A colorimetric sensor array for detection and discrimination of biothiols based on aggregation of gold nanoparticles

Developments of sensitive, rapid, and cheap systems for identification of a wide range of biomolecules have been recognized as a critical need in the biology field. Here, we introduce a simple colorimetric sensor array for detection of biological thiols, based on aggregation of three types of surface engineered gold nanoparticles (AuNPs). The low-molecular-weight biological thiols show high affinity to the surface of AuNPs; this causes replacement of AuNPs’ shells with thiol containing target molecules leading to the aggregation of the AuNPs through intermolecular electrostatic interaction or hydrogen-bonding. As a result of the predetermined aggregation, color and UV–vis spectra of AuNPs are changed. We employed the digital mapping approach to analyze the spectral variations with statistical and chemometric methods, including hierarchical cluster analysis (HCA) and principal component analysis (PCA). The proposed array could successfully differentiate biological molecules (e.g., cysteine, glutathione and glutathione disulfide) from other potential interferences such as amino acids in the concentration range of 10–800 μmol L⁻¹.     

Polymer coated sensor array based on quartz crystal microbalance for chemical agent analysis

Quartz crystal microbalance (QCM) gas sensors based on polymeric material were fabricated and their gas response characteristics were examined for four simulant gases of chemical agents, which were dimethyl methyl phosphonate (DMMP), N,N-dimethylacetamide (DMA), 1,5-dichloropentane (DCP) and dichloroethane (DCE). For the selection of appropriate coating materials, both principal component analysis (PCA) and hierarchical cluster methods were applied to a data set collected from 15 QCM sensors for 12 analytes. Four appropriate coating materials were selected after optimizing the correlation between the 15 coating materials and the first four principal component (PC) factors. The four chosen polymers were used as sensitive component for a sensor array, and then PCA is adapted to classify four simulant gases. The results show that the QCM sensor array has high sensitivity and selectivity to four chemical agents.     

A colorimetric and surface-enhanced Raman scattering dual-signal sensor for Hg based on Bismuthiol II-capped gold nanoparticles

The addition of Bismuthiol II to the gold nanoparticles (AuNPs) solution led to the aggregation of AuNPs with a color change from red to blue. As a result, hot spots were formed and strong surface-enhanced Raman scattering (SERS) signal of Bismuthiol II was observed. However, the Bismuthiol II-induced aggregation of AuNPs could be reversed by Hg²⁺ in the system, accompanied by a remarkable color change from blue to red. As evidenced by UV–vis and SERS spectroscopy, the variation in absorption band and SERS intensity was strongly dependent on the concentration of Hg²⁺, suggesting a colorimetric and SERS dual-signal sensor for Hg²⁺. The sensor had a high sensitivity, low detection limits of 2 nM and 30 nM could be achieved by UV–vis spectroscopy and by SERS spectroscopy, respectively. Other environmentally relevant metal ions did not interfere with the detection of Hg²⁺. The method was successfully applied to detect Hg²⁺ in water samples. It was simple, rapid and cost-effective without any modifying or labeling procedure.     

Rare earth ions-enhanced gold nanoclusters as fluorescent sensor array for the detection and discrimination of phosphate anions

The discrimination and detection of phosphate anions have attracted extensive attention due to their important roles in various biological processes. Compared with sensors to detect one individual phosphate at a time, sensor arrays are able to discriminate multiple phosphates simultaneously. In this study, we developed a rare earth ions enhanced AuNCs-based sensor array to achieve facile and rapid identification of phosphate anions (PPi, ADP and ATP). The rare earth ions (i. e., Ce³⁺, Gd³⁺, Tm³⁺ and Yb³⁺) can significantly enhance the fluorescence of AuNCs through aggregation-induced emission effect. And the subsequent addition of phosphate anions can recover the fluorescence of the AuNCs-rare earth ions assembly. Thanks to the different numbers of phosphate group and different steric hindrance effects of phosphate anions, the recovery fluorescence of AuNCs-rare earth ions assembly induced by PPi, ADP or ATP are respectively distinct. Thus the sensor array composed of AuNCs and different rare earth ions is able to distinguish those phosphate anions. Finally, the sensor array was successfully demonstrated to identify the phosphates in blind samples.     

Method of gas mixtures discrimination based on sensor array, temporal response and data driven approach

This work presents a method of gas mixtures discrimination. The principal concept of the method is to apply measurement data provided by a combination of sensors at single time point of their temporal response as input of the discrimination models. The pattern data combinations are selected for classes of target gases based on the criterion of 100% efficient discrimination. Combinations of sensors and time points, which provide pattern data combinations in course or repeated measurements, are encoded in the form of addresses. The designer of sensor system is responsible for their selection and they are included in the software of the final instrument. The study of the method involved the discrimination of gas mixtures composed of air and single chemical: hexane, ethanol, acetone, ethyl acetate and toluene. Two sensor arrays were utilized. Each consisted of six TGS sensors of the same type. The dynamic operation of sensors was employed. As an example the stop-flow mode was chosen. The work provides the evidence of the existence of sensor combinations and time points, which are successful in discrimination of studied classes of target gases. The persistence of addresses was discussed considering the ability of sensor array to recognize analytes, variability of repeated measurement results, number of repeated measurements and a twin sets of sensors. Altogether, the validity of the method was demonstrated.     

Evaluation of chemometric techniques for the identification and quantification of solvent mixtures using a thin-film metal oxide sensor array

An evaluation was made of suitable chemometric techniques that can be used in both the selection of suitable sensors for a sensor array and the subsequent identification and quantification of analytes using such a device. Data fro a thin-film tin oxide-based gas sensor were obtained for a range of analytes, both pure and in mixtures and analysed using several chemometric techniques, including principal component analysis, cluster analysis and partial least squares. It was shown that the array produced a characteristic response pattern for the analytes, and this was then used for the identification of ethyl acetate, acetone, ethanol and pentane, and the determination of ethanol in various mixtures. The chemometric techniques were not only used to identify and quantify components in the solvent mixture but also indicated which of the array elements were acting independently and the level of interaction which was occurring. The results obtained describe a chemometric and fabrication protocol for sensor array design.     

基于分子印迹聚合物的化学发光传感器测定尿样中的甲福明

合成了甲福明的分子印迹聚合物,以此聚合物为识别物质,在线分离富集甲福明,建立了一种测定甲福明的流动式化学发光但感器。N-溴代丁二酰亚胺(NBS)和荧光素与甲福明发生化学反应,产生强的化学发光。甲福明质量浓度在2×10-8~8×10-6g/mL范围内同发光强度成良好线性关系,方法的检出限为6×10-9g/mL,相对标准偏差小于5%(n=9)。选择性实验表明将分子印迹聚合物作为识别物质应用于化学发光分析中,能大大提高化学发光分析方法的选择性。该传感器可逆性强、稳定性好,可重复使用100次以上,已用于人体尿样中甲福明的测定。     

A colorimetric assay for d-Penicillamine in urine and plasma samples based on the aggregation of gold nanoparticles

We report herein the development of a highly sensitive colorimetric method for detection of d-Penicillamine using citrate-capped gold nanoparticles (AuNPs). This assay relies upon the distance-dependent of gold nanoparticles surface plasmon resonance band of gold nanoparticles. By replacing the thiol-containing chelator drug, d-Penicillamine, with citrate on the gold nanoparticles surface, a new peak appearing at a longer wavelength intensifies and shifts further to the red from the original peak position due to aggregation of gold nanoparticles which depends on ionic strength, gold nanoparticles and d-Penicillamine concentration. During this process, the plasmon band at 521 nm decreases gradually along with the formation of a new red-shifted band at 630 nm. The calibration curve which is derived from the ratio intensities of absorbance at longer wavelength (630 nm) to original wavelength (521 nm) displays a linear relation in the range of 5.0 × 10^?6–3.0 × 10^?4 M d-Penicillamine. Lower limit of detection for d-Penicillamine, at the signal-to-noise ratio of 3 (3σ), was 3.8 × 10^?6 M. The developed methodology was successfully applied for the determination of d-Penicillamine in human urine and plasma.     

A solid colorimetric sensor for the analysis of amphetamine-like street samples

A solid sensor obtained by embedding 1,2-naphthoquinone-4-sulfonate (NQS) into polydimethylsiloxane/tetraethylortosilicate/silicon dioxide nanoparticles composite has been developed to identify and determine amphetamine (AMP), methamphetamine (MAMP), 3,4-methylenedioxymetamphetamine (MDMA) and 3,4-methylenedioxyamphetamine (MDA). The analytes are derivatized inside the composite for 10 min to create a colored product which can be then quantified by measuring the diffuse reflectance or the color intensity after processing the digitalized image. Satisfactory limits of detection (0.002–0.005 g mL⁻¹) and relative standard deviations (<10%) have been achieved. The proposed kit has been successfully validated and applied to the analysis of amphetamine-like drugs street samples. The kit allows the in-situ screening of the mentioned illicit drugs owing to its simplicity, rapidity and portability, with excellent sensor stability and at a very low-cost.     

Determination of calcium and total hardness in natural waters using a potentiometric sensor array

The determination of calcium and total hardness in natural waters is carried out with a potentiometric sensor array which consists of a series of ion-selective electrodes (ISEs) for Ca²⁺, Mg²⁺, NH₄⁺, K⁺, Na⁺, Li⁺, and H⁺. The selectivity of the calcium and magnesium ISEs is not fully achieved as other cation species may interfere with the analysis. The proposed sensor array device can overcome this drawback since it can take advantage of the cross-selectivities of cation species towards each ISE. In this approach, the multivariate data generated by the sensor array results in a richer source of analytical information which allows the quantification of calcium and total hardness in the water samples by means of chemometric methods. Results obtained are in reasonable concordance with those given by the standard method based on complexometry.     

Quartz crystal microbalance sensor array for the detection of volatile organic compounds

A sensor array system consisting of five quartz crystal microbalance (QCM) sensors (four for measuring and one for reference) and an artificial neural network (ANN) method is presented for on-line detection of volatile organic compounds. Three ionic liquids, 1-butyl-3-methylimidazolium chloride (C₄mimCl), 1-butyl-3-methylimidazolium hexafluorophosphate (C₄mimPF₆), 1-dedocyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide (C₄mimNTf₂), and silicone oil II, which is widely used as gas chromatographic stationary phase, have been selected as sensitive coatings on the quartz surface allowing the sensor array effective to identify chemical vapors, such as toluene, ethanol, acetone and dichloromethane. The success rate for the qualitative recognition reached 100%. Quantitative analysis has also been investigated, within the concentration range of 0.6-6.1 mg/L for toluene, 0.9-7.5 mg/L for ethanol, 2.8-117 mg/L for dichloromethane, and 0.7-38 mg/L for acetone, with a prediction error lower than 8%.     

Dual-response colorimetric sensor array for the identification of amines in water based on supramolecular host-guest complexation

Amines have been found as a challenging compound class in previous works on chemical tongues. Herein, we describe the successful application of libraries based on host-guest inclusion complexes in cyclodextrins (CDs) and cucurbiturils (CBs) for the discrimination of primary, secondary, tertiary, aliphatic and aromatic as well as linear and branched amines in water. Besides the clear need for new detection, identification and quantification techniques of organic compounds in water, the main advantage of our approach is that an array made by combining six simple basic dyes with seven commercial organic capsules allows a perfect discrimination among 14 amines (see list in Table S1 in Supplementary data) with only very subtle structural differences.     

Rapid analysis of L-dopa in urine samples using gold nanoelectrode ensembles

This work describes the application of a three-dimensional gold nanoelectrode ensembles (GNEE) for monitoring l-dopa in standards and human urine samples using flow injection analysis (FIA) with amperometric detection. Analytical results reveal that the GNEE exhibited better electrocatalytic activity than a gold disk or glassy carbon electrode. Under optimal conditions of l-dopa analysis at GNEE, the calibration plot has a linear range of 5-300 ng/mL with a coefficient of variation (CV) of 3.1% in pH 7.0 phosphate buffer saline (PBS, pH 7.0). The detection limit was 3.0 ng/mL for FIA. The high precision and sensitivity of GNEE provides a feasible means of directly determining l-dopa in urine samples.     

A high performance liquid chromatography-electrochemical array method for the measurement of oxidative/nitrative changes in human urine

Oxidative stress has been implicated in various pathologies as well as in environmental pollutant-induced negative health outcomes. In this work we have developed an analytical method to measure oxidative stress markers namely m-, o-tyrosine, 3-chlorotyrosine, 3-nitrotyrosine, and the DNA damage marker 8-hydroxy deoxyguanosine in human urine. The method involves the base hydrolysis of the urine sample followed by solid phase extraction of target analytes using a reverse phase polymeric sorbent column prior to the HPLC-EC analysis. The recovery studies indicated that the overall method recovery for all analytes were >60%. The limit of quantification of all target analytes was <10 nM with a linear range from 2 nM to 150 μM. The applicability of this method is demonstrated by analyzing the above markers in healthy human urine (n = 10) samples.     

Selective recognition and discrimination of water‐soluble azo dyes by a seven‐channel molecularly imprinted polymer sensor array

A seven‐channel molecularly imprinted polymer sensor array was prepared and characterized by scanning electron microscopy, Fourier transform infrared spectroscopy, UV‐Vis spectroscopy, and nitrogen physisorption studies. The results revealed that the imprinted polymers have distinct‐binding affinities from those of structurally similar azo dyes. Analysis of the UV‐Vis spectral response patterns of the seven dye analytes against the imprinted polymer array suggested that the different selectivity patterns of the array were closely connected to the imprinting process. To evaluate the effectiveness of the array format, the binding of a series of analytes was individually measured for each of the seven polymers, made with different templates (including one control polymer synthesized without the use of a template). The response patterns of the array to the selected azo dyes were processed by canonical discriminant analysis. The results showed that the molecularly imprinted array was able to discriminate each analyte with 100% accuracy. Moreover, the azo dyes in two real samples, spiked chrysoidin in smoked bean curd extract and Fanta lime soda (containing tartrazine), were successfully classified by the array.     

Deconvolution and quantitation of unresolved mixtures in liquid chromatographic-diode array detection using evolving factor analysis

Summary A recently developed self-modeling curve resolution method based in different factor analysis techniques has been applied for the first time to the study of liquid-chromatography-diode array data under situation where the separation of two components is not achieved. Two applications are reported: the resolution and quantitation of a coeluted mixture of carbamate pesticides pirimicarb and 1-naphthol, and the estimation of the concentration profiles of the double peak obtained in the elution of the triazine metabolite chlorodiamino-s-triazine. Different methods of quantitation are compared, including Evolving Factor Analysis and Rank annihilation. Quantitation from the area of the elution profiles once the component spectra have been transformed for their area contribution to the signal, gives a relative composition for pirimicarb and naphthol pesticides which agrees with the known sample composition. In the case of the unknown triazine mixture, an approximate quantitation of the two peaks obtained for this metabolite is obtained by assuming equal signal contribution or equal maximum absorbance of the individual spectra of the two detected components.     

电氧化异丙肾上腺素的纳米复合电催化剂：用作传感器

在金纳米粒子(AuNPs)上经苯硫酚衍生物(3,4二羟基苯基-偶氮-苯硫酚, DAT)自组装制得了一种新型纳米复合物,用于修饰玻璃碳电极(GCE/AuNP-DAT).采用循环伏安法研究了该新型电极的性质,并将其用作异丙肾上腺素(IP)电催化剂,考察了该纳米复合物的电催化活性,从而得到反应机理和催化反应速率常数.由于GCE/AuNP-DAT电极对尿酸氧化没有电催化活性,因此可将IP的氧化信号从该改进电极中分离出来,从而排除了尿酸对IP测定的干扰.该电极可作为传感器,当用于差动脉冲伏安法测定IP时,线性动态范围为1.0–1500.0μmol/L,检测极限为0.46μmol/L.     

Highly chemoselective colorimetric/fluorometric dual-channel sensor with fast response and good reversibility for the selective and sensitive detection of Cu2+

A novel colorimetric and fluorometric dual-channel sensor DA with a favorable optical property and high specificity via a facile synthesis for Cu²⁺ was developed. DA showed a remarkably rapid response and high selectivity for Cu²⁺ over other metal ions with low detection limit of 15.1 nM. The sensing mechanism of DA for Cu²⁺ was based on the chelation-enhanced fluorescence quenching (CHEQ) mechanism, and further confirmed by optical measurements, FTIR, HRMS and DFT calculations. Importantly, DA for sensing Cu²⁺ possessed excellent sensing performances including colorimetric and fluorometric dual-mode detection, fast response, good reversibility, wide pH response range and strong anti-interference ability. Moreover, the DA could be not only applied to quantitatively detect Cu²⁺ in environmental water, food and drink samples, but also show highly colorimetric detection of Cu²⁺ on test strips and silica, indicating its possibility to be utilized as a convenient and low-cost sensor for environment and food monitoring.     

Using combinations of principal component scores from different spectral ranges in near-infrared region to improve discrimination for samples of complex composition

Principal component analysis (PCA) is widely used as an exploratory data analysis tool in the field of vibrational spectroscopy, particularly near-infrared (NIR) spectroscopy. PCA represents original spectral data containing large variables into a few feature-containing variables, or scores. Although multiple spectral ranges can be simultaneously used for PCA, only one series of scores generated by merging the selected spectral ranges is generally used for qualitative analysis. Alternatively, the combined use of an independent series of scores generated from separate spectral ranges has not been exploited.The aim of this study is to evaluate the use of PCA to discriminate between two geographical origins of sesame samples, when scores independently generated from separate spectral ranges are optimally combined. An accurate and rapid analytical method to determine the origin is essentially required for the correct value estimation and proper production distribution. Sesame is chosen in this study because it is difficult to visually discriminate the geographical origins and its composition is highly complex. For this purpose, we collected diffuse reflectance near-infrared (NIR) spectroscopic data from geographically diverse sesame samples over a period of eight years. The discrimination error obtained by applying linear discriminant analysis (LDA) was improved when separate scores from two spectral ranges were optimally combined, compared to the discrimination errors obtained when scores from singly merged two spectral ranges were used.