The major elderberry (Sambucus nigra) fruit protein is a lectin derived from a truncated type 2 ribosome-inactivating protein

The major protein of elderberry ( Sambucus nigra L.) fruits is a lectin, called Sambucus nigra agglutinin IVf or SNAIVf. This lectin is composed of subunits that strongly resemble the B chain of the type 2 ribosome-inactivating protein (RIP), called SNAVf, present in the same tissue. To corroborate the possible relationship between both proteins their corresponding cDNAs were cloned and compared. Alignment of the deduced amino acid sequences revealed that the cDNA encoding SNAIVf is almost identical to that of SNAVf except that its A chain is truncated. Northern blot analysis confirmed that the mRNA encoding SNAIVf is about 500 nucleotides shorter than the SNAVf mRNA. In addition, the occurrence of a truncated type 2 RIP gene was unambiguously demonstrated by the analysis of PCR amplified genomic sequences. These results not only demonstrate for the first time that a plant lectin is encoded by a truncated type 2 RIP gene but also address important questions with respect to the molecular evolution of RIP and lectins.     

Noise Reduction in Electron Tomographic Reconstructions Using Nonlinear Anisotropic Diffusion

Electron tomography is a powerful technique capable of giving unique insights into the three-dimensional structural organization of pleomorphic biological objects. However, visualization and interpretation of the resulting volumetric data are hampered by an extremely low signal-to-noise ratio, especially when ice-embedded biological specimens are investigated. Usually, isosurface representation or volume rendering of such data is hindered without any further signal enhancement. We propose a novel technique for noise reduction based on nonlinear anisotropic diffusion. The approach combines efficient noise reduction with excellent signal preservation and is clearly superior to conventional methods (e.g., low-pass and median filtering) and invariant wavelet transform filtering. The gain in the signal-to-noise ratio is verified and demonstrated by means of Fourier shell correlation. Improved visualization performance after processing the 3D images is demonstrated with two examples, tomographic reconstructions of chromatin and of a mitochondrion. Parameter settings and discretization stencils are presented in detail.     

Relationship Between Time- and Frequency-Domain Analyses of Angular Head Movements in the Squirrel Monkey

We used the three-dimensional magnetic search-coil recording technique to study the range of active angular head movements made by squirrel monkeys. There were two goals in this study: (1) to determine the range of angular velocities and accelerations as well as the bandwidth and other frequency characteristics of active head movements and (2) to compare analyses of transients of velocity and acceleration that are studied by residual analysis, Fourier transform, and wavelet transform of the head velocity signal.The residual analysis showed that the shape and duration of the transients affected the bandwidth. During the time after the head had begun to accelerate, the frequency content of the head movement extended into the range of 6 to 12 Hz. When considering all three planes of rotation, approximately 75% of the transients had peak acceleration between 2,000 and 10,000 deg/s² and a peak velocity of 50 to 400 deg/s. A peak acceleration of >10,000 deg/s² was recorded in 10% of the transients.These findings indicate that active head movements in squirrel monkeys cover a higher range of frequencies, accelerations, and velocities than have typically been used in previous eye-movement and neuronal studies of the reflexes that control gaze. We further conclude that the choice of a method for analyzing transient, time-varying biological signals is dependent on the desired information. Residual analysis provides detailed resolution in the time domain, but estimation of the frequency content of the signal is dependent on the portions selected for analysis and the choice of filters. Fourier transform provides a representation of the power spectrum in the frequency domain but without any inherent temporal resolution. We show that the wavelet transform, a novel method as applied to the signal analysis goals of this study, is the most useful technique for relating time- and frequency-domain information during a continuous signal.     

ECG Data Compression Using Modified Run Length Encoding of Wavelet Coefficients for Holter Monitoring

ObjectiveIn cardiac patient-care, compression of long-term ECG data is essential to minimize the data storage requirement and transmission cost. Hence, this paper presents a novel electrocardiogram data compression technique which utilizes modified run-length encoding of wavelet coefficients.MethodFirst, wavelet transform is applied to the ECG data which decomposes it and packs maximum energy to less number of transform coefficients. The wavelet transform coefficients are quantized using dead-zone quantization. It discards small valued coefficients lying in the dead-zone interval while other coefficients are kept at the formulated quantized output interval. Among all the quantized coefficients, an average value is assigned to those coefficients for which energy packing efficiency is less than 99.99%. The obtained coefficients are encoded using modified run-length coding. It offers higher compression ratio than conventional run-length coding without any loss of information.ResultsCompression performance of the proposed technique is evaluated using different ECG records taken from the MIT-BIH arrhythmia database. The average compression performance in terms of compression ratio, percent root mean square difference, normalized percent mean square difference, and signal to noise ratio are 17.18, 3.92, 6.36, and 28.27 dB respectively for 48 ECG records.ConclusionThe compression results obtained by the proposed technique is better than techniques recently introduced by others. The proposed technique can be utilized for compression of ECG records of Holter monitoring.     

Evaluation of texture features in spatial and frequency domain for automatic discrimination of histologic tissue

OBJECTIVE: To investigate the applicability of different texture features in automatic discrimination of microscopic views from benign common nevi and malignant melanoma lesions. STUDY DESIGN: In tissue counter analysis (TCA) the images are dissected into square elements used for feature calculation. The first class of features is based on the histogram, the co-occurrence matrix and the texture moments. The second class is derived from spectral properties of the wavelet Daubechie 4 and the Fourier transform. Square elements from images of a training set are classified by Classification and Regression Trees analysis. RESULTS: Features from the histogram and the co-occurrence matrix enable correct classification of 94.7% of nevi elements and 92.6% of melanoma elements in the training set. Classification results are applied to individual test set cases. Discriminant analysis based on the percentage of "malignant elements" showed correct classification of all nevi cases and 95% of melanoma cases. Features derived from the wavelet and Fourier spectrum showed correct results for 88.8% and 79.3% of nevi and 85.6% and 81.5% of melanoma elements, respectively. CONCLUSION: TCA is a potential diagnostic tool in automatic analysis of melanocytic skin tumors. Histogram and co-occurrence matrix features are superior to the wavelet and the Fourier features.     

繁缕核糖体失活蛋白基因克隆及序列分析

采用同源克隆结合RACE法,克隆了繁缕核糖体失活蛋白的全长cDNA,命名为q3(GenBank accession GQ870262)。序列分析结果表明,q3的开放阅读框(ORF)长780 bp,编码259个氨基酸。序列G+C含量为41.5%,与大部分Ⅰ型RIP基因相近。q3编码的蛋白质命名为Q3,理论分子量为28.16 kD,pI为9.44,均与Ⅰ型核糖体失活蛋白相近;包含由23个氨基酸组成的信号肽。功能结构域分析发现,该蛋白含有3个蛋白激酶磷酸化位点、4个络氨酸蛋白激酶磷酸化位点和7个N-肉豆蔻酰化位点。三级结构预测发现,有35.52%的氨基酸残基参与了α螺旋,24.32%的氨基酸残基组成延伸链,40.15%的氨基酸残基随机缠绕其中。基于繁缕及其近缘种核糖体失活蛋白的氨基酸序列构建的系统发育树显示,其结构与经典分类结果基本一致。     

Research on Similarity Measurement for Texture Image Retrieval

A complete texture image retrieval system includes two techniques: texture feature extraction and similarity measurement. Specifically, similarity measurement is a key problem for texture image retrieval study. In this paper, we present an effective similarity measurement formula. The MIT vision texture database, the Brodatz texture database, and the Outex texture database were used to verify the retrieval performance of the proposed similarity measurement method. Dual-tree complex wavelet transform and nonsubsampled contourlet transform were used to extract texture features. Experimental results show that the proposed similarity measurement method achieves better retrieval performance than some existing similarity measurement methods.     

Non-mulberry silk sericin/poly (vinyl alcohol) hydrogel matrices for potential biotechnological applications

This study reports a novel biopolymeric matrix fabricated by chemically cross-linking poly (vinyl alcohol) with silk sericin protein obtained from cocoons of the tropical tasar silkworm Antheraea mylitta. Glutaraldehyde was used as a cross-linking agent with hydrochloric acid acting as an initiator. The matrices were biophysically characterized and the cytocompatibility of the matrices was evaluated for their suitability as biomaterials. The surface morphology was assessed using atomic force microscopy while the changes taking place after cross-linking were confirmed by Fourier transform infrared spectroscopy. The enhanced thermal stability of the constructs was assessed by thermogravimetric and differential scanning calorimetry. Fourier transform infrared spectroscopy analysis showed that sericin was chemically cross-linked with poly (vinyl alcohol) using glutaraldehyde. Silk sericin protein demonstrated a favorable effect on animal cell culture by successfully improving the adhering and spreading of cells on the poorly adhering surface of poly (vinyl alcohol). Confocal microscopy revealed cell spreading and actin filament development in sericin/poly (vinyl alcohol) hydrogel matrices. These findings prove the potential of non-mulberry silk sericin/poly (vinyl alcohol) hydrogel matrices to be used as biocompatible and biopolymeric material for tissue-engineering and biotechnological applications.     

Wavelet transform to quantify heart rate variability and to assess its instantaneous changes.

Heart rate variability is a recognized parameter for assessing autonomous nervous system activity. Fourier transform, the most commonly used method to analyze variability, does not offer an easy assessment of its dynamics because of limitations inherent in its stationary hypothesis. Conversely, wavelet transform allows analysis of nonstationary signals. We compared the respective yields of Fourier and wavelet transforms in analyzing heart rate variability during dynamic changes in autonomous nervous system balance induced by atropine and propranolol. Fourier and wavelet transforms were applied to sequences of heart rate intervals in six subjects receiving increasing doses of atropine and propranolol. At the lowest doses of atropine administered, heart rate variability increased, followed by a progressive decrease with higher doses. With the first dose of propranolol, there was a significant increase in heart rate variability, which progressively disappeared after the last dose. Wavelet transform gave significantly better quantitative analysis of heart rate variability than did Fourier transform during autonomous nervous system adaptations induced by both agents and provided novel temporally localized information.     

Rate matrices for analyzing large families of protein sequences.

We propose and study a new approach for the analysis of families of protein sequences. This method is related to the LogDet distances used in phylogenetic reconstructions; it can be viewed as an attempt to embed these distances into a multidimensional framework. The proposed method starts by associating a Markov matrix to each pairwise alignment deduced from a given multiple alignment. The central objects under consideration here are matrix-valued logarithms L of these Markov matrices, which exist under conditions that are compatible with fairly large divergence between the sequences. These logarithms allow us to compare data from a family of aligned proteins with simple models (in particular, continuous reversible Markov models) and to test the adequacy of such models. If one neglects fluctuations arising from the finite length of sequences, any continuous reversible Markov model with a single rate matrix Q over an arbitrary tree predicts that all the observed matrices L are multiples of Q. Our method exploits this fact, without relying on any tree estimation. We test this prediction on a family of proteins encoded by the mitochondrial genome of 26 multicellular animals, which include vertebrates, arthropods, echinoderms, molluscs, and nematodes. A principal component analysis of the observed matrices L shows that a single rate model can be used as a rough approximation to the data, but that systematic deviations from any such model are unmistakable and related to the evolutionary history of the species under consideration.     

On the contentious sequence and glycosylation motif of the ribosome inactivating plant protein gelonin

The amino acid sequence and the glycosylation motif of the ribosome inactivating protein (RIP) gelonin are identified by Fourier transform ion cyclotron resonance mass spectrometry. Intact gelonin as isolated from the seeds of Gelonium multiflorum consists of at least three different post-translational modified forms: analysis of gelonin peptides as obtained by proteolytic digestion is consistent with the amino acid sequence published by Nolan et al. High resolution mass determination established a glycosylation pattern of GlcNAc2Man(3-5)Xyl. N189 was identified as glycosylation site. The proposed glycan structure is consistent with a standard plant N-glycosylation pattern as found in other RIP. Based on these results we suggest that gelonin is located in the vacuole of Gelonium multiflorum seeds.     

Wavelet transform as a potential tool for ECG analysis and compression

The recently introduced wavelet transform is a member of the class of time-frequency representations which include the Gabor short-time Fourier transform and Wigner-Ville distribution. Such techniques are of significance because of their ability to display the spectral content of a signal as time elapses. The value of the wavelet transform as a signal analysis tool has been demonstrated by its successful application to the study of turbulence and processing of speech and music. Since, in common with these subjects, both the time and frequency content of physiological signals are often of interest (the ECG being an obvious example), the wavelet transform represents a particularly relevant means of analysis. Following a brief introduction to the wavelet transform and its implementation, this paper describes a preliminary investigation into its application to the study of both ECG and heart rate variability data. In addition, the wavelet transform can be used to perform multiresolution signal decomposition. Since this process can be considered as a sub-band coding technique, it offers the opportunity for data compression, which can be implemented using efficient pyramidal algorithms. Results of the compression and reconstruction of ECG data are given which suggest that the wavelet transform is well suited to this task.     

Empirical Mode Decomposition and Wavelet Transform Based ECG Data Compression Scheme

ObjectiveIn health-care systems, compression is an essential tool to solve the storage and transmission problems. In this regard, this paper reports a new electrocardiogram (ECG) data compression scheme which employs sifting function based empirical mode decomposition (EMD) and discrete wavelet transform.MethodEMD based on sifting function is utilized to get the first intrinsic mode function (IMF). After EMD, the first IMF and four significant sifting functions are combined together. This combination is free from many irrelevant components of the signal. Discrete wavelet transform (DWT) with mother wavelet ‘bior4.4’ is applied to this combination. The transform coefficients obtained after DWT are passed through dead-zone quantization. It discards small transform coefficients lying around zero. Further, integer conversion of coefficients and run-length encoding are utilized to achieve a compressed form of ECG data.ResultsCompression performance of the proposed scheme is evaluated using 48 ECG records of the MIT-BIH arrhythmia database. In the comparison of compression results, it is observed that the proposed method exhibits better performance than many recent ECG compressors. A mean opinion score test is also conducted to evaluate the true quality of the reconstructed ECG signals.ConclusionThe proposed scheme offers better compression performance with preserving the key features of the signal very well.     

Wavelets in bioinformatics and computational biology: state of art and perspectives

MOTIVATION: At a recent meeting, the wavelet transform was depicted as a small child kicking back at its father, the Fourier transform. Wavelets are more efficient and faster than Fourier methods in capturing the essence of data. Nowadays there is a growing interest in using wavelets in the analysis of biological sequences and molecular biology-related signals. RESULTS: This review is intended to summarize the potential of state of the art wavelets, and in particular wavelet statistical methodology, in different areas of molecular biology: genome sequence, protein structure and microarray data analysis. I conclude by discussing the use of wavelets in modeling biological structures.     

Identification of plasma membrane macro- and microdomains from wavelet analysis of FRET microscopy

In this study, we sought to characterize functional signaling domains by applying the multiresolution properties of the continuous wavelet transform to fluorescence resonance energy transfer (FRET) microscopic images of plasma membranes. A genetically encoded FRET reporter of protein kinase C (PKC)-dependent phosphorylation was expressed in COS1 cells. Differences between wavelet coefficient matrices revealed several heterogeneous domains (typically ranging from 1 to 5 microm), reflecting the dynamic balance between PKC and phosphatase activity during stimulation with phorbol-12,13-dibutyrate or acetylcholine. The balance in these domains was not necessarily reflected in the overall plasma membrane changes, and observed heterogeneity was absent when cells were exposed to a phosphatase or PKC inhibitor. Prolonged exposure to phorbol-12,13-dibutyrate and acetylcholine yielded more homogeneous FRET distribution in plasma membranes. The proposed wavelet-based image analysis provides, for the first time, a basis and a means of detecting and quantifying dynamic changes in functional signaling domains, and may find broader application in studying fine aspects of cellular signaling by various imaging reporters.     

Mechanistic Evaluation of the Effect of Sintering on Compritol® 888 ATO Matrices

The present research studied the effect of sintering technique in the development of a controlled release formulation for ketorolac tromethamine. The method consisted of mixing drug and wax powder (Compritol® 888 ATO) along with lactose as diluent and talc as lubricant followed by direct compression at room temperature. The compressed fluffy matrices were kept at 80°C for 1, 2, and 3 h for sintering. The sintered tablets were characterized by their physical parameters and in vitro dissolution profile. The sintering time markedly affected the drug release properties of Compritol® 888 ATO matrices. It is notable that the release rate of ketorolac tromethamine from matrices was inversely related to the time of sintering. This may be due to the increase in the extent and firmness of sintering which further compacts the mass so that drug release is affected. Contact angle measurement and scanning electron microscopy analysis indicated that heat treatment caused the wax to melt and redistribute. This redistributed wax formed a network-like structure in which the drug along with lactose is entrapped. This particular formed matrix is responsible for retarding the drug release. Fourier transform infrared spectroscopy results did not show any drug–wax interaction due to sintering. Differential scanning calorimetric and powder X-ray diffraction studies ruled out the occurrence of solid solution and polymorphic changes of the drug. Drug release from the wax tablets with or without sintering was best described by the Higuchi equation.     

Dynamics of local maxima chains in spectra of human electroencephalogram

The continuous wavelet transform was applied to the human EEG signals recorded in different states of brain activity. The dynamics of local maxima chains in the matrices of the continuous wavelet transform coefficients was studied. The typologization method was developed for local maxima chains to separate by their drift in the frequency space as well as by dynamics of their signal “energy.” The method proved to be highly informative. It was shown that it was highly sensitive to a selection of one of two responses to the test question. It is determined that local maxima chains in most cases are gradually increasing and decreasing in the frequency space and by changes in the values of their continuous wavelet transform coefficients. The functional asymmetry in local maxima chains types’ distribution is determined. The results obtained allow us to consider the types of the local maxima chains dynamics as a new phenomenon of EEG activity.     

A novel approach to the recognition of protein architecture from sequence using Fourier analysis and neural networks

A novel method is presented for the prediction of protein architecture from sequence using neural networks. The method involves the preprocessing of protein sequence data by numerically encoding it and then applying a Fourier transform. The encoded and transformed data are then used to train a neural network to recognize a number of different protein architectures. The method proved significantly better than comparable alternative strategies such as percentage dipeptide frequency, but is still limited by the size of the data set and the input demands of a neural network. Its main potential is as a complement to existing fold recognition techniques, with its ability to identify global symmetries within protein structures its greatest strength.