Academic Journal

Evaluation of Neem (Azadirachta indica) Nano-Extracts as Antibacterial Agents Against Uropathogenic Bacterial isolates.

Λεπτομέρειες βιβλιογραφικής εγγραφής
Τίτλος: Evaluation of Neem (Azadirachta indica) Nano-Extracts as Antibacterial Agents Against Uropathogenic Bacterial isolates.
Συγγραφείς: Ali, Hussein Khader, Azeez, Dhay A., Hamdan, Israa A.
Πηγή: Journal of Nanostructures; Autumn2026, Vol. 16 Issue 4, p4847-4864, 18p
Θεματικοί όροι: Neem, Antibacterial agents, Multidrug resistance in bacteria, Phytochemicals, Plant extracts, Silver nanoparticles, Urinary tract infections
Περίληψη: Urinary tract infections (UTIs) are considered the second most common type of infection in humans, and a variety of pathogens can cause them, including Gram-positive and Gram-negative bacteria. UTIs are the major health bother that affects millions of people yearly in both a community and hospital setting worldwide. The majority of (Utls) are caused by Uropathogenic Escherichia coli, although other pathogenic bacteria, such as Klebsiella penumoniae, Pseudomonas aeruginosa, and Enterococcus faecalis, can also cause UTIs. Azadirachta indica (neem) is a multipurpose tree with multiple health benefits. It is a well-studied therapeutic plant, known for its diverse phytochemicals and antimicrobial properties against numerous bacterial pathogens Nanoparticles by means of plant extracts have emerged as an eco-friendly and lucrative approach that leverages phytochemical plummeting agents to produce biocompatible nanostructures with improved antimicrobial activity These biologically synthesized nanoparticles have been recognized as potent antibacterial agents against a variety of pathogens, including uropathogens, through mechanisms such as membrane disruption and inhibition of biofilm development. Objective: To isolate and identify bacteria responsible for urinary tract infections (UTIs)and evaluate the antibiotic susceptibility patterns of the isolated bacteria, and to assess the potential effectiveness of Azadirachta indica (Neem) leaf Nano-Extracts against UTI pathogens. A study was conducted between October 1, 2025, and December 30, 2025. A total of 100 urine specimens from men and women aged 5 to 70 were carefully collected and examined. Bacterial isolates were diagnosed. This was confirmed using HiCrome UTI agar, and the isolated bacteria were tested for antibiotic susceptibility using the Kirby-Bauer disk diffusion method in accordance with CLSI standards. The prepared silver nanoparticles were characterized using two methods, one using an aqueous extract and the other using an alcoholic extract of the neem plant, by several spectroscopic techniques, Uv-Vis spectrum, FT-IR spectroscopy, Gas Chromatography GC-MS, TEM, SEM (Scanning Electron Microscopy), and finally with X-Ray (XR-D), which were applied on inoculated plates of Muller-Hinton agar. The disc diffusion method was used to screen the antibacterial activity of both Azadirachta indica extract and synthetic antibiotics. Results: The most frequently identified organisms were as follows: 35.9% Enterococcus faecalis, followed by 29.3% Staphylococcus aureus, 21.0% E. coli, and 6.6% Pseudomonas aeruginosa, all of which were multidrug-resistant (MDR). The successful synthesis of silver nanoparticles was confirmed by color changes and characterization analyses. UV-Visible spectroscopy showed a peak at 440-460 nm, indicating nanoparticle formation. SEM revealed spherical and uniform nanoparticles. EDAX confirmed the presence of silver. Azadirachta indica leaf Nano-Extracts showed significant antibacterial action against every bacterial species at all tested concentrations. Azadirachta indica (neem) leaf Nano-Extracts showed strong antibacterial activity against a range of bacterial pathogen strains. [ABSTRACT FROM AUTHOR]
Copyright of Journal of Nanostructures is the property of University of Kashan and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Βάση Δεδομένων: Complementary Index
Περιγραφή
ISSN:22517871
DOI:10.22052/JNS.2026.04.032