Current advancement in nanomaterial-based emerging techniques for the determination of aminoglycosides antibiotics for antibiotic resistance surveillances

Sajwan, Reena K.; Hashmi, S. Z. H.; Himanshu, Jayendra Kumar; Kumari, Anjali; Solanki, Pratima R.

doi:10.1039/d3ma00632h

Cited by 4 publications

References 197 publications

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Multi‐Mode/Signal Biosensors: Electrochemical Integrated Sensing Techniques

Han,

Wang,

Wang

2024

Adv Funct Materials

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Electrochemical (EC) analysis has emerged as a high‐sensitivity, reliable, cost‐effective, and rapidly evolving technique that has garnered significant attention across diverse domains. Furthermore, EC‐based techniques hold great potential for miniaturization and integration. The integration of EC techniques with diverse mode/signal (such as light, magnetic, and thermal signals, etc.) provides unique opportunities for biosensors to acquire more information through a single sensing platform. By coupling multiple signals or processing them logically, the detection accuracy can be further improved, and the probability of false positives or negatives can be minimized. In this review, a thorough analysis of multi‐ mode/signal sensors in the field of EC sensing is conducted, along with their integration with various sensing techniques (e.g., fluorescence, photothermal, colorimetry, microfluidic, etc.). The aim is to delve into the latest advances, potential applications, as well as challenges in multi‐mode/signal biosensors, where the utilization of multiple sensing modalities helps enhance accuracy, sensitivity, and selectivity. This review provides new insight into the synergistic effects of integrating EC sensing with other techniques, aiming to shed light on the near‐future developments in EC‐integrated multi‐mode/signal biosensors.

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Multi‐Mode/Signal Biosensors: Electrochemical Integrated Sensing Techniques

Han,

Wang,

Wang

2024

Adv Funct Materials

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A Selective Detection of Tetracycline in Animal-Derived Food Samples Using Carbon Quantum Dots as a Fluorescent Eye

Kumari,

Sajwan,

Lakshmi

et al. 2024

ACS Sustainable Resour. Manage.

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We all are surrounded by millions of bacteria, and antibiotics are the only medicine that exists on the Earth to protect us from the thousands of bacterial infections. However, excess consumption of these antibiotics has accelerated the bacterial resistance process. The resistive bacteria then spread and grew exponentially and created several health problems. So, a system is necessarily required that smartly detects the presence of antibiotics in the contaminated samples. Here in this work, a carbon quantum dots (CQDs) based fluorescence resonance energy transfer (FRET) "Turn-Off" sensor was developed for tetracycline (Tetra) detection in animal-derived food samples. The highly fluorescent CQDs have average particle size of around 1.80 ± 0.435 nm were synthesized using pyrolysis method. Here, CQDs-Tetra form a FRET pair, and the emission intensity of CQDs reduced to 57. 3% in the presence of Tetra due to the transfer of energy from donor (CQDs) to acceptor (Tetra). Further, analyzing the lifetime decay of CQDs, which changed from 9.43 ns to 8.89 ns with addition of Tetra, confirms the FRET quenching mechanism. The sensor show the linear response with Tetra concentration varies as 0.05−100 μM with a limit of detection 10.47 nM. The applicability test of the sensor was carried out with real milk and egg samples spiked with standard concentration of Tetra. The test results proved that the sensor could be used as a food monitoring tool.

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Predictive Analytics for Antibiotic Resistance Mitigation in Cloud-Powered Healthcare Systems Using Random Forest

Raman,

Dwivedi

2024

2024 11th International Conference on Reliability, Infocom Technologies and Optimization (Trends and Future Directions) (ICRITO

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Current advancement in nanomaterial-based emerging techniques for the determination of aminoglycosides antibiotics for antibiotic resistance surveillances

Abstract: The graphical abstract represents the nanomaterial-based sensing approach for the detection of aminoglycosides (AMGs) antibiotics.

Cited by 4 publications

References 197 publications

Multi‐Mode/Signal Biosensors: Electrochemical Integrated Sensing Techniques

Multi‐Mode/Signal Biosensors: Electrochemical Integrated Sensing Techniques

A Selective Detection of Tetracycline in Animal-Derived Food Samples Using Carbon Quantum Dots as a Fluorescent Eye

Predictive Analytics for Antibiotic Resistance Mitigation in Cloud-Powered Healthcare Systems Using Random Forest

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