The choroid plexus epithelium as a novel player in the stomach-brain axis during Helicobacter infection.

Several studies suggest a link between shifts in gut microbiota and neurological disorders. Recently, we reported a high prevalence of Helicobacter suis (H. suis) in patients with Parkinson's disease. Here, we evaluated the effect of gastric H. suis infection on the brain in mice. One month of infection with H. suis resulted in increased brain inflammation, reflected in activation of microglia and cognitive decline. Additionally, we detected choroid plexus inflammation and disruption of the epithelial blood-cerebrospinal fluid (CSF) barrier upon H. suis infection, while the endothelial blood-brain barrier (BBB) remained functional. These changes were accompanied by leakage of the gastrointestinal barrier and low-grade systemic inflammation, suggesting that H. suis-evoked gastrointestinal permeability and subsequent peripheral inflammation induces changes in brain homeostasis via changes in blood-CSF barrier integrity. In conclusion, this study shows for the first time that H. suis infection induces inflammation in the brain associated with cognitive decline and that the choroid plexus is a novel player in the stomach-brain axis.

X-linked congenital ptosis and associated intellectual disability, short stature, microcephaly, cleft palate, digital and genital abnormalities define novel Xq25q26 duplication syndrome.

Submicroscopic duplications along the long arm of the X-chromosome with known phenotypic consequences are relatively rare events. The clinical features resulting from such duplications are various, though they often include intellectual disability, microcephaly, short stature, hypotonia, hypogonadism and feeding difficulties. Female carriers are often phenotypically normal or show a similar but milder phenotype, as in most cases the X-chromosome harbouring the duplication is subject to inactivation. Xq28, which includes MECP2 is the major locus for submicroscopic X-chromosome duplications, whereas duplications in Xq25 and Xq26 have been reported in only a few cases. Using genome-wide array platforms we identified overlapping interstitial Xq25q26 duplications ranging from 0.2 to 4.76 Mb in eight unrelated families with in total five affected males and seven affected females. All affected males shared a common phenotype with intrauterine- and postnatal growth retardation and feeding difficulties in childhood. Three had microcephaly and two out of five suffered from epilepsy. In addition, three males had a distinct facial appearance with congenital bilateral ptosis and large protruding ears and two of them showed a cleft palate. The affected females had various clinical symptoms similar to that of the males with congenital bilateral ptosis in three families as most remarkable feature. Comparison of the gene content of the individual duplications with the respective phenotypes suggested three critical regions with candidate genes (AIFM1, RAB33A, GPC3 and IGSF1) for the common phenotypes, including candidate loci for congenital bilateral ptosis, small head circumference, short stature, genital and digital defects.

Comprehending emotional eating in obese youngsters: the role of parental rejection and emotion regulation.

OBJECTIVES: The present study examined the role of emotion regulation in the relation between parental rejection and emotional eating of obese youngsters. METHOD: Participants were 110 obese youngsters between the ages of 10 and 16 years who were referred to a Belgian treatment centre for obesity. Participants completed questionnaires assessing maternal and paternal rejection, emotion regulation strategies and emotional eating during their intake at the treatment centre. Bootstrapping procedure was used to test if emotion regulation mediated the relationship between maternal and paternal rejection on the one hand and emotional eating of the youngster on the other hand. RESULTS: Results revealed that the use of maladaptive emotion regulation strategies mediated the relation between maternal rejection and emotional eating. Paternal rejection was neither associated with the emotion regulation nor with the emotional eating of the youngster. DISCUSSION: The findings highlight the importance of assessing the emotional bond between mother and child and the emotion regulation of the youngster in the treatment of pediatric obesity.

Short communication: Circadian variations and day-to-day variability of clinical signs used for the early diagnosis of pneumonia within and between calves.

For rational antimicrobial use, a timely and correct diagnosis of bovine respiratory disease, especially pneumonia, in calves is required. Current approaches often rely on clinical signs observed at a single time point, and do not take potential diurnal patterns in the manifestation of these clinical signs into account. Therefore, the aim of this pilot study was to investigate how clinical signs utilized for the (early) detection of pneumonia vary both within and between calves, throughout the day and across days. A longitudinal study was conducted in which 36 pre-weaned Holstein-Friesian calves were clinically examined eight times over the course of 48 h. The following parameters were considered: respiratory rate, type of respiration, dyspnea, stridor, induced cough (trachea reflex), spontaneous cough, eye and nasal discharge, ear positions, head tilt, rectal temperature, diarrhea, milk residue, body posture, Wisconsin and Davis BRD scorecard. The advent of thoracic ultrasonography (TUS) enables detection of (sub)clinical pneumonia in a more reliable way, compared to the diagnosis based solely on clinical signs. In this study, 14% (5/36) of the calves had an ultrasound confirmed pneumonia (consolidation ≥1 cm in depth). No variations were observed in the prevalence of clinical signs at the various time points of the day. However, we did observe a difference in the manifestation of clinical signs in individual calves (intra) and between (inter) them. Due to the significant intra-calf variability, diagnosing pneumonia based solely on a single observation of clinical signs, is likely to be insufficient. Hence, misdiagnosis might lead to incorrect use of antimicrobials.

Acinetobacter, Aeromonas and Trichococcus populations dominate the microbial community within urban sewer infrastructure.

We evaluated the population structure and temporal dynamics of the dominant community members within sewage influent from two wastewater treatment plants (WWTPs) in Milwaukee, WI. We generated > 1.1 M bacterial pyrotag sequences from the V6 hypervariable region of 16S rRNA genes from 38 influent samples and two samples taken upstream in the sanitary sewer system. Only a small fraction of pyrotags from influent samples (∼ 15%) matched sequences from human faecal samples. The faecal components of the sewage samples included enriched pyrotag populations from Lactococcus and Enterobacteriaceae relative to their fractional representation in human faecal samples. In contrast to the large number of distinct pyrotags that represent faecal bacteria such as Lachnospiraceae and Bacteroides, only one or two unique V6 sequences represented Acinetobacter, Aeromonas and Trichococcus, which collectively account for nearly 35% of the total sewage community. Two dominant Acinetobacter V6 pyrotags (designated Acineto tag 1 and Acineto tag 2) fluctuated inversely with a seasonal pattern over a 3-year period, suggesting two distinct Acinetobacter populations respond differently to ecological forcings in the system. A single nucleotide change in the V6 pyrotags accounted for the difference in these populations and corresponded to two phylogenetically distinct clades based on full-length sequences. Analysis of wavelet functions, derived from a mathematical model of temporal fluctuations, demonstrated that other abundant sewer associated populations including Trichococcus and Aeromonas had temporal patterns similar to either Acineto tag 1 or Acineto tag 2. Populations with related temporal fluctuations were found to significantly correlate with the same WWTP variables (5-day BOD, flow, ammonia, total phosphorous and suspended solids). These findings illustrate that small differences in V6 sequences can represent phylogenetically and ecologically distinct taxa. This work provides insight into microbial community composition and dynamics within the defined environment of urban sewer infrastructure.

Erythema multiforme in the esophagus.

Erythema multiforme is an immune-mediated mucocutaneous disorder. Mucosal involvement usually affects the oral region, the genitals or the eyes. We report a case of esophagitis caused by erythema multiforme in a patient diagnosed with lung cancer. Esophageal manifestation in erythema multiforme is rarely seen. Besides esophagitis it can lead to esophageal strictures. Erythema multiforme is mostly triggered by infection or drugs but the association with malignancy has been described.

Detection and validation of copy number variation in X-linked mental retardation.

Studies to identify the genetic defects associated with X-linked mental retardation (XLMR) in males have revealed tens of genes important for normal brain development and cognitive functioning in men. Despite extensive efforts in breakpoint cloning of chromosomal rearrangements and mutation screening of candidate genes on the X chromosome, still many XLMR families and sporadic cases remain unsolved. It is now clear that submicroscopic copy number changes on the X chromosome can explain about 5% of these idiopathic cases. Interestingly, beside gene deletions, an increase in gene dosage due to genomic duplications seems to contribute to causality more often than expected. Since larger duplications on the X chromosome are tolerated compared to deletions, they often harbour more than one gene hampering the identification of the causal gene. In contrast to copy number variations (CNVs) on autosomes, most disease-associated CNVs on the X chromosome in males are inherited from their mothers who normally do not present with any clinical symptoms due to non-random X inactivation. Here, we review the different methods applied to study copy number alterations on the X chromosome in patients with cognitive impairment, discuss those CNVs that are associated with disease and elaborate on the genes and mechanisms involved. At the end, we will resume in vivo assays to study the relation of CNVs on the X chromosome and mental disability.

Efficiently updating and tracking the dominant kernel principal components.

The dominant set of eigenvectors of the symmetrical kernel Gram matrix is used in many important kernel methods (like e.g. kernel Principal Component Analysis, feature approximation, denoising, compression, prediction) in the machine learning area. Yet in the case of dynamic and/or large-scale data, the batch calculation nature and computational demands of the eigenvector decomposition limit these methods in numerous applications. In this paper we present an efficient incremental approach for fast calculation of the dominant kernel eigenbasis, which allows us to track the kernel eigenspace dynamically. Experiments show that our updating scheme delivers a numerically stable and accurate approximation for eigenvalues and eigenvectors at every iteration in comparison to the batch algorithm.

Plasma and urinary cortisol levels after dexamethasone in affective disorders.

The validity of the dexamethasone suppression test was evaluated for the differential diagnosis of primary and secondary depressions. Forty hospitalized psychiatric patients (14 primary depressed, 15 secondary depressed and 11 non-depressed controls) were studied. The Research Diagnostic Criteria of Spitzer et al. (1978) were used to classify these patients. Eight out of the 14 primary depressed patients had an abnormally high plasma cortisol at 4 p.m. after dexamethasone. Only 2 out of the 15 secondary depressed patients and none of the 11 controls had an abnormal response to dexamethasone. Based on these results, the dexamethasone suppression test has a sensitivity of 57%, a specificity of 87% and a predictive value of 80%. The determination of urinary free cortisol excretion does not improve the performance of the test.

Fetal electrocardiogram extraction by blind source subspace separation.

In this paper, we propose the emerging technique of independent component analysis, also known as blind source separation, as an interesting tool for the extraction of the antepartum fetal electrocardiogram from multilead cutaneous potential recordings. The technique is illustrated by means of a real-life example.

Multichannel adaptive enhancement of the electrogastrogram.

The electrogastric signal can be measured cutaneously on the abdomen. This is attractive because it is harmless to patients or volunteers. However, the poor quality of the cutaneous measurements necessitates signal enhancements. Hence, in this paper, an adaptive multichannel signal enhancing system is proposed. The mu-vector least mean square (LMS) algorithm is applied to adjust the weights of the adaptive filters in the system. The detailed description and the performance analysis of the system is given in the paper. Applying the proposed system, the respiratory artifact, the electrode-skin noise, some of motion artifacts, and the electrocardiography (ECG) can be efficiently reduced while the characteristics of the relevant gastric signal is less affected.

Optimal control by least squares support vector machines.

Support vector machines have been very successful in pattern recognition and function estimation problems. In this paper we introduce the use of least squares support vector machines (LS-SVM's) for the optimal control of nonlinear systems. Linear and neural full static state feedback controllers are considered. The problem is formulated in such a way that it incorporates the N-stage optimal control problem as well as a least squares support vector machine approach for mapping the state space into the action space. The solution is characterized by a set of nonlinear equations. An alternative formulation as a constrained nonlinear optimization problem in less unknowns is given, together with a method for imposing local stability in the LS-SVM control scheme. The results are discussed for support vector machines with radial basis function kernel. Advantages of LS-SVM control are that no number of hidden units has to be determined for the controller and that no centers have to be specified for the Gaussian kernels when applying Mercer's condition. The curse of dimensionality is avoided in comparison with defining a regular grid for the centers in classical radial basis function networks. This is at the expense of taking the trajectory of state variables as additional unknowns in the optimization problem, while classical neural network approaches typically lead to parametric optimization problems. In the SVM methodology the number of unknowns equals the number of training data, while in the primal space the number of unknowns can be infinite dimensional. The method is illustrated both on stabilization and tracking problems including examples on swinging up an inverted pendulum with local stabilization at the endpoint and a tracking problem for a ball and beam system.

Training multilayer perceptron classifiers based on a modified support vector method.

In this paper we describe a training method for one hidden layer multilayer perceptron classifier which is based on the idea of support vector machines (SVM's). An upper bound on the Vapnik-Chervonenkis (VC) dimension is iteratively minimized over the interconnection matrix of the hidden layer and its bias vector. The output weights are determined according to the support vector method, but without making use of the classifier form which is related to Mercer's condition. The method is illustrated on a two-spiral classification problem.

Robust local stability of multilayer recurrent neural networks.

In this paper we derive a condition for robust local stability of multilayer recurrent neural networks with two hidden layers. The stability condition follows from linking theory about linearization, robustness analysis of linear systems under nonlinear perturbation and matrix inequalities. A characterization of the basin of attraction of the origin is given in terms of the level set of a quadratic Lyapunov function. In a similar way like for NL theory, local stability is imposed around the origin and the apparent basin of attraction is made large by applying the criterion, while the proven basin of attraction is relatively small due to conservatism of the criterion. Modifying dynamic backpropagation by the new stability condition is discussed and illustrated by simulation examples.

A support vector machine formulation to PCA analysis and its kernel version.

In this paper, we present a simple and straightforward primal-dual support vector machine formulation to the problem of principal component analysis (PCA) in dual variables. By considering a mapping to a high-dimensional feature space and application of the kernel trick (Mercer theorem), kernel PCA is obtained as introduced by Scholkopf et al. (2002). While least squares support vector machine classifiers have a natural link with the kernel Fisher discriminant analysis (minimizing the within class scatter around targets +1 and -1), for PCA analysis one can take the interpretation of a one-class modeling problem with zero target value around which one maximizes the variance. The score variables are interpreted as error variables within the problem formulation. In this way primal-dual constrained optimization problem interpretations to the linear and kernel PCA analysis are obtained in a similar style as for least square-support vector machine classifiers.

Financial time series prediction using least squares support vector machines within the evidence framework.

The Bayesian evidence framework is applied in this paper to least squares support vector machine (LS-SVM) regression in order to infer nonlinear models for predicting a financial time series and the related volatility. On the first level of inference, a statistical framework is related to the LS-SVM formulation which allows one to include the time-varying volatility of the market by an appropriate choice of several hyper-parameters. The hyper-parameters of the model are inferred on the second level of inference. The inferred hyper-parameters, related to the volatility, are used to construct a volatility model within the evidence framework. Model comparison is performed on the third level of inference in order to automatically tune the parameters of the kernel function and to select the relevant inputs. The LS-SVM formulation allows one to derive analytic expressions in the feature space and practical expressions are obtained in the dual space replacing the inner product by the related kernel function using Mercer's theorem. The one step ahead prediction performances obtained on the prediction of the weekly 90-day T-bill rate and the daily DAX30 closing prices show that significant out of sample sign predictions can be made with respect to the Pesaran-Timmerman test statistic.

Adaptive spectral analysis of cutaneous electrogastric signals using autoregressive moving average modelling.

The recording of the human gastric myoelectrical activity by means of cutaneous electrodes is called electrogastrography (EGG). It provides a noninvasive method of studying electrogastric behaviour. The normal frequency of the gastric signal is about 0.05 Hz. However, sudden changes of its frequency have been observed and are generally considered to be related to gastric motility disorders. Thus, spectral analysis, especially online spectral analysis, can serve as a valuable tool for practical purposes. The paper presents a new method of the adaptive spectral analysis of cutaneous electrogastric signals using autoregressive moving average (ARMA) modelling. It is based on an adaptive ARMA filter and provides both time and frequency information of the signal. Its performance is investigated in comparison with the conventional FFT-based periodogram method. Its properties in tracking time-varying instantaneous frequencies are shown. Its applications to the running spectral analysis of cutaneous electrogastric signals are presented. The proposed adaptive ARMA spectral analysis method is easy to implement and is efficient in computations. The results presented in the paper show that this new method provides a better performance and is very useful for the online monitoring of cutaneous electrogastric signals.

Classification of normal and abnormal electrogastrograms using multilayer feedforward neural networks.

A neural network approach is proposed for the automated classification of the normal and abnormal EGG. Two learning algorithms, the quasi-Newton and the scaled conjugate gradient method for the multilayer feedforward neural networks (MFNN), are introduced and compared with the error backpropagation algorithm. The configurations of the MFNN are determined by experiment. The raw EGG data, its power spectral data, and its autoregressive moving average (ARMA) modelling parameters are used as the input to the MFNN and compared with each other. Three indexes (the percent correct, sum-squared error and complexity per iteration) are used to evaluate the performance of each learning algorithm. The results show that the scaled conjugate gradient algorithm performs best, in that it is robust and provides a super-linear convergence rate. The power spectral representation and the ARMA modelling parameters of the EGG are found to be better types of the input to the network for this specific application, both yielding a percent correctness of 95% on the test set. Although the results are focused on the classification of the EGG, this paper should provide useful information for the classification of other biomedical signals.