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.

It has long been desired to develop rapid methods for the rapid identification and quantification of pesticides and their metabolites. Carbofuran, a representative pesticide of the carbamate group, is highly systemic and is used on vegetables, fruits and grains, which has led many countries to test for residues in food and the environment. In this study, gold and silver composite core–shell (Au@Ag) nanoparticles were used to label the carbofuran antibody and Raman molecule 5,5-dithiobis-2-nitrobenzoic acid (DTNB) to synthesize Raman immune probes. The signal value of DTNB was read using a Raman spectrometer, and the quantitative detection technology of carbofuran was established based on lateral flow immunochromatographic assay (ICA) combined with surface-enhanced Raman spectroscopy (SERS). SERS-ICA is a rapid, quantitative and ultrasensitive test for the determination of carbofuran in fruits and vegetables with a sensitivity of 0.1 pg mL⁻¹. Consequently, the results demonstrate that the SERS-based lateral flow immunosensor developed in this study has the advantages of excellent assay sensitivity and remarkable multiplexing capability, and thus it will have great application potential in food safety monitoring.

E. coli O157:H7 contamination in food and the environment poses a serious threat to human health. Rapid and sensitive identification of foodborne pathogens remains challenging. Here, we prepared tungsten disulfide (WS₂)–Au nanocomposites coupled with the Raman signal molecule 5,5′-dithio-bis-(2-nitrobenzoic acid) (DTNB) and antibodies to replace the conventional colloidal gold nanoparticles and applied SERS-active nanotags in the SERS-ICA method for highly sensitive detection of E. coli O157:H7. The large surface area and numerous effective SERS hotspots of WS₂-Au nanotags provide superior SERS signals. Under optimized conditions, this ICA achieves the quantitative detection of E. coli O157:H7 in a broad linear range of 8 × 10²–8 × 10⁷ CFU/mL and at a low detection limit of 175 CFU/mL. In addition, the test strip indicates high specificity for E. coli O157:H7 identification, favorable reproducibility, and shows good accuracy in the detection of actual food samples, such as milk and pork. The proposed assay can be used for rapid qualitative and quantitative detection of E. coli O157:H7 and has great potential for field application.

Fentanyl and its derivatives have been mainstays for the treatment of pain for many years. To accurately detect them in medical applications and customs, a rapid, sensitive, and selective method is urgently needed. In this study, we established a point-of-care-testing (POCT) differential Raman approach for the detection of fentanyl substances in liquid and solid conditions. The silver nanoparticle was prepared and characterized as SERS substrate, which can adsorb fentanyl-related molecules on the rough surface to enhance the Raman signal. Subsequently, 27 kinds of fentanyl-related substances were detected to determine that the POCT spectral resolution is better than 6 cm⁻¹, Raman detection range is 100–3200 cm⁻¹, and the detection limit of the fentanyl-related substances at 1002 cm⁻¹ is 0.1–25 ppb. Furthermore, the Raman characteristic peaks of fentanyl were checked through comparison between theoretical calculations and experiments to obtain a database for rapid on-site inspection. Thus, the fast, accurate, stable POCT approach can be widely applied to monitor drugs and toxins due to its sensitivity, specificity, and abundance database.