Recent advances in dual recognition based surface enhanced Raman scattering for pathogenic bacteria detection: A review

Wang, Panxue; Sun, Yan; Li, Xiang; Wang, Li; Xu, Ying; He, Lili; Li, Guoliang

doi:10.1016/j.aca.2021.338279

Cited by 64 publications

(27 citation statements)

References 97 publications

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“…Also, the benefits of dual-recognition SERS-based approaches for pathogenic bacteria detection are increasingly recognized; these include superior specificity and sensitivity, minimized matrix interference and reduced costs when using non-specific recognition elements (antibiotics, bifunctional small molecules, etc.). 184 3.2. Spectral data intelligent analysis by using unsupervised and supervised multivariate analysis methods Spectroscopic techniques require instrument calibration using a chemical reference.…”

Section: Sers Biosensorsmentioning

confidence: 99%

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

et al. 2021

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Section: Sers Biosensorsmentioning

confidence: 99%

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

et al. 2021

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“…For SERSbased aptasensors, nanoparticle and SERS label batch-to-batch reproducibility should be carefully considered. 79…”

Section: Sers-based Aptasensors In a Colloidalmentioning

confidence: 99%

“…On the basis of the advantages of microfluidics, multi-residue determination methods can be further studied to simultaneously analyze various interesting targets. For SERS-based aptasensors, nanoparticle and SERS label batch-to-batch reproducibility should be carefully considered …”

Section: Platforms For Sers-based Aptasensorsmentioning

confidence: 99%

Advances in Surface-Enhanced Raman Scattering-Based Aptasensors for Food Safety Detection

Yan

et al. 2021

J. Agric. Food Chem.

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Owing to the excellent performances of high sensitivity, high specificity, on-site detection, and multiplexing capability, surface-enhanced Raman scattering (SERS)-based aptasensors have performed prosperous applications and gained impressive progress in food safety. Herein, we reviewed the SERS-based aptasensors from the principles to specific applications in food safety. First, the sensor-working principles, SERS label design and preparation are introduced. Then, the popular platforms in the aptasensors are summarized with their advantages and disadvantages, followed by their representative applications. Further, the specific applications of developing SERS-based aptasensors in food safety are systematically provided. Moreover, the multiplex analysis using SERS labels are highlighted. Finally, challenges and perspectives for improving the SERS-based aptasensor performance are also discussed, aiming to give some proposes for researchers to choose suitable SERS-based aptasensors according to specific applications.

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“…Surface-enhanced Raman spectroscopy (SERS) is an enhancement effect on the surface of nanosized metal structures, which can escalate the intensity of ordinary Raman scattering by several orders of magnitude, even to the level of single-molecule detection. SERS has the advantages of high sensitivity, fast detection speed, low cost, and strong versatility and has been widely used in many fields such as biomedicine [ 12 ], drug detection, and bacterial detection [ 13 ]. The serum is composed of water, carbohydrates, proteins, and other components.…”

Section: Introductionmentioning

confidence: 99%

Application of Surface-Enhanced Raman Spectroscopy in the Screening of Pulmonary Adenocarcinoma Nodules

Peng

Yan

Lin

et al. 2022

BioMed Research International

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This study is aimed at evaluating the feasibility of a screening method for the pulmonary adenocarcinoma nodules through surface-enhanced Raman spectroscopy (SERS). Objective. Using SERS to measure serum from pulmonary nodules and healthy subjects, intraoperative biopsy pathological diagnosis was regarded as the gold standard for labeling serum samples. To explore the application value of SERS in the differential diagnosis of pulmonary adenocarcinoma nodules, benign nodules, and healthy, we build a machine learning model. Method. We collected 116 serum samples from patients. Radiographically confirmed nodules less than 3 cm in maximum diameter in all patients, including 58 cancer (pathologic diagnosis: adenocarcinoma nodules, labeled as cancer) patients, 58 pathologic diagnoses as benign nodule (labeled as benign) patients, and 63 healthy (labeled as normal) people from the clinical laboratory of Sichuan Cancer Hospital. Gold nanorods were employed as SERS substrates. Support vector machine (SVM) was used to classify the normal, benign, and cancer sample groups, and SVM model evaluated using cross-validation. Results. The average SERS spectra of serum were significantly different between the normal group and the cancer/benign group. While the average SERS spectra of the cancer group and the benign group differed slightly, for the cancer, benign, and normal groups, SVM models can predict with 93.33% accuracy. Conclusion. This exploratory study demonstrates that the SERS technique based on nanoparticles in conjunction with SVM has great potential as a clinical auxiliary diagnosis and screening for pulmonary adenocarcinoma nodules.

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Recent advances in dual recognition based surface enhanced Raman scattering for pathogenic bacteria detection: A review

Cited by 64 publications

References 97 publications

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

Surface-enhanced Raman spectroscopy for bioanalysis and diagnosis

Advances in Surface-Enhanced Raman Scattering-Based Aptasensors for Food Safety Detection

Application of Surface-Enhanced Raman Spectroscopy in the Screening of Pulmonary Adenocarcinoma Nodules

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