An Electrochemical and Raman Scattering Dual Detection Biosensor for Rapid Screening and Biomolecular Profiling of Cancer Biomarkers

Dey, Shuvashis; Ahmed, Emtiaz; Somvanshi, Pranjal; Sina, Abu Ali Ibn; Wuethrich, Alain; Trau, Matt

doi:10.3390/chemosensors10030093

Cited by 5 publications

(2 citation statements)

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“…SERS -based methods have had a high impact on biomolecular analysis due to several factors, such as the fingerprint signal from the SERS nanotag and the stability [ 31 ]. As a rule, when a laser illuminates nanoparticles immobilized with the Raman reporter molecule, a local hotspot is initiated, and the Raman signal intensity of the reporter molecule is amplified by several orders of magnitude [ 32 ]. So far, research papers have been published demonstrating the potential of SERS-based methods for detecting sensitive and multiplexed biomarkers [ 33 ].…”

Section: Introductionmentioning

confidence: 99%

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

et al. 2022

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The ability to interpret information through automatic sensors is one of the most important pillars of modern technology. In particular, the potential of biosensors has been used to evaluate biological information of living organisms, and to detect danger or predict urgent situations in a battlefield, as in the invasion of SARS-CoV-2 in this era. This work is devoted to describing a panoramic overview of optical biosensors that can be improved by the assistance of nonlinear optics and machine learning methods. Optical biosensors have demonstrated their effectiveness in detecting a diverse range of viruses. Specifically, the SARS-CoV-2 virus has generated disturbance all over the world, and biosensors have emerged as a key for providing an analysis based on physical and chemical phenomena. In this perspective, we highlight how multiphoton interactions can be responsible for an enhancement in sensibility exhibited by biosensors. The nonlinear optical effects open up a series of options to expand the applications of optical biosensors. Nonlinearities together with computer tools are suitable for the identification of complex low-dimensional agents. Machine learning methods can approximate functions to reveal patterns in the detection of dynamic objects in the human body and determine viruses, harmful entities, or strange kinetics in cells.

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Section: Introductionmentioning

confidence: 99%

A Framework for Biosensors Assisted by Multiphoton Effects and Machine Learning

et al. 2022

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“…A number of studies have demonstrated the ability of SERS-based methods for multiplex detection with high sensitivity [21,22]. An original method for the double detection of cancer biomarkers for rapid screening and biomolecular profiling has previously been proposed.…”

Section: Introductionmentioning

confidence: 99%

Detection of Polynitro Compounds at Low Concentrations by SERS Using Ni@Au Nanotubes

et al. 2022

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The identification of high-energy compounds in trace concentrations not only in the laboratory, but also in field conditions is of particular interest. The process should be clear, easy, and well-recognizable. We formed SERS-active substrates by using elongated nickel nanotubes synthesized by electrochemical deposition in the pores of ion-track membranes and coated them with gold for further application in the detection of low concentrations of analytes. The substrates were characterized using various techniques to determine the morphology of the nanotubes and modifying gold layer. The possibility of obtaining two types of gold-layer morphology was shown: in the form of a smooth film up to 20–50 nm thick and a coating with nanoneedles up to 250 nm long. The electric fields around the nanotubes were simulated at a laser wavelength of 532 nm to demonstrate the influence of the gold-layer morphology on the field distribution. The “needle” morphology was chosen to form the most effective SERS-active substrates for detection of low concentrations of aromatic polynitro compounds. The spectral peaks were identified by comparing the model and experimental Raman spectra at concentrations down to 10−5 M. Within this limit, all peaks (“fingerprints” of the substance) were clearly distinguishable.

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