Analytical Chemistry Chemical Cytometry Quantitates Superoxide

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Table 3. Eicosanoid Levels (pg/µL) in Mouse Serum and Bronchial Epithelial Cells a serum (µL) TxB2 PGE2 PGD2 PGF2〈 LTB4 5(S)-HETE 8(S)-HETE 11(S)-HETE 12(S)-HETE 15(S)-HETE Arachi-donic Acid 1 46 15 198 748 393 437 11 345 240 28 623 1 49 11 340 1075 545 646 17 840 703 23 246 5 43 13 174 792 490 350 14 116 617 14 900 5 43 11 169 986 469 350 16 512 672 16 631 10 51 9 255 971 586 536 15 108 749 12 200 10 39 13 248 958 593 416 14 487 732 15 476 bronchial epithelial cellsb 4 (7) 105 (195) 25 (22) 170 (300) 5 (19) 880 (1210) a Eicosanoids not listed in the table were not detected. b The first number is for unstimulated cells, and the number in parentheses is for stimulated cells. Values are for 0.47 million cells per sample stimulated in 200 µL of Hank’s balanced salt solution. MS (19 pg on-column) (Table 2). Coefficients of variation ranged from 2.8 to 28.2%. We also analyzed three independent serum aliquots (10 µL), and the coefficient of variation ranged from 3.7 to 13.7%. We then analyzed the set of endogenous eicosanoids present in mouse serum in order to test the AMPP derivatization method on a complex biological sample. Representative LC-ESI-MS/MS traces are shown in the Supporting Information Supplementary Material Figure 7 for a relatively high abundant serum eicosanoid (TxB 2) and a relatively low abundant eicosanoid (PGF2R). Traces for the full set of eicosanoids and internal standards are shown in the Supporting Information Supplementary Material Figure 3. Eicosanoids levels are shown in Table 3 for multiple runs and with different volumes of serum analyzed. As another example of low-level eicosanoid analysis in a complex biological matrix, we analyzed eicosanoid formation in calcium ionophore stimulated primary bronchial epithelial cells. Results are summarized in Table 3, and selected ion traces for the full set of eicosanoids are shown as Supplementary Material Figure 4 in the Supporting Information. Finally, we cross-validated the AMPP method with a commercially available antibody-based assay kit. We analyzed PGE 2 production by Rat 3Y1 cells and compared the results obtained via LC-ESI-MS/MS analysis of AMPP amides with those obtained from the EIA kit. Results are summarized in the Supporting Information Supplementary Material Figure 8. There is strong agreement between the two methods. CONCLUSIONS We developed a simple derivatization procedure to convert carboxylic acids to AMPP amides and showed that this significantly improves the sensitivity for detection of eicosanoids by LC-ESI-MS/MS. Antibody-based quantifications of eicosanoids 6796 <strong>Analytical</strong> <strong>Chemistry</strong>, Vol. 82, No. 16, August 15, 2010 have a limit of quantification around 1 pg, and the method requires that each analyte be quantified in a single assay well. Thus, if 12 eicosanoids are to be analyzed, one requires a sample containing ∼12 pg of each species. The AMPP amide method disclosed in the current study can detect all 12 eicosanoid species in a single sample containing ∼0.3-1 pg of each eicosanoid and is thus more than an order of magnitude more sensitive than antibody based detection. Previously reported LC-ESI-MS/MS detection of underivatized eicosanoids in negative ion mode provide a limit of quantification in the 10-20 pg range 1–3 (see also our data in Table 1), and thus our method is more than an order of magnitude more sensitive than these methods. We are currently studying the use of AMPP to improve the detection sensitivity for other oxygenated fatty acids including cysteinyl-leukotrienes, lipoxins, resolvins, and protectans. Analysis of the full spectrum of fatty acids should be feasible based on the results with AA reported in this study. This new method based on AMPP amides should find widespread use in the quantification of lipid mediator levels where sample supply is limited. ACKNOWLEDGMENT This work was supported by grants from the National Institutes of Health (Grant HL50040 to M.H.G. and Grant HL089215 to T.S.H.) and by grants from the National Science Foundation (Grants CHE-0750048 and CHE-0349595 to F.T.). SUPPORTING INFORMATION AVAILABLE Additional information as noted in text. This material is available free of charge via the Internet at http://pubs.acs.org. Received for review March 19, 2010. Accepted July 8, 2010. AC100720P
Anal. Chem. 2010, 82, 6797–6806 δ 13 C Stable Isotope Analysis of Atmospheric Oxygenated Volatile Organic Compounds by Gas Chromatography-Isotope Ratio Mass Spectrometry Brian M. Giebel,* Peter K. Swart, and Daniel D. Riemer University of Miami, Rosenstiel School of Marine and Atmospheric Science, 4600 Rickenbacker Causeway, Miami, Florida 33149 We present a new method for analyzing the δ 13 C isotopic composition of several oxygenated volatile organic compounds (OVOCs) from direct sources and ambient atmospheric samples. Guided by the requirements for analysis of trace components in air, a gas chromatograph isotope ratio mass spectrometer (GC-IRMS) system was developed with the goal of increasing sensitivity, reducing dead-volume and peak band broadening, optimizing combustion and water removal, and decreasing the split ratio to the isotope ratio mass spectrometer (IRMS). The technique relies on a twostage preconcentration system, a low-volume capillary reactor and water trap, and a balanced reference gas delivery system. The instrument’s measurement precision is 0.6 to 2.9‰ (1σ), and results indicate that negligible sample fractionation occurs during gas sampling. Measured δ 13 C values have a minor dependence on sample size; linearity for acetone was 0.06‰ ng C -1 and was best over 1-10 ng C. Sensitivity is ∼10 times greater than similar instrumentation designs, incorporates the use of a diluted working reference gas (0.1% CO2), and requires collection of >0.7 ng C to produce accurate and precise results. With this detection limit, a 1.0 L sample of ambient air provides sufficient carbon for isotopic analysis. Emissions from vegetation and vehicle exhaust are compared and show clear differences in isotopic signatures. Ambient samples collected in metropolitan Miami and the Everglades National Park can be differentiated and reflect multiple sources and sinks affecting a single sampling location. Vehicle exhaust emissions of ethanol, and those collected in metropolitan Miami, have anomalously enriched δ 13 C values ranging from -5.0 to -17.2‰; we attribute this result to ethanol’s origin from corn and use as an additive in automotive fuels. Oxygenated volatile organic compounds (OVOCs) such as methanol, ethanol, acetaldehyde, and acetone are gases found throughout the troposphere that influence atmospheric chemistry in many ways. These compounds act as a source of radicals and a sink for the hydroxyl radical (OH), participate in tropospheric * Corresponding author. Fax: 305-421-4689. E-mail: bgiebel@rsmas.miami.edu. ozone formation, and are precursors to formaldehyde and CO. 1 Mixing ratios for OVOCs are typically at the low parts per billion by volume (ppbv) level and depend on sampling location and season. 2-5 Most atmospheric OVOC measurements have reported information on ambient levels, source emission strengths, and flux rates, 2,3,5-9 with two individual OVOCs, methanol and acetone, receiving the majority of focus thus far. Methanol is the second most abundant organic gas in the atmosphere after methane and its global budget has been studied extensively. 3,10-12 Emissions from vegetation are the single largest source to the atmosphere and are estimated between 75-312 Tg year -1 . Other sources of methanol exist, including fossil fuel combustion, biomass burning, plant decay, and in situ atmospheric production via oxidation of methane. Combined, these sources are estimated at
Page 1 and 2: Anal. Chem. 2010, 82, 6745-6750 Let
Page 3 and 4: purchased from Invitrogen-Molecular
Page 5 and 6: Figure 3. Electropherograms of TPP-
Page 7 and 8: Anal. Chem. 2010, 82, 6751-6755 Res
Page 9 and 10: (pH 8.0) with cysteine and cystamin
Page 11 and 12: Figure 4. Ion mobility mass spectra
Page 13 and 14: GOx glucose + O298 gluconic acid +
Page 15 and 16: coater at 2000 rpm for 20 s, and th
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Page 19 and 20: in channels with either no grooves
Page 21 and 22: indicators of atmospheric processin
Page 23 and 24: Figure 1. GC/MS total ion chromatog
Page 25 and 26: Table 2. Concentrations and Stable
Page 27 and 28: on a substrate are preferred. 20-24
Page 29 and 30: Figure 4. SERS analysis of NAADP co
Page 31 and 32: Anal. Chem. 2010, 82, 6775-6781 Hig
Page 33 and 34: tion, 2 µL of proprionaldehyde wer
Page 35 and 36: Figure 4. Analysis of 2a by HPLC-MS
Page 37 and 38: eaction of 1a with PBH can be condu
Page 39 and 40: Numerous references had demonstrate
Page 41 and 42: Figure 1. TEM images of the prepare
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Page 45 and 46: esult in a big SPR signal change wi
Page 47 and 48: also reduces chemical noise, which
Page 49 and 50: Table 1. Extraction Yields, Liquid
Page 51: scanning of AMPP amides of the anal
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Page 59 and 60: Figure 4. (A) IRMS mass-44 chromato
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Page 63 and 64: Anal. Chem. 2010, 82, 6807-6813 Dir
Page 65 and 66: Polymerase (1 U per sample). Reacti
Page 67 and 68: of which was constant for all ampli
Page 69 and 70: analytically useful signals at less
Page 71 and 72: carbon black and RP-C18 for the ext
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Page 75 and 76: Table 2. Concentrations and Ratios
Page 77 and 78: Anal. Chem. 2010, 82, 6821-6829 Mac
Page 79 and 80: mg/mL protein, followed by separati
Page 81 and 82: Figure 2. Productivity of SEQUST an
Page 83 and 84: Figure 4. High-resolution MS/MS spe
Page 85 and 86: Figure 6. Characterization of PSMs
Page 87 and 88: containing T-T mismatches. 23 Based
Page 89 and 90: Figure 1. Extinction spectra of sol
Page 91 and 92: Figure 3. (A) The value of Ex650 nm
Page 93 and 94: Figure 5. Extinction spectra and co
Page 95 and 96: wished to explore the dehydration o
Page 97 and 98: constant medium for separation; we
Page 99 and 100: Figure 2. Standards of (Pi)n, n ) 1
Page 101 and 102: 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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Figure 2. With a suitable removal o
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the NB signal in a much better foot
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Scheme 1. Reactions of Selenium Rea
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Figure 2. (a) ESI-MS spectrum showi
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Figure 4. (a) ESI-MS spectrum showi
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Anal. Chem. 2010, 82, 6933-6939 Dif
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trode 28 by a finite element using
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Figure 4. Comparison between simula
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Figure 6. Comparison between simula
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educed in the vicinity of double bo
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Figure 2. Normalized product ion ab
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Figure 4. EID (a) and IRMPD (b) of
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Anal. Chem. 2010, 82, 6947-6957 Ide
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Figure 1. Schematic flowchart showi
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difference, ppm compound Table 1. I
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isoforms, its successful use, in th
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Figure 5. Extracted ion current ESI
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m/z 1172.935 was observed for Ser14
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linked products via affinity tags.
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Scheme 2. Fragmentation Mechanism o
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Figure 1. (A) ESI-LTQ-CID-MS 2 prod
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Figure 3. (A) ESI-LTQ-CID-MS 2 prod
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Figure 5. (A) MALDI-TOF/TOF product
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Anal. Chem. 2010, 82, 6969-6975 Ana
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Figure 3. Equilibrium response as a
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Figure 6. The average measured resp
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for the fill time, and we find that
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nucleotide tails. 3-5 Thus, the amo
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allow the use of higher aptamer con
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quent ligation of the aptamers afte
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Anal. Chem. 2010, 82, 6983-6990 Imp
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Figure 2. Configuration editor wind
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Figure 4. Dependencies between volu
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Since the time for liquid expulsion
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Anal. Chem. 2010, 82, 6991-6999 Int
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Figure 1. Representation of the Car
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Table 2. Capillary Electrophoresis
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Figure 4. (A) Typical raw electroph
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field. DNA profiles were delivered
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Another approach to handle this lim
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(principal components, PCs) in whic
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Figure 5. Relevant score plots and
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CONCLUSIONS In this paper we have i
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electroactive-species loaded liposo
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Figure 2. Qdot-based FLFTS response
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Figure 6. Fluorescence imaging of Q
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Anal. Chem. 2010, 82, 7015-7020 Sel
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Table 1. Effect of 1 D-LC Condition
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Figure 3. Peak-production rate vers
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Anal. Chem. 2010, 82, 7021-7026 Cel
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luciferase (T7 control vector) was
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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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