In the 45 years since its discovery, surface-enhanced Raman scattering (SERS) as a source of very exciting scientific phenomena and one of the most sensitive analytical techniques currently available, has become a research field in its own right. Significant efforts have been directed toward understanding the effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields, especially in health care including pathogens and disease-related biomarker detection. However, additional efforts including the robust SERS substrate design, the development of the compatible miniature read-out platform as well as effective spectral analysis methods are still needed before it can be routinely used analytically and in commercial products of pathogens and biomarker detection.
The switch from biomedical SERS-based applications on real samples towards SERS-based point-of-care devices for clinical oriented rapid testing and diagnosis is a crucial and omnipresent topic. SERS technique is a competitive, ultrasensitive technology, which is very suitable for bacteria fingerprinting, pathogenicity barcoding and monitoring, mostly in sub-lethal antibiotic concentrations. With the help of chemometric and machine learning models, the scenarios of susceptibility, resistance, pseudo-resistance and tolerance can all be reflected by analyzing SERS spectral data. Moreover, we pinpoint, after a sustained effort to extract the essential SERS features of bacteria, which are the SERS marker bands relevant in monitoring antibiotic treatment and clinical decision of the appropriate drug. In addition, by rationally designing robust SERS probes and compatible POC devices, multiplexing detection of pathogens and disease-related biomarkers is capable of being realized in clinical practice. Herein, we hope that this Research Topic will serve as a token to induce advanced SERS strategies for the readers in terms of efficiency, turn-around time, readout signal, and clinical decision making.
Like every up-to-date analytical technique with high potential for clinical application, SERS has evolved into a futuristic asset in advanced diagnosis, offering promising solutions for pathogens sensing, drug susceptibility testing, early cancer diagnosis or prognosis and various other crucial clinical issues.
1. This Research Topic offers new perspectives on the development of SERS-based sensing studies with the potential for early and advanced diagnosis, by targeting pathogens at single-cell level or relevant biomarkers.
2. Rational design of novel, robust, highly reproducible, and sensitive SERS probes enabling accurate multiplexing detection is included.
3. This research topic also focuses on POC platforms compatible with SERS including lateral flow approaches, microfluidics, and bio-chip technologies.
4. This research topic also welcomes research aimed to explore multivariate analysis including artificial intelligence, machine learning, or other chemometrics and adaptive, robust computational tools to enable SERS-based application.
In the 45 years since its discovery, surface-enhanced Raman scattering (SERS) as a source of very exciting scientific phenomena and one of the most sensitive analytical techniques currently available, has become a research field in its own right. Significant efforts have been directed toward understanding the effect and demonstrating its potential in various types of ultrasensitive sensing applications in a wide variety of fields, especially in health care including pathogens and disease-related biomarker detection. However, additional efforts including the robust SERS substrate design, the development of the compatible miniature read-out platform as well as effective spectral analysis methods are still needed before it can be routinely used analytically and in commercial products of pathogens and biomarker detection.
The switch from biomedical SERS-based applications on real samples towards SERS-based point-of-care devices for clinical oriented rapid testing and diagnosis is a crucial and omnipresent topic. SERS technique is a competitive, ultrasensitive technology, which is very suitable for bacteria fingerprinting, pathogenicity barcoding and monitoring, mostly in sub-lethal antibiotic concentrations. With the help of chemometric and machine learning models, the scenarios of susceptibility, resistance, pseudo-resistance and tolerance can all be reflected by analyzing SERS spectral data. Moreover, we pinpoint, after a sustained effort to extract the essential SERS features of bacteria, which are the SERS marker bands relevant in monitoring antibiotic treatment and clinical decision of the appropriate drug. In addition, by rationally designing robust SERS probes and compatible POC devices, multiplexing detection of pathogens and disease-related biomarkers is capable of being realized in clinical practice. Herein, we hope that this Research Topic will serve as a token to induce advanced SERS strategies for the readers in terms of efficiency, turn-around time, readout signal, and clinical decision making.
Like every up-to-date analytical technique with high potential for clinical application, SERS has evolved into a futuristic asset in advanced diagnosis, offering promising solutions for pathogens sensing, drug susceptibility testing, early cancer diagnosis or prognosis and various other crucial clinical issues.
1. This Research Topic offers new perspectives on the development of SERS-based sensing studies with the potential for early and advanced diagnosis, by targeting pathogens at single-cell level or relevant biomarkers.
2. Rational design of novel, robust, highly reproducible, and sensitive SERS probes enabling accurate multiplexing detection is included.
3. This research topic also focuses on POC platforms compatible with SERS including lateral flow approaches, microfluidics, and bio-chip technologies.
4. This research topic also welcomes research aimed to explore multivariate analysis including artificial intelligence, machine learning, or other chemometrics and adaptive, robust computational tools to enable SERS-based application.