我国电化学血糖传感器的产业化发展

回顾葡萄糖的电化学分析测试历史,讨论目前我国电化学葡萄糖传感器的研究、开发和生产的现状,展望今后的发展趋势。还讨论了相关血糖测试仪器的研究进展,包括血糖测试仪器的电路集成设计和软件开发以及目前国内血糖测试系统的市场发展现状等。     

A nano-copper electrochemical sensor for sensitive detection of chemical oxygen demand

Copper nanoparticle (nano-Cu) was electrodeposited on the surface of Cu disk electrode under −1 V for 60 s, and then used to construct an electrochemical sensor for chemical oxygen demand (COD). The electrochemical oxidation behavior of glycine, a standard compound for evaluating the COD, was investigated. The potential shifts negatively, and the current increases greatly at the surface of nano-Cu, indicating remarkable enhancement effect on the detection of COD. The analytical conditions such as electrolyte, deposition potential, deposition time and detected potential were studied. As a result, a sensitive, simple and rapid electroanalytical method was developed for COD using amperometric detection. The linear range is from 4.8 to 600 mg L⁻¹, and the limit of detection is as low as 3.6 mg L⁻¹. Moreover, this method exhibits high tolerance level to chloride ion, and 0.02 M chloride ion has no influence. Finally, the sensor was used to detect the COD values of different water samples, and the results were testified by the standard dichromate method.     

Electrochemical sensor for simultaneous detection of ascorbic acid, uric acid and xanthine based on the surface enhancement effect of mesoporous silica

The measurement of ascorbic acid (AA), uric acid (UA) and xanthine (XA) is very important in the clinical diagnosis because many diseases have been found to be associated with their concentrations. Herein, an electrochemical sensor using mesoporous SiO₂ as sensing material was firstly developed for the simultaneous detection of AA, UA and XA. With distinctive properties such as uniform porous networks, large surface area and high sorption ability, the mesoporous SiO₂ sensor exhibits remarkable surface enhancement effect, and greatly increases the response signals of AA, UA and XA. In addition, the electrochemical responses of coexistence of AA, UA and XA were studied, and three well-shaped oxidation peaks were observed at 0.00, 0.25 and 0.63 V. Further studies suggest that their oxidation takes place independently and has no mutual interference. This sensor possesses high sensitivity, and the limit of detections are 3.0 × 10⁻⁶ mol L⁻¹, 1.0 × 10⁻⁷ mol L⁻¹ and 7.5 × 10⁻⁷ mol L⁻¹ for AA, UA and XA. Finally, the mesoporous SiO₂ sensor was successfully employed to detect AA, UA and XA in the urine and blood serum samples.     

Pt-Au二元双金属/氧化石墨烯电化学传感器同时检测尿酸及多巴胺的应用研究

尿酸(UA)是人体最基础的代谢产物,多巴胺(DA)是一种重要的神经递质。二者同时存在于体液当中,其含量对于人体的健康有着极大的影响,因此实现快速、高效、准确的同时检测具有非常重要的意义。该文研制了一种基于Pt-Au二元双金属负载石墨烯的电化学传感器用于尿酸和多巴胺的测定,结果表明Pt-Au和石墨烯的纳米复合物对尿酸和多巴胺具有非常好的催化氧化作用,并且能实现峰的分离(ΔE>200mV),为尿酸和多巴胺的同时测定提供了有力条件。该传感器对尿酸和多巴胺同时测定的检测下限分别为1.996μmol/L和0.999μmol/L,线性范围分别为17.417μmol/L～1259.357μmol/L和2.486μmol/L～260.141μmol/L。基于Pt-Au二元双金属和石墨烯的电化学传感器具有制作简单方便,成本低廉且具有良好的重现性,用于实际样品的同时测定也得到较好的效果。     

A disposable electrochemical immunofiltration test strip for rapid detection of α-fetoprotein

A disposable electrochemical immunofiltration test strip for the rapid detection of α-fetoprotein (AFP) was developed. The test strip was constructed by assembly of screen-printed carbon electrodes, absorption-water pad, nitrocellulose membrane modified by anti-AFP antibody and glass fiber membrane conjugated with ferrocene monocarboxylic acid (FC) labeling AFP. The analytical system utilizes flow-through immunofiltration and competitive immunoassay techniques in combination with an amperometric sensor. The parameters affecting the immunoassay such as selection of filter membrane, membrane pore-size, and antibody binding capacity were investigated and optimized. The immunofiltration system allows us to specifically and directly detect AFP in serum with a low detection limit of 6 ng/mL. The working range is from 6 to 500 ng/mL with an overall analysis time of 5 min for one sample. This electrochemical immunoassay system enabled us to construct a novel point-of-care testing device for the monitoring of biomarker including AFP.     

Two-dimensional molecular imprinting approach for the electrochemical detection of trinitrotoluene

In this work, we demonstrated a sensitive and selective electrochemical sensing protocol for the detection of TNT prepared from alkanethiols self-assembled on AuNPs modified glassy carbon (GC) electrode with preadsorbed templates of TNT. It demonstrated that the 2D molecular imprinting monolayers (MIMs) can provide a better site accessibility and lower mass-transfer resistance, while the AuNPs can enhance electrode conductivity, facilitate the electron transfer and increase the amount of TNT-imprinted sites. The prepared sensor showed not only high selectivity toward TNT in comparison to other similar nitroaromatic compounds (NACs), but also a wide linear range over TNT concentration from 4.0 × 10⁻⁸ to 3.2 × 10⁻⁶ M with a detection limit of 1.3 × 10⁻⁸ M (S/N = 3). Moreover, the imprinted sensor has been applied to the determination of TNT in spiked environmental water samples and shows promise for fast and sensitive measurement of trace levels of TNT in real samples.     

基于NaOH刻蚀玻碳电极的电化学传感器在检测膀胱癌DNA中的应用

制备了一种基于活化的玻碳电极的新型电化学DNA生物传感器,可用于膀胱癌DNA的检测.通过循环伏安法(CV)实现玻碳电极在NaOH溶液中的刻蚀,使电极表面负载大量官能团,为DNA提供连接位点,由Laviron方程计算得到玻碳电极表面的羧基浓度为 1.022×10-6 mol/cm2.亚甲基蓝(MB)作为电化学检测的杂交指示剂.采用原子力显微镜(AFM)对刻蚀后的电极进行了形貌表征.在最优杂交条件下,通过差分脉冲法(DPV)计算出最佳检测限为5.677×10-13 mol/L(n=5),适用目标 DNA浓度范围1×10-8 mol/L~1×10-12 mol/L.该传感器有望用于实际样品中膀胱癌DNA的快速检测.     

基于核酸适体和纳米材料构建电化学生物传感器用于多巴胺的检测

该文探究了一种基于核酸适体和纳米金包四氧化三铁（Au@Fe,041纳米粒子所构建的新型电化学生物传感器用于多巴胺（DA）的检测。首先,在玻碳电极（GCE）表面电沉积一层纳米金（nano—Au）用于多巴胺适体（DBA）的固定。然后HT做为封闭剂以减少非特异性吸附。接着通过与DBA的特异性结合将DA固载于电极表面。在EDC／NHS作用下,生物素（Bio）的羧基与DA的氨基结合,最后通过生物素与亲和素特异性识别作用将含有电化学活性物质硫堇的纳米复合材料固定于电极表面,制得夹心型的适体传感器。在最优条件下．该传感器对0．001nmol／L-100nmol／LDA的检测具有良好的电流响应,检出限0．33pmol／LfS／N=31。该适体传感器具有操作简单、操作简便、选择性好、灵敏度高、检测范围广、检出限低的优点。     

纳米Au修饰电化学传感器直接检测液相中沙林的研究

采用电势阶跃法,在Au电极表面修饰纳米Au,制备出的电化学传感器采用循环伏安法直接检测液相中的沙林,探讨了检测沙林的电化学反应机理.研究发现,检测沙林中,在1.4～0.1 V范围循环伏安扫描之前,预先进行2.0～-2.0V循环伏安扫描,是实现电化学方法检测沙林的重要先决条件.实验表明,纳米Au修饰Au电极表面后,提高了...     

A mid-infrared optical fibre sensor for the detection of carbon monoxide exhaust emissions

An optical fibre presented is capable of monitoring the presence of carbon dioxide and carbon monoxide in the exhaust system of petrol engines. At present there exists no commercial sensor, which is capable of providing online measurements of these exhaust gases as required by European legislation. The design of this sensor using low cost and compact mid-infrared components, which make it suitable for insertion into a vehicle, is presented. Results are presented for 200 ppm step changes in concentration of carbon monoxide supplied from a laboratory controlled supply is presented.     

基于鼠精细胞的味觉阻抗传感器 用于苦味物质检测的研究

本文设计了一种基于雄鼠精细胞的细胞阻抗传感器用于苦味物质的特异性检测.雄鼠精细胞内含有大量T2Rs受体(G蛋白偶联受体)可以对苦味物质产生特异性响应,苦味受体被苦味物质激活后产生的响应会引起细胞形态骨架的变化,从而可以被细胞阻抗传感器检测.本文探索了实验的最佳细胞密度,检测了苯硫脲和奎宁两种常见的苦味物质的响应,苯硫脲检测范围为10μmol/L~200μmol/L,检出限为4μmol/L;奎宁检测范围为62.5μmol/L~1000μmol/L,检出限为40μmol/L.传感器阻抗值增量与苦味物质浓度呈一定的线性相关性.此外,论文对该味觉传感器的特异性进行了测试分析,表明了基于细胞传感器的检测方法为代替动物和人的苦味测试提供了一种可能的新的手段.     

A framework for use of wireless sensor networks in forest fire detection and monitoring

Forest fires are one of the main causes of environmental degradation nowadays. Current surveillance systems for forest fires lack in supporting real-time monitoring of every point of a region at all times and early detection of fire threats. Solutions using wireless sensor networks, on the other hand, can gather sensory data values, such as temperature and humidity, from all points of a field continuously, day and night, and, provide fresh and accurate data to the fire-fighting center quickly. However, sensor networks face serious obstacles like limited energy resources and high vulnerability to harsh environmental conditions, that have to be considered carefully. In this paper, we propose a comprehensive framework for the use of wireless sensor networks for forest fire detection and monitoring. Our framework includes proposals for the wireless sensor network architecture, sensor deployment scheme, and clustering and communication protocols. The aim of the framework is to detect a fire threat as early as possible and yet consider the energy consumption of the sensor nodes and the environmental conditions that may affect the required activity level of the network. We implemented a simulator to validate and evaluate our proposed framework. Through extensive simulation experiments, we show that our framework can provide fast reaction to forest fires while also consuming energy efficiently.     

A dual enzyme electrochemical assay for the detection of organophosphorus compounds using organophosphorus hydrolase and horseradish peroxidase

Neurotoxic organophosphorus (OP) compounds are commonly used as chemical warfare agents and pesticides. Due to their high toxicity, rapid and sensitive field detection of these compounds has been an ongoing topic of interest. Biosensors made with organophosphate hydrolase enzyme (OPH) are generally designed to either amperometrically detect an electroactive leaving group produced following enzymatic cleavage, or to potenitometrically detect the pH change that occurs during cleavage. Since OPs are more likely to have phenolic leaving groups as compared to electroactive leaving groups, we have developed a new amperometric dual enzyme electrochemical assay that enables the detection of a broad class of OP compounds using the OPH enzyme combined with horseradish peroxidase (HRP). The assay has been applied to the detection of dichlofenthion, which does not have an electroactive leaving group and is not a commonly investigated OPH substrate. Using reverse phase HPLC, we have determined the Michaelis-Menten kinetic parameters of an engineered OPH enzyme to be K_M = 0.11 ± 0.02 mM and k_cat = 0.046 ± 0.003 s⁻¹ with dichlofenthion as the substrate. Detection of the phenolic leaving group from the OPH enzyme reaction using the HRP electrode is carried out at −50 mV vs. Ag/AgCl where the noise and background are low and interferences are negligible. After optimization of the solution pH, the dual enzyme biosensor was found to have a limit of detection (LOD) of 24 μM (7.6 ppm), and a sensitivity of 0.095 ± 0.024 nA/μM for dichlorofenthion. By detecting the phenolic leaving groups from the OP targets using the HRP electrode, biosensors made using this new platform have the potential to detect a broad range of important OP compounds.     

A metallic oxide gas sensor array for a selective detection of the CO and NH3 gases

An analysis of single gases using non-selective sensor elements is presented. It contains two steps: the identification of an unknown substance and the estimation of its concentration. To prepare the identification step, a calibration procedure is done to associate a class with each definite gas. In order to do this classification, the signals of the sensor array are transformed into quantities independent of the gas concentration but characteristic for its chemical compound. Then, the analysis parameters of an unknown substance allow to identify it with one of the calibration classes. After the identification of the gas, its concentration can be estimated with the model which is specific for each class of a single gas. The accuracy of this estimation is discussed.     

基于混合神经网络的O3质量浓度软测量

在线臭氧测试仪价格昂贵。用神经网络与机理分析结合的软测量方法，探讨了高效臭氧发生装置中臭氧质量浓度的在线测量。试验表明，这种混合软测量方法是有效的，为臭氧质量浓度的现场测量提供了一个新思路。     

Enantioselective recognition of chiral mandelic acid in the presence of Zn(II) ions by l-cysteine-modified electrode

An obviously enantioselective strategy for the recognition of mandelic acid (MA) enantiomers in the presence of Zn(II) ions on a l-cysteine (l-Cys) self-assembled gold electrode is described. The high recognition of MA was evaluated via electrochemical impedance spectroscopy and cyclic voltammetry. After the modified electrode interacted with R- or S-MA solution containing Zn(II) ions for 10 min, larger electrochemical response signals were observed for R-MA. Time dependencies of the enantioselective interaction for the modified electrode with the solitary Zn(II) solution and MA enantiomers solutions containing Zn(II) were also investigated. The results showed that the enantioselective recognition was caused by the selective formation of Zn complex with l-Cys and MA enantiomers. In addition, the enantiomeric composition of R- and S-MA enantiomer mixtures could be monitored by measuring the current responses of the sample.     

A rapid and selective method for monitoring the growth of coliforms in milk using the combination of amperometric sensor and reducing of methylene blue

A novel method for monitoring the growth of coliforms in milk was developed based on measuring the current change in an amperometric sensor. The sensor consists of a circuit with a homemade potentiostat and a pair of electrodes. The electrode was immersed in milk samples containing methylene blue with various concentrations of bacterial inoculums. The microbial metabolism led to the reduction of methylene blue resulting in a change of current. The time required to identify readily detectable change (detection time, DT) provided an approximate measurement of the amount of microorganisms in the initial inoculums. The sensor system used in this study has the selectivity towards coliform bacteria such as Escherichia coli and Enterobacter aerogenes. The calibration curve of DT against concentration of coliform showed a linear correlation coefficient (R² = 0.9192) over the range of 10²–10⁸ CFU/mL. The sensor was able to detect the coliform bacteria at initial concentrations of 10⁵ CFU/mL within 6 h, making it suitable for use in real-time monitoring of bacterial growth. This system has potential application in the detection of coliform concentration in milk at dairy farms when a proper selective media is designed.     

A variance shift model for detection of outliers in the linear mixed model

A variance shift outlier model (VSOM), previously used for detecting outliers in the linear model, is extended to the variance components model. This VSOM accommodates outliers as observations with inflated variance, with the status of the ith observation as an outlier indicated by the size of the associated shift in the variance. Likelihood ratio and score test statistics are assessed as objective measures for determining whether the ith observation has inflated variance and is therefore an outlier. It is shown that standard asymptotic distributions do not apply to these tests for a VSOM, and a modified distribution is proposed. A parametric bootstrap procedure is proposed to account for multiple testing. The VSOM framework is extended to account for outliers in random effects and is shown to have an advantage over case-deletion approaches. A simulation study is presented to verify the performance of the proposed tests. Challenges associated with computation and extensions of the VSOM to the general linear mixed model with correlated errors are discussed.     

A proteomic approach combining MS and bioinformatic analysis for the detection and identification of biomarkers of administration of exogenous human growth hormone in humans

An integrated MS-based proteomic approach is described that combines MALDI-MS and LC-MS with artificial neural networks for the identification of protein and peptide biomarkers associated with recombinant human growth hormone (rhGH) administration. Serum from exercised males administered with rhGH or placebo was analysed using ELISA to determine insulin-like growth factor-I concentrations. Diluted serum from rhGH- and placebo-treated subjects was analysed for protein biomarkers by MALDI-MS, whereas LC-MS was used to analyse tryptically digested ACN-depleted serum extracts for peptide biomarkers. Ion intensities and m/z values were used as inputs to artificial neural networks to classify samples into rhGH- and placebo-treated groups. Six protein ions (MALDI-MS) correctly classified 96% of samples into their respective groups, with a sensitivity of 91% (20 of 22 rhGH treated) and specificity of 100% (24 of 24 controls). Six peptide ions (LC-MS) were also identified and correctly classified 93% of samples with a sensitivity of 90% (19 of 21 rhGH treated) and a specificity of 95% (20 of 21 controls). The peptide biomarker ion with the highest significance was sequenced using LC-MS/MS and database searching and found to be associated with leucine-rich α-2-glycoprotein.