Perspective—Prospect of Nano-Enabled Optical Biosensors for Antibiotic Abuse Surveillance as an Early Prevention Tool for Antimicrobial Resistance

Chaudhary, Vishal; Rustagi, Sarvesh; Kaushik, Ajeet; Bhutani, Manisha

doi:10.1149/2162-8777/ad1c8d

Cited by 6 publications

(2 citation statements)

References 53 publications

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“…This research highlights the significance of this integration as a game-changing development in medical diagnostics, which led to the creation of intelligent biosensors with sophisticated features that are fifthgeneration nanoenabled. 119 In general, the use of nanophotonics in Artificial Neural Networks (ANNs) holds great promise for developing efficient and high-performance computer systems. However, many challenges remain, including the integration of nanophotonic components into existing electronic systems and the development of new technologies for the manufacturing of nanophotonic devices (see Table 2).…”

Section: Challenges Alternate Solutions and Opportunitiesmentioning

confidence: 99%

“…It stresses the importance of creating optical biosensors enabled by nanomaterials for the detection of antibiotic abuse. This research highlights the significance of this integration as a game-changing development in medical diagnostics, which led to the creation of intelligent biosensors with sophisticated features that are fifth-generation nanoenabled . In general, the use of nanophotonics in Artificial Neural Networks (ANNs) holds great promise for developing efficient and high-performance computer systems.…”

Section: Challenges Alternate Solutions and Opportunitiesmentioning

confidence: 99%

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

Taha,

Ahmed,

Talreja

et al. 2024

ACS Synth. Biol.

Self Cite

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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, timeconsuming 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.

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Section: Challenges Alternate Solutions and Opportunitiesmentioning

confidence: 99%

Section: Challenges Alternate Solutions and Opportunitiesmentioning

confidence: 99%

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

Taha,

Ahmed,

Talreja

et al. 2024

ACS Synth. Biol.

Self Cite

View full text Add to dashboard Cite

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Nano biosensors: Classification, electrochemistry, nanostructures, and optical properties

Rheima,

Al-Sharify,

Mohaimeed

et al. 2024

Results in Engineering

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Nose-on-Chip Nanobiosensors for Early Detection of Lung Cancer Breath Biomarkers

Chaudhary,

Taha,

Lucky

et al. 2024

ACS Sens.

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Lung cancer remains a global health concern, demanding the development of noninvasive, prompt, selective, and point-of-care diagnostic tools. Correspondingly, breath analysis using nanobiosensors has emerged as a promising noninvasive nose-on-chip technique for the early detection of lung cancer through monitoring diversified biomarkers such as volatile organic compounds/gases in exhaled breath. This comprehensive review summarizes the state-of-the-art breath-based lung cancer diagnosis employing chemiresistive-module nanobiosensors supported by theoretical findings. It unveils the fundamental mechanisms and biological basis of breath biomarker generation associated with lung cancer, technological advancements, and clinical implementation of nanobiosensor-based breath analysis. It explores the merits, challenges, and potential alternate solutions in implementing these nanobiosensors in clinical settings, including standardization, biocompatibility/toxicity analysis, green and sustainable technologies, life-cycle assessment, and scheming regulatory modalities. It highlights nanobiosensors' role in facilitating precise, real-time, and on-site detection of lung cancer through breath analysis, leading to improved patient outcomes, enhanced clinical management, and remote personalized monitoring. Additionally, integrating these biosensors with artificial intelligence, machine learning, Internet-of-things, bioinformatics, and omics technologies is discussed, providing insights into the prospects of intelligent nose-on-chip lung cancer sniffing nanobiosensors. Overall, this review consolidates knowledge on breathomic biosensorbased lung cancer screening, shedding light on its significance and potential applications in advancing state-of-the-art medical diagnostics to reduce the burden on hospitals and save human lives.

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Perspective—Prospect of Nano-Enabled Optical Biosensors for Antibiotic Abuse Surveillance as an Early Prevention Tool for Antimicrobial Resistance

Cited by 6 publications

References 53 publications

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

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

Nano biosensors: Classification, electrochemistry, nanostructures, and optical properties

Nose-on-Chip Nanobiosensors for Early Detection of Lung Cancer Breath Biomarkers

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