What makes one person paranoid and another person anxious? The differential prediction of social anxiety and persecutory ideation in an experimental situation

The study shows that social anxiety and persecutory ideation share many of the same predictive factors. Non-clinical paranoia may be a type of anxious fear. However, perceptual anomalies are a distinct predictor of paranoia. In the context of an individual feeling anxious, the occurrence of odd internal feelings in social situations may lead to delusional ideas through a sense of" things not seeming right". The study illustrates the approach of focusing on experiences such as paranoid thinking rather than diagnoses such as schizophrenia.

Identification of in vitro HSC fate regulators by differential lipid raft clustering.

Most hematopoietic stem cells (HSC) in the bone marrow reside in a quiescent state and occasionally enter the cell cycle upon cytokine-induced activation. Although the mechanisms regulating HSC quiescence and activation remain poorly defined, recent studies have revealed a role of lipid raft clustering (LRC) in HSC activation. Here, we tested the hypothesis that changes in lipid raft distribution could serve as an indicator of the quiescent and activated state of HSCs in response to putative niche signals. A semi-automated image analysis tool was developed to map the presence or absence of lipid raft clusters in live HSCs cultured for just one hour in serum-free medium supplemented with stem cell factor (SCF). By screening the ability of 19 protein candidates to alter lipid raft dynamics, we identified six factors that induced either a marked decrease (Wnt5a, Wnt3a and Osteopontin) or increase (IL3, IL6 and VEGF) in LRC. Cell cycle kinetics of single HSCs exposed to these factors revealed a correlation of LRC dynamics and proliferation kinetics: factors that decreased LRC slowed down cell cycle kinetics, while factors that increased LRC led to faster and more synchronous cycling. The possibility of identifying, by LRC analysis at very early time points, whether a stem cell is activated and possibly committed upon exposure to a signaling cue of interest could open up new avenues for large-scale screening efforts.

Screening for wound-induced oxylipins in Arabidopsis thaliana by differential HPLC-APCI/MS profiling of crude leaf extracts and subsequent characterisation by capillary-scale NMR

A simple non-targeted differential HPLC-APCI/MS approach has been developed in order to survey metabolome modifications that occur in the leaves of Arabidopsis thaliana following wound-induced stress. The wound-induced accumulation of metabolites, particularly oxylipins, was evaluated by HPLC-MS analysis of crude leaf extracts. A generic, rapid and reproducible pressure liquid extraction procedure was developed for the analysis of restricted leaf samples without the need for specific sample preparation. The presence of various oxylipins was determined by head-to-head comparison of the HPLC-MS data, filtered with a component detection algorithm, and automatically compared with the aid of software searching for small differences in similar HPLC-MS profiles. Repeatability was verified in several specimens belonging to different series. Wound-inducible jasmonates were efficiently highlighted by this non-targeted approach without the need for complex sample preparation as is the case for the 'oxylipin signature' procedure based on GC-MS. Furthermore this HPLC-MS screening technique allowed the isolation of induced compounds for further characterisation by capillary-scale NMR (CapNMR) after HPLC scale-up. In this paper, the screening method is described and applied to illustrate its potential for monitoring polar and non-polar stress-induced constituents as well as its use in combination with CapNMR for the structural assignment of wound-induced compounds of interest

In vivo nuclear translocation of mineralocorticoid and glucocorticoid receptors in rat kidney: differential effect of corticosteroids along the distal tubule.

Aldosterone and corticosterone bind to mineralocorticoid (MR) and glucocorticoid receptors (GR), which, upon ligand binding, are thought to translocate to the cell nucleus to act as transcription factors. Mineralocorticoid selectivity is achieved by the 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2) that inactivates 11β-hydroxy glucocorticoids. High expression levels of 11β-HSD2 characterize the aldosterone-sensitive distal nephron (ASDN), which comprises the segment-specific cells of late distal convoluted tubule (DCT2), connecting tubule (CNT), and collecting duct (CD). We used MR- and GR-specific antibodies to study localization and regulation of MR and GR in kidneys of rats with altered plasma aldosterone and corticosterone levels. In control rats, MR and GR were found in cell nuclei of thick ascending limb (TAL), DCT, CNT, CD cells, and intercalated cells (IC). GR was also abundant in cell nuclei and the subapical compartment of proximal tubule (PT) cells. Dietary NaCl loading, which lowers plasma aldosterone, caused a selective removal of GR from cell nuclei of 11β-HSD2-positive ASDN. The nuclear localization of MR was unaffected. Adrenalectomy (ADX) resulted in removal of MR and GR from the cell nuclei of all epithelial cells. Aldosterone replacement rapidly relocated the receptors in the cell nuclei. In ASDN cells, low-dose corticosterone replacement caused nuclear localization of MR, but not of GR. The GR was redistributed to the nucleus only in PT, TAL, early DCT, and IC that express no or very little 11β-HSD2. In ASDN cells, nuclear GR localization was only achieved when corticosterone was replaced at high doses. Thus ligand-induced nuclear translocation of MR and GR are part of MR and GR regulation in the kidney and show remarkable segment- and cell type-specific characteristics. Differential regulation of MR and GR may alter the level of heterodimerization of the receptors and hence may contribute to the complexity of corticosteroid effects on ASDN function.

Investigation of discrete imaging models and iterative image reconstruction in differential X-ray phase-contrast tomography.

Differential X-ray phase-contrast tomography (DPCT) refers to a class of promising methods for reconstructing the X-ray refractive index distribution of materials that present weak X-ray absorption contrast. The tomographic projection data in DPCT, from which an estimate of the refractive index distribution is reconstructed, correspond to one-dimensional (1D) derivatives of the two-dimensional (2D) Radon transform of the refractive index distribution. There is an important need for the development of iterative image reconstruction methods for DPCT that can yield useful images from few-view projection data, thereby mitigating the long data-acquisition times and large radiation doses associated with use of analytic reconstruction methods. In this work, we analyze the numerical and statistical properties of two classes of discrete imaging models that form the basis for iterative image reconstruction in DPCT. We also investigate the use of one of the models with a modern image reconstruction algorithm for performing few-view image reconstruction of a tissue specimen.

An active strain electromechanical model for cardiac tissue

We propose a finite element approximation of a system of partial differential equations describing the coupling between the propagation of electrical potential and large deformations of the cardiac tissue. The underlying mathematical model is based on the active strain assumption, in which it is assumed that a multiplicative decomposition of the deformation tensor into a passive and active part holds, the latter carrying the information of the electrical potential propagation and anisotropy of the cardiac tissue into the equations of either incompressible or compressible nonlinear elasticity, governing the mechanical response of the biological material. In addition, by changing from an Eulerian to a Lagrangian configuration, the bidomain or monodomain equations modeling the evolution of the electrical propagation exhibit a nonlinear diffusion term. Piecewise quadratic finite elements are employed to approximate the displacements field, whereas for pressure, electrical potentials and ionic variables are approximated by piecewise linear elements. Various numerical tests performed with a parallel finite element code illustrate that the proposed model can capture some important features of the electromechanical coupling, and show that our numerical scheme is efficient and accurate.

Analysis of thermal properties of phase change materials (PCM) using differential scanning calorimeter (DSC)

Commercially available PCM RT 20, RT 27, SP 22, A17 and SP 25 A8. Were analyzed using dynamic and step method of heat flux DSC. The results of the dinamic and step method were compared with commercial valures. It was found that RT 20 & RT 27 showed good conforming of results with commercial values while SP 22 A17 & SP 25 A8 did not show conformity.

On the differential evolution algorithm and its appliation to training radial basis function networks

The parameter setting of a differential evolution algorithm must meet several requirements: efficiency, effectiveness, and reliability. Problems vary. The solution of a particular problem can be represented in different ways. An algorithm most efficient in dealing with a particular representation may be less efficient in dealing with other representations. The development of differential evolution-based methods contributes substantially to research on evolutionary computing and global optimization in general. The objective of this study is to investigatethe differential evolution algorithm, the intelligent adjustment of its controlparameters, and its application. In the thesis, the differential evolution algorithm is first examined using different parameter settings and test functions. Fuzzy control is then employed to make control parameters adaptive based on an optimization process and expert knowledge. The developed algorithms are applied to training radial basis function networks for function approximation with possible variables including centers, widths, and weights of basis functions and both having control parameters kept fixed and adjusted by fuzzy controller. After the influence of control variables on the performance of the differential evolution algorithm was explored, an adaptive version of the differential evolution algorithm was developed and the differential evolution-based radial basis function network training approaches were proposed. Experimental results showed that the performance of the differential evolution algorithm is sensitive to parameter setting, and the best setting was found to be problem dependent. The fuzzy adaptive differential evolution algorithm releases the user load of parameter setting and performs better than those using all fixedparameters. Differential evolution-based approaches are effective for training Gaussian radial basis function networks.

On Modelling, System Identification and Control of Servo-Systems with a Flexible Load

The present study was done with two different servo-systems. In the first system, a servo-hydraulic system was identified and then controlled by a fuzzy gainscheduling controller. The second servo-system, an electro-magnetic linear motor in suppressing the mechanical vibration and position tracking of a reference model are studied by using a neural network and an adaptive backstepping controller respectively. Followings are some descriptions of research methods. Electro Hydraulic Servo Systems (EHSS) are commonly used in industry. These kinds of systems are nonlinearin nature and their dynamic equations have several unknown parameters.System identification is a prerequisite to analysis of a dynamic system. One of the most promising novel evolutionary algorithms is the Differential Evolution (DE) for solving global optimization problems. In the study, the DE algorithm is proposed for handling nonlinear constraint functionswith boundary limits of variables to find the best parameters of a servo-hydraulic system with flexible load. The DE guarantees fast speed convergence and accurate solutions regardless the initial conditions of parameters. The control of hydraulic servo-systems has been the focus ofintense research over the past decades. These kinds of systems are nonlinear in nature and generally difficult to control. Since changing system parameters using the same gains will cause overshoot or even loss of system stability. The highly non-linear behaviour of these devices makes them ideal subjects for applying different types of sophisticated controllers. The study is concerned with a second order model reference to positioning control of a flexible load servo-hydraulic system using fuzzy gainscheduling. In the present research, to compensate the lack of dampingin a hydraulic system, an acceleration feedback was used. To compare the results, a pcontroller with feed-forward acceleration and different gains in extension and retraction is used. The design procedure for the controller and experimental results are discussed. The results suggest that using the fuzzy gain-scheduling controller decrease the error of position reference tracking. The second part of research was done on a PermanentMagnet Linear Synchronous Motor (PMLSM). In this study, a recurrent neural network compensator for suppressing mechanical vibration in PMLSM with a flexible load is studied. The linear motor is controlled by a conventional PI velocity controller, and the vibration of the flexible mechanism is suppressed by using a hybrid recurrent neural network. The differential evolution strategy and Kalman filter method are used to avoid the local minimum problem, and estimate the states of system respectively. The proposed control method is firstly designed by using non-linear simulation model built in Matlab Simulink and then implemented in practical test rig. The proposed method works satisfactorily and suppresses the vibration successfully. In the last part of research, a nonlinear load control method is developed and implemented for a PMLSM with a flexible load. The purpose of the controller is to track a flexible load to the desired position reference as fast as possible and without awkward oscillation. The control method is based on an adaptive backstepping algorithm whose stability is ensured by the Lyapunov stability theorem. The states of the system needed in the controller are estimated by using the Kalman filter. The proposed controller is implemented and tested in a linear motor test drive and responses are presented.

Analysis of vineyard differential management zones and relation to vine development, grape maturity and quality

The objective of research was to analyse the potential of Normalized Difference Vegetation Index (NDVI) maps from satellite images, yield maps and grapevine fertility and load variables to delineate zones with different wine grape properties for selective harvesting. Two vineyard blocks located in NE Spain (Cabernet Sauvignon and Syrah) were analysed. The NDVI was computed from a Quickbird-2 multi-spectral image at veraison (July 2005). Yield data was acquired by means of a yield monitor during September 2005. Other variables, such as the number of buds, number of shoots, number of wine grape clusters and weight of 100 berries were sampled in a 10 rows × 5 vines pattern and used as input variables, in combination with the NDVI, to define the clusters as alternative to yield maps. Two days prior to the harvesting, grape samples were taken. The analysed variables were probable alcoholic degree, pH of the juice, total acidity, total phenolics, colour, anthocyanins and tannins. The input variables, alone or in combination, were clustered (2 and 3 Clusters) by using the ISODATA algorithm, and an analysis of variance and a multiple rang test were performed. The results show that the zones derived from the NDVI maps are more effective to differentiate grape maturity and quality variables than the zones derived from the yield maps. The inclusion of other grapevine fertility and load variables did not improve the results.

Identifying the preferred subset of enzymatic profiles in nonlinear kinetic metabolic models via multiobjective global optimization and pareto filters

Optimization models in metabolic engineering and systems biology focus typically on optimizing a unique criterion, usually the synthesis rate of a metabolite of interest or the rate of growth. Connectivity and non-linear regulatory effects, however, make it necessary to consider multiple objectives in order to identify useful strategies that balance out different metabolic issues. This is a fundamental aspect, as optimization of maximum yield in a given condition may involve unrealistic values in other key processes. Due to the difficulties associated with detailed non-linear models, analysis using stoichiometric descriptions and linear optimization methods have become rather popular in systems biology. However, despite being useful, these approaches fail in capturing the intrinsic nonlinear nature of the underlying metabolic systems and the regulatory signals involved. Targeting more complex biological systems requires the application of global optimization methods to non-linear representations. In this work we address the multi-objective global optimization of metabolic networks that are described by a special class of models based on the power-law formalism: the generalized mass action (GMA) representation. Our goal is to develop global optimization methods capable of efficiently dealing with several biological criteria simultaneously. In order to overcome the numerical difficulties of dealing with multiple criteria in the optimization, we propose a heuristic approach based on the epsilon constraint method that reduces the computational burden of generating a set of Pareto optimal alternatives, each achieving a unique combination of objectives values. To facilitate the post-optimal analysis of these solutions and narrow down their number prior to being tested in the laboratory, we explore the use of Pareto filters that identify the preferred subset of enzymatic profiles. We demonstrate the usefulness of our approach by means of a case study that optimizes the ethanol production in the fermentation of Saccharomyces cerevisiae.

Signalling by neurotrophins and hepatocyte growth factor regulates axon morphogenesis by differential β-catenin phosphorylation

Tyrosine phosphorylation of ß-catenin, a component of adhesion complexes and the Wnt pathway, affects cell adhesion, migration and gene transcription. By reducing ßcatenin availability using shRNA-mediated gene silencing or expression of intracellular N-cadherin, we show that ß-catenin is required for axon growth downstream of Brain Derived Neurotrophic Factor (BDNF) and Hepatocyte Growth Factor (HGF) signalling. We demonstrate that receptor tyrosine kinases (RTK) Trk and Met interact with and phosphorylate ß-catenin. Neurotrophins (NT) stimulation of Trk receptors results in phosphorylation of ß-catenin at residue Y654 and increased axon growth and branching. Conversely, pharmacological inhibition of Trk or a Y654F mutant blocks these effects. ß-catenin phospho(P)-Y654 colocalizes with the cytoskeleton at growth cones. However, HGF that also increases axon growth and branching, induces ß-catenin phosphorylation at Y142 and a nuclear localization. Interestingly, dominant negative ΔN-TCF4 abolishes the effects of HGF in axon growth and branching, but not of NT. We conclude that NT and HGF signalling differentially phosphorylate ß-catenin, targeting ß-catenin to distinct compartments to regulate axon morphogenesis by TCF4-transcription-dependent and independent mechanisms. These results place ß-catenin downstream of growth factor/RTK signalling in axon differentiation.

Eosinophilic fasciitis: Typical abnormalities, variants and differential diagnosis of fasciae abnormalities using MR imaging.

Eosinophilic fasciitis is a rare condition. It is generally limited to the distal parts of the arms and legs. MRI is the ideal imaging modality for diagnosing and monitoring this condition. MRI findings typically evidence only fascial involvement but on a less regular basis signal abnormalities may be observed in neighboring muscle tissue and hypodermic fat. Differential diagnosis of eosinophilic fasciitis by MRI requires the exclusion of several other superficial and deep soft tissue disorders.

Differential monocular vs. binocular pupil responses from melanopsin-based photoreception in patients with anterior ischemic optic neuropathy.

We examined the effect of anterior ischemic optic neuropathy (AION) on the activity of intrinsically photosensitive retinal ganglion cells (ipRGCs) using the pupil as proxy. Eighteen patients with AION (10 unilateral, 8 bilateral) and 29 age-matched control subjects underwent chromatic pupillometry. Red and blue light stimuli increasing in 0.5 log steps were presented to each eye independently under conditions of dark and light adaptation. The recorded pupil contraction was plotted against stimulus intensity to generate scotopic and photopic response curves for assessment of synaptically-mediated ipRGC activity. Bright blue light stimuli presented monocularly and binocularly were used for melanopsin activation. The post-stimulus pupil size (PSPS) at the 6th second following stimulus offset was the marker of intrinsic ipRGC activity. Finally, questionnaires were administered to assess the influence of ipRGCs on sleep. The pupil response and PSPS to all monocularly-presented light stimuli were impaired in AION eyes, indicating ipRGC dysfunction. To binocular light stimulation, the PSPS of AION patients was similar to that of controls. There was no difference in the sleep habits of the two groups. Thus after ischemic injury to one or both optic nerves, the summated intrinsic ipRGC activity is preserved when both eyes receive adequate light exposure.

Conjugation of a Ru(II) Arene Complex to Neomycin or to Guanidinoneomycin Leads to Compounds with Differential Cytotoxicities and Accumulation between Cancer and Normal Cells

A straightforward methodology for the synthesis of conjugates between a cytotoxic organometallic ruthenium(II) complex and amino- and guanidinoglycosides, as potential RNA-targeted anticancer compounds, is described. Under microwave irradiation, the imidazole ligand incorporated on the aminoglycoside moiety (neamine or neomycin) was found to replace one triphenylphosphine ligand from the ruthenium precursor [(η6-p-cym)RuCl(PPh3)2]+, allowing the assembly of the target conjugates. The guanidinylated analogue was easily prepared from the neomycin-ruthenium conjugate by reaction with N,N′-di-Boc-N″-triflylguanidine, a powerful guanidinylating reagent that was compatible with the integrity of the metal complex. All conjugates were purified by semipreparative high-performance liquid chromatography (HPLC) and characterized by electrospray ionization (ESI) and matrix-assisted laser desorption-ionization time-of-flight (MALDI-TOF) mass spectrometry (MS) and NMR spectroscopy. The cytotoxicity of the compounds was tested in MCF-7 (breast) and DU-145 (prostate) human cancer cells, as well as in the normal HEK293 (Human Embryonic Kidney) cell line, revealing a dependence on the nature of the glycoside moiety and the type of cell (cancer or healthy). Indeed, the neomycin-ruthenium conjugate (2) displayed moderate antiproliferative activity in both cancer cell lines (IC50 ≈ 80 μM), whereas the neamine conjugate (4) was inactive (IC50 ≈ 200 μM). However, the guanidinylated analogue of the neomycin-ruthenium conjugate (3) required much lower concentrations than the parent conjugate for equal effect (IC50 = 7.17 μM in DU-145 and IC50 = 11.33 μM in MCF-7). Although the same ranking in antiproliferative activity was found in the nontumorigenic cell line (3 2 > 4), IC50 values indicate that aminoglycoside-containing conjugates are about 2-fold more cytotoxic in normal cells (e.g., IC50 = 49.4 μM for 2) than in cancer cells, whereas an opposite tendency was found with the guanidinylated conjugate, since its cytotoxicity in the normal cell line (IC50 = 12.75 μM for 3) was similar or even lower than that found in MCF-7 and DU-145 cancer cell lines, respectively. Cell uptake studies performed by ICP-MS with conjugates 2 and 3 revealed that guanidinylation of the neomycin moiety had a positive effect on accumulation (about 3-fold higher in DU-145 and 4-fold higher in HEK293), which correlates well with the higher antiproliferative activity of 3. Interestingly, despite the slightly higher accumulation in the normal cell than in the cancer cell line (about 1.4-fold), guanidinoneomycin-ruthenium conjugate (3) was more cytotoxic to cancer cells (about 1.8-fold), whereas the opposite tendency applied for neomycin-ruthenium conjugate (2). Such differences in cytotoxic activity and cellular accumulation between cancer and normal cells open the way to the creation of more selective, less toxic anticancer metallodrugs by conjugating cytotoxic metal-based complexes such as ruthenium(II) arene derivatives to guanidinoglycosides.