Performance analysis of a dual-buffer architecture for digital flow cytometry.

BACKGROUND: Most current commercial flow cytometers employ analog circuitry to provide feature values describing the pulse waveforms produced from suspended cells and particles. This restricts the type of features that can be extracted (typically pulse height, width, and integral) and consequently places a limit on classification performance. In previous work, we described a first-generation digital data acquisition and processing system that was used to demonstrate the classification advantages provided by the extraction of additional waveform features. An improved version of the system is discussed in this paper, focusing on dual-buffering to ensure increased pulse capture. A mathematical model of the system is also presented for performance analysis. METHODS: The second-generation system incorporates fast digitization of analog pulse waveforms, instantaneous pulse detection hardware, and a novel dual-buffering scheme. A mathematical model of the system was developed to theoretically compute the capture-rate performance. RESULTS: The capture rate of the system was theoretically analyzed and empirically measured. Under typical conditions, a capture rate of 8,000 pulses/s was experimentally achieved. CONCLUSIONS: Based on these results, the dual-buffer architecture shows great potential for use in flow cytometry.     

Model of brain rhythmic activity

1. A model of a neuronal network has been set up in a digital computer based on histological and biophysical data experimentally obtained from the thalamus; the model includes two populations of neurons interconnected by means of negative feedback; in the model allowance is also made for other sort of interactions.
2. To test the hypothesis that the alpha-rhythm (8–13 Hz rhythmic activity characteristic of the EEG) is a filtered noise signal the simulated neuronal network was stimulated by random trains of pulses with a Poisson distribution. The density of pulses fired by the simulated neurons was computed as well as the oscillations of the mean membrane potential of the population of simulated neurons. The latter was found to be equivalent to the experimentally obtained alpha rhythms.
3. In order to test the hypothesis that several noise sources are responsible for thalamo-cortical coherences three simulated neuronal networks were coupled together using several noise sources as secondary inputs. It was shown that although all the networks produced simulated alpha signals with identical spectra they could have significantly different values of coherence depending on the relation between correlated and uncorrelated input signals.
4. The model was analysed by means of linear systems analysis after introducing the necessary simplifications and approximations. In this way it was possible to evaluate the influence of different physiological or histological parameters upon the statistical properties of the resulting rhythmic activity in an analytical form.
5. By changing the model parameters it was shown that a family of spectral curves could be obtained which simulated the development of the EEG as function of age from a predominantly low frequency to a clearly rhythmic type of signal. This was shown to depend mainly on the feedback coupling parameters.

     

Mechanisms of measuring the velocity and acceleration of an underwater target by the sonar of the dolphinTursiops truncatus

The performed study of peculiarities of echo-detection of moving underwater targets by the Black Sea bottlenosed dolphins,Tursiops truncatus, suggests that the biosonar can purposefully change the structure of its probe signal, depending on the problem to be solved. It was shown experimentally for the first time that the animal emits the two-pulse probe signal to measure the constant velocity, while the three-pulse one, to measure acceleration. This provides an essential advantage over the single pulse, as it becomes possible to measure simultaneously parameters of the movement and distance.     

Ontogeny of the circadian system controlling release of sperm from the insect testis.

In the gypsy moth, the release of sperm bundles from the testis into the vas deferens is rhythmic and is controlled by a circadian pacemaker located in the reproductive system. However, in males kept since pupation in constant darkness (DD) and temperature, the release of sperm was arrhythmic. The release of sperm became rhythmic when males were transferred from a light-dark cycle (LD 16:8) to DD 6-7 days after pupation. To further investigate the development of the circadian system during the pupal stage, we exposed DD pupae to a single 8-hr pulse of light or 8-hr pulse of a 4 degrees C temperature increase on different days after pupation. The pattern of sperm release was determined 5-6 days after the pulse. Males that were exposed to light or temperature pulses 5 days after pupation subsequently showed nonrhythmic sperm release. However, about half of the pupae that received the pulse on day 6 and most of the pupae that received it on day 7 subsequently showed synchronized sperm release. These results suggested that the clock underlying rhythmic release of sperm becomes operational at approximately 6 days after pupation--that is, 2 days prior to initiation of rhythmic sperm release from the testis.     

Simulating Discrete and Rhythmic Multi-joint Human Arm Movements by Optimization of Nonlinear Performance Indices

An optimization approach applied to mechanical linkage models is used to simulate human arm movements. Predicted arm trajectories are the result of minimizing a nonlinear performance index that depends on kinematic or dynamic variables of the movement. A robust optimization algorithm is presented that computes trajectories which satisfy the necessary conditions with high accuracy. It is especially adapted to the analysis of discrete and rhythmic movements. The optimization problem is solved by parameterizing each generalized coordinate (e.g., joint angular displacement) in terms of Jacobi polynomials and Fourier series, depending on whether discrete or rhythmic movements are considered, combined with a multiple shooting algorithm. The parameterization of coordinates has two advantages. First, it provides an initial guess for the multiple shooting algorithm which solves the optimization problem with high accuracy. Second, it leads to a low dimensional representation of discrete and rhythmic movements in terms of expansion coefficients. The selection of a suitable feature space is an important prerequisite for comparison, recognition and classification of movements. In addition, the separate computational analysis of discrete and rhythmic movements is motivated by their distinct neurophysiological realizations in the cortex. By investigating different performance indices subject to different boundary conditions, the approach can be used to examine possible strategies that humans adopt in selecting specific arm motions for the performance of different tasks in a plane and in three-dimensional space.     

Parameters describing the pulse wave

Pulse wave analysis permits non-invasive assessment of arterial elasticity indices. The contour varies in different parts of the circulation. It depends on physiological or pathophysiological conditions of the organism. The pathological events like arteriosclerosis or diabetes have a primary effect to the artery elasticity. Hypertension or some heart diseases also influence the pulse wave velocity and resulted in earlier wave reflections. There are several methods of pulse wave measurements based on different principles and depending on the type of measured pulse wave. The evaluation parameters can be assessed from the time domain, derivations, velocity or frequency domain. The main aim of this review article is to offer a recent overview of pulse wave measurement parameters and main results obtained. The principles of pulse wave measurement and current experience in clinical practice are shortly discussed too.     

Acoustic Characteristics of Stridor in Multiple System Atrophy

Nocturnal stridor is a breathing disorder prevalent in patients with multiple system atrophy (MSA). An improved understanding of this breathing disorder is essential since nocturnal stridor carries a poor prognosis (an increased risk of sudden death). In this study, we aimed to classify types of stridor by sound analysis and to reveal their clinical significance. Patients who met the criteria for probable MSA and had undergone polysomnography (PSG) were recruited. Patients were then assessed clinically with sleep questionnaires, including the Pittsburgh Sleep Quality Index, and the Hoehn and Yahr scale. Nocturnal stridor and snoring were analyzed with the Multi-Dimensional Voice Program. Nocturnal stridor was recorded in 22 patients and snoring in 18 patients using the PSG. Waveforms of stridors were classified into rhythmic or semirhythmic after analysis of the oscillogram. Formants and harmonics were observed in both types of stridor, but not in snoring. Of the 22 patients diagnosed with stridor during the present study, fifteen have subsequently died, with the time to death after the PSG study being 1.9 ± 1.4 years (range 0.8 to 5.0 years). The rhythmic waveform group presented higher scores on the Hoehn and Yahr scale and the survival outcome of this group was lower compared to the semirhythmic waveform group (p = 0.030, p = 0.014). In the Kaplan Meier’s survival curve, the outcome of patients with rhythmic waveform was significantly less favorable than the outcome of patients with semirhythmic waveform (log-rank test, p < 0.001). Stridor in MSA can be classified into rhythmic and semirhythmic types and the rhythmic component signifies a poorer outcome.     

Multiple cases of striking genetic similarity between alternate electric fish signal morphs in sympatry

Striking trait polymorphisms are worthy of study in natural populations because they can often shed light on processes of phenotypic divergence and specialization, adaptive evolution, and (in some cases) the early stages of speciation. We examined patterns of genetic variation within and between populations of mormyrid fishes that are morphologically cryptic in sympatry but produce alternate types of electric organ discharge (EOD). Other species in a large group containing a clade of these morphologically cryptic EOD types produce stereotyped, species-typical EOD waveforms thought to function in mate recognition. First, for six populations from Gabon's Brienomyrus species flock, we confirm that forms of electric fish that exhibit distinctive morphologies and unique EOD waveforms (i.e., good reference species) are reproductively isolated from coexisting congeners. These sympatric species deviate from genetic panmixia across five microsatellite loci. Given this result, we examined three focal pairs of syntopic and morphologically cryptic EOD waveform types that are notable exceptions to the pattern of robust genetic partitioning among unique waveform classes within assemblages. These exceptional pairs constitute a monophyletic group within the Brienomyrus flock known as the magnostipes complex. One member of each pair (type I) produces a head-negative EOD, while the other member (either type II or type III, depending on location) produces a longer duration EOD differing in waveform from type I. We show that signal development in these pairs begins with juveniles of all magnostipes-complex morphs emitting head-positive EODs resembling those of type II adults. Divergence of EOD waveforms occurs with growth such that there are two discrete and fixed signal types in morphologically indistinguishable adults at each of several localities. Strong microsatellite partitioning between allopatric samples of any of these morphologically cryptic signal types suggests that geographically isolated populations are genetically decoupled from one another. By contrast, sympatric morphs appear genetically identical across microsatellite loci in Mouvanga Creek and the Okano River and only very weakly diverged, if at all, in the Ivindo River. Our results for the magnostipes complex fail to detect species boundaries between the focal morphs and are, instead, fully consistent with the existence of relatively stable signal dimorphisms at each of several different localities. No mechanism for the maintenance of this electrical polymorphism is suggested by the known natural history of the magnostipes complex. Despite a lack of evidence for genetic differentiation, the possibility of incipient sympatric speciation between morphs (especially type I and type II within the Ivindo River) merits further testing due to behavioral and neurobiological lines of evidence implying a general role for stereotyped EOD waveforms in species recognition. We discuss alternative hypotheses concerning the origins, stability, and evolutionary significance of these intriguing electrical morphs in light of geographical patterns of population structure and signal variation.     

Oscillatory structure of the parameters of the pulse signal of the radial artery

The typology analysis of the spectral density curves of time series obtained from various parameters of unit pulse oscillations was performed. The formal classification (typology) of spectral curves was performed using correlations of peak values of the spectral density of VLF, LF, and HF slow waves. To include a spectral density curve into a particular type, the criteria were introduced that characterize the intensity of these oscillatory components. The experimental data was collected during examinations of children and adolescents that were performed to detect the early stage of arterial hypertension (AH). The distribution of the subjects among the types of spectral density based on various parameters of pulse oscillation was evaluated. The results of the comparative analysis of spectral type distribution for various parameters are shown. This analysis has revealed the most informative spectral parameters for differential diagnosis of conditions of two types: type 1, essential hypertension, and type 2, various functional disorders with a normal blood pressure. It has been found that the parameters of the oscillatory components of dicrotic pulse wave time characteristics are the most informative for detecting hypertension in children.     

System for flow sorting chromosomes on the basis of pulse shape

Sorting on the basis of the complex features resolved by chromosome slit-scan analysis requires rapid and flexible pulse shape acquisition and processing for determining sort decisions before droplet breakoff. Fluorescence scans of chromosome morphology contain centromeric index and banding information suitable for chromosome classification, but these scans are often characterized by variability in length and height and require sophisticated data processing procedures for identification. Setting sort criteria on such complex morphological data requires digitization and subsequent computation by an algorithm tolerant of variations in overall pulse shape. We demonstrate here the capability to sort individual chromosomes based on their morphological features measured by slit-scan flow cytometry. To do this we have constructed a sort controller capable of acquiring an 128 byte chromosome waveform and executing a series of numerical computations resulting in an area-based centromeric index sort decision in less than 2 ms. The system is configured in a NOVIX microprocessor, programmed in FORTH, and interfaced to a slit-scan flow cytometer data acquisition system. An advantage of this configuration is direct control over the machine state during program execution for minimal processing time. Examples of flow sorted chromosomes are shown with their corresponding fluorescence pulse shapes.     

Feature-based reappraisal of the Bacillus subtilis exoproteome

Proteomics-based verification of computer-assisted predictions on bacterial protein export have indicated that problems occur with the distinction between (Sec-type) signal peptides that govern protein secretion, and lipoprotein signal peptides or amino-terminal membrane anchors that cause protein retention in the membrane. Therefore, the main aim of this study was to investigate whether feature-based predictions by the SecretomeP (SecP) algorithm will aid the proteomics-based analysis of protein export in Bacillus subtilis. The SecP algorithm is trained to recognize features such as secondary structure and disordered regions, which are generally present in secreted proteins. The results showed that membrane-retained proteins receive, in general, high SecP scores, similar to the scores of secretory proteins. Importantly, the SecP algorithm aided in the re-evaluation of a class of previously identified proteins that remain attached to the membrane despite the presence of an apparent Sec-type signal peptide. These so-called 'Sec-attached' proteins receive on average a lower SecP score, and several of these proteins could be unmasked as transmembrane proteins by combined SecP and signal peptide analyses. Finally, the present study suggests that feature-based outlier analysis may provide leads towards the discovery of novel special-purpose pathways for bacterial protein export.     

A technique for characterizing the development of rhythms in bird song

The developmental trajectory of nervous system dynamics shows hierarchical structure on time scales spanning ten orders of magnitude from milliseconds to years. Analyzing and characterizing this structure poses significant signal processing challenges. In the context of birdsong development, we have previously proposed that an effective way to do this is to use the dynamic spectrum or spectrogram, a classical signal processing tool, computed at multiple time scales in a nested fashion. Temporal structure on the millisecond timescale is normally captured using a short time Fourier analysis, and structure on the second timescale using song spectrograms. Here we use the dynamic spectrum on time series of song features to study the development of rhythm in juvenile zebra finch. The method is able to detect rhythmic structure in juvenile song in contrast to previous characterizations of such song as unstructured. We show that the method can be used to examine song development, the accuracy with which rhythm is imitated, and the variability of rhythms across different renditions of a song. We hope that this technique will provide a standard, automated method for measuring and characterizing song rhythm.     

Automatic classification of electrocardiogram signals based on transfer learning and continuous wavelet transform

Classification and subsequent diagnosis of cardiac arrhythmias is an important research topic in clinical practice. Confirmation of the type of arrhythmia at an early stage is critical for reducing the risk and occurrence of cardiovascular events. Nevertheless, diagnoses must be confirmed by a combination of specialist experience and electrocardiogram (ECG) examination, which can lead to delays in diagnosis. To overcome such obstacles, this study proposes an automatic ECG classification algorithm based on transfer learning and continuous wavelet transform (CWT). The transfer learning method is able to transfer the domain knowledge and features of images to a EGG, which is a one-dimensional signal when a convolutional neural network (CNN) is used for classification. Meanwhile, CWT is used to convert a one-dimensional ECG signal into a two-dimensional signal map consisting of time-frequency components. Considering that morphological features can be helpful in arrhythmia classification, eight features related to the R peak of an ECG signal are proposed. These auxiliary features are integrated with the features extracted by the CNN and then fed into the fully linked arrhythmia classification layer. The CNN developed in this study can also be used for bird activity detection. The classification experiments were performed after converting the two types of audio files containing songbird sounds and those without songbird sounds from the NIPS4Bplus bird song dataset into the Mel spectrum. Compared to the most recent methods in the same field, the classification results improved accuracy and recognition by 11.67% and 11.57%, respectively.     

The role of parameter identification in finite element contact analyses with reference to orthopaedic biomechanics applications.

A finite element model accounting for large sliding frictional contact requires, depending on the type of contact algorithm in use, the definition of many numerical parameters such as contact stiffness, convergence norm and tolerance, compenetration monitoring, over-relaxing factors, etc. All these parameters do not have a physical meaning and thus they cannot be measured experimentally. This makes their identification quite complex. The aim of this study was to investigate the role of parameter identification on the accuracy of results produced by finite element models accounting for bone-implant frictional contact, when the Penalty method is used. The sensitivity analysis of several numerical parameters that may govern the state of results was carried out. Two parameters, contact stiffness and convergence tolerance, were found to play a crucial role in establishing the accuracy of the finite element results. Based on the achieved results it was stated that any numerical-only study involving contact non-linearity and omitting careful qualification of the model limits should be rejected from any peer-reviewed journal.     

A synaptic modification algorithm in consideration of the generation of rhythmic oscillation in a ring neural network

In consideration of the generation of bursts of nerve impulses (that is, rhythmic oscillation in impulse density) in the ring neural network, a synaptic modification algorithm is newly proposed. Rhythmic oscillation generally occurs in the regular ring network with feedback inhibition and in fact such signals can be observed in the real nervous system. Since, however, various additional connections can cause a disturbance which easily extinguishes the rhythmic oscillation in the network, some function for maintaining the rhythmic oscillation is to be expected to exist in the synapses if such signals play an important part in the nervous system. Our preliminary investigation into the rhythmic oscillation in the regular ring network has led to the selection of the parameters, that is, the average membrane potential (AMP) and the average impulse density (AID) in the synaptic modification algorithm, where the decrease of synaptic strength is supposed to be essential. This synaptic modification algorithm using AMP and AID enables both the rhythmic oscillation and the non-oscillatory state to be dealt with in the algorithm without distinction. Simulation demonstrates cases in which the algorithm catches and holds the rhythmic oscillation in the disturbed ring network where the rhythmic oscillation was previously extinguished.     

Toward a noninvasive subject-specific estimation of abdominal aortic pressure

A method for estimation of central arterial pressure based on linear one-dimensional wave propagation theory is presented in this paper. The equations are applied to a distributed model of the arterial tree, truncated by three-element windkessels. To reflect individual differences in the properties of the arterial trees, we pose a minimization problem from which individual parameters are identified. The idea is to take a measured waveform in a peripheral artery and use it as input to the model. The model subsequently predicts the corresponding waveform in another peripheral artery in which a measurement has also been made, and the arterial tree model is then calibrated in such a way that the computed waveform matches its measured counterpart. For the purpose of validation, invasively recorded abdominal aortic, brachial, and femoral pressures in nine healthy subjects are used. The results show that the proposed method estimates the abdominal aortic pressure wave with good accuracy. The root mean square error (RMSE) of the estimated waveforms was 1.61 +/- 0.73 mmHg, whereas the errors in systolic and pulse pressure were 2.32 +/- 1.74 and 3.73 +/- 2.04 mmHg, respectively. These results are compared with another recently proposed method based on a signal processing technique, and it is shown that our method yields a significantly (P < 0.01) lower RMSE. With more extensive validation, the method may eventually be used in clinical practice to provide detailed, almost individual, specific information as a valuable basis for decision making.     

Detection of Abnormal Respiratory Events with Single Channel ECG and Hybrid Machine Learning Model in Patients with Obstructive Sleep Apnea

Respiratory scoring is an important step in the diagnosis of Obstructive Sleep Apnea (OSA). Airflow, abdolmel-thorax and pulse oximetry signals are obtained with the help of Polysomnography (PSG) device for the respiration scoring stage. These signals are visually scored by a specialist physician. The PSG has several disadvantages: one of them is that a technician is required to use the device. In addition, the records must be taken in the hospital environment. The aim of this study is to develop a new machine learning based hybrid sleep/awake detection method with single channel ECG alternative to respiratory scoring. For this purpose, electrocardiography (ECG) signal of 10 patients with OSA was used. The Heart Rate Variable signal was derived from the ECG signal. Then, QRS components in different frequency bands were obtained from ECG signal by digital filtering. In this way, a total of nine more signals were obtained. Each of the nine signals consists of 25 features, which amounts to a total of 225 features. Fisher feature selection algorithm and Principal Component Analysis (PCA) were used to reduce the number of features. Ultimately the features extracted from the first received signals were classified with Decision Tree, Support Vector Machines, k-Nearest Neighborhood Algorithm and Ensemble classifiers. In addition, the proposed model was checked with the Leave One Out method. At the end of the study, for the detection of apnea, 82.11% accuracy with only 3 features and 85.12% accuracy with 13 features were obtained. The sensitivity and specificity values for the 3 properties are 0.82 and 0.82, respectively. For the 13 properties, 0.85 and 0.86, respectively. These results show that the proposed model can be used for the detection of Respiratory Scoring in the OSA diagnostic process.     

The circular topology of rhythm in asynchronous random Boolean networks

The analysis of previously evolved rhythmic asynchronous random Boolean networks [Biosystems 59 (2001) 185] reveals common topological characteristics indicating that rhythm originates from a circular functional structure. The rhythm generating core of the network has the form of a closed ring which operates as a synchronisation substrate by supporting a travelling wave of state change; the size of the ring corresponds well with the period of oscillation. The remaining nodes in the network are either stationary or follow the activity of the ring without feeding back into it so as to form a coherent whole. Rings are typically formed early on in the evolutionary search process. Alternatively, long chains of nodes are favoured before they close upon themselves to stabilize. Analysis of asynchronous networks with de-correlated (non-rhythmic, non-stationary) attractors reveals no such common topological characteristics. These results have been obtained using statistical analysis and a specifically developed bottom-up pruning algorithm. This algorithm works from local interactions to global configuration by eliminating redundant links. The suitability of the algorithm has been confirmed by both numerical and single lesion analysis. The ring topology solution for the generation of rhythm implies that it will be harder to evolve rhythmic networks for big sizes and small periods and for bigger number of connections per node. These trends are confirmed empirically. Finally, the identified mechanisms are utilised to handcraft rhythmic networks of different periods showing that a low number of connections suffices for a large variety of rhythms. Random asynchronous update forces the evolved solutions to be highly robust maintaining their performance in the presence of intrinsic noise. The biological implications of such robust designs for molecular clocks are discussed.     

The characteristics of the minute fluctuations in haloperidol-induced catalepsy and the contribution of different sections of the striatum to their formation in rats]

After constant recording of haloperidol catalepsy in rats a rhythmic structure with waves of minute range was observed. On the basis of individual pharmacological sensitivity all rats may be divided in animals with strong rhythmic fluctuations but rapid tolerance (hyperkinetic type) and with weak rhythmicity but delayed adaptation to haloperidol (hypokinetic type). Oscillatory pattern of catalepsy increased after bilateral lesions of dorsal striatum and decreased after ventral striatectomy. As suggested, ventral striatum has a rhythmogenic function which conditions a more easy neuroleptic tolerance.