Exosomes contain different functional bimolecular characteristics related to physiological or pathological processes and are now recognized as new biomarkers in different human cancers. Rapid detection and classification of cancer-related exosomes might be helpful in the rapid screening of patients that may have cancer. Here, we report a surface enhanced Raman scattering technology for rapid and label-free exosomal detection (Exo-SERS) to aid in the discrimination of different cancer cells based on specific Raman phenotypes and multivariate statistical analysis. The results demonstrated that exosomes derived from both tumor cells and normal cells exhibit special, unique Raman phenotypes. Using the Exo-SERS method, the cancer cells were accurately discriminated from normal cells, and subtle molecular changes between the different cell types could be detected with high sensitive. This research provides a rapid, label-free and non-destructive manner for detecting and discriminating between cancer types.

This study aims to develop a simple, sensitive, low-cost, environmentally friendly and flexible surface-enhanced Raman scattering (SERS) platform, combined with a portable Raman spectrometer, for the rapid and on-site SERS detection of bacteria. Commercial tobacco packaging paper (TPP) with little background interference was used as a loading medium that effectively adsorbed Au nanoparticles and provided sufficient “hot spots”. This Au-tobacco packaging paper (Au-TPP) substrate used as a flexible SERS platform can maximize sample collection by wiping irregular surfaces, and was successfully applied to the on-site and rapid detection of pathogenic bacteria. Raman fingerprints of pathogenic bacteria can be obtained by SERS detection of spiked pork using wipeable Au-TPP, which verifies its value in practical applications. The results collected by SERS were further verified by polymerase chain reaction (PCR) results. It showed several advantages in on-site SERS detection, including accurate discrimination, simple preparation, easy operation, good sensitivity, accuracy and reproducibility. This study indicates that the established flexible SERS platform has good practical applications in pathogenic bacterial identification and other rapid detections.

The rapid identification of bacterial antibiotic susceptibility is pivotal to the rational administration of antibacterial drugs. In this study, cefotaxime (CTX)-derived resistance in Salmonella typhimurium (abbr. CTX^r-S. typhimurium) during 3 months of exposure was rapidly recorded using a portable Raman spectrometer. The molecular changes that occurred in the drug-resistant strains were sensitively monitored in whole cells by label-free surface-enhanced Raman scattering (SERS). Various degrees of resistant strains could be accurately discriminated by applying multivariate statistical analyses to bacterial SERS profiles. Minimum inhibitory concentration (MIC) values showed a positive linear correlation with the relative Raman intensities of I₉₉₀/I₁₃₄₈, and the R² reached 0.9962. The SERS results were consistent with the data obtained by MIC assays, mutant prevention concentration (MPC) determinations, and Kirby-Bauer antibiotic susceptibility tests (K-B tests). This preliminary proof-of-concept study indicates the high potential of the SERS method to supplement the time-consuming conventional method and help alleviate the challenges of antibiotic resistance in clinical therapy.

Aspergillus flavus and Aflatoxins in grain crops give rise to a serious threat to food security and cause huge economic losses. In particular, aflatoxin B₁ has been identified as a Class I carcinogen to humans by the International Agency for Research on Cancer (IARC). Compared with conventional methods, Surface-Enhanced Raman Scattering (SERS) has paved the way for the detection of Aspergillus flavus and Aflatoxins in grain crops as it is a rapid, nondestructive, and sensitive analytical method. In this work, the rapid detection of Aspergillus flavus and quantification of Aflatoxin B₁ in grain crops were performed by using a portable Raman spectrometer combined with colloidal Au nanoparticles (AuNPs). With the increase of the concentration of Aspergillus flavus spore suspension in the range of 10²–10⁸ CFU/mL, the better the combination of Aspergillus flavus spores and AuNPs, the better the enhancement effect of AuNPs solution on the Aspergillus flavus. A series of different concentrations of aflatoxin B₁ methanol solution combined with AuNPs were determined based on SERS and their spectra were similar to that of solid powder. Moreover, the characteristic peak increased gradually with the increase of concentration in the range of 0.0005–0.01 mg/L and the determination limit was 0.0005 mg/L, which was verified by HPLC in ppM concentration. This rapid detection method can greatly shorten the detection time from several hours or even tens of hours to a few minutes, which can help to take effective measures to avoid causing large economic losses.

Lead pollution has remained a significant global concern for several decades due to its detrimental effects on the brain, heart, kidneys, lungs, and immune system across all age groups. Addressing the demand for detecting trace amounts of lead in food samples, we have developed a novel biosensor based on fluorescence resonance energy transfer (FRET) from fluorescein R6G to gold nanoclusters (AuNCs-CCY). By utilizing polypeptides as a template, we successfully synthesized AuNCs-CCY with an excitation spectrum that overlaps with the emission spectrum of R6G. Exploiting the fact that Pb²⁺ induces the aggregation of gold nanoclusters, leading to the separation of R6G from AuNCs-CCY and subsequent fluorescence recovery, we achieved the quantitative detection of Pb²⁺. Within the concentration range of 0.002-0.20 μM, a linear relationship was observed between the fluorescence enhancement value (F-F₀) and Pb²⁺ concentration, characterized by the linear equation y = 2398.69x + 87.87 (R² = 0.996). The limit of detection (LOD) for Pb²⁺ was determined to be 0.00079 μM (3σ/K). The recovery rate ranged from 96 % to 104 %, with a relative standard deviation (RSD) below 10 %. These findings demonstrate the potential application value of our biosensor, which offers a promising approach to address the urgent need for sensitive detection of heavy metal ions, specifically Pb²⁺, in food samples.