Human endothelin converting enzyme-2 (ECE2): characterization of mRNA species and chromosomal localization.

Generation of the functionally pleiotropic members of the endothelin vasoactive peptide family is critically catalyzed by unique type II metalloproteases, termed endothelin converting enzymes (ECE). Isolation of human ECE-2 (EC 3.4.24.71) cDNAs revealed deduced open reading frames of 787 and 765 amino acids with approximately 60% identity with human ECE-1. Characterization of mRNA variants revealed mRNA structural diversity at the 5'-terminus. Two mRNA species exist containing distinct first and second exons. Furthermore, in one of these species, an in-frame deletion of the intracytoplasmic domain removed 29 amino acids. Because of the previously reported human genetic diseases ascribed to germline mutations of member genes of the endothelin family, ECE2 was localized in human chromosomes with fluorescence in situ hybridization and radiation hybrid mapping to 3q28-q29 and SHGC-20171/D3S1571, respectively.

Medical image compression by discrete cosine transform spectral similarity strategy.

Due to the bandwidth and storage limitations, medical images must be compressed before transmission and storage. However, the compression will reduce the image fidelity, especially when the images are compressed at lower bit rates. The reconstructed images suffer from blocking artifacts and the image quality will be severely degraded under the circumstance of high compression ratios. In this paper, we present a strategy to increase the compression ratio with simple computational burden and excellent decoded quality. We regard the discrete cosine transform as a bandpass filter to decompose a sub-block into equal-sized bands. After a band gathering operation, a high similarity property among bands is found. By the utilization of similarity property, the bit rate of compression can be greatly reduced. Meanwhile, the characteristics of the original image are not sacrificed. Thus, it can avoid the misdiagnosis of diseases for doctors. Simulations are carried to different kind of medical images to demonstrate that the proposed method achieves better performance when compared to other existing transform coding scheme as the JPEG in terms of bit rate and quality. For the case of angiogram image, its peak signal-to-noise-ratio gain is 13.5 dB at the same bit rate of 0.15 bits per pixel when comparing to the JPEG compression. As to the other kind of medical images, their benefits are not so obvious as an angiogram image; however, the gains for them are still from 4-8 dB at high compression ratios. Two doctors from the Department of Radiology, National Cheng Kung University Hospital, Tainan, Taiwan, R.O.C., and Chang Gung Medical Hospital, Kaoshuing, Taiwan, R.O.C., are invited to verify the decoded image quality; the diagnoses of all the test images are correct when the compression ratios are below 20.

An adaptive 3-D discrete cosine transform coder for medical image compression.

In this communication, a new three-dimensional (3-D) discrete cosine transform (DCT) coder for medical images is presented. In the proposed method, a segmentation technique based on the local energy magnitude is used to segment subblocks of the image into different energy levels. Then, those subblocks with the same energy level are gathered to form a 3-D cuboid. Finally, 3-D DCT is employed to compress the 3-D cuboid individually. Simulation results show that the reconstructed images achieve a bit rate lower than 0.25 bit per pixel even when the compression ratios are higher than 35. As compared with the results by JPEG and other strategies, it is found that the proposed method achieves better qualities of decoded images than by JPEG and the other strategies.

In vivo expression profile of an endothelial nitric oxide synthase promoter-reporter transgene.

Endothelium-derived nitric oxide (NO) is primarily attributable to constitutive expression of the endothelial nitric oxide synthase (eNOS) gene. Although a more comprehensive understanding of transcriptional regulation of eNOS is emerging with respect to in vitro regulatory pathways, their relevance in vivo warrants assessment. In this regard, promoter-reporter insertional transgenic murine lines were created containing 5,200 bp of the native murine eNOS promoter directing transcription of nuclear-localized beta-galactosidase. Examination of beta-galactosidase expression in heart, lung, kidney, liver, spleen, and brain of adult mice demonstrated robust signal in large and medium-sized blood vessels. Small arterioles, capillaries, and venules of the microvasculature were notably negative, with the exception of the vasa recta of the medullary circulation of the kidney, which was strongly positive. Only in the brain was the reporter expressed in non-endothelial cell types, such as the CA1 region of the hippocampus. Epithelial cells of the bronchi, bronchioles, and alveoli were scored as negative, as was renal tubular epithelium. Cardiac myocytes, skeletal muscle, and smooth muscle of both vascular and nonvascular sources failed to demonstrate beta-galactosidase staining. Expression was uniform across multiple founders and was not significantly affected by genomic integration site. These transgenic eNOS promoter-reporter lines will be a valuable resource for ongoing studies addressing the regulated expression of eNOS in vivo in both health and disease.

Designing better adaptive sampling algorithms for ECG Holter systems.

Let psi be any adaptive sampling algorithm that can run in real time on a tapeless multichannel electrocardiogram (ECG) Holter system. Simple methods which can significantly improve psi's fidelity are described and their results are compared in this paper. It is shown that by adding some simple tests to psi, the signals reconstructed by psi can be improved as much as 5.45 dB. It is also shown that under the same data rate, a good data compressor with slowly sampled input ECG is preferable to a bad data compressor with highly sampled input ECG.

Improving the performance of electrocardiogram sub-band coder by extensive Markov system.

The paper reports on a continuation of previous work on the digital coding of 500 samples s-1 ECG at 240 bits s-1. Focus is on six-band sub-band coding (SBC) with extensive Markov system as post-processors for each sub-band signal. An extensive Markov process, which considers both the coding redundancy and the intersample redundancy, utilises the redundancies by predicting the incoming n samples based on the previous m samples that constitute an extensive Markov process state. Both the previous m samples and the incoming n samples are considered as extension codes of the quantisation levels. Simulation results show that a reproduction with an average of signals ratio (SNR) of 27.21 dB or peak SNR of 58.6 dB was achieved at an average bit rate of 0.48 bit per sample, which corresponds to an average compression ratio of 25, whereas under the same signal fidelity, the previous proposed SBC system achieved an average bit rate of 0.714 bit per sample.

An extensive Markov system for ECG exact coding.

In this paper, an extensive Markov process, which considers both the coding redundancy and the intersample redundancy, is presented to measure the entropy value of an ECG signal more accurately. It utilizes the intersample correlations by predicting the incoming n samples based on the previous m samples which constitute an extensive Markov process state. Theories of the extensive Markov process and conventional n repeated applications of m-th order Markov process are studied first in this paper. After that, they are realized for ECG exact coding. Results show that a better performance can be achieved by our system. The average code length for the extensive Markov system on the second difference signals was 2.512 b/sample, while the average Huffman code length for the second difference signals was 3.326 b/sample.

AZTDIS--a two-phase real-time ECG data compressor.

An ECG sampled at a rate of 360 samples s-1 or more produces a large amount of redundant data that are difficult to store and transmit; we therefore need a process to represent the signals with clinically acceptable fidelity and with as small a number of code bits as possible. In this paper, a real-time ECG data-compression algorithm, AZTDIS, is presented. AZTDIS is an efficient algorithm which locates significant samples and at the same time encodes linear segments between them by using linear interpolation. The significant samples selected include, but are not limited to, the samples that have significant displacement from the encoded signal such that the allowed maximal error is limited to a constant epsilon, which is specified by the user. The way that AZTDIS computes the displacement of a sample from the encoded signal guarantees that the high activity regions are more accurately coded. The results from AZTDIS are compared with those from the well-known data-compression algorithm, AZTEC, which is also a real-time algorithm. It is found that under the same bit rate, a considerable improvement of root-mean-square error (RMSerr) can be achieved by employing the proposed AZTDIS algorithm. An average value of RMSerr of 9.715 can be achieved even at an average bit rate of 0.543 bits per sample by employing AZTDIS. By tuning the allowed maximal error of AZTDIS such that it has similar bit rate to AZTEC, the average value of RMSerr achieved by AZTDIS is 5.554 while the average value of RMSerr achieved by AZTEC under the same bit rate is 19.368.

ECG data compression by corner detection.

An ECG sampled at a rate of 360, 500 samples s-1 or more produces a large amount of redundant data that are difficult to store and transmit. A process is therefore required to represent the signals with clinically acceptable fidelity and with the least code bits possible. In the paper, a real-time ECG data compressing algorithm, CORNER, is presented. CORNER is an efficient algorithm which locates significant samples and at the same time encodes the linear segments between them using linear interpolation. The samples selected include, but are not limited to, the samples that are significantly displaced from the encoded signal such that the allowed maximum error is limited to a constant epsilon which is specified by the users. The way in which CORNER computes the displacement of a sample from the encoded signal guarantees that the high activity regions are more accurately coded. The results are compared with those of the well known data compression algorithm, AZTEC, which is also a real-time algorithm. It is found that, under the same bit rate, a considerable improvement of the signal-to-noise ratio (SNR) and root mean square error (RMSerr) can be achieved by employing the proposed CORNER algorithm. An average value of SNR (RMSerr) of 27.0 dB (5.668) can be achieved even at an average bit rate of 0.79 bit sample-1 by employing CORNER, whereas the average value of SNR (RMSerr) achieved by AZTEC under the same bit rate is 16.60 dB (19.368).

Six-band sub-band coder on ECG waveforms.

An ECG sampled at a rate of 500 samples s-1 or more produces a large amount of redundant data that are difficult to store and transmit. A process is therefore required to represent the signals with clinically acceptable fidelity and with the least code bits possible. In the paper, an efficient sub-band coding method for encoding ECG waveforms is presented. Although sub-band coding has been successfully applied to speech signals, it is the first time that this technique has been applied to the encoding of ECG waveforms. A frequency band decomposition of an ECG waveform is carried out by means of quadrature mirror filters (QMF), which split the ECG spectrum into six bands of unequal width. In the lower frequency bands, which contain most of the ECG spectrum energy, a larger number of bits per sample is used, whereas in upper frequency bands, which contain noise-like signals, fewer bits per sample and the run length coding method are used. The simulation results are presented in terms of bit rates and the quality of the reconstructed waveforms. The results show that a reproduction with an average signal-to-noise ratio (SNR) of 29.97 dB can be achieved even at an average bit rate of 0.81 bits per sample.

SLOPE--a real-time ECG data compressor.

An ECG sampled at a rate of 250 samples s-1 or more produces a large amount of redundant data that are difficult to store and transmit. In the paper, a real-time ECG data compressor, SLOPE, is presented. SLOPE considers some adjacent samples as a vector, and this vector is extended if the coming sample falls in a fan spanned by this vector and a threshold angle; otherwise, it is delimited as a linear segment. By this means SLOPE repeatedly delimits linear segments of different lengths and different slopes. The Huffman codes for the parameters to describe this linear segment are transmitted for that linear segment. SLOPEa, which is a slightly modified version of SLOPE, is used to compress ambulatory ECG data. All the operations used by SLOPE and SLOPEa are simple integer operations, both SLOPE and SLOPEa being real-time compressors. Experimental results show that an average of 192 bits per channel per second (bpcs) for each ECG signal is obtained by SLOPE and an average of 148 bpcs for each ECG signal is obtained by SLOPEa.