Self-supporting liquid film as reproducible SERS platform for therapeutic drug monitoring of berberine hydrochloride in human urine

Monitoring kinetic processes of drugs and metabolites: Surface-enhanced Raman spectroscopy

Monitoring the kinetic changes of drugs and metabolites plays a crucial role in fundamental research, preclinical and clinical application. Raman spectroscopy (RS) is regarded as a fingerprinting technique that can reflect molecular structures but limited in applications due to poor sensitivity. Surface-enhanced Raman spectroscopy (SERS) significantly amplifies the detection sensitivity by plasmonic substrates, facilitating the identification and quantification of small molecules in biological samples, such as serum, urine, and living cells. This review will focus on advances in how SERS has been utilized to monitor the dynamic processes of small molecule drugs and metabolites in recent years. We first provide readers with a comprehensive overview of the mechanism and practical considerations of SERS, including enhancement theory, substrate design, sample pretreatment, molecule-substrate interactions and spectral analysis. Then we describe the latest advances in SERS for the detection and analysis of metabolites and drugs in cells, dynamic monitoring of drug in various biological matrices, and metabolic profiling for health assessment in biological fluids. We believe that high-performance SERS substrates, standardized technical regulations, and artificial intelligence spectral analysis will boost sensitive, accurate, reproducible, and universal molecular detection in the future. We hoped this review could inspire researchers working in related fields to better understand and utilize SERS for the analytical detection of drugs and metabolites.

Rapid diagnosis and recurrence prediction of choledocholithiasis disease using raw bile with machine learning assisted SERS

Surface-enhanced Raman spectroscopy (SERS) analysis based on body fluids has been widely applied in disease diagnose. Choledocholithiasis is a widespread and often recurrent digestive system disease, with limited data on factors predicting its formation and reappearance. Bile contains many components that could provide valuable diagnostic information; however, the current diagnosis of biliary disease by SERS focuses on detecting specific component in the bile, overlooking the complex interplay and correlations among multiple factors that could be crucial for accurate diagnosis. This work directly obtained multi-component SERS spectral information of raw bile from 46 patients. Characteristic information was extracted from bile SERS spectra using Principal Component Analysis (PCA), revealing variations in the content of characteristic components associated with different choledocholithiasis types and their recurrence frequency. Pearson correlation analysis was also introduced to reveal the interactions of primary active substances pertinent to choledocholithiasis diagnosis. The efficacy of PCA and Support Vector Machine (SVM) models in classifying stone types, presented an accuracy of 99.2 %. Furthermore, the interaction patterns among SERS characteristic components in choledocholithiasis recurrence frequency were revealed, and with the support of SVM, the prediction for different recurrence rates reached an accuracy of 95.2 %. Overall, this work demonstrates that integrating SERS with machine learning can support disease diagnosis and the interpretation of correlations among multiple components, facilitating elucidating the disease mechanisms.

Digital colloid-enhanced Raman spectroscopy for the pharmacokinetic detection of bioorthogonal drugs

Bioorthogonal drug molecules are currently gaining prominence for their excellent efficacy, safety and metabolic stability. Pharmacokinetic study is critical for understanding their mechanisms and guiding pharmacotherapy, which is primarily performed with liquid chromatography-mass spectrometry as the gold standard. For broader and more efficient applications in clinics and fundamental research, further advancements are especially desired in cheap and portable instrumentation as well as rapid and tractable pretreatment procedures. Surface-enhanced Raman spectroscopy (SERS) is capable of label-free detection of various molecules based on the spectral signatures with high sensitivity even down to a single-molecule level. But limited by irreproducibility at low concentrations and spectral interference in complex biofluids, SERS hasn't been widely applied for pharmacokinetics, especially in live animals. In this work, we propose a new method to quantify bioorthogonal drug molecules with signatures at the spectral silent region (SR) by the digital colloid-enhanced Raman spectroscopy (dCERS) technique. This method was first validated using 4-mercaptobenzonitrile in a mixture of analogous molecules, exhibiting reliable and specific identification capability based on the unique SR signature and Poisson-determined quantification accuracy. We further developed a single-step serum pretreatment method and successfully profiled the pharmacokinetic behavior of an anticancer drug, erlotinib, from animal studies. In a word, this method, superior in sensitivity, controllable accuracy, minimal background interference and facile pretreatment and measurement, promises diverse applications in fundamental studies and clinical tests of bioorthogonal drug molecules.

Iodine-Modified Ag NPs for Highly Sensitive SERS Detection of Deltamethrin Residues on Surfaces

It is essential to estimate the indoor pesticides/insecticides exposure risk since reports show that 80% of human exposure to pesticides occurs indoors. As one of the three major contamination sources, surface collected pesticides contributed significantly to this risk. Here, a highly sensitive liquid freestanding membrane (FSM) SERS method based on iodide modified silver nanoparticles (Ag NPs) was developed for quantitative detection of insecticide deltamethrin (DM) residues in solution phase samples and on surfaces with good accuracy and high sensitivity. The DM SERS spectrum from 500 to 2500 cm-1 resembled the normal Raman counterpart of solid DM. Similar bands at 563, 1000, 1165, 1207, 1735, and 2253 cm-1 were observed as in the literature. For the quantitative analysis, the strongest peak at 1000 cm-1 that was assigned to the stretching mode of the benzene ring and the deformation mode of C-C was selected. The peak intensity at 1000 cm-1 and the concentration of DM showed excellent linearity from 39 to 5000 ppb with a regression equation I = 649.428 + 1.327 C (correlation coefficient R2 = 0.991). The limit of detection (LOD) of the DM was found to be as low as 11 ppb. Statistical comparison between the proposed and the HPLC methods for the analysis of insecticide deltamethrin (DM) residues in solution phase samples showed no significant difference. DM residue analysis on the surface was mimicked by dropping DM pesticide on the glass surface. It is found that DM exhibited high residue levels up to one week after exposure. This proposed SERS method could find application in the household pesticide residues analysis.

Ameliorating SERS Sensitivity for Pesticide Malathion Detection with Synergistic Boosting Effect by Hydrogen Cations and Chloride Anions

Although SERS has been widely recognized as one of the highly sensitive analytical methods that can be deployed in the field with high sensitivity and short analysis time, reports regarding the fast determination of malathion at low concentrations are still scarce. Here, in this work, the solution pH and various halogen co-adsorbates were explored to promote the SERS signal of malathion using the citrate-reduced Ag NPs. It was found that chloride anions were the most efficient signal booster among the three halogen ions screened. Further examination of the SERS profile of the malathion in the presence of different halogen species found that the stretching mode of the P-S bond shifted to a lower frequency with Cl^-, which may imply closer (and stronger) binding of malathion to the Ag NPs. This concurs with literature reports that halogen ions could facilitate the adsorption of a certain analyte onto the SERS substrate. In addition, hydrogen ions showed a synergistic effect on SERS signal enhancement when combined with chloride anions. At optimum conditions, the malathion could be detected with a limit of detection (LOD) of 3 ppb. Malathion-spiked cherry tomatoes and oranges were analyzed, and the recovery rates were found to be within 85-100%.

Boosting bacteria differentiation efficiency with multidimensional surface-enhanced Raman scattering: the example of Bacillus cereus

Surface-enhanced Raman scattering (SERS) is a powerful tool for constructing biomolecular fingerprints, which play a vital role in differentiation of bacteria. Due to the rather subtle differences in the SERS spectra among different bacteria, artificial intelligence is usually adopted and enormous amounts of spectral data are required to improve the differentiation efficiency. However, in many cases, large volume data acquisition on bacteria is not only technical difficult but labour intensive. It is known that surface modification of SERS nanomaterials can bring additional dimensionality (difference) of the SERS fingerprints. Here in this work, we show that the concept could be used to improve the bacteria differentiation efficiency. Ag NPs were modified with 11-mercaptoundecanoic acid, 11-mercapto-1-undecanol, and 1-dodecanethiol to provide additional dimensionality. The modified NPs then were mixed with cell lysate from different strains of Bacillus cereus (B. cereus). Even by applying a simple PCA process to the resulting SERS spectra data, all the three modified Ag NPs showed superior differentiation results compared with bare Ag NPs, which could only separate Staphylococcus aureus (S. aureus) and B. cereus. It is believed that the multidimensional SERS could find great potential in bacteria differentiation.

Quantitative detection of 6-thioguanine in body fluids based on a free-standing liquid membrane SERS substrate

The adverse reactions caused by 6-thioguanine (6-TG) in anti-cancer treatment are closely related to the dose, leading to the urgent need for clinical monitoring of its concentration. In this work, a highly reproducible free-standing liquid membrane (FLM) surface-enhanced Raman spectroscopy (SERS) substrate was developed to detect 6-TG in human urine and serum quantitatively. Briefly, a prepared sample was adjusted to pH 2 and mixed with concentrated core-shell bimetallic nanoparticle (Ag_coreAu_shell NP) suspension. The Au/Ag ratio of the Ag_coreAu_shell NPs was optimized. Then the mixture was formed into an FLM using a custom mold. The relative standard deviation (RSD) of the experimental results can be stabilized below 10% (n ≥ 10). The R² of the calibration curve in the range of 10 ~ 100 μg kg^-1 was 0.988. In addition, the limit of detection (LOD) (3σ/k) of 6-TG was 5 μg kg^-1. The FLM SERS platform has been successfully applied to the rapid and reliable analysis of 6-TG spiked in body fluids.

Optical biosensors - Illuminating the path to personalized drug dosing

Optical biosensors are low-cost, sensitive and portable devices that are poised to revolutionize the medical industry. Healthcare monitoring has already been transformed by such devices, with notable recent applications including heart rate monitoring in smartwatches and COVID-19 lateral flow diagnostic test kits. The commercial success and impact of existing optical sensors has galvanized research in expanding its application in numerous disciplines. Drug detection and monitoring seeks to benefit from the fast-approaching wave of optical biosensors, with diverse applications ranging from illicit drug testing, clinical trials, monitoring in advanced drug delivery systems and personalized drug dosing. The latter has the potential to significantly improve patients' lives by minimizing toxicity and maximizing efficacy. To achieve this, the patient's serum drug levels must be frequently measured. Yet, the current method of obtaining such information, namely therapeutic drug monitoring (TDM), is not routinely practiced as it is invasive, expensive, time-consuming and skilled labor-intensive. Certainly, optical sensors possess the capabilities to challenge this convention. This review explores the current state of optical biosensors in personalized dosing with special emphasis on TDM, and provides an appraisal on recent strategies. The strengths and challenges of optical biosensors are critically evaluated, before concluding with perspectives on the future direction of these sensors.

An overview of surface-enhanced Raman scattering substrates by pulsed laser deposition technique: fundamentals and applications

Metallic nanoparticles (NPs), as an efficient substrate for surface-enhanced Raman scattering (SERS), attract much interests because of their various shapes and sizes. The appropriate size and morphology of metallic NPs are critical to serve as the substrate for achieving an efficient SERS. Pulsed laser deposition (PLD) is one of the feasible physical methods employed to synthesize metallic NPs with controllable sizes and surface characteristics. It has been recognized to be a successful tool for the deposition of SERS substrates due to its good controllability and high reproducibility in the manufacture of metallic NPs. This review provides an overview about the recent advances for the preparation of SERS substrates by PLD technique. The influences of parameters on the sizes and morphologies of metallic NPs during the deposition processes in PLD technique including laser output parameters, gas medium, liquid medium, substrate temperature, and properties of 3D substrate are presented. The applications of SERS substrates produced by PLD in the environmental monitoring and biomedical analysis are summarized. This knowledge could serve as a guideline for the researchers in exploring further applications of PLD technique in the production of SERS substrate.