| Title |
Automated method for analysis of tryptophan and tyrosine metabolites using capillary electrophoresis with native fluorescence detection
|
|---|---|
| Published in |
Analytical & Bioanalytical Chemistry, January 2013
|
| DOI | 10.1007/s00216-012-6685-0 |
| Pubmed ID | |
| Authors |
Christopher A. Dailey, Nicolas Garnier, Stanislav S. Rubakhin, Jonathan V. Sweedler |
| Abstract |
Capillary electrophoresis (CE) with laser-induced native fluorescence (LINF) detection offers the ability to characterize low levels of selected analyte classes, depending on the excitation and emission wavelengths used. Here a new automated CE-LINF system that provides deep ultraviolet (DUV) excitation (224 nm) and variable emission wavelength detection was evaluated for the analysis of small molecule tryptophan- and tyrosine-related metabolites. The optimized instrument design includes several features that increase throughput, lower instrument cost and maintenance, and decrease complexity when compared with earlier systems using DUV excitation. Sensitivity is enhanced by using an ellipsoid detection cell to increase the fluorescence collection efficiency. The limits of detection ranged from 4 to 30 nmol/L for serotonin and tyrosine, respectively. The system demonstrated excellent linearity over several orders of magnitude of concentration and intraday precision from 1-11 % relative standard deviation (RSD). The instrument's performance was validated via tryptophan and serotonin characterization using tissue extracts from the mammalian brain stem, with RSDs of less than 10 % for both metabolites. The flexibility and sensitivity offered by DUV laser excitation and tunable emission enables a broad range of small-volume measurements. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 4 | 36% |
| Researcher | 2 | 18% |
| Professor | 1 | 9% |
| Student > Bachelor | 1 | 9% |
| Professor > Associate Professor | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 2 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Chemistry | 5 | 45% |
| Agricultural and Biological Sciences | 1 | 9% |
| Biochemistry, Genetics and Molecular Biology | 1 | 9% |
| Earth and Planetary Sciences | 1 | 9% |
| Engineering | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 2 | 18% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 15 August 2013.
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#22,759,802
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Outputs from Analytical & Bioanalytical Chemistry
#7,542
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#259,186
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Outputs of similar age from Analytical & Bioanalytical Chemistry
#81
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