Analytical Chemistry Chemical Cytometry Quantitates Superoxide

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Figure 7. The measured sorption time, τmeas, is proportional to the inverse saturation vapor pressure. The nonzero y intercept of 13.8 s is the flow cell fill time, which when subtracted from the measured sorption time gives the true sorption time, τd. The sorption time of undecane is nearly 2 orders of magnitude larger than that of toluene despite their equilibrium response curves being nearly identical as in Figure 2. analyte activity as demonstrated in Figure 6. A plot of this average time versus the inverse analyte saturation vapor pressure results in a straight line with a nonzero y intercept, as seen in Figure 7. Of course, at infinite saturation vapor pressure the sorption time τd must be zero since the diffusive flux is infinite. Therefore, this finite intercept of 13.8 s corresponds to the fill time of the flow cell and can be used to produce the corrected sorption times, τd, in Figure 7. This measured flow cell fill time is in good agreement with the theoretical prediction, using Vf/F. Figure 7 shows a nearly perfect proportionality between the sorption time, τd, and the analyte saturation vapor pressure, P*. Equation 7b shows that other analyte parameters, such as the diffusivity and the � parameter, also determine this sorption time, but apparently these combined factors are more-or-less constant for the analytes we tested. Also, the saturation vapor pressure varies strongly from analyte to analyte. If finer resolution was desired for differentiation between similarly volatile analytes, these other analyte parameters could be taken into account. The homologous series of aromatic analytes, all of which have nearly identical Flory parameters, and thus identical equilibrium chemiresistor responses as a function of activity, are now easily distinguished. For toluene, p-xylene, and mesitylene the sorption times are 3.7, 10.0, and 37.0 s, respectively, which are in good agreement with their relative reciprocal saturation vapor pressures, 3.45, 11.4, and 39.2 (×10 -2 Torr -1 ). These sorption time differences are large compared to the errors associated with our measurements, even though the sorption time of toluene is much faster than the fill time of 13.8 s. The measurement of faster sorption times is possible, but would require either higher flow rates and a smaller flow cell volume, so that the fill time is faster, or thicker sensors, to increase the sorption time. Of course, increased sorption time comes at the cost of increased sensor response time, so this would only be desireable if high-volatility analytes are to be measured. DISCUSSION In the pulsed flow experiments the determination of the sorption time is straightforward, but would require a test unit with an engineered flow system. This mechanical requirement is antithetical to the inexpensive and simple chemiresistor concept. 6974 Analytical Chemistry, Vol. 82, No. 16, August 15, 2010 Other approaches are possible, but are yet untested in the context of vapor sorption, though analogous approaches have been used to determine photoluminescence lifetimes. In fact, luminescence is a useful language in which to describe the other possibilities. First, a luminescence lifetime can be measured by suddenly subjecting a material such as a phosphor to steady illumination. The rise time of the photoemission is the luminescent lifetime. This approach is analogous to the sorption kinetics reported above. If instead the steady illumination is suddenly shut off, the emission decay gives the lifetime. This is analogous to analyzing the desorption kinetics shown in Figure 1. A third approach is to excite a phosphor with amplitude-modulated light. The photoemission will also be amplitude modulated, but shifted in phase, and the lifetime can be determined from the phase shift and the modulation frequency. This is analogous to modulating the activity of the analyte, which is not really practical. The fourth approach is to excite a phosphor with light that randomly fluctuates in intensity. The photoemission then also fluctuates in intensity, but these fluctuations are time correlated. The associated correlation time can be determined from the photoemission time autocorrelation function, which is easily computed with a simple shift register device. This fourth method is applicable to a sensor in an environment where there is nonstationary air movement that causes fluctuations in the delivered analyte activity. An engineered mechanical system needed to deliver a flow pulse can potentially be supplanted by an electronic chip that computes the correlation time of the sensor response. Of course, we cannot expect the activity fluctuations delivered to the sensor to be purely random. Instead, these activity fluctuations will themselves have a correlation time (which is an interesting issue in and of itself). Therefore, the measured response fluctuations will in general be a convolution of both the activity fluctuations and the sorption kinetics. Extracting the true sorption kinetics will require two sensors that have widely disparate response kinetics (e.g., a thick and a thin polymer film). The thin sensor will respond rapidly, relative to the correlation time of the activity fluctuations, to changes in analyte activity. This sensor will thus measure the correlation time of the activity fluctuations. The thick sensor will have a sorption time long compared to this correlation time, and its response will be largely determined by the sorption kinetics. The thin sensor can be used to correct this measured sorption time to obtain the true sorption time. Therefore, by standard time correlation techniques, discrimination based on sorption kinetics can be developed without an engineered flow system. This approach will be the subject of our future research. CONCLUSIONS We have used a field-structured chemiresistor to demonstrate that response kinetics can be used to discriminate between analytes, even between those that have identical chemical affinities for the polymer phase of the sensor. To do this, we have used the analyte-independent transduction curve (conductance versus polymer swelling) to transform the time-dependent sensor conductance into a time-dependent polymer swelling. From these swelling data we can determine the measured sorption time, which is a combination of the true sorption kinetics and the fill time of the flow cell. The true sorption kinetics is obtained by correcting
for the fill time, and we find that the sorption kinetics is independent of the analyte activity, but inversely proportional to the saturation vapor pressure of the analyte. Saturation vapor pressures vary greatly from analyte to analyte, making response kinetics a powerful method of analyte discrimination, even with a single sensor. Finally, we suggest that when the sensing environment presents fluctuations in the analyte activity, an analysis of the fluctuations in the sensor response fluctuations can be used to extract the sorption kinetics. This approach would obviate the need for an engineered flow system that can deliver an analyte pulse and will be the focus of our future work. ACKNOWLEDGMENT This work was supported by the Division of Materials Sciences and Engineering, Office of Basic Energy Sciences, U.S. Department of Energy. Sandia National Laboratories is a multiprogram laboratory operated by Sandia Corp., a Lockheed Martin Co., for the Department of Energy’s National Nuclear Security Administration under Contract DE-AC04-94AL85000. Received for review May 13, 2010. Accepted July 1, 2010. AC101259W Analytical Chemistry, Vol. 82, No. 16, August 15, 2010 6975
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Anal. Chem. 2010, 82, 6745-6750 Let
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purchased from Invitrogen-Molecular
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Figure 3. Electropherograms of TPP-
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Anal. Chem. 2010, 82, 6751-6755 Res
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(pH 8.0) with cysteine and cystamin
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Figure 4. Ion mobility mass spectra
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GOx glucose + O298 gluconic acid +
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coater at 2000 rpm for 20 s, and th
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Figure 5. Comparison of cyclic volt
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in channels with either no grooves
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indicators of atmospheric processin
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Figure 1. GC/MS total ion chromatog
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Table 2. Concentrations and Stable
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on a substrate are preferred. 20-24
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Figure 4. SERS analysis of NAADP co
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Anal. Chem. 2010, 82, 6775-6781 Hig
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tion, 2 µL of proprionaldehyde wer
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Figure 4. Analysis of 2a by HPLC-MS
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eaction of 1a with PBH can be condu
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Numerous references had demonstrate
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Figure 1. TEM images of the prepare
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Figure 4. Schematic representation
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esult in a big SPR signal change wi
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also reduces chemical noise, which
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Table 1. Extraction Yields, Liquid
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scanning of AMPP amides of the anal
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Anal. Chem. 2010, 82, 6797-6806 δ
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Figure 1. Schematic view of the pre
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from the specimen and enclosed in a
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Figure 4. (A) IRMS mass-44 chromato
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Table 3. Ambient Measurement Result
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Anal. Chem. 2010, 82, 6807-6813 Dir
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Polymerase (1 U per sample). Reacti
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of which was constant for all ampli
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analytically useful signals at less
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carbon black and RP-C18 for the ext
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solution in an equal volume, and 1
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Table 2. Concentrations and Ratios
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Anal. Chem. 2010, 82, 6821-6829 Mac
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mg/mL protein, followed by separati
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Figure 2. Productivity of SEQUST an
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Figure 4. High-resolution MS/MS spe
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Figure 6. Characterization of PSMs
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containing T-T mismatches. 23 Based
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Figure 1. Extinction spectra of sol
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Figure 3. (A) The value of Ex650 nm
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Figure 5. Extinction spectra and co
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wished to explore the dehydration o
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constant medium for separation; we
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Figure 2. Standards of (Pi)n, n ) 1
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Figure 5. Quantitative calibration
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Anal. Chem. 2010, 82, 6847-6853 Met
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Figure 1. 226 Ra spectrum by liquid
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Table 1. Counting Properties and De
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Table 3. Analysis of 226 Ra in Sedi
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mercial microarray scanner and fabr
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Figure 2. Optical transmission meas
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Figure 5. Volcano plots detailing t
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data as well. The 41 genes in Table
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corresponding compound if its chemi
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Figure 1. Schematic illustration of
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Table 1. Absolute Quantification Re
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ment. Therefore, the long-time drea
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Figure 1. Chemically actuated micro
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Figure 2. Influence of a surfactant
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Figure 5. Device to eject and mix s
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Anal. Chem. 2010, 82, 6877-6886 Imm
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NaCl, phosphate buffer saline (PBS)
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Figure 2. Product ion mass spectra
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-70 °C resolved the problem, givin
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Table 1. Intraday Precision and Acc
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Anal. Chem. 2010, 82, 6887-6894 Fer
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Figure 1. Infrared spectra of (A) u
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Figure 3. Cyclic voltammograms obta
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Figure 6. Calculated charge from ch
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Anal. Chem. 2010, 82, 6895-6903 Ele
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Table 1. Chemical Structure, pKa Va
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pH with a tilted baseline (Figure 1
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Table 2. Linearity and Detection Li
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ascorbic acid (AA), uric acid (UA),
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the multielement capabilities, the
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RESULTS AND DISCUSSION Sulfur Detec
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Table 2. Molecular Properties and C
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Anal. Chem. 2010, 82, 6911-6918 Dir
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dilution and hybridization buffer.
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solution under appropriate incubati
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Figure 4. Standardization curve for
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Anal. Chem. 2010, 82, 6919-6925 Ele
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the ×10 objective, to have a large
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Page 183 and 184: Scheme 1. Reactions of Selenium Rea
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Page 263 and 264: CONCLUSIONS In this paper we have i
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Figure 3. Inhibitory effects of luc
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Anal. Chem. 2010, 82, 7027-7034 Pat
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Electrochemistry. Electrochemical m
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Figure 2. SEM images of Au substrat
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Table 3. Film Thickness Measurement
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Anal. Chem. 2010, 82, 7035-7043 Qua
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Figure 1. (A) FL spectra of BSPOTPE
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Figure 4. (A) Variation in the FL i
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Figure 6. (A) FL spectra of BSPOTPE
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Scheme 1. Proposed Mechanism for Fl
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one or more drawbacks including poo
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Figure 2. Free fluorophores do not
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Anal. Chem. 2010, 82, 7049-7052 Dev
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Figure 2. Comparative analysis of d
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