Capillary isoelectric focusing with whole column imaging detection (iCIEF): A new approach to the characterization and quantification of salivary α-amylase.

Saliva is an easily collected biological fluid with potentially important diagnostic value. While gel electrophoresis is generally used for salivary analysis, we employed the capillary isoelectric focusing technique to allow for a rapid, automated mode of electrophoresis. Capillary isoelectric focusing coupled with UV whole column imaging detection (iCIEF) was used to develop a robust protocol to characterize salivary α-amylase collected from various glands. Notably, three sample preparation methods were examined: ultrafiltration, gel-filtration, and starch affinity interaction with salivary amylase. Salivary α-amylase separated into two major peaks before sample treatment; while both filtration methods and starch affinity interaction of salivary amylase enhanced the resolution of isozymes, desalting with gel-filtration displayed the best recovery and the highest resolution of isozymes. Good agreement existed between the observed isoelectric points and the values reported in the literature. In addition, a high level of precision was apparent, and the relative standard deviation for replicates was less than 0.5% for pIs (peak positions) and below 10% for peak area. Furthermore, saliva secreted from the parotid gland proved to have a higher amylase content compared to either secretions from the submandibular/sublingual complex, or whole saliva, as well as amylase enhancement under stimulation. The results suggest that the iCIEF technique can be used to accurately resolve and quantitate amylase isozymes in a rapid and automated fashion, and that gel-filtration should be applied to saliva samples beforehand to allow for optimal purification and characterization.

Development of a multichannel microfluidic system with Schlieren imaging microscopy for online chip-based moving boundary electrophoresis.

The concentration gradient detection method based on the Schlieren optics employed for electrophoresis analyses by extending the technology to a multi-channel system using a prototyped microfluidic chip (thinXXS Micro-technology, Germany). The results prove that coupling a chip-based microfluidic device with Schlieren detection is an appropriate approach to improve the electrophoretic separations. The effects of channel's geometry and dimension were investigated by conducting the experiments in channels with different cross sectional areas. Fast kinetic data acquisition of the charge-coupled device (CCD) camera facilitated recording of a time sequence of optical images, demonstrating the potential of the CCD camera as a powerful tool for studying dynamic processes such as diffusion. Diffusion coefficients of sample proteins were measured under static and dynamic conditions, where the static mode demonstrated more accurate results. Furthermore, the Fourier transformation was employed to improve the Schlieren images for quantitative analysis of the diffusion coefficient measurement.

Accurate determination of the diffusion coefficient of proteins by Fourier analysis with whole column imaging detection.

Analysis in the frequency domain is considered a powerful tool to elicit precise information from spectroscopic signals. In this study, the Fourier transformation technique is employed to determine the diffusion coefficient (D) of a number of proteins in the frequency domain. Analytical approaches are investigated for determination of D from both experimental and data treatment viewpoints. The diffusion process is modeled to calculate diffusion coefficients based on the Fourier transformation solution to Fick's law equation, and its results are compared to time domain results. The simulations characterize optimum spatial and temporal conditions and demonstrate the noise tolerance of the method. The proposed model is validated by its application for the electropherograms from the diffusion path of a set of proteins. Real-time dynamic scanning is conducted to monitor dispersion by employing whole column imaging detection technology in combination with capillary isoelectric focusing (CIEF) and the imaging plug flow (iPF) experiment. These experimental techniques provide different peak shapes, which are utilized to demonstrate the Fourier transformation ability in extracting diffusion coefficients out of irregular shape signals. Experimental results confirmed that the Fourier transformation procedure substantially enhanced the accuracy of the determined values compared to those obtained in the time domain.