Quantitative analysis of thymine with surface-enhanced Raman spectroscopy and partial least squares (PLS) regression

Optical fiber surface plasmon resonance sensor using electroless-plated gold film for thrombin detection

This paper describes the simple and label-free detection of thrombin using optical fiber surface plasmon resonance (SPR) sensors based on gold films prepared by the cost-effective method of electroless plating. The plating conditions for simultaneously obtaining gold film on cylindrical core and end surfaces of an optical fiber suitable for measurement were optimized. The fabricated sensor exhibited a linear refractive index sensitivity of 2150 nm/RIU and 7.136 (a.u.)/RIU in the refractive index of 1.3329-1.3605 interrogated by resonance wavelength and amplitude methods respectively and a single wavelength monitoring method was proposed to investigate the sensing performance of this sensor. Polyadenine diblock and thiolated thrombin aptamers were immobilized on gold nanoparticles and gold films respectively to implement a sandwich optical fiber assay for thrombin. The developed optical fiber SPR sensors were successfully used in the determination of thrombin down to 0.56 nM over a wide range from 2 to 100 nM and showed good selectivity for thrombin, which indicated their potential clinical applications for biomedical samples.

Spectral encoder to extract the efficient features of Raman spectra for reliable and precise quantitative analysis

Raman spectroscopy has become a powerful analytical tool highly demanded in many applications such as microorganism sample analysis, food quality control, environmental science, and pharmaceutical analysis, owing to its non-invasiveness, simplicity, rapidity and ease of use. Among them, quantitative research using Raman spectroscopy is a crucial application field of spectral analysis. However, the entire process of quantitative modeling largely relies on the extraction of effective spectral features, particularly for measurements on complex samples or in environments with poor spectral signal quality. In this paper, we propose a method of utilizing a spectral encoder to extract effective spectral features, which can significantly enhance the reliability and precision of quantitative analysis. We built a latent encoded feature regression model; in the process of utilizing the autoencoder for reconstructing the spectrometer output, the latent feature obtained from the intermediate bottleneck layer is extracted. Then, these latent features are fed into a deep regression model for component concentration prediction. Through detailed ablation and comparative experiments, our proposed model demonstrates superior performance to common methods on single-component and multi-component mixture datasets, remarkably improving regression precision while without needing user-selected parameters and eliminating the interference of irrelevant and redundant information. Furthermore, in-depth analysis reveals that latent encoded feature possesses strong nonlinear feature representation capabilities, low computational costs, wide adaptability, and robustness against noise interference. This highlights its effectiveness in spectral regression tasks and indicates its potential in other application fields. Sufficient experimental results show that our proposed method provides a novel and effective feature extraction approach for spectral analysis, which is simple, suitable for various methods, and can meet the measurement needs of different real-world scenarios.

Industrial wastewater source tracing: The initiative of SERS spectral signature aided by a one-dimensional convolutional neural network

The spectral fingerprint is a significant concept in nontarget screening of environmental samples to direct identification efforts to relevant and important features. Surface-enhanced Raman scattering (SERS) has long been recognized as an optical method that can provide fingerprint-like chemical information at the single-molecule level. Here, the advanced one-dimensional convolutional neural network (1D-CNN) approach was applied to accurately identify the SERS spectral signature of industrial wastewaters for source tracing. A total of 66,000 SERS spectra were acquired from wastewaters of 22 factories across 10 industrial categories at three excitation wavelengths after data augmentation. The dataset was used to train a 1D-CNN model consisting of three convolutional layers to achieve adequate feature extraction of SERS spectra. As a proof-of-concept, multimixed wastewater samples were used to simulate practical pollution scenarios and evaluate the application potential of the model. The SERS-1D-CNN platform can identify the amount and factory information of wastewaters in multimixed samples, which achieves a recognition accuracy rate of 97.33%. The results suggest that even in a complex and unknown water environment, the 1D-CNN model can accurately identify industrial wastewaters in precollected datasets, exhibiting excellent potential in pollution source tracing.

Dual Function of 4-Aminothiophene in Surface-Enhanced Raman Scattering Application as an Internal Standard and Adsorbent for Controlling Au Nanocrystal Morphology

The sensitivity and quantitative accuracy of surface-enhanced Raman scattering (SERS) are the main factors that restrict its application. Here, novel Au nanoscale convex polyhedrons (Au NCPs) were designed and fabricated to solve these problems via an embedded standard, including eight pods and six small protrusions. Spherical Au seeds regrew into different sizes of Au NCPs with a face-centered cubic structure. This morphology is due to the dual mechanism of the 4-aminothiophene (4-ATP) molecule that serves as an internal standard and a surface ligand regulator combined with the regulatory role of hexadecyl trimethyl ammonium chloride. The results show that Au NCPs were enclosed by high-index {12 9 1} facets, which greatly improved the local plasma resonance and reduced the lowest SERS detectable concentration of pyrene in standard seawater to 0.5 nM. An effective reference was produced by embedding 4-ATP with a relative standard deviation value less than 2.97% (in the same batch) and 3.92% (between different batches). Our research offers a new strategy for morphological regulation of metal nanocrystals, which is useful for the preparation of highly sensitive SERS substrates and trace analysis.

CNN-assisted SERS enables ultra-sensitive and simultaneous detection of Scr and BUN for rapid kidney function assessment

Kidney disease is highly prevalent and may result in severe clinical outcomes. Serum creatinine (Scr) and blood urea nitrogen (BUN) are the most widely used biomarkers for kidney function assessment, yet when measured alone, the result can be affected by a variety of parameters such as age, gender, protein consumption, etc. Measuring Scr and BUN simultaneously can eliminate most of the external influences and greatly improve the assessment of kidney function. In this study, a real-time kidney function assessment system based on dual biomarker detection was proposed. Scr and BUN were determined using surface-enhanced Raman scattering (SERS) within the concentration range of 10^-1 to 10^-6 M and 0.28 to 100 mg dl^-1, respectively. A one-dimensional convolutional neural network (1D-CNN) model was employed to quantitatively analyze the concentration of biomarkers from the SERS spectral measurements. Moreover, we simulated a variety of kidney health conditions with 16 groups of mixed Scr and BUN in serum. The proposed CNN-assisted SERS method was used to quantify both biomarkers and provide diagnostic results. The Au core-Ag shell nanoprobes provided ultra-sensitive SERS detection and the CNN model achieved excellent regression results with an R² of 0.9871 in the testing dataset. The system demonstrated a rapid and robust evaluation for the assessment of kidney function, providing a promising idea for medical diagnosis with the help of spectroscopy and deep learning methods.

Competitive Ratiometric Aptasensing with Core-Internal Standard-Shell Structure Based on Surface-Enhanced Raman Scattering

Reproducibility and stability are important indicators for the evaluation of quantitative sensing methods based on surface-enhanced Raman scattering (SERS) technology. Developing a SERS substrate with self-calibration capabilities is vital for effectively quantifying targets. In this work, a competitive ratiometric SERS aptasensor was developed. 4-Aminothiophenol as an internal standard (IS) was embedded in the substrate followed by gradually loading with the aptamer and methylene blue functionalizing of the complementary sequences of the aptamer (MB-cDNA). Recognition and binding of the target to the aptamer resulted in the shedding of MB-cDNA after magnetic separation reducing the SERS signal of MB, allowing for the ratiometric determination of the target based on the constant intensity from the IS. For the selective detection of okadaic acid (OA), a good negative correlation was achieved between the SERS ratiometric intensity and OA concentration in the range of 0.5-100 ng/mL. The magnetic separation strategy effectively simplifies the production steps of the aptasensor, and the ratiometric strategy effectively improved the reproducibility and stability of the OA sensing. This ratiometric aptasensor has been successfully employed to detect OA in food and environmental samples and is expected to be extended to detect other targets.

A Rapid Therapeutic Drug Monitoring Strategy of Carbamazepine in Serum by Using Coffee-Ring Effect Assisted Surface-Enhanced Raman Spectroscopy

Carbamazepine (CBZ) has a narrow therapeutic concentration range, and therapeutic drug monitoring (TDM) is necessary for its safe and effective individualized medication. This study aims to develop a procedure for CBZ detection in serum using coffee-ring effect assisted surface-enhanced Raman spectroscopy (SERS). Silver nanoparticles deposited onto silicon wafers were used as the SERS-active material. Surface treatment optimization of the silicon wafers and the liquid-liquid extraction method were conducted to eliminate the influence of impurities on the silicon wafer surface and the protein matrix. The proposed detection procedure allows for the fast determination of CBZ in artificially spiked serum samples within a concentration range of 2.5-40 μg·mL^-1, which matches the range of the drug concentrations in the serum after oral medication. The limit of detection for CBZ was found to be 0.01 μg·mL^-1. The developed method allowed CBZ and its metabolites to be ultimately distinguished from real serum samples. The developed method is anticipated to be a potential tool for monitoring other drug concentrations.

Quantitative Analysis of Acetone in Transformer Oil Based on ZnO NPs@Ag NWs SERS Substrates Combined with a Stoichiometric Model

Acetone is an essential indicator for determining the aging of transformer insulation. Rapid, sensitive, and accurate quantification of acetone in transformer oil is highly significant in assessing the aging of oil-paper insulation systems. In this study, silver nanowires modified with small zinc oxide nanoparticles (ZnO NPs@Ag NWs) were excellent surface-enhanced Raman scattering (SERS) substrates and efficiently and sensitively detected acetone in transformer oil. Stoichiometric models such as multiple linear regression (MLR) models and partial least square regressions (PLS) were investigated to quantify acetone in transformer oil and compared with commonly used univariate linear regressions (ULR). PLS combined with a preprocessing algorithm provided the best prediction model, with a correlation coefficient of 0.998251 for the calibration set, 0.997678 for the predictive set, a root mean square error in the calibration set (RMSECV = 0.12596 mg/g), and a prediction set (RMSEP = 0.11408 mg/g). For an acetone solution of 0.003 mg/g, the mean absolute percentage error (MAPE) was the lowest among the three quantitative models. For a concentration of 7.29 mg/g, the MAPE was 1.60%. This method achieved limits of quantification and detections of 0.003 mg/g and 1 μg/g, respectively. In general, these results suggested that ZnO NPs@Ag NWs as SERS substrates coupled with PLS simply and accurately quantified trace acetone concentrations in transformer oil.

Self-Referenced Surface-Enhanced Raman Scattering Nanosubstrate for the Quantitative Detection of Neurotransmitters

Quantitative, label-free detection of neurotransmitters is of vital importance to the diagnosis and treatment of neurologic diseases. The surface-enhanced Raman scattering (SERS) effect has great application prospects in the field of biosensing and bioimaging because of its unique nondestructive testing and its capability of being used in molecular fingerprint identification. However, the quantitative SERS analysis of neurotransmitters is still a great challenge because of the poor reproducibility of the SERS-active sites, as well as the small Raman cross-section and low physiological concentration of neurotransmitter molecules. Here, we report the development of a stellate gold nanostructure with a 1 nm interior gap for the quantitative detection of neurotransmitters. The internal reference embedded into the hollow gap of the stellate gold nanoparticle allows the calibration of the signal of analytes absorbed on the surface, which improves the R-squared value of the linear fitting curve from 0.56 to 0.97 for quantitative dopamine detection. Our developed self-referenced SERS substrate holds great potential for label-free, quantitative SERS-based biosensing.

The Influence of pH on Complexation Process of Copper(II) Phosphoethanolamine to Pyrimidine Nucleosides

The influence of pH on the complex formation of phosphoethanolamine and pyrimidine nucleosides (uridine, cytidine and thymidine) with copper(II) ions was studied. All investigations were performed in aqueous solution. The overall stability constants of the complexes and non-covalent compounds were obtained using the potentiometric method with computer calculation of the data. Moreover, equilibrium constants of the reaction were determined. The mode of coordination was obtained using spectroscopic methods. Analysis of the potentiometric and spectroscopic data confirmed the involvement and effectiveness of phosphate groups in species formation as well as the influence of pH on the mode of coordination of the investigated biomaterials. In the next step, studied complexes will be applied as potential biomaterials with biological applications.

MCR-ALS with sample insertion constraint to enhance the sensitivity of surface-enhanced Raman scattering detection

The multivariate curve resolution-alternative least squares (MCR-ALS) algorithm was modified with sample insertion constraint to deconvolute the overlapping peaks in SERS spectra. The developed method was evaluated by the spectral data simulated using a Gaussian distribution function to generate two independent peaks corresponding to a capping agent and an analyte. The spectra were generated with different overlapping levels and various intensity ratios of the analyte to the capping agent. By using MCR-ALS with the sample insertion constraint, the peak of the capping agent was completely excluded to obtain a calibration model of the analyte with R² > 0.95 under all conditions. Furthermore, our developed method was later applied to a real SERS measurement to quantify carbofuran (analyte) using the azo-coupling reaction with p-ATP (capping agent) on silver nanoparticles as a SERS substrate. A calibration model of derivative carbofuran phenol was generated with R² = 0.99 and LOD = 28.19 ppm. To assess the performance of the calibration model, the model was used to estimate the concentration of carbofuran in an external validation set. It was found that the RMSE of prediction was only 2.109 with a promising R² = 0.97.

Label-free surface-enhanced Raman spectroscopy with artificial neural network technique for recognition photoinduced DNA damage

Taking advantage of surface-enhanced Raman scattering (SERS) methodology with its unique ability to collect abundant intrinsic fingerprint information and noninvasive data acquisition we set up a SERS-based approach for recognition of physically induced DNA damage with further incorporation of artificial neural network (ANN). As a proof-of-concept application, we used the DNA molecules, where the one oligonucleotide (OND) was grafted to the plasmonic surface while complimentary OND was exposed to UV illumination with various exposure doses and further hybridized with the grafted counterpart. All SERS spectra of entrapped DNA were collected by several operators using the portable spectrometer, without any optimization of measurements procedure (e.g., optimization of acquisition time, laser intensity, finding of optimal place on substrate, manual baseline correction, etc.) which usually takes a significant amount of operator's time. The SERS spectra were employed as input data for ANN training, and the performance of the system was verified by predicting the class labels for SERS validation data, using a spectra dataset, which has not been involved in the training process. During that phase, accuracy higher than 98% was achieved with a level of confidence exceeding 95%. It should be noted that utilization of the proposed functional-SERS/ANN approach allows identifying even the minor DNA damage, almost invisible by control measurements, performed with common analytical procedures. Moreover, we introduce the advanced ANN design, which allows not only classifying the samples but also providing the ANN analysis feedback, which associates the spectral changes and chemical transformations of DNA structure.

Control of Silver Coating on Raman Label Incorporated Gold Nanoparticles Assembled Silica Nanoparticles

Signal reproducibility in surface-enhanced Raman scattering (SERS) remains a challenge, limiting the scope of the quantitative applications of SERS. This drawback in quantitative SERS sensing can be overcome by incorporating internal standard chemicals between the core and shell structures of metal nanoparticles (NPs). Herein, we prepared a SERS-active core Raman labeling compound (RLC) shell material, based on Au⁻Ag NPs and assembled silica NPs (SiO₂@Au@RLC@Ag NPs). Three types of RLCs were used as candidates for internal standards, including 4-mercaptobenzoic acid (4-MBA), 4-aminothiophenol (4-ATP) and 4-methylbenzenethiol (4-MBT), and their effects on the deposition of a silver shell were investigated. The formation of the Ag shell was strongly dependent on the concentration of the silver ion. The negative charge of SiO₂@Au@RLCs facilitated the formation of an Ag shell. In various pH solutions, the size of the Ag NPs was larger at a low pH and smaller at a higher pH, due to a decrease in the reduction rate. The results provide a deeper understanding of features in silver deposition, to guide further research and development of a strong and reliable SERS probe based on SiO₂@Au@RLC@Ag NPs.

Fourier based partial least squares algorithm: new insight into influence of spectral shift in "frequency domain"

Developments in analytical chemistry technology, especially the combination between the partial least squares and spectroscopy, have contributed significantly to predicting the chemical concentrations and discriminating similar chemical analytes. However, spectral shift is an unwanted but inevitable factor for the spectroscopic analyzer, especially in practical application, which decreases the method's accuracy and stability. To remove the term of spectral shift completely and increase the robustness of spectroscopic analysis method, Fourier transform based partial least squares method was proposed. The approach used Fourier transform first to transform the spectral shift in the "time domain" to the phase term in the "frequency domain." The module of the Fourier transformed spectra was then calculated. As a result, the phase term was removed (the module of the phase term is 1), which means the spectral shift term was removed completely. Finally, the spectra modules were used to build the model and validate. The approach's advantages are: (i) that the approach provides a new insight to treat the spectral shift in spectroscopic analyzer; (ii) that the model is insensitive to spectral shift; (iii) that the approach makes partial least squares combined with spectroscopy more suitable for practical application, rather than lab experiment, because spectral shift is permitted, which means the decreased requirements of measure environment. As an example, blood species discrimination, using Raman spectroscopy, was used in order to demonstrate this approach's effectiveness.

Antipsychotic drug poisoning monitoring of clozapine in urine by using coffee ring effect based surface-enhanced Raman spectroscopy

Antipsychotics are the drugs most often involved in drug poisoning cases, and therefore, therapeutic drug monitoring (TDM) is necessary for safe and effective medication administration of these drugs. In this study, a coffee ring effect-based surface-enhanced Raman spectroscopy (CRE-SERS) method was developed and successfully used to monitor antipsychotic poisoning by using urine samples for the first time. The established method exhibited excellent SERS performance since more hot spots were obtained in the "coffee ring". Using the optimized CRE-SERS method, the sensitivity was improved one order more than that of the conventional method with reasonable reproducibility. The antipsychotic drug clozapine (CLO) spiked into urine samples at 0.5-50 μg mL^-1 was quantitatively detected, at concentrations above the thresholds for toxicity. The CRE-SERS method allowed CLO and its metabolites to be ultimately distinguished from real poisoning urine samples. The coffee-ring effect would provide more opportunities for practical applications of the SERS-based method. The frequent occurrence of drug poisoning may have created a new area for the application of the CRE-SERS method. It is anticipated that the developed method will also have great potential for other drug poisoning monitoring.

Identification and analysis of Triphenyltin chloride with surface enhanced Raman scattering spectroscopy

Triphenyltin (TPhT) is a kind of organotin compounds which have been used ubiquitously as herbicide, pesticide, and fungicide in agriculture. The present study provides the possibility to detect and monitor TPhT with normal Raman spectroscopy and surface enhanced Raman scattering (SERS) spectroscopy. Firstly, the complete vibrational Raman spectra characterization of TPhT along with the IR spectroscopy were reported for the first time. Then a wide range of pH values were carried out to choose the optimal pH value in TPhT detection by using Raman spectroscopy. Afterwards, Raman spectra of various TPhT solutions were collected and analyzed. The results indicate that the optimal pH value for TPhT detection by Raman spectroscopy is 5.5, and with silver nanoparticles (Ag NPs) as SERS substrate is an effective technique for trace TPhT detection with an enhancement by 5 orders of magnitude and the detection limit can be as low as 0.6 ng/L within less than 30 s. Finally, in this study, the residual of TPhT on apple peel was investigated by casting different concentrations of TPhT on apple peel under the current optimized condition. The result demonstrates that TPhT could be detected based on its SESR spectra at 6.25 ng/cm(2) in standard solutions.

Cooperative hydrogen-bonding of the adenine–thymine pair as a strategy for lowering the limit of detection of thymine by surface-enhanced Raman spectroscopy

The formation of cooperative hydrogen bonds between the thymine–adenine pair was used to indirectly determine thymine by SERS, improving the limit of detection values up to two orders of magnitude.

Characterization of the Adsorption of Nucleic Acid Bases onto Ferrihydrite via Fourier Transform Infrared and Surface-Enhanced Raman Spectroscopy and X-ray Diffractometry

Minerals could have played an important role in concentration, protection, and polymerization of biomolecules. Although iron is the fourth most abundant element in Earth's crust, there are few works in the literature that describe the use of iron oxide-hydroxide in prebiotic chemistry experiments. In the present work, the interaction of adenine, thymine, and uracil with ferrihydrite was studied under conditions that resemble those of prebiotic Earth. At acidic pH, anions in artificial seawater decreased the pH at the point of zero charge (pHpzc) of ferrihydrite; and at basic pH, cations increased the pHpzc. The adsorption of nucleic acid bases onto ferrihydrite followed the order adenine >> uracil > thymine. Adenine adsorption peaked at neutral pH; however, for thymine and uracil, adsorption increased with increasing pH. Electrostatic interactions did not appear to play an important role on the adsorption of nucleic acid bases onto ferrihydrite. Adenine adsorption onto ferrihydrite was higher in distilled water compared to artificial seawater. After ferrihydrite was mixed with artificial seawaters or nucleic acid bases, X-ray diffractograms and Fourier transform infrared spectra did not show any change. Surface-enhanced Raman spectroscopy showed that the interaction of adenine with ferrihydrite was not pH-dependent. In contrast, the interactions of thymine and uracil with ferrihydrite were pH-dependent such that, at basic pH, thymine and uracil lay flat on the surface of ferrihydrite, and at acidic pH, thymine and uracil were perpendicular to the surface. Ferrihydrite adsorbed much more adenine than thymine; thus adenine would have been better protected against degradation by hydrolysis or UV radiation on prebiotic Earth.

Trace cancer biomarker quantification using polystyrene-functionalized gold nanorods

We demonstrate the application of polystyrene-functionalized gold nanorods (AuNRs) as a platform for surface enhanced Raman scattering (SERS) quantification of the exogenous cancer biomarker Acetyl Amantadine (AcAm). We utilize the hydrophobicity of the polystyrene attached to the AuNR surface to capture the hydrophobic AcAm from solution, followed by drying and detection using SERS. We achieve a detection limit of 16 ng/mL using this platform. This result shows clinical potential for low-cost early cancer detection.

An experimental and theoretical vibrational study of interaction of adenine and thymine with artificial seawaters: A prebiotic chemistry experiment

Nucleic acid bases play important roles in living beings. Thus, their interaction with salts the prebiotic Earth could be an important issue for the understanding of origin of life. In this study, the effect of pH and artificial seawaters on the structure of adenine and thymine was studied via parallel determinations using FT-IR, Raman spectroscopy and theoretical calculations. Thymine and adenine lyophilized in solutions at basic and acidic conditions showed characteristic bands of the enol-imino tautomer due to the deprotonation and the hydrochloride form due to protonation, respectively. The interaction of thymine and adenine with different seawaters representative of different geological periods on Earth was also studied. In the case of thymine a strong interaction with Sr(2+) promoted changes in the Raman and infrared spectra. For adenine changes in infrared and Raman spectra were observed in the presence of salts from all seawaters tested. The experimental results were compared to theoretical calculations, which showed structural changes due to the presence of ions Na(+), Mg(2+), Ca(2+) and Sr(2+) of artificial seawaters. For thymine the bands arising from C4=C5 and C6=O stretching were shifted to lower values, and for adenine, a new band at 1310cm(-1) was observed. The reactivity of adenine and thymine was studied by comparing changes in nucleophilicity and energy of the HOMO orbital.

Quantitative analysis of entacapone isomers using surface-enhanced Raman spectroscopy and partial least squares regression

Surface-enhanced Raman spectroscopy (SERS) and partial least squares (PLS) regression have been applied for the quantification of entacapone isomers E and Z in solution. Nine mixtures of isomers Z and E in ethanol ranging from 0% to 100% w/w were analyzed, for a total entacapone concentration of 1 × 10(-3) mol L(-1). Upon deposition onto commercially available Klarite® gold plates, highly intense and reproducible SERS spectra were obtained from the entacapone isomers. Based on the spectral measurements, a two-component PLS model for correlation of predicted and real content of the isomers mixtures was developed. Root-mean-square error of the predicted composition was found to be 8% of isomer Z in the isomers mixture, corresponding to the absolute concentration of 8 × 10(-5) mol L(-1) of isomer Z in solution.

Functionalized gold nanoparticles as nanosensor for sensitive and selective detection of silver ions and silver nanoparticles by surface-enhanced Raman scattering

We have developed a surface-enhanced Raman scattering (SERS) nanosensor firstly for Ag ions and Ag nanoparticles detection based on 2-mercaptoisonicotinic acid (2MNA)-functionalized Au nanoparticles. Ag(+) can coordinate with 2MNA resutling in a variation of its SERS spectrum, which is used as a criterion to determine Ag(+) in a solution. This sensor exhibits a detection limit no more than 25 nM and has a high selectivity against other metal ions. More importantly, it can be directly applied in real sample detection.

Quantitative analysis of mononucleotides by isotopic labeling surface-enhanced Raman scattering spectroscopy

A novel surface-enhanced Raman scattering (SERS) approach for accurate quantification of mononucleotides of deoxyribonucleic acid (DNA) is described. Reproducible SERS measurement was achieved by using isotopically labeled internal standard. By measuring the SERS spectra of mononucleotides and its isotope internal standard in combination with multivariate data analysis, the method was successfully applied to quantify mononucleotides. The independent validation of analyte concentrations gave a standard deviation of within 2%, which is comparable to HPLC result. Finally, a mixture of four mononucleotides of DNA was prepared to explore the possibility of quantifying the concentration of label-free, sequence-specific DNA strands by this approach. As compared to liquid chromatography/mass spectrometry (LC/MS), our method can be similarly precise but the SERS measurement is simple, rapid and potentially cheap.