Advances of surface-enhanced Raman spectroscopy in exosomal biomarkers analysis DOI
Hongsheng Tan, Tong Wang,

He-Nan Sun

et al.

TrAC Trends in Analytical Chemistry, Journal Year: 2023, Volume and Issue: 167, P. 117253 - 117253

Published: Aug. 23, 2023

Language: Английский

SERS Tags for Biomedical Detection and Bioimaging DOI Creative Commons
Huiqiao Liu, Xia Gao, Chen Xu

et al.

Theranostics, Journal Year: 2022, Volume and Issue: 12(4), P. 1870 - 1903

Published: Jan. 1, 2022

Surface-enhanced Raman scattering (SERS) has emerged as a valuable technique for molecular identification. Due to the characteristics of high sensitivity, excellent signal specificity, and photobleaching resistance, SERS been widely used in fields environmental monitoring, food safety, disease diagnosis. By attaching organic molecules surface plasmonic nanoparticles, obtained tags show high-performance multiplexing capability biosensing. The past decade witnessed progress liquid biopsy, bioimaging, theranostics applications. This review focuses on advances biomedical fields. We first introduce building blocks tags, followed by summarization recent employed detecting biomarkers, such DNA, miRNA, protein biological fluids, well imaging from

Language: Английский

Citations

198

Prospects of Surface-Enhanced Raman Spectroscopy for Biomarker Monitoring toward Precision Medicine DOI Creative Commons
Javier Plou, Pablo S. Valera, Isabel Garcı́a

et al.

ACS Photonics, Journal Year: 2022, Volume and Issue: 9(2), P. 333 - 350

Published: Feb. 2, 2022

Future precision medicine will be undoubtedly sustained by the detection of validated biomarkers that enable a precise classification patients based on their predicted disease risk, prognosis, and response to specific treatment. Up now, genomics, transcriptomics, immunohistochemistry have been main clinically amenable tools at hand for identifying key diagnostic, prognostic, predictive biomarkers. However, other molecular strategies, including metabolomics, are still in infancy require development new biomarker technologies, toward routine implementation into clinical diagnosis. In this context, surface-enhanced Raman scattering (SERS) spectroscopy has recognized as promising technology monitoring thanks its high sensitivity label-free operation, which should help accelerate discovery corresponding screening simpler, faster, less-expensive manner. Many studies demonstrated excellent performance SERS biomedical applications. such also revealed several variables considered accurate monitoring, particular, when signal is collected from biological sources (tissues, cells or biofluids). This Perspective aimed piecing together puzzle with view future challenges implications. We address most relevant requirements plasmonic substrates applications, well artificial intelligence biotechnology guide highly versatile sensors.

Language: Английский

Citations

104

Exosome detection via surface-enhanced Raman spectroscopy for cancer diagnosis DOI Creative Commons
Juan Li, Yanru Li, Peilong Li

et al.

Acta Biomaterialia, Journal Year: 2022, Volume and Issue: 144, P. 1 - 14

Published: March 28, 2022

As nanoscale extracellular vesicles, exosomes are secreted by various cell types, and they widely distributed in multiple biological fluids. Studies have shown that tumor-derived can carry a variety of primary tumor-specific molecules, which may represent novel tool for the early detection cancer. However, clinical translation remains challenge due to requirement large quantities samples when enriching cancer-related fluids, insufficiency traditional techniques exosome subpopulations, complex isolation current commercially available phenotype profiling approaches. The evolving surface-enhanced Raman scattering (SERS) technology, with properties unique optoelectronics, easy functionalization, particular interaction between light metallic materials, achieve sensitive without multiplexed profiling, providing new mode real-time noninvasive analysis cancer patients. In present review, we mainly discussed based on SERS, especially SERS immunoassay. basic structure function were firstly introduced. Then, recent studies using technique critically reviewed, included substrates, modification SERS-based detection, combination other technologies diagnosis. This review systematically essential aspects, limitations, considerations applying technology cancer-derived exosomes, could provide valuable reference diagnosis through technology. Surface-enhanced has been applied obtain better diagnostic results. past three years, several reviews published narrowly focus methods detection. Selection surface functionalization substrate different will strategies exosomes. above aspects. emerging method is constantly contributing discovery diseases future.

Language: Английский

Citations

101

Recent Trends in SERS-Based Plasmonic Sensors for Disease Diagnostics, Biomolecules Detection, and Machine Learning Techniques DOI Creative Commons
Reshma Beeram,

Kameswara Rao Vepa,

S. Venugopal Rao

et al.

Biosensors, Journal Year: 2023, Volume and Issue: 13(3), P. 328 - 328

Published: Feb. 27, 2023

Surface-enhanced Raman spectroscopy/scattering (SERS) has evolved into a popular tool for applications in biology and medicine owing to its ease-of-use, non-destructive, label-free approach. Advances plasmonics instrumentation have enabled the realization of SERS’s full potential trace detection biomolecules, disease diagnostics, monitoring. We provide brief review on recent developments SERS technique biosensing applications, with particular focus machine learning techniques used same. Initially, article discusses need plasmonic sensors advantage over existing techniques. In later sections, are organized as SERS-based diagnosis focusing cancer identification respiratory diseases, including SARS-CoV-2 detection. then discuss progress sensing microorganisms, such bacteria, detecting biohazardous materials view homeland security. At end article, we (a) identification, (b) classification, (c) quantification applications. The covers work from 2010 onwards, language is simplified suit needs interdisciplinary audience.

Language: Английский

Citations

83

Label‐Free Identification of Exosomes using Raman Spectroscopy and Machine Learning DOI
Uğur Parlatan, Mehmet Ozgun Ozen, Ibrahim Keçoğlu

et al.

Small, Journal Year: 2023, Volume and Issue: 19(9)

Published: Jan. 15, 2023

Abstract Exosomes, nano‐sized extracellular vesicles (EVs) secreted from cells, carry various cargo molecules reflecting their cells of origin. As EV content, structure, and size are highly heterogeneous, classification via by determining origin is challenging. Here, a method presented combining surface‐enhanced Raman spectroscopy (SERS) with machine learning algorithms to employ the EVs derived five different cell lines reveal cellular origins. Using an artificial neural network algorithm, it shown that label‐free method's prediction ratio correlates HT‐1080 exosomes in mixture. This learning‐assisted SERS enables new direction through investigation preparations differentiating cancer cell‐derived those healthy. approach will potentially open up avenues research for early detection monitoring diseases, including cancer.

Language: Английский

Citations

61

Early cancer detection by serum biomolecular fingerprinting spectroscopy with machine learning DOI Creative Commons
Shilian Dong, Dong He, Qian Zhang

et al.

eLight, Journal Year: 2023, Volume and Issue: 3(1)

Published: July 24, 2023

Abstract Label-free surface-enhanced Raman scattering (SERS) technique with ultra-sensitivity becomes more and desirable in biomedical analysis, which is yet hindered by inefficient follow-up data analysis. Here we report an integrative method based on SERS Artificial Intelligence for Cancer Screening (SERS-AICS) liquid biopsy such as serum via silver nanowires, combining molecular vibrational signals processing large-scale mining algorithm. According to 382 healthy controls 1582 patients from two independent cohorts, SERS-AICS not only distinguishes pan-cancer health 95.81% overall accuracy 95.87% sensitivity at 95.40% specificity, but also screens out those samples early cancer stage. The supereminent efficiency potentiates a promising tool detecting broader types earlier stage, accompanying the establishment of platform further deep

Language: Английский

Citations

48

Early cancer detection by SERS spectroscopy and machine learning DOI Creative Commons
Lingyan Shi, Yajuan Li, Zhi Li

et al.

Light Science & Applications, Journal Year: 2023, Volume and Issue: 12(1)

Published: Sept. 15, 2023

Abstract A new approach for early detection of multiple cancers is presented by integrating SERS spectroscopy serum molecular fingerprints and machine learning.

Language: Английский

Citations

47

Biomedical SERS – the current state and future trends DOI Creative Commons
Dana Cialla‐May, Alois Bonifacio, Thomas Bocklitz

et al.

Chemical Society Reviews, Journal Year: 2024, Volume and Issue: 53(18), P. 8957 - 8979

Published: Jan. 1, 2024

Surface enhanced Raman spectroscopy (SERS) is meeting the requirements in biomedical science being a highly sensitive and specific analytical tool. By employing portable systems combination with customized sample pre-treatment, point-of-care-testing (POCT) becomes feasible. Powerful SERS-active sensing surfaces high stability modification layers if required are available for testing application complex biological matrices such as body fluids, cells or tissues. This review summarizes current state collection pretreatment SERS detection protocols, schemes,

Language: Английский

Citations

40

Single Particle Automated Raman Trapping Analysis of Breast Cancer Cell-Derived Extracellular Vesicles as Cancer Biomarkers DOI Creative Commons
Jelle Penders, Anika Nagelkerke, Eoghan M. Cunnane

et al.

ACS Nano, Journal Year: 2021, Volume and Issue: 15(11), P. 18192 - 18205

Published: Nov. 4, 2021

Extracellular vesicles (EVs) secreted by cancer cells provide an important insight into biology and could be leveraged to enhance diagnostics disease monitoring. This paper details a high-throughput label-free extracellular vesicle analysis approach study fundamental EV biology, toward diagnosis monitoring of in minimally invasive manner with the elimination interpreter bias. We present next generation our single particle automated Raman trapping analysis─SPARTA─system through development dedicated standalone device optimized for EVs. Our visualization approach, dubbed dimensional reduction (DRA), presents convenient comprehensive method comparing multiple spectra. demonstrate that SPARTA system can differentiate between noncancer EVs high degree sensitivity specificity (>95% both). further show predictive ability is consistent across isolations from same cell types. Detailed modeling reveals accurate classification derived various closely related breast subtypes, supporting utility SPARTA-based detailed profiling.

Language: Английский

Citations

95

Emerging SERS biosensors for the analysis of cells and extracellular vesicles DOI
Mohammad Tavakkoli Yaraki, Anastasiia Tukova, Yuling Wang

et al.

Nanoscale, Journal Year: 2022, Volume and Issue: 14(41), P. 15242 - 15268

Published: Jan. 1, 2022

Cells and their derived extracellular vesicles (EVs) or exosomes contain unique molecular signatures that could be used as biomarkers for the detection of severe diseases such cancer, well monitoring treatment response. Revealing these requires developing non-invasive ultrasensitive tools to enable single molecule/cell-level using a small volume sample with low signal-to-noise ratio background multiplex capability. Surface-enhanced Raman scattering (SERS) can address current limitations in studying cells EVs through two main mechanisms: plasmon-enhanced electric field (the so-called electromagnetic mechanism (EM)), chemical (CM). In this review, we first highlight SERS mechanisms then discuss nanomaterials have been develop biosensors based on each aforementioned combination order take advantage synergic effect between enhancement enhancement. Then, review recent advances designing label-aided label-free both colloidal planar systems investigate surface cancer EVs. Finally, perspectives emerging future biomedical applications. We believe article will thus appeal researchers nanobiotechnology including material sciences, biosensors, fields.

Language: Английский

Citations

55