Parkinsonian tremor identification with multiple local field potential feature classification

This paper explores the development of multi-feature classification techniques used to identify tremor-related characteristics in the Parkinsonian patient. Local field potentials were recorded from the subthalamic nucleus and the globus pallidus internus of eight Parkinsonian patients through the implanted electrodes of a Deep brain stimulation (DBS) device prior to device internalization. A range of signal processing techniques were evaluated with respect to their tremor detection capability and used as inputs in a multi-feature neural network classifier to identify the activity of Parkinsonian tremor. The results of this study show that a trained multi-feature neural network is able, under certain conditions, to achieve excellent detection accuracy on patients unseen during training. Overall the tremor detection accuracy was mixed, although an accuracy of over 86% was achieved in four out of the eight patients.

Multiplexed quantitative proteomics using differential metabolic 15N-labeling

There are several advantages of using metabolic labeling in quantitative proteomics. The early pooling of samples compared to post-labeling methods eliminates errors from different sample processing, protein extraction and enzymatic digestion. Metabolic labeling is also highly efficient and relatively inexpensive compared to commercial labeling reagents. However, methods for multiplexed quantitation in the MS-domain (or ‘non-isobaric’ methods), suffer from signal dilution at higher degrees of multiplexing, as the MS/MS signal for peptide identification is lower given the same amount of peptide loaded onto the column or injected into the mass spectrometer. This may partly be overcome by mixing the samples at non-uniform ratios, for instance by increasing the fraction of unlabeled proteins. We have developed an algorithm for arbitrary degrees of nonisobaric multiplexing for relative protein abundance measurements. We have used metabolic labeling with different levels of 15N, but the algorithm is in principle applicable to any isotope or combination of isotopes. Ion trap mass spectrometers are fast and suitable for LC-MS/MS and peptide identification. However, they cannot resolve overlapping isotopic envelopes from different peptides, which makes them less suitable for MS-based quantitation. Fourier-transform ion cyclotron resonance (FTICR) mass spectrometry is less suitable for LC-MS/MS, but provides the resolving power required to resolve overlapping isotopic envelopes. We therefore combined ion trap LC-MS/MS for peptide identification with FTICR LC-MS for quantitation using chromatographic alignment. We applied the method in a heat shock study in a plant model system (A. thaliana) and compared the results with gene expression data from similar experiments in literature.

The relationship between well-being, future planning and intentions to utilise intervention programmes: what can be learned from homeless service users?

There has been an increasing interest in the impact of individual well-being on the attitudes and actions of people receiving services designed to offer support. If well-being factors are important in the uptake and success of service programmes it is important that the nature of the relationships involved is understood by service designers and implementers. As a contribution to understanding, this paper examines the impact of well-being on the uptake of intervention programmes for homeless people. From the literature on well-being a number of factors are identified that contribute towards overall well-being, which include personal efficacy and identity, but also more directly well-being can be viewed as personal or group/collective esteem. The impact of these factors on service use is assessed by means of two studies of homelessness service users, comparing the implementation of two research tools: a shortened and a fuller one. The conclusions are that the factors identified are related to service use. The higher the collective esteem – esteem drawn from identification with services and their users and providers – and the less that they feel isolated, the more benefits that homeless people will perceive with service use, and in turn the more likely they are to be motivated to use services. However, the most important factors in explaining service use are a real sense that it is appropriate to accept social support from others, a rejection of the social identity as homeless but a cultivation of being valued as part of a non-homeless community, and a positive perception of the impact of the service.

Application of DIGE and mass spectrometry in the study of type 2 Diabetes Mellitus (T2DM) mouse models

Knowledge of the differences between the amounts and types of protein that are expressed in diseased compared to healthy subjects may give an understanding of the biological pathways that cause disease. This is the reasoning behind the presented protocol, which uses difference gel electrophoresis to discover up‐ or down‐regulated proteins between mice of different genotypes, or of those fed on different diets, that may thus be prone to develop diabetes‐like phenotypes. Subsequent analysis of these proteins by tandem mass spectrometry typically facilitates their identification with a high degree of confidence.

Identification of a serine protease involved with the regulation of adrenal growth

The adrenal cortex is a dynamic organ in which the cells of the outer cortex continually divide. It is well known that this cellular proliferation is dependent on constant stimulation from peptides derived from the ACTH precursor pro-opiomelanocortin (POMC) because disruption of pituitary corticotroph function results in rapid atrophy of the gland. Previous results from our laboratory have suggested that the adrenal mitogen is a fragment derived from the N-terminal of POMC not containing the gamma-MSH sequence. Because such a peptide is not generated during processing of POMC in the pituitary, we proposed that the mitogen is generated from circulating pro-gamma-MSH by an adrenal protease. Using degenerate oligonucleotides, we identified a secreted serine protease expressed by the adrenal gland that we named adrenal secretory protease (ASP). In the adrenal cortex, expression of ASP is limited to the outer zona glomerulosa/fasciculata, the region where cortical cells are believed to be derived, and is significantly up-regulated during compensatory growth. Y1 adrenocortical cells transfected with a vector expressing an antisense RNA (and thus having reduced levels of endogenous ASP) were found to grow slower than sense controls while also losing their ability to utilize exogenous pro-gamma-MSH in the media supporting a role for ASP in adrenal growth. Digestion of an N-POMC peptide substrate encompassing the residues around the dibasic cleavage site at positions 49/50 with affinity-purified ASP showed cleavage not to occur at the dibasic site but two residues downstream leading us to propose the identity of the adrenal mitogen to be N-POMC (1-52).

Proteome analysis for identification of target proteins of genistein in primary human endothelial cells stressed with oxidized LDL or homocysteine

Background Epidemiological studies suggest that soy consumption contributes to the prevention of coronary heart disease. The proposed anti-atherogenic effects of soy appear to be carried by the soy isoflavones with genistein as the most abundant compound. Aim of the study To identify proteins or pathways by which genistein might exert its protective activities on atherosclerosis, we analyzed the proteomic response of primary human umbilical vein endothelial cells ( HUVEC) that were exposed to the pro-atherosclerotic stressors homocysteine or oxidized low-density lipoprotein (ox-LDL). Methods HUVEC were incubated with physiological concentrations of homocysteine or ox-LDL in the absence and presence of genistein at concentrations that can be reached in human plasma by a diet rich in soy products (2.5 muM) or by pharmacological intervention ( 25 muM). Proteins from HUVEC were separated by two-dimensional polyacrylamide gel electrophoresis and those that showed altered expression level upon genistein treatment were identified by peptide mass fingerprints derived from tryptic digests of the protein spots. Results Several proteins were found to be differentially affected by genistein. The most interesting proteins that were potently decreased by homocysteine treatment were annexin V and lamin A. Annexin V is an antithrombotic molecule and mutations in nuclear lamin A have been found to result in perturbations of plasma lipids associated with hypertension. Genistein at low and high concentrations reversed the stressor-induced decrease of these anti-atherogenic proteins. Ox-LDL treatment of HUVEC resulted in an increase in ubiquitin conjugating enzyme 12, a protein involved in foam cell formation. Treatment with genistein at both doses reversed this effect. Conclusions Proteome analysis allows the identification of potential interactions of dietary components in the molecular process of atherosclerosis and consequently provides a powerful tool to define biomarkers of response.

Sparse model identification using orthogonal forward regression with basis pursuit and D-optimality

An efficient model identification algorithm for a large class of linear-in-the-parameters models is introduced that simultaneously optimises the model approximation ability, sparsity and robustness. The derived model parameters in each forward regression step are initially estimated via the orthogonal least squares (OLS), followed by being tuned with a new gradient-descent learning algorithm based on the basis pursuit that minimises the l(1) norm of the parameter estimate vector. The model subset selection cost function includes a D-optimality design criterion that maximises the determinant of the design matrix of the subset to ensure model robustness and to enable the model selection procedure to automatically terminate at a sparse model. The proposed approach is based on the forward OLS algorithm using the modified Gram-Schmidt procedure. Both the parameter tuning procedure, based on basis pursuit, and the model selection criterion, based on the D-optimality that is effective in ensuring model robustness, are integrated with the forward regression. As a consequence the inherent computational efficiency associated with the conventional forward OLS approach is maintained in the proposed algorithm. Examples demonstrate the effectiveness of the new approach.

Early identification of stimulant treatment responders, partial responders and non-responders using objective measures in children and adolescents with hyperkinetic disorder

Background: The aim of this study was to evaluate stimulant medication response following a single dose of methylphenidate (MPH) in children and young people with hyperkinetic disorder using infrared motion analysis combined with a continuous performance task (QbTest system) as objective measures. The hypothesis was put forward that a moderate testdose of stimulant medication could determine a robust treatment response, partial response and non-response in relation to activity, attention and impulse control measures. Methods: The study included 44 children and young people between the ages of 7-18 years with a diagnosis of hyperkinetic disorder (F90 & F90.1). A single dose-protocol incorporated the time course effects of both immediate release MPH and extended release MPH (Concerta XL, Equasym XL) to determine comparable peak efficacy periods post intake. Results: A robust treatment response with objective measures reverting to the population mean was found in 37 participants (84%). Three participants (7%) demonstrated a partial response to MPH and four participants (9%) were determined as non-responders due to deteriorating activity measures together with no improvements in attention and impulse control measures. Conclusion: Objective measures provide early into prescribing the opportunity to measure treatment response and monitor adverse reactions to stimulant medication. Most treatment responders demonstrated an effective response to MPH on a moderate testdose facilitating a swift and more optimal titration process.

On merging gradient estimation with mean-tracking techniques for cluster identification

This paper discusses how numerical gradient estimation methods may be used in order to reduce the computational demands on a class of multidimensional clustering algorithms. The study is motivated by the recognition that several current point-density based cluster identification algorithms could benefit from a reduction of computational demand if approximate a-priori estimates of the cluster centres present in a given data set could be supplied as starting conditions for these algorithms. In this particular presentation, the algorithm shown to benefit from the technique is the Mean-Tracking (M-T) cluster algorithm, but the results obtained from the gradient estimation approach may also be applied to other clustering algorithms and their related disciplines.

An introduction to radial basis functions for system identification: a comparison with other neural network methods

A look is taken at the use of radial basis functions (RBFs), for nonlinear system identification. RBFs are firstly considered in detail themselves and are subsequently compared with a multi-layered perceptron (MLP), in terms of performance and usage.

Identification of nonlinear systems with a dynamic recurrent neural network

Two approaches are presented to calculate the weights for a Dynamic Recurrent Neural Network (DRNN) in order to identify the input-output dynamics of a class of nonlinear systems. The number of states of the identified network is constrained to be the same as the number of states of the plant.

Wiener System identification using B-spline functions with De Boor recursion

A simple and effective algorithm is introduced for the system identification of Wiener system based on the observational input/output data. The B-spline neural network is used to approximate the nonlinear static function in the Wiener system. We incorporate the Gauss-Newton algorithm with De Boor algorithm (both curve and the first order derivatives) for the parameter estimation of the Wiener model, together with the use of a parameter initialization scheme. The efficacy of the proposed approach is demonstrated using an illustrative example.

Reaction of (±)-1,1′-binaphthyl-2,2′-diyl hydrogen phosphate {(±)-phosH} with copper(II), cobalt(II) and iron(II) compounds; Identification by x-ray diffraction of [Co(CH3OH)4(H2O)2][(+)-phos][(−)-phos]. 2CH3OH·H2O

[Cu2(μO2CCH3)4(H2O)2], [CuCO3·Cu(OH)2], [CoSO4·7H2O], [Co((+)-tartrate)], and [FeSO4·7H2O] react with excess racemic (±)- 1,1′-binaphthyl-2,2′-diyl hydrogen phosphate {(±)-PhosH} to give mononuclear CuII, CoII and FeII products. The cobalt product, [Co(CH3OH)4(H2O)2]((+)-Phos)((−)-Phos) ·2CH3OH·H2O (7), has been identified by X-ray diffraction. The high-spin, octahedral CoII atom is ligated by four equatorial methanol molecules and two axial water molecules. A (+)- and a (−)-Phos− ion are associated with each molecule of the complex but are not coordinated to the metal centre. For the other CoII, CuII and FeII samples of similar formulation to (7) it is also thought that the Phos− ions are not bonded directly to the metal. When some of the CuII and CoII samples are heated under high vacuum there is evidence that the Phos− ions are coordinated directly to the metals in the products.