Behavioural disinhibition in frontotemporal dementia investigated within an ecological framework

Disinhibition is a core symptom in behavioural variant frontotemporal dementia (bvFTD) particularly affecting the daily lives of both patients and caregivers. Yet, characterisation of inhibition disorders is still unclear and management options of these disorders are limited. Questionnaires currently used to investigate behavioural disinhibition do not differentiate between several subtypes of disinhibition, encompass observation biases and lack of ecological validity. In the present work, we explored disinhibition in an original semi-ecological situation, by distinguishing three categories of disinhibition: compulsivity, impulsivity and social disinhibition. First, we measured prevalence and frequency of these disorders in 23 bvFTD patients and 24 healthy controls (HC) in order to identify the phenotypical heterogeneity of disinhibition. Then, we examined the relationships between these metrics, the neuropsychological scores and the behavioural states to propose a more comprehensive view of these neuropsychiatric manifestations. Finally, we studied the context of occurrence of these disorders by investigating environmental factors potentially promoting or reducing them. As expected, we found that patients were more compulsive, impulsive and socially disinhibited than HC. We found that 48% of patients presented compulsivity (e.g., repetitive actions), 48% impulsivity (e.g., oral production) and 100% of the patients group showed social disinhibition (e.g., disregards for rules or investigator). Compulsivity was negatively related with emotions recognition. BvFTD patients were less active if not encouraged in an activity, and their social disinhibition decreased as activity increased. Finally, impulsivity and social disinhibition decreased when patients were asked to focus on a task. Summarising, this study underlines the importance to differentiate subtypes of disinhibition as well as the setting in which they are exhibited, and points to stimulating area for non-pharmacological management.

Automated electrohysterographic detection of uterine contractions for monitoring of pregnancy: feasibility and prospects

Background

Preterm birth is a major public health problem in developed countries. In this context, we have conducted research into outpatient monitoring of uterine electrical activity in women at risk of preterm delivery. The objective of this preliminary study was to perform automated detection of uterine contractions (without human intervention or tocographic signal, TOCO) by processing the EHG recorded on the abdomen of pregnant women. The feasibility and accuracy of uterine contraction detection based on EHG processing were tested and compared to expert decision using external tocodynamometry (TOCO) .

Methods

The study protocol was approved by local Ethics Committees under numbers ID-RCB 2016-A00663-48 for France and VSN 02-0006-V2 for Iceland.

Two populations of women were included (threatened preterm birth and labour) in order to test our system of recognition of the various types of uterine contractions.

EHG signal acquisition was performed according to a standardized protocol to ensure optimal reproducibility of EHG recordings. A system of 18 Ag/AgCl surface electrodes was used by placing 16 recording electrodes between the woman’s pubis and umbilicus according to a 4 × 4 matrix. TOCO was recorded simultaneously with EHG recording.

EHG signals were analysed in real-time by calculation of the nonlinear correlation coefficient H². A curve representing the number of correlated pairs of signals according to the value of H² calculated between bipolar signals was then plotted. High values of H² indicated the presence of an event that may correspond to a contraction.

Two tests were performed after detection of an event (fusion and elimination of certain events) in order to increase the contraction detection rate.

Results

The EHG database contained 51 recordings from pregnant women, with a total of 501 contractions previously labelled by analysis of the corresponding tocographic recording. The percentage recognitions obtained by application of the method based on coefficient H² was 100% with 782% of false alarms. Addition of fusion and elimination tests to the previously obtained detections allowed the false alarm rate to be divided by 8.5, while maintaining an excellent detection rate (96%).

Conclusion

These preliminary results appear to be encouraging for monitoring of uterine contractions by algorithm-based automated detection to process the electrohysterographic signal (EHG). This compact recording system, based on the use of surface electrodes attached to the skin, appears to be particularly suitable for outpatient monitoring of uterine contractions, possibly at home, allowing telemonitoring of pregnancies. One of the advantages of EHG processing is that useful information concerning contraction efficiency can be extracted from this signal, which is not possible with the TOCO signal.

Classification of pregnancy and labor contractions using a graph theory based analysis

In this paper, we propose a new framework to characterize the electrohysterographic (EHG) signals recorded during pregnancy and labor. The approach is based on the analysis of the propagation of the uterine electrical activity. The processing pipeline includes i) the estimation of the statistical dependencies between the different recorded EHG signals, ii) the characterization of the obtained connectivity matrices using network measures and iii) the use of these measures in clinical application: the classification between pregnancy and labor. Due to its robustness to volume conductor, we used the imaginary part of coherence in order to produce the connectivity matrix which is then transformed into a graph. We evaluate the performance of several graph measures. We also compare the results with the parameter mostly used in the literature: the peak frequency combined with the propagation velocity (PV +PF). Our results show that the use of the network measures is a promising tool to classify labor and pregnancy contractions with a small superiority of the graph strength over PV+PF.

A node-wise analysis of the uterine muscle networks for pregnancy monitoring

The recent past years have seen a noticeable increase of interest in the correlation analysis of electrohysterographic (EHG) signals in the perspective of improving the pregnancy monitoring. Here we propose a new approach based on the functional connectivity between multichannel (4×4 matrix) EHG signals recorded from the women's abdomen. The proposed pipeline includes i) the computation of the statistical couplings between the multichannel EHG signals, ii) the characterization of the connectivity matrices, computed by using the imaginary part of the coherence, based on the graph-theory analysis and iii) the use of these measures for pregnancy monitoring. The method was evaluated on a dataset of EHGs, in order to track the correlation between EHGs collected by each electrode of the matrix (called `node-wise' analysis) and follow their evolution along weeks before labor. Results showed that the strength of each node significantly increases from pregnancy to labor. Electrodes located on the median vertical axis of the uterus seemed to be the more discriminant. We speculate that the network-based analysis can be a very promising tool to improve pregnancy monitoring.

Detecting labor using graph theory on connectivity matrices of uterine EMG

Premature labor is one of the most serious health problems in the developed world. One of the main reasons for this is that no good way exists to distinguish true labor from normal pregnancy contractions. The aim of this paper is to investigate if the application of graph theory techniques to multi-electrode uterine EMG signals can improve the discrimination between pregnancy contractions and labor. To test our methods we first applied them to synthetic graphs where we detected some differences in the parameters results and changes in the graph model from pregnancy-like graphs to labor-like graphs. Then, we applied the same methods to real signals. We obtained the best differentiation between pregnancy and labor through the same parameters. Major improvements in differentiating between pregnancy and labor were obtained using a low pass windowing preprocessing step. Results show that real graphs generally became more organized when moving from pregnancy, where the graph showed random characteristics, to labor where the graph became a more small-world like graph.

Nonlinear estimation of coupling and directionality between signals: application to uterine EMG propagation

Understanding the direction and quantity of information flowing in a complex system is a fundamental task in signal processing. Several measures have been proposed to detect the quantity of synchronization and the directionality between time series and in physiological data. In this paper we use two methods that are widely used in synchronization and directionality analysis: Nonlinear correlation coefficient (h(2)) and the general synchronization (H). The performances of both methods were tested on four dimensional coupled synthetic nonlinear Rössler models. They were then applied to a single real labor contraction uterine EMG burst with the aim of using them to detect synchronization and to plot the map of direction of information flow between the whole signal channels. The results on synthetic signal show a slight superiority of H over h(2). The results obtained on a single contraction are encouraging for the future use of these tools for resolving the open question of the directionality of uterine contractions and may provide a way of finding their source loci.

Genome-wide analysis of the AP2/ERF family in Eucalyptus grandis: an intriguing over-representation of stress-responsive DREB1/CBF genes

BACKGROUND

The AP2/ERF family includes a large number of developmentally and physiologically important transcription factors sharing an AP2 DNA-binding domain. Among them DREB1/CBF and DREB2 factors are known as master regulators respectively of cold and heat/osmotic stress responses.

EXPERIMENTAL APPROACHES

The manual annotation of AP2/ERF family from Eucalyptus grandis, Malus, Populus and Vitis genomes allowed a complete phylogenetic study for comparing the structure of this family in woody species and the model Arabidopsis thaliana. Expression profiles of the whole groups of EgrDREB1 and EgrDREB2 were investigated through RNAseq database survey and RT-qPCR analyses.

RESULTS

The structure and the size of the AP2/ERF family show a global conservation for the plant species under comparison. In addition to an expansion of the ERF subfamily, the tree genomes mainly differ with respect to the group representation within the subfamilies. With regard to the E. grandis DREB subfamily, an obvious feature is the presence of 17 DREB1/CBF genes, the maximum reported to date for dicotyledons. In contrast, only six DREB2 have been identified, which is similar to the other plants species under study, except for Malus. All the DREB1/CBF and DREB2 genes from E. grandis are expressed in at least one condition and all are heat-responsive. Regulation by cold and drought depends on the genes but is not specific of one group; DREB1/CBF group is more cold-inducible than DREB2 which is mainly drought responsive.

CONCLUSION

These features suggest that the dramatic expansion of the DREB1/CBF group might be related to the adaptation of this evergreen tree to climate changes when it expanded in Australia.

Quantitative performance analysis of four methods of evaluating signal nonlinearity: application to uterine EMG signals

Recently, much attention has been paid to the use of nonlinear analysis techniques for the characterization of biological signals. Several measures have been proposed to detect nonlinear characteristics in time series. The sensitivity of several nonlinear methods to the actual nonlinearity level and their sensitivity to noise have never been evaluated. In this paper we perform this analysis for four methods that are widely used in nonlinearity detection: Time reversibility, Sample Entropy, Lyapunov Exponents and Delay Vector Variance. The evolution of methods with complexity degree (CD) and with different Signal to Noise Ratio was computed for the four methods on nonlinear synthetic signals. The methods were then applied to real uterine EMG signals with the aim of using them to distinguish between pregnancy and labor signals. The results show a clear superiority of the Time reversibility method, in classification of pregnancy and labor signals.

Detecting missing signals in multichannel recordings by using higher order statistics

In real world applications, a multichannel acquisition system is susceptible of having one or many of its sensors displaced or detached, leading therefore to the loss or corruption of the recorded signals. In this paper, we present a technique for detecting missing or corrupted signals in multichannel recordings. Our approach is based on Higher Order Statistics (HOS) analysis. Our approach is tested on real uterine electromyogram (EMG) signals recorded by 4×4 electrode grid. Results have shown that HOS descriptors can discriminate between the two classes of signals (missing vs. non-missing). These results are supported by statistical analysis using the t-test which indicated good statistical significance of 95% confidence level.

Cross-correlation analysis of multichannel uterine EMG signals

The prevention of preterm labor remains one of the primary goals of obstetric research. One way to achieve this goal effectively is to understand the mechanisms regulating the uterine contractility. Herein, we evaluate the correlation between uterine electrical activities recorded from spatially-distributed regions by calculating the nonlinear regression coefficient. Results have shown that, during pregnancy, the degree of interdependence between signals is very high whereas, at labor, the correlation between the signals decreases remarkably. We conclude that pregnancy is characterized by the presence of few local potential sources dominating the other sources while at the onset of labor, the number of these sources increases remarkably which affects therefore the correlation between the signals.

Classification performance of the frequency-related parameters derived from uterine EMG signals

Frequency-related parameters derived from the uterine electromyogram (EMG) signals are widely used in many pregnancy monitoring and preterm delivery prediction studies. Although they are classical parameters, they are well suited for quantifying uterine EMG signals and have many advantages over amplitude-related parameters. The present work aims to compare various frequency-related parameters according to their classification performances (pregnancy vs. labor) using the receiver operating characteristic (ROC) curve analysis. The comparison between the parameters indicates that median frequency is the best frequency-related parameter that can be used for distinguishing between pregnancy and labor contractions. We conclude that median frequency can be the representative frequency-related parameter for classification problems of uterine EMG.

Classification of multichannel uterine EMG signals

Classification of multichannel uterine electromyogram (EMG) signals is addressed. Signals were recorded by a matrix of 16 electrodes. First, signals corresponding to each channel were individually classified using an artificial neural network (ANN) based on radial basis functions (RBF). The results have shown that the classification performance varies from one channel to another. Then, a decision fusion method based on these classification performances was tested. After fusion, the network yielded better classification accuracy than any individual channel could provide. The high percentage of correctly classified labor/non-labor events proves the efficiency of multichannel recordings in detecting labor. These findings can be very useful for the aim of classifying antepartum versus labor patients.

Nonlinearity of EHG signals used to distinguish active labor from normal pregnancy contractions

Labor prediction using the electrohysterogram has immediate clinical applications and has been the aim of several studies in recent years. Studies using various linear methods such as classic spectral analysis do not give clinically useful results. In this paper we present the use of two methods that investigate nonlinearity to predict normal labor. We show the comparison between a linear method that is known from the literature (mean power frequency) and two nonlinear methods (approximate entropy and time reversibility) using ROC analysis. The comparison indicates that the best method for pretreatment to classify pregnancy and labor signals is time reversibility. The results indicate that time reversibility is a very promising tool for distinguishing between labor and physiological contractions during pregnancy. This could be the first step in developing a clinical application method to predict preterm labor.

Evolution of phase synchronization of the two frequency components of the electrohysterogram (EHG): application to the detection of human labor

The analysis of the electrical activity of the uterus recorded externally, the electrohysterogram (EHG), may find an application in the prediction of labor. In the literature parameters that are supposed to be related to the excitability of the uterine cells have almost exclusively been used for this purpose. In the present paper we evaluate the possible use of synchronization parameters for EHG measured in several places on the uterus for this prediction. The EHG is mainly composed of two frequency components called FWL and FWH. These components may be related to the synchronization and the excitability phenomenon respectively. In order to study independently these frequency components, we extracted the corresponding ridges of the wavelet transform of the EHG using the GVF-snake method. For each frequency component we computed parameters that are related to the frequency content of the signals and parameters that consider the synchronization relationship between signals. The synchronization parameters used were the mean phase coherence and the phase entropy. The values of the different parameters were compared during pregnancy and labor by statistical analysis. The detection quality of each parameter was evaluated using ROC curves. Our results suggest that synchronization parameters could be used for the detection of labor in addition to the classical previously published parameters. Another important result of our study is that both FWH and FWL seem related to excitability but only FWL seems to be related to the synchronization of the uterus at term.

Spatial analysis of uterine EMG signals: evidence of increased in synchronization with term

Evaluation of synchronization between signals can give new insights into the functioning of the related systems. Methods that can detect synchronization or coupling between signals can be divided two types: linear and non linear methods. In this paper we use the non linear correlation coefficient (h(2)) to show the difference in synchronization between efficient uterine contractions during labor and normal physiological contractions during pregnancy, in uterine activity bursts recorded at different places on the pregnant abdomen. Our interest in the non linear correlation coefficient is based on the fact that the propagation mechanism of uterine EMG signal may be strongly non linear. The results obtained from estimating the synchronization between 16 uterine EMG channels indicate that synchronization between contractions as measured by h(2) is stronger in labor than in pregnancy. Limited data indicates that the h(2) value increases markedly with term when expressed in duration before spontaneous labor.

Complexity analysis of the uterine electromyography

In respect to the main goal of our ongoing work for predicting preterm birth, we analyze in this paper the complexity of the uterine electromyography (EMG) by using the sample entropy (SampEn) algorithm. By considering recent methodological developments, we measure the SampEn over multiple scales using the wavelet packet decomposition method. The results obtained from the analyzed data indicate that SampEn decreases along pregnancy. Furthermore, we demonstrate that the computed SampEn parameter may discriminate between the two classes (pregnancy/labor). The results are supported by statistical analysis using t-test indicating good statistical significance with a confidence level of 95%. A surrogate data test is also performed to investigate the nature of the underlying dynamics of our experimental data. The results are very promising for monitoring pregnancy and detecting labor to help identify preterm labor.

Improving the classification rate of labor vs. normal pregnancy contractions by using EHG multichannel recordings

Most of the studies on the synchronization between EHG signals, recorded during the same contractions at different locations, are limited to the use of only two channels. Multichannel techniques have however been widely applied to EEG signals but rarely to EHG. In this paper, we investigate the use of multichannel uterine EMG signals for classifying contractions. We compare the performance of phase synchronization in distinguishing between labor and normal pregnancy contractions by using either only two channels or a 4x4 matrix positioned on the woman's abdomen. We used two indexes to measure the phase synchronization: mean phase coherence and phase entropy. ROC curves indicate that the use of multichannel signals can significantly improve the classification rate of pregnancy and labor contractions.

Use of piecewise stationary segmentation as a pre-treatment for synchronization measures

The analysis of the synchronization between biological signals can be helpful for the characterization of biological functions. Biological signals are however often strongly non stationary. This is in contradiction to the assumption of commonly used synchronization measures which assume that the signal is stationary. We propose to use a piecewise stationary pre-segmentation (PSP) of the signals of interest, before the computation of synchronization measures. We show on synthetic as well as real biological signals (EEG and uterine EMG) that the proposed piecewise stationary pre-segmentation approach increases the accuracy of the measures by making a good tradeoff between the stationary assumption and length of the analyzed segments, when compared to the classical windowing method.

Preterm labor--modeling the uterine electrical activity from cellular level to surface recording

Uterine electrical activity is correlated to the appearance of uterine contractions. forceful contractions appear at the end of term. Therefore, understanding the genesis and the propagation of uterine electrical activity may provide an efficient tool to diagnose preterm labor. Moreover, the control of uterine excitability seems to have important consequences in the control of preterm labor. Modeling the electrical activity in uterine tissue is thus an important step in understanding physiological uterine contractile mechanisms and to permit uterine EMG simulation. Our model presented in this paper, incorporates ion channel models at the cell level, the reaction diffusion equations at the tissue level and the spatiotemporal integration at the uterine EMG reconstructed level. This model validates some key physiological observation hypotheses concerning uterine excitability and propagation.

Nonlinearity testing in the case of non Gaussian surrogates, applied to improving analysis of synchronicity in uterine contraction

Surrogates are commonly used to test a particular hypothesis on time series. The parameter commonly used in the literature to test these hypotheses is the z score. The z score assumes that the distribution of the statistics obtained on the surrogates is Gaussian. In this paper, we propose the use of a more general parameter than the z score that will also work in the case of non-Gaussian distribution of the statistics. We also derive a statistical test, based on the fitting of the distribution of the surrogate measure profile, in order to test the initial hypothesis. We validate the proposed approach on both synthetic signals and real uterine EMG signals by using the nonlinear correlation coefficient as initial statistic. We further show that this corrected nonlinear correlation coefficient can discriminate between pregnancy contractions and labor in a monkey, but the uncorrected nonlinear correlation coefficient cannot. This makes the corrected nonlinear correlation coefficient a promising candidate in a future application for preterm labor prediction in humans.

Complementary regulation of four Eucalyptus CBF genes under various cold conditions

CBF transcription factors play central roles in the control of freezing tolerance in plants. The isolation of two additional CBF genes, EguCBF1c and EguCBF1d, from E. gunnii, one of the cold-hardiest Eucalyptus species, is described. While the EguCBF1D protein sequence is very similar to the previously characterized EguCBF1A and EguCBF1B sequences, EguCBF1C is more distinctive, in particular in the AP2-DBD (AP2-DNA binding domain). The expression analysis of the four genes by RT-qPCR reveals that none of them is specific to one stress but they are all preferentially induced by cold, except for the EguCBF1c gene which is more responsive to salt. The calculation of the transcript copy number enables the quantification of constitutive CBF gene expression. This basal level, significant for the four genes, greatly influences the final EguCBF1 transcript level in the cold. A cold shock at 4 degrees C, as well as a progressive freezing which mimics a natural frost episode, trigger a fast and strong response of the EguCBF1 genes, while growth at acclimating temperatures results in a lower but more durable induction. The differential expression of the four EguCBF1 genes under these cold regimes suggests that there is a complementary regulation. The high accumulation of the CBF transcript, observed in response to the different types of cold conditions, might be a key for the winter survival of this evergreen broad-leaved tree.

Spectral characterization of human EHG frequency components based on the extraction and reconstruction of the ridges in the scalogram

Numerous studies have observed and analyzed the external electrical activity of the uterus, the so-called electrohysterogram (EHG), associated with contractions during pregnancy and labor. The EHG is mainly composed of two distinct frequency components, FWL (Fast Wave Low, low frequency component) and FWH (Fast Wave High, high frequency component). It has been suggested that FWH is mainly associated with uterine cell excitability and FWL with the propagation of this activity. This hypothesis is still unproven. We compared two procedures for ridge extraction/reconstruction of the EHG scalogram, with the objective of analyzing the propagation of the EHG on FWH and FWL separately. The performance of the methods under investigation was tested on both synthetic and real signals. The results indicate that the EHG can be characterized by two distinct continuous ridges, supposed to be FWH and FWL, with a low reconstruction error. We have also shown that the extracted ridges have different energy, temporal characteristics and bandwidths.

A two dimension model of the uterine electrical wave propagation

The uterus, usually quiescent during pregnancy, exhibits forceful contractions at term leading to delivery. These contractions are caused by the synchronized propagation of electrical waves from the pacemaker cells to its neighbors inducing the whole coordinated contraction of the uterus wall leading to labor. In a previous work, we simulate the electrical activity of a single uterine cell by a set of ordinary differential equations. Then, this model has been used to simulate the electrical activity propagation. In the present work, the uterine cell tissue is assumed to have uniform and isotropic propagation, and constant electrical membrane properties. The stability of the numerical solution imposes the choice of a critical temporal step. A wave starts at a pacemaker cell; this electrical activity is initiated by the injection of an external stimulation current to the cell membrane. We observe synchronous wave propagation for axial resistance values around 0.5 GOmega or less and propoagation blocking for values greater than 0.7 GOmega. We compute the conduction velocity of the excitation, for different axial resistance values, and obtain a velocity about 10 cm/sec, approaching the one described by the literature for the rat at end of term.

An unsupervised classification method of uterine electromyography signals using wavelet decomposition

The purpose of this study is to classify the uterine contractions in the electromyography (EMG) signal. As the frequency content of the contraction changes from one woman to another and during the pregnancy, wavelet decomposition is used to extract the parameters of each contraction, and an unsupervised statistical classification method based on Fisher test is used to classify events. A principal component analysis projection is then used to evidence the groups resulting from this classification. Results show that uterine contractions may be classified into independent groups according to their frequency content.

Graphic-user-interface system for people with severely impaired vision in mathematics class

Computer software is more and more developed based on graphic-user-interface system (GUI) in order to be user-friendly program. However, this development creates some difficulties for people with impaired vision to use the computers. The "Braille Box", an assistive device, has been developed by modifying Braille cells to form a tactile stimulator array which is compatible with the fingertip. This device allows people with impaired vision to access graphic information on computer screen by tactile perception. We applied the "Braille Box" in mathematics class focused on linear graph, with visually impaired children. The result shows that they can perform task as determining the slope, the intercept and the coordinates of the intersection of two lines.

Dynamical analysis of uterine cell electrical activity model

The uterus is a physiological system consisting of a large number of interacting smooth muscle cells. The uterine excitability changes remarkably with time, generally quiescent during pregnancy, the uterus exhibits forceful synchronized contractions at term leading to fetus expulsion. These changes characterize thus a dynamical system susceptible of being studied through formal mathematical tools. Multiple physiological factors are involved in the regulation process of this complex system. Our aim is to relate the physiological factors to the uterine cell dynamic behaviors. Taking into account a previous work presented, in which the electrical activity of a uterine cell is described by a set of ordinary differential equations, we analyze the impact of physiological parameters on the response of the model, and identify the main subsystems generating the complex uterine electrical activity, with respect to physiological data.

Adaptive filtering for ECG rejection from surface EMG recordings

Surface electromyograms (EMG) of back muscles are often corrupted by electrocardiogram (ECG) signals. This noise in the EMG signals does not allow to appreciate correctly the spectral content of the EMG signals and to follow its evolution during, for example, a fatigue process. Several methods have been proposed to reject the ECG noise from EMG recordings, but seldom taking into account the eventual changes in ECG characteristics during the experiment. In this paper we propose an adaptive filtering algorithm specifically developed for the rejection of the electrocardiogram corrupting surface electromyograms (SEMG). The first step of the study was to choose the ECG electrode position in order to record the ECG with a shape similar to that found in the noised SEMGs. Then, the efficiency of different algorithms were tested on 28 erector spinae SEMG recordings. The best algorithm belongs to the fast recursive least square family (FRLS). More precisely, the best results were obtained with the simplified formulation of a FRLS algorithm. As an application of the adaptive filtering, the paper compares the evolutions of spectral parameters of noised or denoised (after adaptive filtering) surface EMGs recorded on erector spinae muscles during a trunk extension. The fatigue test was analyzed on 16 EMG recordings. After adaptive filtering, mean initial values of energy and of mean power frequency (MPF) were significantly lower and higher respectively. The differences corresponded to the removal of the ECG components. Furthermore, classical fatigue criteria (increase in energy and decrease in MPF values over time during the fatigue test) were better observed on the denoised EMGs. The mean values of the slopes of the energy-time and MPF-time linear relationships differed significantly when established before and after adaptive filtering. These results account for the efficacy of the adaptive filtering method proposed here to denoise electrophysiological signals.

Rejection of the maternal electrocardiogram in the electrohysterogram signal

The electrohysterogram (EHG) signal is mainly corrupted by the mother's electrocardiogram (ECG), which remains present despite analog filtering during acquisition. Wavelets are a powerful denoising tool and have already proved their efficiency on the EHG. In this paper, we propose a new method that employs the redundant wavelet packet transform. We first study wavelet packet coefficient histograms and propose an algorithm to automatically detect the histogram mode number. Using a new criterion, we compute a best basis adapted to the denoising. After EHG wavelet packet coefficient thresholding in the selected basis, the inverse transform is applied. The ECG seems to be very efficiently removed.

Use of the electrohysterogram signal for characterization of contractions during pregnancy

This article proposes a method to evaluate the ability of the electrohysterogram signal to characterize the contractions during pregnancy, in a population with high risk of preterm deliveries. This study constitutes a first stage of a project intended to develop a monitoring system for the early diagnosis of preterm deliveries. After a proper signal denoising, we calculate some parameters characteristic of the extracted contractions. These contractions are then divided into classes of different physiological terms. Classical techniques of data analysis, such as principal component analysis and discriminant analysis, permit us to show an evolution of the contractions during pregnancy, which is different between the groups of preterm deliveries and that of deliveries at term. We show that, in an early term of pregnancy, we can separate the two populations: women delivering at term from women delivering preterm. We then show that these two kinds of pregnancy are of different evolutions. These results are encouraging, because they would permit, in a follow-up medical study, to diagnose a possible preterm delivery, as well as the proximity of the delivery.

Denoising of the uterine EHG by an undecimated wavelet transform

We propose two original methods of denoising of the uterine electrohysterography (EHG) signal by wavelets. This external electrophysiological signal is corrupted by electronic, electromagnetic noises and by the remaining electrocardiogram of the mother. The interfering signals have overlapping spectra. Therefore, a classical filtering is unusable. Wavelets should be a very well-suited denoising tool. The first proposed method uses the algorithm "à trou" with nonsymmetrical filters. The computation is rapid and the results are satisfying compared to the classical denoising techniques. The second algorithm is an improvement of the first method. It uses orthogonal wavelets and the result of the thresholding corresponds to the average of all circulant shifts denoised by a decimated wavelet transform. Results are compared to traditional denoising algorithms by wavelet (orthogonal, maximally decimated). The proposed algorithms are more efficient on simulated signals as well as on uterine EHG.

Fourier-transform infrared and Raman spectroscopic evidence for the incorporation of cinnamaldehydes into the lignin of transgenic tobacco (Nicotiana tabacum L.) plants with reduced expression of cinnamyl alcohol dehydrogenase

Xylem from stems of genetically manipulated tobacco plants which had had cinnamyl alcohol dehydrogenase (CAD; EC 1.1.1.195) activity down-regulated to a greater or lesser degree (clones 37 and 49, respectively) by the insertion of antisense CAD cDNA had similar, or slightly higher, lignin contents than xylem from wild-type plants. Fourier-transform infrared (FT-IR) microspectroscopy indicated that down-regulation of CAD had resulted in the incorporation of moieties with conjugated carbonyl groups into lignin and that the overall extent of cross-linking, particularly of guaiacyl (4-hydroxy-3-methoxyphenyl) rings, in the lignin had altered. The FT-Raman spectra of manipulated xylem exhibited maxima consistent with the presence of elevated levels of aldehydic groups conjugated to a carbon-carbon double bond and a guaiacyl ring. These maxima were particularly intense in the spectra of xylem from clone 37, the xylem of which exhibits a uniform red coloration, and their absolute frequencies matched those of coniferaldehyde. Furthermore, xylem from clone 37 was found to have a higher content of carbonyl groups than that of clone 49 or the wild-type (clone 37: clone 49: wild-type; 2.4:1.6:1.0) as measured by a degradative chemical method. This is the first report of the combined use of FT-IR and FT-Raman spectroscopies to study lignin structure in situ. These analyses provide strong evidence for the incorporation of cinnamaldehyde groups into the lignin of transgenic plants with down-regulated CAD expression. In addition, these non-destructive analyses also suggest that the plants transformed with antisense CAD, in particular clone 37, may contain lignin that is less condensed (cross-linked) than that of the wild-type.

Uterine EMG spectral analysis and relationship to mechanical activity in pregnant monkeys

The objective is to analyse internal and external recordings of uterine EMG in order to reveal common features and to assess the relationship between electrical activity and intra-uterine pressure modification. Three monkeys participated in the study, one as a reference and the others for data. EMGs are recorded simultaneously, internally by unipolar wire electrodes and externally by bipolar Ag/AgCl electrodes. Intra-uterine pressure is recorded as a mechanical index. Except for delay measurements, parameters are derived from spectral analysis and relationships between recordings are assessed by studying the coherence. Spectral analysis exhibits two basic activities in the analysed frequency band, and frequency limits are defined as relevant parameters for electrical activity description. Parameter values do not depend on the internal electrode location. Internal and external EMGs present a similar spectral shape, despite differences in electrode configuration and tissue filtering. It is deduced that external uterine EMG is a good image of the genuine uterine electrical activity. To some extent, it can be related to an average cellular electrical activity.

DNA delivery into Eucalyptus globulus zygotic embryos through biolistics: optimization of the biological and physical parameters of bombardment for two different particle guns

DNA transfer into zygotic embryos of Eucalyptus globulus by microprojectile bombardment was studied with two devices: a gunpowder apparatus and a compressed-helium system. Using, as a test, the transient expression of a reporter gene, we optimized the physical and biological conditions of bombardment. Six-day-old cultured embryos were found to be the best target material, and osmotic treatment increased the expression rate. Conditions of bombardment (particle acceleration and quality of the particle: DNA mix) were studied. In optimal conditions, we were able to obtain up to 130 GUS expression events per embryo with a good distribution over the tissue.In our transient expression experiments, the gunpowder and helium devices exhibited similar efficiencies, reliabilities and reproducibilities.

Uterine electromyography: a critical review

On the basis of a literature review, this work summarizes uterine animal and human electromyographic information obtained at cellular, myometrial, and abdominal levels during gestation and parturition. We show that both internal and external electromyograms occur in phase with intrauterine pressure increase and exhibit similar spectra, including a slow wave (0.01 < frequency < 0.03 Hz) probably because of mechanical artifacts and a fast wave whose frequency content can be subdivided into a low-frequency band always present in every contraction and a high-frequency band related to efficient parturition contractions. Application of classic spectral techniques to electromyogram envelopes has identified group propagation but not pacemaker areas. However, no time delay or classic propagation has been demonstrated by applying the same spectral techniques to the electromyogram itself, probably because of the nonlinearity and three-dimensional nature of the propagating process.

Electrohysterography during pregnancy: preliminary report

The purpose of this study was to test the ability of uterine electrical activity recorded by electrohysterography (EHG) from abdominal electrodes during pregnancy to provide reliable information about uterine contractions. In this preliminary study, abdominal EHG was used to monitor the uterine contractions of eight women, three of whom were having spontaneous contractions related to preterm labor and five of whom were having medical abortions after intrauterine fetal death. The EHG signal consisting of one electrical burst (EB) correlated with a single episode of mechanical activity (MA) in more than 66% of the recorded contractions. When mechanical or electrical activity identified as artifactual was excluded, the temporal correlation of EBs with MA was found in 89% of the recorded contractions. Furthermore, the electrical bursts detected had temporal and spectral characteristics similar to those described previously. Reliable detection of mechanical activity during early pregnancy remains problematic. Nevertheless, abdominal EHG appears suitable for noninvasive monitoring of pregnancies at risk. Further studies are needed to elucidate the significance of the EHG signal in both normal and abnormal pregnancies. It may eventually be possible to use EHG as an ambulatory monitoring tool for the early diagnosis of preterm labor.