Iraqi Journal Of Science
Blending a New Polymers Containing Oxadiazole Ring with PVA: Synthesis , Thermal Analysis and Biological Activity
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This study focused on the synthesis of novel polymers incorporating the 1,3,4-oxadiazole ring. Four polymers were specifically prepared by blending polymers (6-9) with polyvinyl alcohol (PVA) in defined ratios, resulting in the formation of blended polymers (10-13). The synthesized polymers were characterized using Fourier Transform Infrared (FTIR) spectroscopy and proton nuclear magnetic resonance (1H-NMR). The results showed that the structure aligned with the proposed synthetic polymers. Furthermore, the physical and thermal properties were studied using scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC). Additionally, the biological activity was examined against two s

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Publication Date
Tue Dec 30 2025
Journal Name
Iraqi Journal Of Science
Blending a New Polymers Containing Oxadiazole Ring with PVA: Synthesis , Thermal Analysis and Biological Activity
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This study focused on the synthesis of novel polymers incorporating the 1,3,4-oxadiazole ring. Four polymers were specifically prepared by blending polymers (6-9) with polyvinyl alcohol (PVA) in defined ratios, resulting in the formation of blended polymers (10-13). The synthesized polymers were characterized using Fourier Transform Infrared (FTIR) spectroscopy and proton nuclear magnetic resonance (1H-NMR). The results showed that the structure aligned with the proposed synthetic polymers. Furthermore, the physical and thermal properties were studied using scanning electron microscopy (SEM), thermogravimetric analysis (TGA) and Differential Scanning Calorimetry (DSC). Additionally, the biological activity was examined against two s

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Publication Date
Wed Feb 01 2023
Journal Name
Optik
Synthesis and characterization of PVDF/PMMA/ZnO hybrid nanocomposite thin films for humidity sensor application
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Publication Date
Sun May 24 2026
Journal Name
Iraqi Journal Of Biotechnology
DETECTION OF GENE EXPRESSION OF SERINE PALMITOYLTRANSFERASE (SPT2) IN MOUSE CELL LINE RAW264.7 INFECTED WITH LEISHMANIA MEXICANA AMASTIGOTES
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Leishmania species are the causative agent of a tropical disease known as leishmaniasis. Previous studies on the old world species Leishmania major, showed that the amastigotes form which resides inside the macrophage of the vertebrate host, utilize host’s sphingolipids for survival and proliferation. In this study, gene expression of serine palmitoyltransferase (SPT) subunit two (MmLCB2) of the mouse macrophage cell line (RAW264.7), which is the first enzyme in the de novo sphingolipid biosynthesis, was detected in both infected and non-infected macrophages. This was detected under condition where available sphingolipid was reduced, with the new world species Leishmania mexicana. Results of qPCR analysis showed that there was no differen

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Publication Date
Mon Feb 01 2021
Journal Name
Indonesian Journal Of Electrical Engineering And Computer Science
Comparative study of logistic regression and artificial neural networks on predicting breast cancer cytology
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<p>Currently, breast cancer is one of the most common cancers and a main reason of women death worldwide particularly in<strong> </strong>developing countries such as Iraq. our work aims to predict the type of tumor whether benign or malignant through models that were built using logistic regression and neural networks and we hope it will help doctors in detecting the type of breast tumor. Four models were set using binary logistic regression and two different types of artificial neural networks namely multilayer perceptron MLP and radial basis function RBF. Evaluation of validated and trained models was done using several performance metrics like accuracy, sensitivity, specificity, and AUC (area under receiver ope

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