Intracellular Compartmentalization of DNA Fragments in Cultured Airway Epithelial Cells Mediated by Cationic Lipids

Purpose. The amount and intracellular distribution of DNA fragments (491 -bp) was characterized after transfection in vitro with a commercially available cationic lipid. Localization of fragment to the nucleus, its subcellular distribution, and integrity within the cells was determined for various times after transfection. Methods. Cystic fibrosis (CF) airway epithelial cells were transfected with ³²P and FITC labeled single-stranded (ss) or double-stranded (ds) DNA fragments complexed with Lipofectamine^® at various charge ratios. Results. A 5/1 (+/–) charge ratio was found to be the optimal ratio for transfection of both ss-and dsDNA. After a 5 h exposure, 7.51 ± 0.89% of the radioactivity was associated with the nuclear fraction whereas only 1.07 ± 0.23%, was found in the nuclear fraction when dsDNA was used. The nuclear radioactivity detected after a 24 h exposure was only 1/3 of that after 5 h. Analysis of fragment stability in the cytosolic and nuclear fractions showed the presence of intact fragment in each subcellular compartment. No intranuclear/intracellular fragment could be detected in control experiments with naked DNA. Conclusions. The results from these experiments indicate that small fragments of DNA can be efficiently and rapidly transferred intact to the cell nucleus using cationic lipids and that ssDNA fragments are more effective than dsDNA fragments for nuclear delivery.     

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An improved windowing technique for heart rate variability power spectrum estimation

Spectral analysis of heart rate variability (HRV) is an accepted method for assessment of cardiac autonomic function and its relationship to numerous disorders and diseases. Discrete Fourier transform (DFT) based methods are widely used for their easy applicability, computational speed and the possibility for direct interpretation of results. This study assesses the limitations of windowing of the RR interval series for power spectrum estimation using DFT for heart rate variability studies. The mean value of the RR interval series should be subtracted before windowing. This may leave a small residual DC component after windowing, but the RR interval series is properly tapered to zero at the beginning and end of the window. However, if the windowed RR interval series has a non-zero mean then subtracting this mean will create an abrupt transition between the first and last data points, and the padded zeros. This is equivalent to superimposing upon the RR interval series a rectangular pulse of the same length as the window, with a height equal to the subtracted mean value. In the present paper an approach to overcome the above effects of the window in reducing the signal energy and introducing low frequency components into the spectrum has been suggested and incorporated. Results have been compared for DC biasing of windowed data spectrum, bias of windowed data removed by subtraction of mean from data, and data preprocessed to remove windowed mean level and to maintain mean power. Thus the preprocessing of RR interval series with this method improves the accuracy of HRV analysis methods. The study was carried out by smoothing the complete RR interval series by single Hann window and by 50% overlapping the data segments of 256 data points followed by DFT. Overlapping the data segments provides equal weight to all values in the RR interval series and a smoothed spectral estimate with clearly dominant peaks in low- and high-frequency regions.