A high sensitivity MEA probe for measuring real time rat brain glucose flux

Design and Evaluation of a Lactate Microbiosensor: Toward Multianalyte Monitoring of Neurometabolic Markers In Vivo in the Brain

Direct in vivo measurements of neurometabolic markers in the brain with high spatio-temporal resolution, sensitivity, and selectivity is highly important to understand neurometabolism. Electrochemical biosensors based on microelectrodes are very attractive analytical tools for continuous monitoring of neurometabolic markers, such as lactate and glucose in the brain extracellular space at resting and following neuronal activation. Here, we assess the merits of a platinized carbon fiber microelectrode (CFM/Pt) as a sensing platform for developing enzyme oxidase-based microbiosensors to measure extracellular lactate in the brain. Lactate oxidase was immobilized on the CFM/Pt surface by crosslinking with glutaraldehyde. The CFM/Pt-based lactate microbiosensor exhibited high sensitivity and selectivity, good operational stability, and low dependence on oxygen, temperature, and pH. An array consisting of a glucose and lactate microbiosensors, including a null sensor, was used for concurrent measurement of both neurometabolic substrates in vivo in the anesthetized rat brain. Rapid changes of lactate and glucose were observed in the cortex and hippocampus in response to local glucose and lactate application and upon insulin-induced fluctuations of systemic glucose. Overall, these results indicate that microbiosensors are a valuable tool to investigate neurometabolism and to better understand the role of major neurometabolic markers, such as lactate and glucose.

Highly sensitive and selective nanostructured microbiosensors for glucose and lactate simultaneous measurements in blood serum and in vivo in brain tissue

Highly sensitive and selective nanostructured lactate and glucose microbiosensors for their in vivo simultaneous determination in rat brain were developed based on carbon fiber microelectrodes (CFM) modified with nanoporous gold (NPG) using the Dynamic Hydrogen Bubble Template (DHBT) method. Electrodeposition of platinum nanoparticles (PtNP) onto the NPG film enhances the sensitivity and the electrocatalytic properties towards H₂O₂ detection. The nanostructured microelectrode platform was modified by glucose oxidase (GOx) and lactate oxidase (LOx) enzyme immobilization. High selective measurements were achieved by covering with a perm-selective layer of electropolymerized m-phenylenediamine, deposition of a Nafion® film and by using a null sensor. The morphological characteristics and electroanalytical performance of the microbiosensors were assessed, by scanning electron microscopy and electrochemical techniques, respectively. The PtNP/NPG/CFM shows a high sensitivity to H₂O₂ (5.96 A M^-1 cm^-2) at 0.36 V vs. Ag/AgCl, with a linear range from 0.2 to 200 μM, and an LOD of 10 nM. The microbiosensors were applied to the simultaneous determination of lactate and glucose in blood serum samples. Moreover, the basal extracellular concentrations of lactate and glucose were measured in vivo in four different rat brain structures. These results support the potential of the microbiosensor to be used as a valuable tool to investigate brain neurochemicals in vivo.

Identifying the pulsed neuron networks' structures by a nonlinear Granger causality method

Background

It is a crucial task of brain science researches to explore functional connective maps of Biological Neural Networks (BNN). The maps help to deeply study the dominant relationship between the structures of the BNNs and their network functions.

Results

In this study, the ideas of linear Granger causality modeling and causality identification are extended to those of nonlinear Granger causality modeling and network structure identification. We employed Radial Basis Functions to fit the nonlinear multivariate dynamical responses of BNNs with neuronal pulse firing. By introducing the contributions from presynaptic neurons and detecting whether the predictions for postsynaptic neurons’ pulse firing signals are improved or not, we can reveal the information flows distribution of BNNs. Thus, the functional connections from presynaptic neurons can be identified from the obtained network information flows. To verify the effectiveness of the proposed method, the Nonlinear Granger Causality Identification Method (NGCIM) is applied to the network structure discovery processes of Spiking Neural Networks (SNN). SNN is a simulation model based on an Integrate-and-Fire mechanism. By network simulations, the multi-channel neuronal pulse sequence data of the SNNs can be used to reversely identify the synaptic connections and strengths of the SNNs.

Conclusions

The identification results show: for 2–6 nodes small-scale neural networks, 20 nodes medium-scale neural networks, and 100 nodes large-scale neural networks, the identification accuracy of NGCIM with the Gaussian kernel function was 100%, 99.64%, 98.64%, 98.37%, 98.31%, 84.87% and 80.56%, respectively. The identification accuracies were significantly higher than those of a traditional Linear Granger Causality Identification Method with the same network sizes. Thus, with an accumulation of the data obtained by the existing measurement methods, such as Electroencephalography, functional Magnetic Resonance Imaging, and Multi-Electrode Array, the NGCIM can be a promising network modeling method to infer the functional connective maps of BNNs.

An Efficient, Recyclable, and Stable Immobilized Biocatalyst Based on Bioinspired Microcapsules-in-Hydrogel Scaffolds

Design and preparation of high-performance immobilized biocatalysts with exquisite structures and elucidation of their profound structure-performance relationship are highly desired for green and sustainable biotransformation processes. Learning from nature has been recognized as a shortcut to achieve such an impressive goal. Loose connective tissue, which is composed of hierarchically organized cells by extracellular matrix (ECM) and is recognized as an efficient catalytic system to ensure the ordered proceeding of metabolism, may offer an ideal prototype for preparing immobilized biocatalysts with high catalytic activity, recyclability, and stability. Inspired by the hierarchical structure of loose connective tissue, we prepared an immobilized biocatalyst enabled by microcapsules-in-hydrogel (MCH) scaffolds via biomimetic mineralization in agarose hydrogel. In brief, the in situ synthesized hybrid microcapsules encapsulated with glucose oxidase (GOD) are hierarchically organized by the fibrous framework of agarose hydrogel, where the fibers are intercalated into the capsule wall. The as-prepared immobilized biocatalyst shows structure-dependent catalytic performance. The porous hydrogel permits free diffusion of glucose molecules (diffusion coefficient: ∼6 × 10(-6) cm(2) s(-1), close to that in water) and retains the enzyme activity as much as possible after immobilization (initial reaction rate: 1.5 × 10(-2) mM min(-1)). The monolithic macroscale of agarose hydrogel facilitates the easy recycling of the immobilized biocatalyst (only by using tweezers), which contributes to the nonactivity decline during the recycling test. The fiber-intercalating structure elevates the mechanical stability of the in situ synthesized hybrid microcapsules, which inhibits the leaching and enhances the stability of the encapsulated GOD, achieving immobilization efficiency of ∼95%. This study will, therefore, provide a generic method for the hierarchical organization of (bio)active materials and the rational design of novel (bio)catalysts.

Characterization of Biosensors Based on Recombinant Glutamate Oxidase: Comparison of Crosslinking Agents in Terms of Enzyme Loading and Efficiency Parameters

Amperometric l-glutamate (Glu) biosensors, based on both wild-type and a recombinant form of l-glutamate oxidase (GluOx), were designed and characterized in terms of enzyme-kinetic, sensitivity and stability parameters in attempts to fabricate a real-time Glu monitoring device suitable for future long-term detection of this amino acid in biological and other complex media. A comparison of the enzyme from these two sources showed that they were similar in terms of biosensor performance. Optimization of the loading of the polycationic stabilization agent, polyethyleneimine (PEI), was established before investigating a range of crosslinking agents under different conditions: glutaraldehyde (GA), polyethylene glycol (PEG), and polyethylene glycol diglycidyl ether (PEGDE). Whereas PEI-free biosensor designs lost most of their meager Glu sensitivity after one or two days, configurations with a 2:5 ratio of dip-evaporation applications of PEI(1%):GluOx(400 U/mL) displayed a 20-fold increase in their initial sensitivity, and a decay half-life extended to 10 days. All the crosslinkers studied had no effect on initial Glu sensitivity, but enhanced biosensor stability, provided the crosslinking procedure was carried out under well-defined conditions. The resulting biosensor design based on the recombinant enzyme deposited on a permselective layer of poly-(ortho-phenylenediamine), PoPD/PEI₂/GluOx₅/PEGDE, displayed good sensitivity (LOD < 0.2 μM), response time (t90% < 1 s) and stability over a 90-day period, making it an attractive candidate for future long-term monitoring of Glu concentration dynamics in complex media.

A Label-Free Microelectrode Array Based on One-Step Synthesis of Chitosan-Multi-Walled Carbon Nanotube-Thionine for Ultrasensitive Detection of Carcinoembryonic Antigen

Carcinoembryonic antigen (CEA) has been an extensively used tumor marker responsible for clinical early diagnosis of cervical carcinomas, and pancreatic, colorectal, gastric and lung cancer. Combined with micro-electro mechanical system (MEMS) technology, it is important to develop a novel immune microelectrode array (MEA) not only for rapid analysis of serum samples, but also for cell detection in vitro and in vivo. In this work, we depict a simple approach to modify chitosan–multi-walled carbon nanotubes–thionine (CS–MWCNTs–THI) hybrid film through one-step electrochemical deposition and the CS-MWCNTs-THI hybrid films are successfully employed to immobilize anti-CEA for fabricating simple, label-free, and highly sensitive electro-chemical immune MEAs. The detection principle of immune MEA was based on the fact that the increasing formation of the antigen-antibody immunocomplex resulted in the decreased response currents and the relationship between the current reductions with the corresponding CEA concentrations was directly proportional. Experimental results indicated that the label-free MEA had good selectivity and the limit of detection for CEA is 0.5 pg/mL signal to noise ratio (SNR) = 3. A linear calibration plot for the detection of CEA was obtained in a wide concentration range from 1 pg/mL to 100 ng/mL (r = 0.996). This novel MEA has potential applications for detecting CEA for the research on cancer cells and cancer tissue slices as well as for effective early diagnosis.

Simultaneous recording of brain extracellular glucose, spike and local field potential in real time using an implantable microelectrode array with nano-materials

Glucose is the main substrate for neurons in the central nervous system. In order to efficiently characterize the brain glucose mechanism, it is desirable to determine the extracellular glucose dynamics as well as the corresponding neuroelectrical activity in vivo. In the present study, we fabricated an implantable microelectrode array (MEA) probe composed of platinum electrochemical and electrophysiology microelectrodes by standard micro electromechanical system (MEMS) processes. The MEA probe was modified with nano-materials and implanted in a urethane-anesthetized rat for simultaneous recording of striatal extracellular glucose, local field potential (LFP) and spike on the same spatiotemporal scale when the rat was in normoglycemia, hypoglycemia and hyperglycemia. During these dual-mode recordings, we observed that increase of extracellular glucose enhanced the LFP power and spike firing rate, while decrease of glucose had an opposite effect. This dual mode MEA probe is capable of examining specific spatiotemporal relationships between electrical and chemical signaling in the brain, which will contribute significantly to improve our understanding of the neuron physiology.

Guiding pancreatic beta cells to target electrodes in a whole-cell biosensor for diabetes

We are developing a cell-based bioelectronic glucose sensor that exploits the multi-parametric sensing ability of pancreatic islet cells for the treatment of diabetes. These cells sense changes in the concentration of glucose and physiological hormones and immediately react by generating electrical signals. In our sensor, signals from multiple cells are recorded as field potentials by a micro-electrode array (MEA). Thus, cell response to various factors can be assessed rapidly and with high throughput. However, signal quality and consequently overall sensor performance rely critically on close cell-electrode proximity. Therefore, we present here a non-invasive method of further exploiting the electrical properties of these cells to guide them towards multiple micro-electrodes via electrophoresis. Parameters were optimized by measuring the cell's zeta potential and modeling the electric field distribution. Clonal and primary mouse or human β-cells migrated directly to target electrodes during the application of a 1 V potential between MEA electrodes for 3 minutes. The morphology, insulin secretion, and electrophysiological characteristics were not altered compared to controls. Thus, cell manipulation on standard MEAs was achieved without introducing any external components and while maintaining the performance of the biosensor. Since the analysis of the cells' electrical activity was performed in real time via on-chip recording and processing, this work demonstrates that our biosensor is operational from the first step of electrically guiding cells to the final step of automatic recognition. Our favorable results with pancreatic islets, which are highly sensitive and fragile cells, are encouraging for the extension of this technique to other cell types and microarray devices.