A smartphone digital image colorimetric method based on nanoparticles for determination of lamotrigine

Spot test with smartphone digital image analysis for determination of methadone in exhaled breath condensate

In this work, we explored the potential of the spot test combined with image analysis using smartphones as a rapid, simple, low-cost, and environmentally friendly method for identifying methadone concentration. Herein, a carbon-gold nanocomposite has been used to generate color variation at different concentrations of methadone. The data obtained from the digital image colorimetric method was compared with those from the UV-Vis spectroscopy as a standard technique. This method was also utilized for extensive optimization and validation procedures. Through image analysis, it can be obtained with the PhotoMetrix smartphone App. and single-variable calibration of collected images. This program computes and processes image histograms from the smartphone camera automatically to determine the concentration of methadone in biological samples. For further analysis, the multivariate calibration technique of PARAFAC can also be used on the images that were taken inside the MATLAB program.

Highly selective colorimetric determination of glutathione based on sandwich-structured nanoenzymes composed of gold nanoparticle-coated molecular imprinted metal-organic frameworks

A sandwich-structured composite nanoenzyme (NH2-MIL-101(Fe)@Au@MIP) was prepared using molecularly imprinted polymers, metal-organic frameworks, and gold nanoparticles and a highly selective glutathione (GSH) colorimetric sensor was constructed. The inner part of the composite nanoenzymes is a metal-organic framework loaded with gold nanoparticles (AuNPs), NH2-MIL-101(Fe)@Au, which has superior peroxidase-like activity compared with  NH2-MIL-101(Fe). This is due to the surface plasmon resonance effect of AuNPs. GSH can form strong Au-S bonds with AuNPs, which can significantly reduce the enzymatic activity of NH2-MIL-101(Fe)@Au, thereby changing the absorbance at 450 nm of the sensing system. The degree of change in absorbance is correlated with the concentration of GSH. In the outer part, the molecularly imprinted polymer with oxidized glutathione (GSSG) as a dummy template provided specific pores, which significantly improved the selectivity of the sensing system. The sensor showed good GSH sensing performance in the range 1 ~ 50 μM with a lower limit of detection (LOD) of 0.231 μM and good sensing performance in fetal bovine serum, indicating its high potential for clinical diagnostic applications.

Label-free SERS assay combined with multivariate spectral data analysis for lamotrigine quantification in human serum

Considering the need for a more time and cost-effective method for lamotrigine (LTG) detection in clinics we developed a fast and robust label-free assay based on surface-enhanced Raman scattering (SERS) for LTG quantification from human serum. The optimization and application of the developed assay is presented  showing the: (i) exploration of different methods for LTG separation from human serum; (ii) implementation of a molecular adsorption step on an ordered Au nanopillar SERS substrate; (iii) adaptation of a fast scanning of the SERS substrate, performed with a custom-built compact Raman spectrometer; and (iv) development of LTG quantification methods with univariate and multivariate spectral data analysis. Our results showed, for the first time, the SERS-based characterization of LTG and its label-free identification in human serum. We found that combining a miniaturized solid phase extraction, as sample pre-treatment with the SERS assay, and using a multivariate model is an optimal strategy for LTG quantification in human serum in a linear range from 9.5 to 75 μM, with LoD and LoQ of 3.2 μM and 9.5 μM, respectively, covering the suggested clinical therapeutic window. We also showed that the developed assay allowed for quantifying LTG from human serum in the presence of other drugs, thereby demonstrating the robustness of label-free SERS. The sensing approach and instrumentation can be further automated and integrated in devices that can advance the drug monitoring in real clinical settings.