Synergizing Nanomaterials and Artificial Intelligence in Advanced Optical Biosensors for Precision Antimicrobial Resistance Diagnosis.

Antimicrobial resistance (AMR) poses a critical global One Health concern, ensuing from unintentional and continuous exposure to antibiotics, as well as challenges in accurate contagion diagnostics. Addressing AMR requires a strategic approach that emphasizes early stage prevention through screening in clinical, environmental, farming, and livestock settings to identify nonvulnerable antimicrobial agents and the associated genes. Conventional AMR diagnostics, like antibiotic susceptibility testing, possess drawbacks, including high costs, time-consuming processes, and significant manpower requirements, underscoring the need for intelligent, prompt, and on-site diagnostic techniques. Nanoenabled artificial intelligence (AI)-supported smart optical biosensors present a potential solution by facilitating rapid point-of-care AMR detection with real-time, sensitive, and portable capabilities. This Review comprehensively explores various types of optical nanobiosensors, such as surface plasmon resonance sensors, whispering-gallery mode sensors, optical coherence tomography, interference reflection imaging sensors, surface-enhanced Raman spectroscopy, fluorescence spectroscopy, microring resonance sensors, and optical tweezer biosensors, for AMR diagnostics. By harnessing the unique advantages of these nanoenabled smart biosensors, a revolutionary paradigm shift in AMR diagnostics can be achieved, characterized by rapid results, high sensitivity, portability, and integration with Internet-of-Things (IoT) technologies. Moreover, nanoenabled optical biosensors enable personalized monitoring and on-site detection, significantly reducing turnaround time and eliminating the human resources needed for sample preservation and transportation. Their potential for holistic environmental surveillance further enhances monitoring capabilities in diverse settings, leading to improved modern-age healthcare practices and more effective management of antimicrobial treatments. Embracing these advanced diagnostic tools promises to bolster global healthcare capacity to combat AMR and safeguard One Health.

Racetrack Ring Resonator-Based on Hybrid Plasmonic Waveguide for Refractive Index Sensing.

In this study, a comprehensive numerical analysis is conducted on a hybrid plasmonic waveguide (HPWG)-based racetrack ring resonator (RTRR) structure, tailored specifically for refractive index sensing applications. The sensor design optimization yields remarkable results, achieving a sensitivity of 275.7 nm/RIU. Subsequently, the boundaries of sensor performance are pushed even further by integrating a subwavelength grating (SWG) structure into the racetrack configuration, thereby augmenting the light-matter interaction. Of particular note is the pivotal role played by the length of the SWG segment in enhancing device sensitivity. It is observed that a significant sensitivity enhancement can be obtained, with values escalating from 377.1 nm/RIU to 477.7 nm/RIU as the SWG segment length increases from 5 µm to 10 µm, respectively. This investigation underscores the immense potential of HPWG in tandem with SWG for notably enhancing the sensitivity of photonic sensors. These findings not only advance the understanding of these structures but also pave the way for the development of highly efficient sensing devices with unprecedented performance capabilities.