Assessment of reward-related brain function after a single-dose of oxytocin in autism: A randomized controlled trial

Background Autism spectrum disorder (ASD) is characterized by difficulties in social communication and interaction, which have been related to atypical neural processing of rewards, especially in the social domain. Since intranasal oxytocin has been shown to modulate activation of the brain’s reward circuit, oxytocin might ameliorate the processing of social rewards in ASD and thus improve social difficulties. Methods In this randomized, double-blind, placebo-controlled, crossover fMRI study, we examined effects of a 24 IU dose of intranasal oxytocin on reward-related brain function in 37 men with ASD without intellectual impairment and 37 age- and IQ-matched control participants. Participants performed an incentive delay task that allows the investigation of neural activity associated with the anticipation and receipt of monetary and social rewards. Results Non-significant tests suggested that oxytocin did not influence neural processes related to the anticipation of social or monetary rewards in either group. Complementary Bayesian analyses indicated moderate evidence for a null model, relative to an alternative model. Our results are inconclusive regarding possible oxytocin effects on amygdala responsiveness to social rewards during reward consumption. There were no significant differences in reward-related brain function between the two groups under placebo. Conclusions Our results do not support the hypothesis that intranasal oxytocin generally enhances activation of reward-related neural circuits in men with and without ASD

FASIMU: flexible software for flux-balance computation series in large metabolic networks

<p>Abstract</p> <p>Background</p> <p>Flux-balance analysis based on linear optimization is widely used to compute metabolic fluxes in large metabolic networks and gains increasingly importance in network curation and structural analysis. Thus, a computational tool flexible enough to realize a wide variety of FBA algorithms and able to handle batch series of flux-balance optimizations is of great benefit.</p> <p>Results</p> <p>We present FASIMU, a command line oriented software for the computation of flux distributions using a variety of the most common FBA algorithms, including the first available implementation of (i) weighted flux minimization, (ii) fitness maximization for partially inhibited enzymes, and (iii) of the concentration-based thermodynamic feasibility constraint. It allows batch computation with varying objectives and constraints suited for network pruning, leak analysis, flux-variability analysis, and systematic probing of metabolic objectives for network curation. Input and output supports SBML. FASIMU can work with free (lp_solve and GLPK) or commercial solvers (CPLEX, LINDO). A new plugin (faBiNA) for BiNA allows to conveniently visualize calculated flux distributions. The platform-independent program is an open-source project, freely available under GNU public license at <url>http://www.bioinformatics.org/fasimu</url> including manual, tutorial, and plugins.</p> <p>Conclusions</p> <p>We present a flux-balance optimization program whose main merits are the implementation of thermodynamics as a constraint, batch series of computations, free availability of sources, choice on various external solvers, and the flexibility on metabolic objectives and constraints.</p

OptFlux: an open-source software platform for in silico metabolic engineering

<p>Abstract</p> <p>Background</p> <p>Over the last few years a number of methods have been proposed for the phenotype simulation of microorganisms under different environmental and genetic conditions. These have been used as the basis to support the discovery of successful genetic modifications of the microbial metabolism to address industrial goals. However, the use of these methods has been restricted to bioinformaticians or other expert researchers. The main aim of this work is, therefore, to provide a user-friendly computational tool for Metabolic Engineering applications.</p> <p>Results</p> <p><it>OptFlux </it>is an open-source and modular software aimed at being the reference computational application in the field. It is the first tool to incorporate strain optimization tasks, i.e., the identification of Metabolic Engineering targets, using Evolutionary Algorithms/Simulated Annealing metaheuristics or the previously proposed OptKnock algorithm. It also allows the use of stoichiometric metabolic models for (i) phenotype simulation of both wild-type and mutant organisms, using the methods of Flux Balance Analysis, Minimization of Metabolic Adjustment or Regulatory on/off Minimization of Metabolic flux changes, (ii) Metabolic Flux Analysis, computing the admissible flux space given a set of measured fluxes, and (iii) pathway analysis through the calculation of Elementary Flux Modes.</p> <p><it>OptFlux </it>also contemplates several methods for model simplification and other pre-processing operations aimed at reducing the search space for optimization algorithms.</p> <p>The software supports importing/exporting to several flat file formats and it is compatible with the SBML standard. <it>OptFlux </it>has a visualization module that allows the analysis of the model structure that is compatible with the layout information of <it>Cell Designer</it>, allowing the superimposition of simulation results with the model graph.</p> <p>Conclusions</p> <p>The <it>OptFlux </it>software is freely available, together with documentation and other resources, thus bridging the gap from research in strain optimization algorithms and the final users. It is a valuable platform for researchers in the field that have available a number of useful tools. Its open-source nature invites contributions by all those interested in making their methods available for the community.</p> <p>Given its plug-in based architecture it can be extended with new functionalities. Currently, several plug-ins are being developed, including network topology analysis tools and the integration with Boolean network based regulatory models.</p

Refining Kidney Survival in 383 Genetically Characterized Patients With Nephronophthisis

Introduction: Nephronophthisis (NPH) comprises a group of rare disorders accounting for up to 10% of end-stage kidney disease (ESKD) in children. Prediction of kidney prognosis poses a major challenge. We assessed differences in kidney survival, impact of variant type, and the association of clinical characteristics with declining kidney function. Methods: Data was obtained from 3 independent sources, namely the network for early onset cystic kidney diseases clinical registry (n = 105), an online survey sent out to the European Reference Network for Rare Kidney Diseases (n = 60), and a literature search (n = 218). Results: A total of 383 individuals were available for analysis: 116 NPHP1, 101 NPHP3, 81 NPHP4 and 85 NPHP11/TMEM67 patients. Kidney survival differed between the 4 cohorts with a highly variable median age at onset of ESKD as follows: NPHP3, 4.0 years (interquartile range 0.3–12.0); NPHP1, 13.5 years (interquartile range 10.5–16.5); NPHP4, 16.0 years (interquartile range 11.0–25.0); and NPHP11/TMEM67, 19.0 years (interquartile range 8.7–28.0). Kidney survival was significantly associated with the underlying variant type for NPHP1, NPHP3, and NPHP4. Multivariate analysis for the NPHP1 cohort revealed growth retardation (hazard ratio 3.5) and angiotensin-converting enzyme inhibitor (ACEI) treatment (hazard ratio 2.8) as 2 independent factors associated with an earlier onset of ESKD, whereas arterial hypertension was linked to an accelerated glomerular filtration rate (GFR) decline. Conclusion: The presented data will enable clinicians to better estimate kidney prognosis of distinct patients with NPH and thereby allow personalized counseling

Blue and Red Light Modulates SigB-Dependent Gene Transcription, Swimming Motility and Invasiveness in Listeria monocytogenes

Background: In a number of gram-positive bacteria, including Listeria, the general stress response is regulated by the alternative sigma factor B (SigB). Common stressors which lead to the activation of SigB and the SigB-dependent regulon are high osmolarity, acid and several more. Recently is has been shown that also blue and red light activates SigB in Bacillus subtilis. Methodology/Principal Findings: By qRT-PCR we analyzed the transcriptional response of the pathogen L. monocytogenes to blue and red light in wild type bacteria and in isogenic deletion mutants for the putative blue-light receptor Lmo0799 and the stress sigma factor SigB. It was found that both blue (455 nm) and red (625 nm) light induced the transcription of sigB and SigB-dependent genes, this induction was completely abolished in the SigB mutant. The blue-light effect was largely dependent on Lmo0799, proving that this protein is a genuine blue-light receptor. The deletion of lmo0799 enhanced the red-light effect, the underlying mechanism as well as that of SigB activation by red light remains unknown. Blue light led to an increased transcription of the internalin A/B genes and of bacterial invasiveness for Caco-2 enterocytes. Exposure to blue light also strongly inhibited swimming motility of the bacteria in a Lmo0799- and SigB-dependent manner, red light had no effect there. Conclusions/Significance: Our data established that visible, in particular blue light is an important environmental signal with an impact on gene expression and physiology of the non-phototrophic bacterium L. monocytogenes. In natural environments these effects will result in sometimes random but potentially also cyclic fluctuations of gene activity, depending on the light conditions prevailing in the respective habitat

Iron Behaving Badly: Inappropriate Iron Chelation as a Major Contributor to the Aetiology of Vascular and Other Progressive Inflammatory and Degenerative Diseases

The production of peroxide and superoxide is an inevitable consequence of aerobic metabolism, and while these particular "reactive oxygen species" (ROSs) can exhibit a number of biological effects, they are not of themselves excessively reactive and thus they are not especially damaging at physiological concentrations. However, their reactions with poorly liganded iron species can lead to the catalytic production of the very reactive and dangerous hydroxyl radical, which is exceptionally damaging, and a major cause of chronic inflammation. We review the considerable and wide-ranging evidence for the involvement of this combination of (su)peroxide and poorly liganded iron in a large number of physiological and indeed pathological processes and inflammatory disorders, especially those involving the progressive degradation of cellular and organismal performance. These diseases share a great many similarities and thus might be considered to have a common cause (i.e. iron-catalysed free radical and especially hydroxyl radical generation). The studies reviewed include those focused on a series of cardiovascular, metabolic and neurological diseases, where iron can be found at the sites of plaques and lesions, as well as studies showing the significance of iron to aging and longevity. The effective chelation of iron by natural or synthetic ligands is thus of major physiological (and potentially therapeutic) importance. As systems properties, we need to recognise that physiological observables have multiple molecular causes, and studying them in isolation leads to inconsistent patterns of apparent causality when it is the simultaneous combination of multiple factors that is responsible. This explains, for instance, the decidedly mixed effects of antioxidants that have been observed, etc...Comment: 159 pages, including 9 Figs and 2184 reference