RESUMEN
Capillary electrophoresis (CE) is a powerful and sensitive tool for speciation analysis when combined with inductively coupled plasma mass spectrometry (ICP-MS); however, the performance of this technique can be limited by the nature of pneumatic nebulizers. This study compares two commercially available pneumatic nebulizers to a newly introduced vibrating capillary nebulizer (VCN) for on-line coupling of CE with ICP-MS. The VCN is a low-cost, non-pneumatic nebulizer that is based on the design of capillary vibrating sharp-edge spray ionization. As a piezoelectrically driven nebulization source, the VCN creates an aerosol independent of gas flows and does not produce a low-pressure region at the nebulizer orifice. To compare the systems, we performed replicate analyses of sulfate in river water with each nebulizer and the same CE and ICP-MS instruments and determined the figures of merit of each setup. With the CE-VCN-ICP-MS setup, we achieved around 2-4 times lower sensitivity compared to the commercial setups. However, the VCN-based setup provided lower noise levels and better linear correlation from the analysis of calibration standards, which resulted in indistinguishable LOD and LOQ values from the in-house-built VCN-based and commercial setups for CE-ICP-MS analysis. The VCN is found to have the highest baseline stability with a standard deviation of 3500 cts s-1, corresponding to an RSD of 2.7%. High reproducibility is found with the VCN with a peak area RSD of 4.1% between 3 replicate measurements.
RESUMEN
We report an analytical methodology for the quantification of sulfur in biological molecules via a species-unspecific postcolumn isotope dilution (online ID) approach using capillary electrophoresis (CE) coupled online with inductively coupled plasma-mass spectrometry (online ID CE/ICP-MS). The method was optimized using a mixture of standard compounds including sulfate, methionine, cysteine, cystine, and albumin, yielding compound recoveries between 98 and 105%. The quantity of sulfur is further converted to the quantity of the compounds owing to the prior knowledge of the sulfur content in the molecules. The limit of detection and limit of quantification of sulfur in the compounds were 1.3-2.6 and 4.1-8.4 mg L-1, respectively, with a correlation coefficient of 0.99 within the concentration range of sulfur of 5-100 mg L-1. The capability of the method was extended to quantify albumin in its native matrix (i.e., in serum) using experimentally prepared serum spiked with a pure albumin standard for validation. The relative expanded uncertainty of the method for the quantification of albumin was 6.7% (k = 2). Finally, we tested the applicability of the method on real samples by the analysis of albumin in bovine and human sera. For automated data assessment, a software application (IsoCor)âwhich was developed by us in a previous workâwas developed further for handling of online ID data. The method has several improvements compared to previously published setups: (i) reduced adsorption of proteins onto the capillary wall owing to a special capillary-coating procedure, (ii) baseline separation of the compounds in less than 30 min via CE, (iii) quantification of several sulfur species within one run by means of the online setup, (iv) SI traceability of the quantification results through online ID, and (v) facilitated data processing of the transient signals using the IsoCor application. Our method can be used as an accurate approach for quantification of proteins and other biological molecules via sulfur analysis in complex matrices for various fields, such as environmental, biological, and pharmaceutical studies as well as clinical diagnosis.