Preparation, characterization, and in vitro bioactivity of magnetic co‐polymer [N, N‐dimethylaminopropylacrylamide‐co‐1‐allylimidazole] as a new nanocarrier for delivery of cefotaxime-Reference-Cited by-同舟云学术

Preparation, characterization, and in vitro bioactivity of magnetic co‐polymer [N, N‐dimethylaminopropylacrylamide‐co‐1‐allylimidazole] as a new nanocarrier for delivery of cefotaxime

Published:2021-04-23 Issue:36 Volume:138 Page:50900
ISSN:0021-8995
Container-title:Journal of Applied Polymer Science
language:en
Short-container-title:J Appl Polym Sci

Author:

Alipour Arash¹,Babaei Shekardasht Mehrnaz¹,Gharbani Parvin²^ORCID

Affiliation:

1. Department of Chemistry Science and Research Branch, Islamic Azad University Tehran Iran

2. Department of Chemistry Ahar Branch, Islamic Azad University Ahar Iran

Publisher

Wiley

Subject

Materials Chemistry,Polymers and Plastics,Surfaces, Coatings and Films,General Chemistry

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/app.50900

Reference23 articles.

1. Development of Cefotaxime Impregnated Chitosan as Nano-antibiotics: De Novo Strategy to Combat Biofilm Forming Multi-drug Resistant Pathogens

2. Newly Developed Topical Cefotaxime Sodium Hydrogels: Antibacterial Activity andIn VivoEvaluation

3. New spectrophotometric method for determination of cephalosporins in pharmaceutical formulations

4. A Critical Review of Analytical Methods for Quantification of Cefotaxime

5. Redefining extended-spectrum -lactamases: balancing science and clinical need

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1. Microspheres with 2D rGO/Alginate Matrix for Unusual Prolonged Release of Cefotaxime;Nanomaterials;2023-05-01

2. In-vitro release study of Pt(II) and Fe(III) metallocefotaxime drug candidates in pH dependent releasing mediums mimicking human biological fluids;Journal of Drug Delivery Science and Technology;2022-05

3. Cephalexin removal by a novel Cu–Zn bionanocomposite biosynthesized in secondary metabolic products of Aspergillus arenarioides EAN603 with pumpkin peels medium: Optimization, kinetic and artificial neural network models;Journal of Hazardous Materials;2021-10