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PubMed1999

Time-frequency methods for detecting spike activity of stomach.

It has been hypothesised by many researchers that the spike activity signals of the stomach are responsible for triggering peristaltic contractions. Since most gastric motility disorders include an abnormality in the contraction pattern, it is very important to access this information non-invasively. The aim in this study is to use abdominal electrogastrogram (EGG) signals to detect the spike activity signals generated by the serosa of the stomach, and hence provide clinicians with a better method to monitor the motility state of the stomach. Through second and third-order spectral estimations performed on the serosal data obtained from canine experiments, it was concluded that the spike activity in serosal signals occupies a frequency range of 50-80 cycles per minute. An increase in this frequency range during strong antral contractions was observed both in the serosal and cutaneous power spectra. By using the 'continuous wavelet transform' with respect to a modified Morlet wavelet, the spike activity signals generated from the serosa of the stomach can be detected and quantified in time from the cutaneous EGG records. During phase III contraction episodes, a detection accuracy of up to 96% from the cutaneous EGG recordings was calculated based on the scored serosal spike activities simultaneously recorded.

Animals↗
PubMed1998

Automated neural network detection of wavelet preprocessed electrocardiogram late potentials.

The aim of the study is to investigate the potential of a feedforward neural network for detecting wavelet preprocessed late potentials. The terminal parts of a simulated QRS complex are processed with a continuous wavelet transform, which leads to a time-frequency representation of the QRS complex. Then, diagnostic feature vectors are obtained by subdividing the representations into several regions and by processing the sum of the decomposition coefficients belonging to each region. The neural network is trained with these feature vectors. Simulated ECGs with varying signal-to-noise ratios are used to train and test the classifier. Results show that correct classification ranges from 79% (high-level noise) to 99% (no noise). The study shows the potential of neural networks for the classification of late potentials that have been preprocessed by a wavelet transform. However, clinical use of this method still requires further investigation.

Arrhythmias, Cardiac↗
PubMedDate not supplied

Multiscale analysis for singularity detection in pulmonary microvascular pressure transients.

This paper addresses the problem of pulmonary microvascular pressure estimation. The "why" and "how" of multiscale approaches in the context of singularity detection are discussed. From a linear viewpoint, the scalogram technique and the multiresolution representation for singularity detection are discussed in general under the wavelet framework. A technique as well as a criterion for the segmentation and the extraction of the region of interest or the optimal scale is proposed. A new nonlinear multiscale technique for singularity detection is also proposed. This multiscale representation is based on rank order filters and on mathematical morphology operators in particular. A scaling parameter is introduced for such operators as in the linear continuous wavelet transform leading to what we call morpholograms. Experiments performed on pulmonary artery pressure transients illustrate how the proposed technique can give a synopsis of the signal characteristics through the scales.

Algorithms↗
PubMedDate not supplied

Adsorptive immobilization of submitochondrial particles on concanavalin A Sepharose-4B.

Submitochondrial particles (SMPs) prepared from beef liver mitochondria were immobilized on concanavalin A Sepharose-4B (Con A-Sepharose). The process of immobilization was optimized by choosing an appropriate buffer system containing Mn2+ and Ca2+. Adsorption of SMPs on Con A-Sepharose was found to be reversible process, nonelectrostatic in nature, and responsive to the presence of methyl alpha-d-glucopyranose and alpha-d-mannose. The involvement of membrane glycoproteins in the adsorption process was thus demonstrated. Further analysis of the data obtained on competition of binding by sugar molecules provided competition constants reflecting the potency of inhibition by each individual carbohydrate. Positive-cooperative interactions for binding to the matrix were observed especially at high concentrations of SMPs. The immobilized preparations were used successfully in continuous catalytic transformations involving succinate-cytochrome c reductase (SCR) and enzyme complex of the inner-mitochondrial membrane. Best results were obtained when such operations were carried out at 37 degrees C.

Adsorption↗
PubMed2006

Understanding of diabetes prevention studies: questionnaire survey of professionals in diabetes care.

AIMS/HYPOTHESIS: Diabetes prevention studies have reported reductions of diabetes risk by up to 60%. Since the underlying metabolic changes are small, the clinical significance of this effect may be overestimated. The present survey explores the extent to which different formats of presenting study results may influence diabetes healthcare professionals' perceptions of the importance of intervention effects on diabetes risk. SUBJECTS, MATERIALS AND METHODS: Participants of three European diabetes conferences (160 nurse educators, 112 physicians, 27 other professionals) were presented with a questionnaire that included nine items, in which results from three diabetes prevention studies were presented in different ways. RESULTS: Participation rate was 96%. Effects were interpreted as important or very important by 92% (255/276) when results were presented as proportions of subjects with diabetes (14% intervention group, 29% control group), by 87% (248/285) when results were communicated as a risk reduction of 57%, by 39% (110/284) when the corresponding fasting plasma glucose values were presented (mean difference 0.3 mmol/l), and by 18% (52/283) when glycosylated haemoglobin values were used (6.0 vs 6.1%). Corresponding results of the three diabetes prevention studies were rated as being of identical importance by only 23, 13 and 16% of participants, respectively. CONCLUSIONS AND INTERPRETATION: Healthcare professionals rate the benefit of preventive interventions substantially higher when changes in diabetes risk are communicated rather than related glycaemic parameters. Transformation of continuous metabolic data into diagnostic categories may impair understanding of study effects.

Allied Health Personnel↗
PubMed2004

A new hybrid strategy for constructing a robust calibration model for near-infrared spectral analysis.

A new hybrid algorithm is proposed for construction of a high-quality calibration model for near-infrared (NIR) spectra that is robust against both spectral interference (including background and noise) and multiple outliers. The algorithm is a combination of continuous wavelet transform (CWT) and a modified iterative reweighted PLS (mIRPLS) procedure. In the proposed algorithm the spectral interference is filtered by CWT at the first stage then mIRPLS is proposed to detect the multiple outliers in the CWT domain. Compared with the original IRPLS method, mIRPLS does not need to adjust variable parameters to achieve optimum calibration results, which makes it very convenient to perform in practice. The final PLS model is constructed robustly because both the spectral interference and multiple outliers are eliminated. In order to validate the effectiveness and universality of the algorithm, it was applied to two different sets of NIR spectra. The results indicate that the proposed strategy can greatly enhance the robustness and predictive ability of NIR spectral analysis.

Journal Article↗
PubMed2006

An adaptive strategy for selecting representative calibration samples in the continuous wavelet domain for near-infrared spectral analysis.

Sample selection is often used to improve the cost-effectiveness of near-infrared (NIR) spectral analysis. When raw NIR spectra are used, however, it is not easy to select appropriate samples, because of background interference and noise. In this paper, a novel adaptive strategy based on selection of representative NIR spectra in the continuous wavelet transform (CWT) domain is described. After pretreatment with the CWT, an extension of the Kennard-Stone (EKS) algorithm was used to adaptively select the most representative NIR spectra, which were then submitted to expensive chemical measurement and multivariate calibration. With the samples selected, a PLS model was finally built for prediction. It is of great interest to find that selection of representative samples in the CWT domain, rather than raw spectra, not only effectively eliminates background interference and noise but also further reduces the number of samples required for a good calibration, resulting in a high-quality regression model that is similar to the model obtained by use of all the samples. The results indicate that the proposed method can effectively enhance the cost-effectiveness of NIR spectral analysis. The strategy proposed here can also be applied to different analytical data for multivariate calibration.

Journal Article↗
PubMedDate not supplied

Automated cardiac auscultation for detection of pathologic heart murmurs.

Experienced cardiologists can usually recognize pathologic heart murmurs with high sensitivity and specificity, although nonspecialists with less clinical experience may have more difficulty. Harsh, pansystolic murmurs of intensity grade > or = 3 at the left upper sternal border (LUSB) are likely to be associated with pathology. In this study, we designed a system for automatically detecting systolic murmurs due to a variety of conditions and examined the correlation between relative murmur intensity and likelihood of pathology. Cardiac auscultatory examinations of 194 children and young adults were recorded, digitized, and stored along with corresponding echocardiographic diagnoses, and automated spectral analysis using continuous wavelet transforms was performed. Patients without heart disease and either no murmur or an innocent murmur (n = 95) were compared to patients with a variety of cardiac diagnoses and a pathologic systolic murmur present at the LUSB (n = 99). The sensitivity and specificity of the automated system for detecting pathologic murmurs with intensity grade > or = 2 were both 96%, and for grade > or = 3 murmurs they were 100%. Automated cardiac auscultation and interpretation may be useful as a diagnostic aid to support clinical decision making.

Adolescent↗
PubMed1998

Neural cell classification by wavelets and multiscale curvature.

A new approach to automatic classification of retinal ganglion cells using multiscale techniques including the continuous wavelet transform, curvature, and standard pattern recognition techniques is described. Each neural cell is represented by its outer contour, and the wavelet transform is calculated from the complex signal defined by the aforementioned contour, leading to the so-called W-representation (Antoine et al. 1996). The normalized multiscale wavelet energy (NMWE) is used to define a set of shape measures associated with the number of details of the shape for a broad range of spatial scales. Next, the more discriminating NMWE coefficients are chosen through a feature ordering technique and fed to statistical classifiers. In addition, the normalized multiscale bending energy (NMBE) is discussed as a means of neural shape description for classification purposes based on the multiscale curvature, i.e. the curvegram, of the neural contour. It is shown that both shape descriptors are suitable for shape classification, presenting similar classification performance. In fact, NMBE has a slightly better recognition rate than NMWE in our experiments. On the other hand, NMWE is less computationally expensive than NMBE, presenting also the potentially useful property of allowing the use of more suitable different analyzing wavelets, depending on the problem under consideration. Therefore, both measures are related and provide a good framework for the design of neural cell description and classification. The methods described in this work have been successfully applied to the classification of two classes of cat retinal ganglion cells, namely alpha and beta (henceforth referred as alpha-cells and beta-cells, respectively), and three statistical classifiers were considered: minimum-distance, k-nearest neighbours and maximum likelihood. The mean recognition rates are near 90%, which is superior to the other shape measures considered. It is argued here that the proposed technique can be adopted as a new general methodology for multiscale shape analysis and recognition, being applicable also to other problems in biological shape characterization in neuroscience and general biomedical image analysis. In the context of analysis of shape complexity, the multiscale energies are coherent with subjective judgements by humans.

Animals↗
PubMed2006

A high resolution approach to estimating time-frequency spectra and their amplitudes.

A high resolution approach to estimating time-frequency spectra (TFS) and associated amplitudes via the use of variable frequency complex demodulation (VFCDM) is presented. This is a two-step procedure in which the previously developed time-varying optimal parameter search (TVOPS) technique is used to obtain TFS, followed by using the VFCDM to obtain even greater TFS resolution and instantaneous amplitudes associated with only the specific frequencies of interest. This combinational use of the TVOPS and the VFCDM is termed the TVOPS-VFCDM. Simulation examples are provided to demonstrate the performance of the TVOPS-VFCDM for high resolution TFS as well as instantaneous amplitude estimation. The simulation results show that the TVOPS-VFCDM approach provides the highest resolution and most accurate amplitude estimates when compared to the smoothed pseudo Wigner-Ville, continuous wavelet transform and Hilbert-Huang transform methods. Application of the TVOPS-VFCDM to renal blood flow data indicates some promise of a quantitative approach to understanding the dynamics of renal autoregulatory mechanisms as well as a possible approach to quantitatively discriminating between different strains of rats.

Algorithms↗
PubMed2006

Adaptive spatio-temporal filtering of multichannel surface EMG signals.

A motor unit (MU) is defined as an anterior horn cell, its axon, and the muscle fibres innervated by the motor neuron. A surface electromyogram (EMG) is a superposition of many different MU action potentials (MUAPs) generated by active MUs. The objectives of this study were to introduce a new adaptive spatio-temporal filter, here called maximum kurtosis filter (MKF), and to compare it with existing filters, on its performance to detect a single MUAP train from multichannel surface EMG signals. The MKF adaptively chooses the filter coefficients by maximising the kurtosis of the output. The proposed method was compared with five commonly used spatial filters, the weighted low-pass differential filter (WLPD) and the marginal distribution of a continuous wavelet transform. The performance was evaluated using simulated EMG signals. In addition, results from a multichannel surface EMG measurement fro from a subject who had been previously exposed to radiation due to cancer were used to demonstrate an application of the method. With five time lags of the MKF, the sensitivity was 98.7% and the highest sensitivity of the traditional filters was 86.8%, which was obtained with the WLPD. The positive predictivities of these filters were 87.4 and 80.4%, respectively. Results from simulations showed that the proposed spatio-temporal filtration technique significantly improved performance as compared with existing filters, and the sensitivity and the positive predictivity increased with an increase in number of time lags in the filter.

Action Potentials↗
PubMed1991

Prothymocyte seeding in the thymus.

A major gap in our understanding of T lymphocyte development is the process of stem cell differentiation into T lymphocyte precursors. An important question is whether bone marrow-derived stem cells become committed to T lymphoid lineage within the bone marrow, or whether this occurs once cells have entered the microenvironment of the thymus. Attempts to identify a haemapoietic precursor of thymocytes in mice, a "prothymocyte", have involved cell transfer experiments involving isolated and selected populations of bone marrow stem cells, as well as transformed or continuous cell lines representing early stage in mouse T cell development. Current information on the properties of stem cells which can seed the thymus is reviewed in this paper, and the possibility that progenitor T cells may be identified by their expression of receptor(s) which localise them into the thymus is considered.

Animals↗
PubMed1990

Psychology of time awareness.

Mind transforms the continuance of physical space-time into moments (the absolute Now) and blends these moments into an apparent continuity through an overlapping of unfolding capsules. The flow of psychological time is an illusion based on the rapid replacement of these capsules. Each mind computes the measure of time passing and duration from the decay of the surface present in relation to a core of past events. As each new surface is generated, that surface, the rim of the immediate past, recedes in the wake of rising contents. This recession, an uncovering of phases latent in the original traversal, exposes layers in the past forming the content of the immediate past moment. The surge of the microgeny to a surface that dissolves the instant it appears, the priority of the Self in the unfolding sequence, the feeling of agency, create a Self in a state of becoming, a Self that travels in time like the crest of a wave, always in pursuit of a future just beyond the grasp of the present.

Arousal↗
PubMed1996

Low dimensional attractors in discharges of sensory neurons of the rat spinal dorsal horn are maintained by supraspinal descending systems.

Background activity was recorded from sensory neurons in laminae I-V of the lumbar spinal dorsal horn of the rat prior to and during cold block spinalization at the cervical cord. To graphically and quantitatively describe the complexity of the discharge patterns, phase space portraits were plotted and the correlation dimension D2 was calculated by using the Grassberger-Procaccia algorithm adopted for point processes, i.e. for series of interspike intervals. The algorithm is validated both for the Baker transformation, which is a simple point process, and for the Lorenz model, whereby a transformation from continuous to point process variables is achieved. A method of surrogate data is provided in order to show the difference between original neuronal patterns and their surrogate stochastic data. Therefore, this method shows that neuronal discharge patterns cannot be fully described in terms of interspike interval histograms. However, in the intact cord most (73%) of the neurons displayed background activity with low (0.28-4.3) D2 values. During spinalization, D2 values significantly increased in 68% of the neurons showing previously low D2 values, irrespective of classification and laminar location of neurons, thus proving that tonic descending systems may maintain a high order in the discharge of sensory dorsal horn neurons.

Animals↗
PubMed1991

Transmembrane molecular assemblies in cell-extracellular matrix interactions.

Several new interactions have been identified and proteins characterized in focal adhesions. Together they suggest alternative or parallel linkages between actin filaments and members of the integrin family of extracellular receptors. Transformed cells continue to serve as models for studying the assembly and disassembly of these adhesions.

Actins↗
PubMed2024

Accessing and exploring the unusual chemistry by radical SAM-RiPP enzymes.

Radical SAM enzymes involved in the biosynthesis of ribosomally synthesized and post-translationally modified peptides catalyze unusual transformations that lead to unique peptide scaffolds and building blocks. Several natural products from these pathways show encouraging antimicrobial activities and represent next-generation therapeutics for infectious diseases. These systems are uniquely configured to benefit from genome-mining approaches because minimal substrate and cognate modifying enzyme expression can reveal unique, chemically complex transformations that outperform late-stage chemical reactions. This report highlights the main strategies used to reveal these enzymatic transformations, which have relied mainly on genome mining using enzyme-first approaches. We describe the general biosynthetic components for rSAM enzymes and highlight emerging approaches that may broaden the discovery and study of rSAM-RiPP enzymes. The large number of uncharacterized rSAM proteins, coupled with their unpredictable transformations, will continue to be an essential and exciting resource for enzyme discovery.

S-Adenosylmethionine↗
PubMed2006

Nonlinear analysis of wheezes using wavelet bicoherence.

Wheezes, as being abnormal breath sounds, are observed in patients with obstructive pulmonary diseases, such as asthma. The aim of this study was to capture and analyze the nonlinear characteristics of asthmatic wheezes, reflected in the quadrature phase coupling of their harmonics, as they evolve over time within the breathing cycle. To achieve this, the continuous wavelet transform (CWT) was combined with third-order statistics/spectra. Wheezes from patients with diagnosed asthma were drawn from a lung sound database and analyzed in the time-bi-frequency domain. The analysis results justified the efficient performance of this combinatory approach to reveal and quantify the evolution of the nonlinearities of wheezes with time.

Algorithms↗