Spontaneous adenosine release frequency and concentration in the caudate-putamen during stroke.

<p>All data and statistics are for n = 10 animals. (A) The average event adenosine concentration per transient for normoxia (n = 829) and ischemia-reperfusion (n = 1306) was not significantly different (unpaired t-test, n = 10 animals, p = 0.57) (B) Average event adenosine concentration per transient were divided into 30 min periods during normoxia, ischemia and reperfusion periods and event concentration did not show any significant difference (One-way ANOVA, p = 0.9354) (C) The cumulative adenosine concentration was significantly different after stroke compared to normoxia (paired t-test, n = 10 animals, p = 0.03). (D) Cumulative adenosine concentration was divided into 30 min periods. The first four bars are 30 min periods during normoxia, then one bar for the 30 min of ischemia, followed by three 30 min bars for the total 90 min of reperfusion. The dashed lines show the average for the normoxia and ischemia-reperfusion periods. Cumulative concentration during normoxia, ischemia and reperfusion was significantly different (One-way ANOVA, p = 0.0022).</p

Effect of the A_2A antagonist, SCH442416 (3 mg/kg. i.p), on adenosine on adenosine transients during stroke.

<p>All data and statistics are for n = 8 animals. (A) Number of adenosine transients decreased significantly after SCH442416 during stroke (paired t-test, p = 0.01). (B) Inter-event time of all adenosine transients. The exponential fit (black line) during normoxia (predrug) is y = 0.5981e^-0.0207x (R² = 0.99) and SCH442416 + ischemia-reperfusion (red line) is y = 0.4491e^-0.0155x (R² = 0.99). After SCH442416 treatment, the inter-event time was significantly longer during stroke, with a median inter-event time change from 39 s (normoxia) to 48 s (I-R). There was a significant difference between the distributions before and after stroke (KS-test, p = p < 0.0001). (C) The average event adenosine concentration per transient after SCH442416 administration during ischemia and reperfusion 0.13 ± 0.01 μM (n = 759 transients) compared to normoxia 0.14 ± 0.01 μM (n = 1030 transients) was not significantly different (unpaired t-test, n = 8 animals, p = 0.05) (D) There was no significant change in the median cumulative concentration after SCH442416 during stroke compared to normoxia (p = 0.11).</p

Control experiments with no ischemia.

<p>All data and statistics are for n = 7 animals (A) Number of adenosine transients did not change between the 1^st and 2^nd 2 hour periods (paired t-test, p = 0.48). (B) Inter-event time of all adenosine transients. The exponential fit (black line) in the first 2 h is y = 0.5592e^-0.0207x (R² = 0.99) and in the second 2 h (grey line) is y = 0.5195e^-0.0172x (R² = 0.99). There was no significant difference between the underlying distributions in the first 2 h and second 2 h (KS-test, n = 7 animals, p = 0.6). (C) The average event adenosine concentration per transient. There was no significant change in the average adenosine concentration per transient for first 2 hrs (n = 1084) and second 2 hrs (n = 1064) (unpaired t-test, n = 7 animals, p = 0.12). (D) There was no significant change in the mean cumulative concentration between the 1^st and 2^nd 2 hour periods (paired t-test, p = 0.55).</p

TEM images of control rat, ischemia induced and A_2A antagonist administered brain slices.

<p>TEM images of the nucleus from rat brain caudate-putamen. Cerebral neurons in sham rats showed (a) normal cell nucleus (arrow) and (b) normal mitochondria (*). Rats after 30 min of BCCAO and 8h of reperfusion led to substantial changes to organelle structure. After BCCAO, (c) cell nucleus appears to have shrunken with condensed chromatin (arrow). (d) Mitochondria are swollen (*) and with disorganized cristae. Rats after the administration A_2A antagonist SCH 442416 prior to 30 min of BCCAO and 8h of reperfusion showed (e) normal cell nucleus (arrow) and (f) normal mitochondria (*) with no disruption to cell membrane. This indicates that A_2A antagonist administration prior to the cerebral ischemia proven to be neuroprotective.</p

Detection of Adenosine <i>in vitro</i> and <i>in vivo</i> using fast scan cyclic voltammetry.

<p>(A) <i>In vitro</i> calibration of adenosine. A 3-D color plot (middle) depicts the time on the x-axis, potential on the y-axis, and current in false color. The primary oxidation at +1.4 V (large green oval in center of color plot) and the secondary oxidation at +1.0 V (green/purple oval below center oval). The current vs time plot (top) shows the change in current in the presence of adenosine. (B) <i>In vivo</i> spontaneous, transient adenosine event, detected in rat caudate-putamen. The 3-D color plot shows primary and secondary oxidation peaks that match the in vitro calibration. The current vs time plot (top) shows the change in current due to the spontaneous adenosine transient.</p

Rat schematic diagram and experimental timeline of normoxia, ischemia and reperfusion.

<p>Top: Rat schematic diagram showing the placement of the occluders around the common carotid artery and placement of carbon fiber microelectrode into the rat brain. Bottom: Timeline diagram of normoxia, ischemia and reperfusion periods.</p

Effect of stroke on the number of adenosine transients in the caudate-putamen.

<p>All data and statistics are for n = 10 animals. Example concentration traces and false color plots showing the number of transients during (A) normoxia (B) ischemia and (C) reperfusion over 180 s time window. There are more transients during ischemia and reperfusion than during normoxia. (D) The average number of adenosine transients during normoxia (2 h) and I-R periods (2 h) is significantly different (paired t-test, n = 10 animals, p = 0.0138). (E) Average number of adenosine transients, divided into 30 min periods. The first four bars are 30 min time periods during normoxia, then one bar for the 30 min of ischemia, followed by three 30 min bars for reperfusion. The dashed lines show the average for the normoxia and ischemia-reperfusion periods. The number of transients during normoxia, ischemia and reperfusion were significantly different (One-way ANOVA, p < 0.0001).</p

Platinum-Doped Ceria Based Biosensor for <i>in Vitro</i> and <i>in Vivo</i> Monitoring of Lactate during Hypoxia

Measurements of lactate concentrations in blood and tissues are an important indication of the adequacy of tissue oxygenation and could be useful for monitoring the state and progress of a variety of diseases. This paper describes the fabrication, analytical characterization, and physiological application of an amperometric microbiosensor based on lactate oxidase and oxygen-rich platinum doped ceria (Pt-ceria) nanoparticles for monitoring lactate levels during hypoxic conditions. The Pt-ceria nanoparticles provided electrocatalytic amplification for the detection of the enzymatically produced hydrogen peroxide and acted as an internal oxygen source for the enzyme, enabling lactate monitoring in an oxygen depleted tissue. <i>In vitro</i> evaluation of the biosensor demonstrated high selectivity against physiological levels of ascorbic acid, a storage stability of 3 weeks, a fast response time of 6 s, and good, linear sensitivity over a wide concentration range. <i>In vivo</i> experiments performed by placing the biosensor in the hippocampus of anesthetized rats demonstrated the feasibility of continuous lactate monitoring over 2 h ischemia and reperfusion. The results demonstrate that Pt-ceria is a versatile material for use in implantable enzyme bioelectrodes, which may be used to assess the pathophysiology of tissue hypoxia. In addition to measurements in hypoxic conditions, the detection limit of this biosensor was low, 100 pM, and the materials used to fabricate this biosensor can be particularly useful in ultrasensitive devices for monitoring lactate levels in a variety of conditions

Automated Algorithm for Detection of Transient Adenosine Release

Spontaneous adenosine release events have been discovered in the brain that last only a few seconds. The identification of these adenosine events from fast-scan cyclic voltammetry (FSCV) data is difficult due to the random nature of adenosine release. In this study, we develop an algorithm that automatically identifies and characterizes adenosine transient features, including event time, concentration, and duration. Automating the data analysis reduces analysis time from 10 to 18 h to about 40 min per experiment. The algorithm identifies adenosine based on its two oxidation peaks, the time delay between them, and their <i>current</i> vs <i>time</i> peak ratios. In order to validate the program, four data sets from three independent researchers were analyzed by the algorithm and then compared to manual identification by an analyst. The algorithm resulted in 10 ± 4% false negatives and 9 ± 3% false positives. The specificity of the algorithm was verified by comparing calibration data for adenosine triphosphate (ATP), histamine, hydrogen peroxide, and pH changes and these analytes were not identified as adenosine. Stimulated histamine release in vivo was also not identified as adenosine. The code is modular in design and could be easily adjusted to detect features of spontaneous dopamine or other neurochemical transients in FSCV data

Carbon Nanotubes Grown on Metal Microelectrodes for the Detection of Dopamine

Microelectrodes modified with carbon nanotubes (CNTs) are useful for the detection of neurotransmitters because the CNTs enhance sensitivity and have electrocatalytic effects. CNTs can be grown on carbon fiber microelectrodes (CFMEs) but the intrinsic electrochemical activity of carbon fibers makes evaluating the effect of CNT enhancement difficult. Metal wires are highly conductive and many metals have no intrinsic electrochemical activity for dopamine, so we investigated CNTs grown on metal wires as microelectrodes for neurotransmitter detection. In this work, we successfully grew CNTs on niobium substrates for the first time. Instead of planar metal surfaces, metal wires with a diameter of only 25 μm were used as CNT substrates; these have potential in tissue applications due to their minimal tissue damage and high spatial resolution. Scanning electron microscopy shows that aligned CNTs are grown on metal wires after chemical vapor deposition. By use of fast-scan cyclic voltammetry, CNT-coated niobium (CNT-Nb) microelectrodes exhibit higher sensitivity and lower Δ<i>E</i>_p value compared to CNTs grown on carbon fibers or other metal wires. The limit of detection for dopamine at CNT-Nb microelectrodes is 11 ± 1 nM, which is approximately 2-fold lower than that of bare CFMEs. Adsorption processes were modeled with a Langmuir isotherm, and detection of other neurochemicals was also characterized, including ascorbic acid, 3,4-dihydroxyphenylacetic acid, serotonin, adenosine, and histamine. CNT-Nb microelectrodes were used to monitor stimulated dopamine release in anesthetized rats with high sensitivity. This study demonstrates that CNT-grown metal microelectrodes, especially CNTs grown on Nb microelectrodes, are useful for monitoring neurotransmitters