Results of correlation analysys of striatal neurochemical changes during neural activation.
Neurochemical pathways involved in brain physiology or disease pathogenesis are mostly unknown either in physiological conditions or in neurodegenerative diseases. Nowadays the most frequent usage for biotelemetry is in medicine, in cardiac care units or step-down units in hospitals, even if virtually any physiological signal could be transmitted (FCC, 2000; Leuher, 1983; Zhou et al., 2002). In this chapter we present a wireless device connected with microsensors and biosensors capable to detect real-time variations in concentrations of important compounds present in central nervous system (CNS) and implicated in brain energetic metabolism (Bazzu et al., 2009; Calia et al., 2009).
Molecular Oxygen (O2), an essential molecule for life, is utilized not only for cellular respiration but also for biosynthesis and metabolism of various important biomolecules such steroids, eicosanoids and neuroactive substances (Watanabe et al., 1997). It is also implicated in several biochemical reactions involving, for instance, ATP in the brain (Bazzu et al., 2009). To monitor istantaneous oxygen concentrations and relative variations could give important information about brain energetic metabolism related to glucose (Fillenz, 2005) or lactate consumption (Aubert et al., 2005). Eletrochemical reduction of oxygen is amperometrically obtained by means of complex transformations occurring at a carbon-epoxy sensor surface by applying a potential of -400 mV
Because of its anatomical characteristics and physiology, the central nervous system (CNS) is assumed to be particularly sensitive to oxidative stress (Emerit et al., 2005). Oxidative stress in CNS is now known as responsible for involvement of reactive oxygen species (ROS) and reactive nitrogen species (RNS). This particular kind of stress is crucial for the modulation of fundamental cellular functions as apoptosis, calcium mobilization, ion transport and all phenomena involved in excitotoxicity (Emerit & Edeas, 2005). Oxidative stress takes place from a disparity, involving the physiological antioxidant capability and free radicals synthesis (Andersen, 2004), so the dynamics concerning antioxidants in CNS are extremely important.
Ascorbic acid (AA) is the most important component of antioxidant pool in the brain (Serra et al., 2002). Low molecular weight antioxidant AA is a water soluble vitamin that owns radical scavenger properties against ROS and RNS (Serra et al., 2002). As it is not produced in human organism but introduced with diet (Hediger, 2002), the presence of a specific transporter (SVCT2) allows its cytosolic internalization in neurons. Ascorbic acid is readily oxidized to dehydroascorbate (DHAA) which can undergo irreversible hydrolysis to 2,3-diketo-L-gulonic acid, but because of its crucial role in CNS, DHAA is easily converted to the reduced form for preventing vitamin C depletion. AA is as well implicated in the protection against excitotoxicity due to high glutamate concentration through ascorbate-glutamate hetero-exchange (Rice, 2000). Ascorbic acid is readily oxidized on epoxy-carbon electrode surface at + 120 mV against Ag/AgCl as follows:
Several biologically interesting compounds are not directely oxidizable at a sensor surface, in this case it is needed a biosensor (Pantano et al., 1995). Biosensor combines a trasducer with an enzyme that is capable to give sensitivity and selectivity to the device (Scheller et al., 1997).
Glucose (GLU) is actively involved in ATP synthesis and its concentration in extracellular spaces is the most important factor for energetic metabolism (Lowry et al., 1998; Magistretti et al., 1999, Fillenz et al., 2005). GLU detection is possible by means of loading on a Pt surface transducer glucose oxidase (GOx) enzyme. GOx is covalently linked with flavin adenine dinucleotide (FAD) (Serra et al., 2007) and is extremely reliable because of its good sensitivity to the enzyme substrate and high stability when immobilized on Pt electrodes by means of poly-orthophenylenediamine (OPD) (Wilson et al., 1992; Lowry et al., 1998). The biosensor-based detection of GLU occurs as follows:
As glucose, lactate (LAC) is an important molecule involved in brain energetic metabolism as product of glicolysys (Fillenz, 2005) or energetic substrate for neurons (Magistretti et al., 1999). LAC is oxidized by lactate oxidase (LOx), an enzyme with a covalently-linked FAD cofactor (Serra et al., 2007). After the oxidation of the substrate, the further oxidation of FADH2 to FAD+ produces H2O2 in the presence of O2.
The application of a positive potential (+700 mV
where the amount of current produced by the previous oxidation (8) is proportional to the quantity of substrate (GLU or LAC) transformed by the enzyme. The intrinsic chemical characteristics of each indicated molecule allow using specific telemetric devices able to work in oxidation mode (Calia et al., 2009) or in reduction mode (Bazzu et al., 2009; Calia et al., 2009). In this chapter we describe the implementation of a distributed biosensor NET, composed by implantable biotelemetry devices and derived from previously published systems (Bazzu et al., 2009; Calia et al., 2009), successfully used in conjunction with micro-biosensors for the
2. Biotelemetric system hardware
The electronic circuit of the implantable biotelemetric device (Figure 1) was built using surface mount components and comprised two different parts: the amperometric module and the microcontroller/transceiver module.
As schematized in Figure 2 and 3, the amperometric module was made soldering a quad operational amplifier (MCP6042), a Zener diode (ZXRE4001), two resistors, a potentiomenter and one capacitor on a 28 mm x 17 mm PCB. The MCP6042 can operate from a single-supply voltage with “rail-to-rail” inputs and outputs; it has been designed for micropower applications consuming only 600 nA per OPA with low input bias current (1 pA) and high input resistance (>1013Ω).
The zener diode plays a pivotal role in the amperometric circuitry; as bandgap voltage reference, it generates a fixed voltage (Vz = 1.22 V) consuming around 10 µA in virtue of a limiting resistance (150K).
In oxidation mode (Figure 3), the above mentioned input of the potentiostat was grounded resulting in a positive potential applied to working electrode (WE) ranging from ground
(GND) to Vz. The inverting input of the potenziostat was directly connected to RE while its output wired to the auxiliary (AE) electrode. This allows the implementation of a feedback circuit in which RE and AE potentials are maintained at the same potential of the not-inverting input (potentiostatic circuit).
The buffered voltage divider, composed by the potentiomenter and the voltage follower, generated the potential necessary to polarize the WE in a range comprised between 0 and 1.22 V (Vz, controlled by ZXRE4001).
The current-to-voltage (I/V) converter is a single-supply adaptation of a classic transimpedance amplifier and derived form a previously-published design (Serra et al., 2007; Rocchitta et al., 2007). The transfer function of the I/V converter is:
in which Iredox is the current flowing through the WE, R is the feedback resistor and VApp is the potential applied to the WE (
A dummy cell was made based on a previously published design (Serra et al., 2007) for testing the amperometric module of the biotelemetric device before sensors calibration. The aim of the design was to devise a Thevenin current source that would reproduce the constant amperometric response of a true electrochemical cell. The voltage applied to the dummy cell was generated between the WE and RE/AE and is equal to the voltage difference between the above electrodes. The resulting currents were converted in an output voltage (VOut) as illustrated above. Data obtained from electronics calibration are similar to those obtained in previous studies (Bazzu et al., 2009; Calia et al., 2009).
The MSP430F2274 (Texas Instruments, TI) is the heart of the digital module. This is a 16-bit CMOS IC with ultra-low power features equipped with internal 10 bit ADCs. The microcontroller unit (MCU) performed the A/D conversion of VOut, VBatt, VApp and in-chip temperature using a 2.5 V internal reference. After the digital signal processing (DSP) of acquired raw data, a serial data packet was generated and sent to the transceiver: the TI CC2500 multi-channel RF transceiver, designed for low-power wireless applications (2.4 GHz).
Several pins of the microcontroller were connected to the CC2500 providing the data lines of the transceiver. In conjunction with the MCU, this component allows the realization of a serial data transmitter working at the speed of 9600 baud. A miniaturized chip antenna was integrated in the PCB board. The in-circuit-serial-programming (ICSP) bus provides the possibility of programming the MCU “on-board” in a few seconds. The digital module (Fig 1B; Fig. 1C) is commercially available pre-assembled by TI (eZ430-RF2500). A 210 mAh, 3 V lithium coin battery (Maxell CR2032) provided the power to the biotelemetric device for up to one week in continuous transmission (1 Hz). A small plastic enclosure (3.2 x 2.1 x 1.4 mm; Fig. 1A) completed the implantable device (Fig. 1B, inset). The weight of the implantable device (Figure 1, inset) is 12.4 grams including battery. A second digital module (wired unit, Fig. 1C), connected to a personal computer (PC) by means of an
3. Firmware and software
The firmware to drive the MSP430F2274 MCUs was realized in C language using IAR Embedded Workbench (version 5.20, KickStart) freely available from www.ti.com. The program, which runs on the biotelemetry device, consists of two routines: the main procedure and a timer-interrupt routine called every second as illustrated in Figure 5.
When the analogue signal VOut was digitized, the hardware ADC resolution (10 bit) was improved following the oversampling and averaging method (Pagnacco et al., 1997):
where w is the number of additional bits of resolution (2), Fs is the sampling frequency (1 Hz) and Fos is the oversampling frequency. In accordance with the Nyquist’s theorem Fs was calculated as follows:
in which Fmax has been fixed to 2 Hz. To do that, the MCU acquired and accumulated 64 consecutive samples then divided the result by 26 (Figure 5). This technique increased the ADC resolution from 10 to 12 bits. The RF data packets (1 per second), sent by the MCU, were encapsulated in an Open Source Stack (SimpliciTI™), implemented by Texas Instruments for the development of low power wireless NETs. Up to 100 implantable units, with an 8 bit ID memorized in their E2PROM, can share the same transmission channel. The interrupt-driven routine on the receiver unit, mounting a second MSP430F2274, communicates to the PC using USB and filters the IN-OUT data. The firmware was downloaded to the MCUs using the TI USB programmer connected to the ICSP bus (Figure 6).
The software, running on the PC under Windows XP Professional™ or Vista™, communicates thought the USB by using the low-level driver freely available from www.ti.com. The graphic user interface (Figure 7) was developed using Profilab Expert® (version 4.0 from Abacom) while the dynamic link library (DLL) serial-data-parser was programmed in C (Dev-C++ ver. 188.8.131.52).
The application (capable of plotting, storing and retrieving data) interfaces the system with a printer via USB and a Local Area Network (LAN) and Internet via TCP/IP (Figure 4). A software alarm was generated if VBatt< 2.7 V, signal strength (RSSI) too low or a data reception time-out occurred.
4. Statistical analysis
Concentrations of O2 were expressed in µM while AA, glucose and lactate in mM. Oxygen, ascorbate and H2O2 signals were expressed in nA and given as baseline-subtracted data (ΔnA). The sensors
Statistical significance of changes was evaluated using paired t-tests between the means of 300 consecutive recordings before (baseline) and during the maximum magnitude of neurochemical changes as a result of physiological stimulation (tail pinch).
Pearson's correlation coefficient was used to show correlation significance of current variations induced by tail pinches among O2, AA, glucose and lactate. Immediately after the stimulus application, the first five minutes of raw data (n=300) were compared point-by-point. The null hypothesis was rejected when p < 0.05.
5. Design, construction and calibration of oxygen and ascorbic acid microsensors
Oxygen microsensor construction and calibration were performed as previously described (Bazzu et al., 2009; Calia et al., 2009). Briefly, 1 mm silver wire (25 mm in length; Ø=125 µm, Advent Research Materials, Suffolk, UK) was introduced in a silica capillary tube (10 mm in length; I.D. Ø=180 µm, Polymicro Technologies, Phoenix, USA), partially filled with epoxy-carbon (EC) obtained mixing 450 mg of graphite with 350 mg epoxy resin (Araldite-M®, Sigma-Aldrich, Milan, Italy). A 180 µm diameter carbon composite disc electrode was made up and left 12 hours at 60 C. A conical shape was provided to the microsensor by drilling the tip.
The final oxygen microsensors (Figure 8) had a length about 250 µm, a surface of 0.00145 cm2 and a tip < 25 µm. Nitrocellulose (NC, collodion) treatment was carried out dipping the microsensor in the collodion solution (4% nitrocellulose in ethanol/diethyl ether) 3 times and drying it for 1 hour at 40 C after each coating. Cellulose nitrate membrane, because of its hydrophobic properties, sets a barrier for large organic molecules, as proteins, avoiding poisoning of microsensor surface while can be crossed by small charged ions and gases (Bazzu et al., 2009).
O2 reduction potential was experimentally determined in a previous study (Bazzu et al., 2009) using cyclic voltammetry and fixed at at -400 mV
AA microsensors (Figure 10) were manufactured in the same way as oxygen microsensors without the collodion layer or any further surface modification.
AA microsensors, calibrated before implantation (Figure 11), showed good sensitivity and good linearity (2.96 nA ± 0.1 mM-1, R2= 0.998, n=6).
6. Design, construction and calibration of glucose and lactate biosensors
The design of the glucose biosensors (Figure 12) has been previously described in detail (Serra et al., 2007). Briefly, 1 mm platinum (Pt) cylinder, obtained cutting Teflon-insulated Pt wire (Ø=125 µm, Advent Research Materials, Suffolk, UK), was immersed for 5 min into a solution of glucose oxidase (GOx) to allow adsorption. After 10 min drying at room temperature, the biosensor was placed in the cell filled with 5 ml of nitrogenated PBS containing the o-phenylenediamine monomer (OPD, 250 mM). The electrosynthesis of poly-o-phenylenediamine (p-OPD) was carried out at +700 mV
The fabrication of the lactate biosensors (Figure 14) has been derived from a previously described procedure used to make glutamate biosensors (McMahon et al., 2006). A Pt cylinder (1 mm) was placed in the electrochemical cell containing nitrogenated PBS and OPD monomer and p-OPD was electrosynthesized as previously described for glucose biosensor. The Pt/p-OPD cylinder was immersed (quick dip) into a solution of polyethylenimmine (PEI, 0.5%in water)-LOx (25 U/50 µl of PBS) to allow oxydase adsorption. After 5 min drying at room temperature, the dipping procedure was repeated four times.
With the purpose of increasing the KM of the biosensor, a diffusion-reducing membrane (Schuvailo et al., 2006) was applied on top of the PEI-LOx layers by dipping the biosensor in a polyurethane (PU) solution (2.5% in tetrahydrofurane). Finally, the biosensor was stored in fridge.
Constant potential amperometry (CPA) was used for
Calibrations showed a classical Michaelis-Menten kinetic (R2=0.944, n=6) with VMAX and KM equal respectively to 92.8±2 nA and 8.7±0.9 mM (Figure 15). Linear region was evaluated at low concentration (0-5 mM) and it showed good linearity (R2=0.997, n=6) with a slope of 6.7±0.2 nA mM-1 (Figure 15, inset).
No significant interference signals were observed on exposing biosensors to AA or other electroactive molecules present in the striatal extracellular fluid, even at pharmacologically relevant concentrations (Calia et al., 2009).
7. Animals and neurosurgery
Male Wistar rats (Morini R. Emilia, Italy), weighing 250-350 g were used in all experiments. Rats were kept under standard animal care conditions with 12 h light/dark cycle, and room temperature 21 C, food and water ad libitum.
All procedures were licensed under the European Community directive 86/609 included in Decreto No. 116/1992 of the Italian Ministry of Public Health.
Stereotaxic surgery was performed under chloral hydrate (400 mg Kg-1 i.p.) anesthesia and body temperature during anaesthesia was maintained at 37 C by means of an isothermal heating pad.
Before each experiment, the health of the animals was assessed according to published guidelines (Wolfensohn and Lloyd, 2003).
O2 and AA microsensors, glucose and lactate biosensors were implanted in the right striatum (Figure 16) using the following coordinates from the atlas of Paxinos & Watson (Paxinos & Watson, 2007): A/P +0.5 from bregma, +2.5 M/L, and -4.0 D/V from dura. Reference and Auxiliary electrodes were implanted in the parietal cortex.
Following surgery, the animals were housed in large Plexiglas bowls (45 cm diameter), and maintained in a temperature- and light- controlled environment, with free access to food and water. The sensors were connected 24 h after surgery. The monitoring of neurochemicals started with the animal in its home bowl allowing the rat free movement (Figure 17).
In-vivo experiments and results
Baseline recordings and physiological stimulation were carried out within the first day after stereotaxic surgery, starting 24 h after implantation. The Oxygen microsensor reached a stable baseline (-24.3 ± 2.7 nA) after a period of about 50 minutes from the application of the working potential. Considering that the background current of the microsensor in nitrogen-saturated PBS was -14.2 ± 0.9 nA, it is possible to estimate the concentration of O2 using
Striatal oxygen dynamics, following physiological stimulation, resulted in a rise in the local O2 signal, mainly related to an increase of rCBF during neural activation in agreement with previous findings (Bazzu et al., 2009; Calia et al., 2009).
A stable AA baseline was reached after a period of about 25 minutes. The calculated AA baseline corresponded to a concentration of 566 µM, in line with previous findings (Calia et al., 2009). A physiological increase (p<0.001; Figure 19, inset) of striatal AA current (+0.447 nA corresponding to +228 µM) was observed immediately after the administration of a 5 min tail pinch (Figure 19).
This result is consistent with the activation of the AA/glutamate heteroexchange system (Rice, 2000) in which AA release is related to glutamate release and uptake subsequent to neural activation (Miele et al., 2000).
A stable baseline was observed 40 min after lactate biosensor polarization and corresponded to 5.09±0.43 nA (759±62 µM from the above
These results are suggestive of glucose consumption and lactate production during neural activation followed by an increase of extracellular levels of glucose subsequent to astroglial glycogenolysis (Fillenz et al., 1999). Figure 22 shows Pearson's correlation analysis of current variations induced by tail pinches among O2, AA, glucose and lactate.
It is important to remember that an increase in anodic currents (AA, glucose and lactate) reflects a striatal increase of the above neurochemicals while an increase in extracellular dissolved O2 levels, corresponds to an increase in cathodic oxygen current, resulting in a more negative signal. Results of correlation analysis are summarized in Table 1.
|Oxygen||r = - 0. 819 P<0.00 0 1||r = 0. 401 P<0.00 0 1||r = - 0. 457 P<0.00 0 1|
|Ascorbic Acid||r = -0.266 P<0.00 0 1||r = 0.5 18 P<0.00 0 1|
|Glucose||r = -0.388 P<0.00 0 1|
After each experiment, rats were sacrificed with an injection of chloral hydrate (800 mg Kg-1 i.p.). The location of each sensor was established by post-mortem histology. Brains were fixed in formal saline and 50 µm coronal sections were made with a cryostat. The slices were stained with cresyl violet and examined under a microscope.
9. Discussion and conclusion
In this chapter we have described the development of a distributed sensor NET for biotelemetric monitoring of brain neurochemistry using amperometric microsensors and biosensors. The implantable biotelemetric units, based on simple and inexpensive components, have been successfully used for accurate transduction of the electrochemical signals generated on the surface of the sensors implanted in the striatum of freely-moving rats. At this stage of development the system exhibits high stability and excellent linear response in the nanoampere current range. The choice of low-power CMOS technology makes the project suitable of further improvements such as the reduction of the power consumption. The use of surface mount components and careful PCB design will make it possible to further miniaturize the circuitry. As result of
Recently, Castro and coworkers (Castro et al., 2009) proposed a new pivotal role for AA as modulator in the
during neural activation, might reflect an increase of rCBF (Bazzu et al., 2009; Calia et al., 2009). Immediately after the end of the physiological stimulation, AA current inverted its trend and slowly (10 min) returned to baseline levels. Oxygen and lactate currents continued to rise for 5 min after the end of the tail pinch then slowly decreased to baseline levels. The drop of glucose during neural activation was followed by its increase as result of astroglial glycogenolysis (Fillenz et al., 1999). Post-activation data are complex to interpret and suggest the return to normal (inactive) condition with glucose as energetic substrate for neurons. It is important to remember that AA is oxidized to DHAA by ROS and RNS in neurons (Serra et al., 2002). DHAA, secreted in the extracellular space, enters astrocyte through GLUT1 transporter and is back-reduced to AA (Hediger, 2002). A sustained increase of extracellular glucose could interfere with AA/DHAA cycle resulting in oxidative stress, AA loss and neuron damage.
The authors acknowledge the Italian distributors of Texas Instruments for free samples of integrated circuits. The research was supported by the Ministero dell’Istruzione, dell’Universita` e della Ricerca (MIUR, PRIN 2007 fund), University of Sassari (ex 60% fund) and Fondazione Banco di Sardegna.This work is dedicated to the beloved memory of Giovanna Pisanu who left us too early.
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