Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 197
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 197
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 271
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3165
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 597
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 511
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 317
Function: require_once
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Rapid and sensitive detection of pathogenic bacteria is essential for healthcare, food safety, and environmental monitoring. However, conventional detection techniques often fall short in terms of the speed and sensitivity required for real-time applications. In this study, we propose a label-free plasmonic optical biosensor based on a metal-insulator-metal (MIM) dual-ring resonator structure for the efficient detection of bacterial species. The sensor geometry was optimized using Particle Swarm Optimization (PSO) and evaluated through three-dimensional finite-difference time-domain (3D-FDTD) simulations to enhance both sensitivity and figure of merit (FOM). Gold nanorings integrated with a gold back reflector were employed due to their superior plasmonic resonance characteristics. The optimized design achieved a sensitivity of 324.76 nm·RIU, a FOM of 10.187 RIU, and a detection limit (LoD) of 0.075 RIU. The biosensor maintained high performance under varying operational conditions, including temperature (0-500 K), incident angle (0°-50°), and polarization states. Strong field confinement in the dielectric gap significantly enhanced the interaction between light and the analyte. The device demonstrated the ability to detect and differentiate between Vibrio cholerae (n = 1.365), Escherichia coli (n = 1.388), and Pseudomonas species (n = 1.437-1.526), highlighting its potential for quantitative bacterial identification. By addressing key limitations in sensitivity and specificity in complex biological environments, this MIM-based sensor offers a robust platform for rapid, high-throughput bacterial detection in clinical diagnostics and beyond.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC12215868 | PMC |
http://dx.doi.org/10.1038/s41598-025-07331-9 | DOI Listing |