Non-fluent aphasia and neural reorganization after speech therapy: insights from human sleep electrophysiology and functional magnetic resonance imaging

Stroke is associated with long-term functional deficits. Behavioral interventions are often effective in promoting functional recovery and plastic changes. Recent studies in normal subjects have shown that sleep, and particularly slow wave activity (SWA), is tied to local brain plasticity and may be used as a sensitive marker of local cortical reorganization after stroke. In a pilot study, we assessed the local changes induced by a single exposure to a therapeutic session of IMITATE (Intensive Mouth Imitation and Talking for Aphasia Therapeutic Effects), a behavioral therapy used for recovery in patients with post-stroke aphasia. In addition, we measured brain activity changes with functional magnetic resonance imaging (fMRI) in a language observation task before, during and after the full IMITATE rehabilitative program. Speech production improved both after a single exposure and the full therapy program as measured by the Western Aphasia Battery (WAB) Repetition subscale. We found that IMITATE induced reorganization in functionally-connected, speech-relevant areas in the left hemisphere. These preliminary results suggest that sleep hd-EEGs, and the topographical analysis of SWA parameters, are well suited to investigate brain plastic changes underpinning functional recovery in neurological disorders.     

Pattern recognition in neural networks with competing dynamics: coexistence of fixed-point and cyclic attractors

We study the properties of the dynamical phase transition occurring in neural network models in which a competition between associative memory and sequential pattern recognition exists. This competition occurs through a weighted mixture of the symmetric and asymmetric parts of the synaptic matrix. Through a generating functional formalism, we determine the structure of the parameter space at non-zero temperature and near saturation (i.e., when the number of stored patterns scales with the size of the network), identifying the regions of high and weak pattern correlations, the spin-glass solutions, and the order-disorder transition between these regions. This analysis reveals that, when associative memory is dominant, smooth transitions appear between high correlated regions and spurious states. In contrast when sequential pattern recognition is stronger than associative memory, the transitions are always discontinuous. Additionally, when the symmetric and asymmetric parts of the synaptic matrix are defined in terms of the same set of patterns, there is a discontinuous transition between associative memory and sequential pattern recognition. In contrast, when the symmetric and asymmetric parts of the synaptic matrix are defined in terms of independent sets of patterns, the network is able to perform both associative memory and sequential pattern recognition for a wide range of parameter values.     

A comparative study of electronic and neural networks involved in pattern recognition

The comparative study of electronic and neural networks involved in pattern recognition starts with the analogies of structure and function which exist between the electronic “basic integrative unit” and the neuron. Both elements represent the basic components in each system of networks and may be considered as functionally equivalent.According to the kind of response given to a standard input signal, four types of integrative units, either electronic or neural, may be distinguished: the fixed, the accommodative, the signal prolongating and the adaptive type.The integrative units perform many different functions. Those involved in pattern recognition, however, can all be grouped into three categories according to one of the following functions they perform: contrast detection, pattern detection and pattern discrimination. A “contrast detecting unit” gives responses in two senses, positive or negative, according to the position of the stimulus over its receptive field. A “pattern detecting unit” gives responses in one sense only, with a maximum for a pattern having the spatial distribution corresponding to the positive acting receptors of its receptive field. For performing the function of discrimination, which leads to reliable identification of any pattern, a network arrangement called a “maximum amplitude filter” is necessary. Examples of such units and arrangements existing in the nervous system are provided.It is concluded that a “logical analysis of neural networks” based on engineering principles is possible and that this could provide a new tool to the neurophysiologist in the study of the nervous system.     

Anaerobic gram-negative faecal flora in patients with Crohn's Disease and healthy subjects

The anaerobic gram-negative faecal flora of five patients with Crohn's Disease (CD) was identified and compared with that of healthy subjects. For isolation and cultivation of the anaerobic gram-negative rods a non-selective medium was used. There were no significant differences in numbers of Bacteroides and Fusobacterium spp. between patients with CD and healthy subjects. However, the numbers of the "Bacteroides fragilis" group were significantly higher in patients than in controls. The high numbers of the "B. fragilis" group in the faeces of patients were particularly due to B. vulgatus which was 6 times more frequent in patients than in healthy subjects. This indicated that B. vulgatus was responsible for the higher numbers of anaerobic gram-negative rods in the faecal flora of patients with CD.     

Plasma sialyltransferase activity in healthy subjects and atherosclerotic patients

Plasma sialyltransferase activity measured by incorporation of cytidine 5;-phospho[14C]acetylneuraminic acid (CMP-NeuAc) into asialofetuin was twofold higher in patients with documented atherosclerosis than in healthy donors. Kinetic studies showed that the enzyme affinity for CMP-NeuAc is the same in donors and patients. Low activity of plasma sialyltransferase in donors may be due to low blood content of this enzyme.     

Prolactin after baclofen in healthy subjects and prolactinoma patients

Serum prolactin (PRL) levels in basal conditions (two samples) and 30, 60, 90, 120, 150 e 180 minutes after oral administration of baclofen (20 mg) were evaluated in 6 healthy subjects and in 10 patients with prolactinoma. The effect of baclofen (20 mg by mouth) on the PRL secretion cimetidine (400 mg i.v.) or domperidone (20 mg i.v.) induced were evaluated in 9 healthy women by administration of baclofen 60 minutes before cimetidine or domperidone. Baclofen was unable to significantly rise serum PRL levels in healthy subjects and in patients affected by prolactinoma and furthermore did not interfere with PRL rise domperidone induced. On the contrary baclofen decreased PRL rise cimetidine induced. It was concluded that: in basal condition, GABAb receptor don't play an obvious role in modulation of PRL secretion; when H2 istaminergic inhibition on PRL secretion is blocked (at an hypothalamic site), a GABA inhibition, b receptor mediated, on PRL secretion became more clear; the domperidone blockade of hypophysial dopaminergic receptors suggests that GABAb modulation of prolactin secretion don't obtain itself by dopaminergic pathways.     

Adaptive encoding neural networks for the recognition of human signal peptide cleavage sites

MOTIVATION: Data representation and encoding are essential for classification of protein sequences with artificial neural networks (ANN). Biophysical properties are appropriate for low dimensional encoding of protein sequence data. However, in general there is no a priori knowledge of the relevant properties for extraction of representative features. RESULTS: An adaptive encoding artificial neural network (ACN) for recognition of sequence patterns is described. In this approach parameters for sequence encoding are optimized within the same process as the weight vectors by an evolutionary algorithm. The method is applied to the prediction of signal peptide cleavage sites in human secretory proteins and compared with an established predictor for signal peptides. CONCLUSION: Knowledge of physico-chemical properties is not necessary for training an ACN. The advantage is a low dimensional data representation leading to computational efficiency, easy evaluation of the detected features, and high prediction accuracy. Availability: A cleavage site prediction server is located at the Humboldt University http://itb.biologie.hu-berlin.de/ approximately jo/sig-cleave/ACNpredictor.cgi Contact: jo@itb.hu-berlin.de; berndj@zedat.fu-berlin.de     

Ensembled neural networks for brain death prediction for patients with severe head injury

The concept of organ donation has gradually been accepted by people in recent years so the judicial brain death determination process becomes very important. Clinically, patients with irreversible apnoeic coma (IAC) will be considered legally as brain death based on a judicial process, but this process can only be applied to people who had already signed the letter of consent to organ donation. The main idea behind the proposed model is to find out an easier way to diagnose the prognosis of patients with severe head injury, and offer the medical staffs more information to determine brain death. Therefore, the technique of ensembled neural networks (ENN) based on multi-layer perceptron (MLP) network has been applied to construct the prediction model of brain death index (BDI). Ten different signals were chosen to be the input data. Using these ten parameters, medical doctors depend on their experience to score the BDI hourly values. The BDI values from medical doctors become the training target of the ANN training process and the standard index of testing process. Moreover, in order to compare the differences between doctors’ and the network's rankings for the input data, the ranking of order of precedence of each input signal is analyzed via sensitivity analysis. The results show that the 4 layers network with validation has better performance than 3 layers. For sensitivity analysis, most of the input variables’ ranking from trained model were similar to the ranking of the medical doctors except RR/RR(Set) this parameter and 4 other parameters (PS-R, PR-R, PS-L, and PR-L) are difficult to rank, even medical doctors cannot decide the ranking accurately. Using the best topology structure of MLP 10-10-5-1, the ensemble neural network could effectively predict the BDI with small errors (i.e. training error = 0.219087; validation error = 0.370485; testing error = 0.280515). In conclusion, this model can provide medical staffs a reference index to evaluate the status of IAC and brain death patients. However, more clinical data are still needed, perhaps to refine the weights of EANN, and certainly to see how widely the model is applicable.     

Classification of electron sub-tomograms with neural networks and its application to template-matching

Classification of electron sub-tomograms is a challenging task, due the missing-wedge and the low signal-to-noise ratio of the data. Classification algorithms tend to classify data according to their orientation to the missing-wedge, rather than to the underlying signal. Here we use a neural network approach, called the Kernel Density Estimator Self-Organizing Map (KerDenSOM3D), which we have implemented in three-dimensions (3D), also having compensated for the missing-wedge, and we comprehensively compare it to other classification methods. For this purpose, we use various simulated macromolecules, as well as tomographically reconstructed in vitro GroEL and GroEL/GroES molecules. We show that the performance of this classification method is superior to previously used algorithms. Furthermore, we show how this algorithm can be used to provide an initial cross-validation of template-matching approaches. For the example of sub-tomogram classification extracted from cellular tomograms of Mycoplasma pneumonia and Spiroplasma melliferum cells, we show the bias of template-matching, and by using differing search and classification areas, we demonstrate how the bias can be significantly reduced.     

Oxidative stress and inflammation in renal patients and healthy subjects

The first goal of this study was to measure the oxidative stress (OS) and relate it to lipoprotein variables in 35 renal patients before dialysis (CKD), 37 on hemodialysis (HD) and 63 healthy subjects. The method for OS was based on the ratio of cholesteryl esters (CE) containing C18/C16 fatty acids (R2) measured by gas chromatography (GC) which is a simple, direct, rapid and reliable procedure. The second goal was to investigate and identify a triacylglycerol peak on GC, referred to as TG48 (48 represents the sum of the three fatty acids carbon chain lengths) which was markedly increased in renal patients compared to healthy controls. We measured TG48 in patients and controls. Mass spectrometry (MS) and MS twice in tandem were used to analyze the fatty acid composition of TG48. MS showed that TG48 was abundant in saturated fatty acids (SFAs) that were known for their pro-inflammatory property. TG48 was significantly and inversely correlated with OS. Renal patients were characterized by higher OS and inflammation than healthy subjects. Inflammation correlated strongly with TG, VLDL-cholesterol, apolipoprotein (apo) C-III and apoC-III bound to apoB-containing lipoproteins, but not with either total cholesterol or LDL-cholesterol.In conclusion, we have discovered a new inflammatory factor, TG48. It is characterized with TG rich in saturated fatty acids. Renal patients have increased TG48 than healthy controls.     

Endothelial cells in peripheral blood of healthy subjects and patients with metastatic carcinomas.

BACKGROUND: A lack of standardized assays and consensus of cell definition has lead to a wide variation in the reported range of circulating endothelial cells (CECs). METHODS: An automated rare cell analysis system was used to enumerate nucleated, CD146+/CD105+/CD45- CECs in 4 mL of blood. RESULTS: Recoveries of spiked HUVECs were linear over a range of 0-1,241 cells (R2>or=0.99) with recoveries of >or=70% at each spike level. Correlation coefficient values for interoperator variability and duplicate sample variation were (R2=0.99 and 0.90), respectively. Correlation of CEC counts between tubes 1-2 and 2-3 drawn from the same subject in sequence differed (R2=0.48 and 0.63, respectively). The normal CEC reference range established in 249 healthy donors was 1-20 CECs/mL blood. CEC counts were significantly higher in the 206 metastatic carcinoma patients (P<0.0001). CONCLUSION: CECs can be accurately and reproducibly enumerated in blood and are elevated in metastatic carcinomas compared with healthy donors. Phlebotomy procedures can affect endothelial cell counts.     

Muscle post-effects and upright standing in healthy subjects and patients with sensory-motor integration disorders

We compared the upright standing in 7 patients with sensory-motor disorders and 7 healthy subjects (control) before and after 30-s involuntary neck muscle contraction. A trajectory of the center of pressure was recorded during 30-s standing with the eyes open, eyes closed and standing on a foam-rubber with the eyes open. As compared to healthy subjects, patients exhibited an increased body sway area during standing with the eyes open on both the firm surface and foam-rubber and a backward shift of the center of pressure during standing with the eyes both open and closed. Closing the eyes affected the upright standing of patients to a lesser extent than standing of healthy subjects. Involuntary neck muscle contraction within 30 s elicited a backward shift of the center of pressure in healthy subjects, especially during standing with the eyes closed, and a decrease in the length of the center-of-pressure trajectory, especially of its frontal component during standing on the foam-rubber. In patients, a post-effect of the neck muscle contraction manifested itself as a decrease in the body sway area during standing on the foam-rubber and relative increase in the frontal component of the center-of-pressure trajectory during standing with the eyes closed. The results suggest that the upright standing of patients with sensory-motor disorders is more sensitive to somatosensory than visual input, and 30-s neck muscle contraction approach their postural stability to the age-matched control.     

Age-related changes in saccadic eye movements in healthy subjects and patients with Parkinson's disease

Age-related changes in characteristics of saccadic eye movements (latency, duration and percentage of multistep saccades) in healthy subjects and patients with Parkinson's disease were evaluated. Healthy volunteers were divided into 6 age groups (17-20 years, 21-30 years, 31-40 years, 41-50 years, 51-60 years, 61-75 years), parkinsonian patients into 3 age groups (41-50 years, 51-60 years, 61-75 years). According to our data, saccade characteristics depend upon age in both healthy subjects and parkinsonian patients. In healthy volunteers the percentage of multistep saccades and the mean saccade latency increase significantly after the age of 60. Values of these characteristics in patients with Parkinson's disease significantly exceed the values in the corresponding age groups of healthy subjects. The "disease" factor (MANOVA) has a greater influence on saccade latency and percentage of multistep saccades then the "age" factor. The duration of single saccades depends on age to a smaller extent and does not change in patients with Parkinson's disease. The peculiarities of neurodegenerative processes during normal aging and aging with Parkinson's disease are discussed.     

Hereditary transferrin system in healthy subjects and schizophrenic patients]

Hereditary polymorphism of transferrin is studied by means of starch gel electrophoresis in a group of healthy inhabitants of Minsk (250 persons) and in a group of schizophrenic patients (128 persons). It is concluded that the inhabitants of Minsk do not differ considerably from the population, living in the European territory by distributing the frequency of transferrin alleles. No considerable differences are found between the group of healthy people and schizophrenic patients.