Ein neuer Genort für eine autosomal-dominante, nichtsyndromale Schwerhörigkeit (DFNA33) liegt auf Chromosom 13q34-qte

Bei der Untersuchung einer deutschen Familie mit nichtsyndromalem Hörverlust mit frühem Beginn und autosomal-dominantem Erbgang konnten wir eine Kopplung zu bekannten DFNA-Loci ausschließen und die Existenz eines neuen Locus (DFNA33) bestätigen. Mit einem nachfolgenden Genom-Scan wurde der Phänotyp auf einem 6-cM-Intervall auf Chromosom 13q34-qter kartiert. Für den Marker D13S285 wurde ein maximaler 2-Punkt-Lodscore von 2,96 erreicht, der maximale Lodscore in der Multipoint-Analyse betrug 3,28 bei 124,56 cM. = By investigation of a German family pedigree with non-syndromic hearing impairment of early onset and autosomal-dominant mode of inheritance, linkage to known DFNA loci was excluded, and the existence of a new locus (DFNA33) was revealed. In a subsequent genomic scan the phenotype was mapped to a 6 cM interval on chromosome 13q34-qter. A maximum two-point lod score of 2.96 was obtained for the marker D13S285 with a maximum lod score in the multipoint analysis of 3.28 at 124.56 cM

In-situ upgrading of Napier grass pyrolysis vapour over microporous and hierarchical mesoporous zeolites

This study presents in-situ upgrading of pyrolysis vapour derived from Napier grass over microporous and mesoporous ZSM-5 catalysts. It evaluates effect of process variables such catalyst–biomass ratio and catalyst type in a vertical fixed bed pyrolysis system at 600 °C, 50 °C/min under 5 L/min nitrogen flow. Increasing catalyst–biomass ratio during the catalytic process with microporous structure reduced production of organic phase bio-oil by approximately 7.0 wt%. Using mesoporous catalyst promoted nearly 4.0 wt% higher organic yield relative to microporous catalyst, which translate to only about 3.0 wt% reduction in organic phase compared to the yield of organic phase from non-catalytic process. GC–MS analysis of bio-oil organic phase revealed maximum degree of deoxygenation of about 36.9% with microporous catalyst compared to the mesoporous catalysts, which had between 39 and 43%. Mesoporous catalysts promoted production olefins and alkanes, normal phenol, monoaromatic hydrocarbons while microporous catalyst favoured the production of alkenes and polyaromatic hydrocarbons. There was no significant increase in the production of normal phenols over microporous catalyst due to its inability to transform the methoxyphenols and methoxy aromatics. This study demonstrated that upgrading of Napier grass pyrolysis vapour over mesoporous ZSM-5 produced bio-oil with improved physicochemical properties

Threatened reef corals of the world

10.1371/journal.pone.0034459PLoS ONE73

Systematic Analysis of Stability Patterns in Plant Primary Metabolism

Metabolic networks are characterized by complex interactions and regulatory mechanisms between many individual components. These interactions determine whether a steady state is stable to perturbations. Structural kinetic modeling (SKM) is a framework to analyze the stability of metabolic steady states that allows the study of the system Jacobian without requiring detailed knowledge about individual rate equations. Stability criteria can be derived by generating a large number of structural kinetic models (SK-models) with randomly sampled parameter sets and evaluating the resulting Jacobian matrices. Until now, SKM experiments applied univariate tests to detect the network components with the largest influence on stability. In this work, we present an extended SKM approach relying on supervised machine learning to detect patterns of enzyme-metabolite interactions that act together in an orchestrated manner to ensure stability. We demonstrate its application on a detailed SK-model of the Calvin-Benson cycle and connected pathways. The identified stability patterns are highly complex reflecting that changes in dynamic properties depend on concerted interactions between several network components. In total, we find more patterns that reliably ensure stability than patterns ensuring instability. This shows that the design of this system is strongly targeted towards maintaining stability. We also investigate the effect of allosteric regulators revealing that the tendency to stability is significantly increased by including experimentally determined regulatory mechanisms that have not yet been integrated into existing kinetic models

Dynamic Modelling under Uncertainty: The Case of Trypanosoma brucei Energy Metabolism

Kinetic models of metabolism require detailed knowledge of kinetic parameters. However, due to measurement errors or lack of data this knowledge is often uncertain. The model of glycolysis in the parasitic protozoan Trypanosoma brucei is a particularly well analysed example of a quantitative metabolic model, but so far it has been studied with a fixed set of parameters only. Here we evaluate the effect of parameter uncertainty. In order to define probability distributions for each parameter, information about the experimental sources and confidence intervals for all parameters were collected. We created a wiki-based website dedicated to the detailed documentation of this information: the SilicoTryp wiki (http://silicotryp.ibls.gla.ac.uk/wiki/Glycolysis). Using information collected in the wiki, we then assigned probability distributions to all parameters of the model. This allowed us to sample sets of alternative models, accurately representing our degree of uncertainty. Some properties of the model, such as the repartition of the glycolytic flux between the glycerol and pyruvate producing branches, are robust to these uncertainties. However, our analysis also allowed us to identify fragilities of the model leading to the accumulation of 3-phosphoglycerate and/or pyruvate. The analysis of the control coefficients revealed the importance of taking into account the uncertainties about the parameters, as the ranking of the reactions can be greatly affected. This work will now form the basis for a comprehensive Bayesian analysis and extension of the model considering alternative topologies

An N-methyl-d-aspartate receptor agonist facilitates sleep-independent synaptic plasticity associated with working memory capacity enhancement

Working memory (WM) capacity improvement is impacted by sleep, and possibly by N-methyl-D-aspartate (NMDA) agonists such as D-cycloserine (DCS), which also affects procedural skill performance. However, the mechanisms behind these relationships are not well understood. In order to investigate the neural basis underlying relationships between WM skill learning and sleep, DCS, and both sleep and DCS together, we evaluated training-retest performances in the n-back task among healthy subjects who were given either a placebo or DCS before the task training, and then followed task training sessions either with wakefulness or sleep. DCS facilitated WM capacity enhancement only occurring after a period of wakefulness, rather than sleep, indicating that WM capacity enhancement is affected by a cellular heterogeneity in synaptic plasticity between time spent awake and time spent asleep. These findings may contribute to development, anti-aging processes, and rehabilitation of higher cognition

Hypoxia Disruption of Vertebrate CNS Pathfinding through EphrinB2 Is Rescued by Magnesium

The mechanisms of hypoxic injury to the developing human brain are poorly understood, despite being a major cause of chronic neurodevelopmental impairments. Recent work in the invertebrate Caenorhabditis elegans has shown that hypoxia causes discrete axon pathfinding errors in certain interneurons and motorneurons. However, it is unknown whether developmental hypoxia would have similar effects in a vertebrate nervous system. We have found that developmental hypoxic injury disrupts pathfinding of forebrain neurons in zebrafish (Danio rerio), leading to errors in which commissural axons fail to cross the midline. The pathfinding defects result from activation of the hypoxia-inducible transcription factor (hif1) pathway and are mimicked by chemical inducers of the hif1 pathway or by expression of constitutively active hif1α. Further, we found that blocking transcriptional activation by hif1α helped prevent the guidance defects. We identified ephrinB2a as a target of hif1 pathway activation, showed that knock-down of ephrinB2a rescued the guidance errors, and showed that the receptor ephA4a is expressed in a pattern complementary to the misrouting axons. By targeting a constitutively active form of ephrinB2a to specific neurons, we found that ephrinB2a mediates the pathfinding errors via a reverse-signaling mechanism. Finally, magnesium sulfate, used to improve neurodevelopmental outcomes in preterm births, protects against pathfinding errors by preventing upregulation of ephrinB2a. These results demonstrate that evolutionarily conserved genetic pathways regulate connectivity changes in the CNS in response to hypoxia, and they support a potential neuroprotective role for magnesium