Measurements of Penetration and Detoxification of PS II Herbicides in Whole Leaves by a Fluorometric Method

The effect of herbicides that inhibit the photosynthetic electron transport at the photosystem II acceptor side has been analyzed in whole plants by using a fluorometric method. The data reported indicate that the apparent variable fluorescence of the induction curve normalized to the control value provides reliable information about the penetration rate and metabolic detoxification of PS II herbicides in whole plants

Hierarchy and Dynamics of Neural Networks

Contains fulltext : 88364.pdf (publisher's version ) (Open Access

Whole Exome Sequencing Identifies Rare Protein-Coding Variants in Behçet's Disease

Behçet's disease (BD) is a systemic inflammatory disease with an incompletely understood etiology. Despite the identification of multiple common genetic variants associated with BD, rare genetic variants have been less explored. We undertook this study to investigate the role of rare variants in BD by performing whole exome sequencing in BD patients of European descent. METHODS: Whole exome sequencing was performed in a discovery set comprising 14 German BD patients of European descent. For replication and validation, Sanger sequencing and Sequenom genotyping were performed in the discovery set and in 2 additional independent sets of 49 German BD patients and 129 Italian BD patients of European descent. Genetic association analysis was then performed in BD patients and 503 controls of European descent. Functional effects of associated genetic variants were assessed using bioinformatic approaches. RESULTS: Using whole exome sequencing, we identified 77 rare variants (in 74 genes) with predicted protein-damaging effects in BD. These variants were genotyped in 2 additional patient sets and then analyzed to reveal significant associations with BD at 2 genetic variants detected in all 3 patient sets that remained significant after Bonferroni correction. We detected genetic association between BD and LIMK2 (rs149034313), involved in regulating cytoskeletal reorganization, and between BD and NEIL1 (rs5745908), involved in base excision DNA repair (P = 3.22 × 10(-4) and P = 5.16 × 10(-4) , respectively). The LIMK2 association is a missense variant with predicted protein damage that may influence functional interactions with proteins involved in cytoskeletal regulation by Rho GTPase, inflammation mediated by chemokine and cytokine signaling pathways, T cell activation, and angiogenesis (Bonferroni-corrected P = 5.63 × 10(-14) , P = 7.29 × 10(-6) , P = 1.15 × 10(-5) , and P = 6.40 × 10(-3) , respectively). The genetic association in NEIL1 is a predicted splice donor variant that may introduce a deleterious intron retention and result in a noncoding transcript variant. CONCLUSION: We used whole exome sequencing in BD for the first time and identified 2 rare putative protein-damaging genetic variants associated with this disease. These genetic variants might influence cytoskeletal regulation and DNA repair mechanisms in BD and might provide further insight into increased leukocyte tissue infiltration and the role of oxidative stress in BD

A simple rule for axon outgrowth and synaptic competition generates realistic connection lengths and filling fractions

Neural connectivity at the cellular and mesoscopic level appears very specific and is presumed to arise from highly specific developmental mechanisms. However, there are general shared features of connectivity in systems as different as the networks formed by individual neurons in Caenorhabditis elegans or in rat visual cortex and the mesoscopic circuitry of cortical areas in the mouse, macaque, and human brain. In all these systems, connection length distributions have very similar shapes, with an initial large peak and a long flat tail representing the admixture of long-distance connections to mostly short-distance connections. Furthermore, not all potentially possible synapses are formed, and only a fraction of axons (called filling fraction) establish synapses with spatially neighboring neurons. We explored what aspects of these connectivity patterns can be explained simply by random axonal outgrowth. We found that random axonal growth away from the soma can already reproduce the known distance distribution of connections. We also observed that experimentally observed filling fractions can be generated by competition for available space at the target neurons--a model markedly different from previous explanations. These findings may serve as a baseline model for the development of connectivity that can be further refined by more specific mechanisms.Comment: 31 pages (incl. supplementary information); Cerebral Cortex Advance Access published online on May 12, 200

Discovering universal statistical laws of complex networks

Different network models have been suggested for the topology underlying complex interactions in natural systems. These models are aimed at replicating specific statistical features encountered in real-world networks. However, it is rarely considered to which degree the results obtained for one particular network class can be extrapolated to real-world networks. We address this issue by comparing different classical and more recently developed network models with respect to their generalisation power, which we identify with large structural variability and absence of constraints imposed by the construction scheme. After having identified the most variable networks, we address the issue of which constraints are common to all network classes and are thus suitable candidates for being generic statistical laws of complex networks. In fact, we find that generic, not model-related dependencies between different network characteristics do exist. This allows, for instance, to infer global features from local ones using regression models trained on networks with high generalisation power. Our results confirm and extend previous findings regarding the synchronisation properties of neural networks. Our method seems especially relevant for large networks, which are difficult to map completely, like the neural networks in the brain. The structure of such large networks cannot be fully sampled with the present technology. Our approach provides a method to estimate global properties of under-sampled networks with good approximation. Finally, we demonstrate on three different data sets (C. elegans' neuronal network, R. prowazekii's metabolic network, and a network of synonyms extracted from Roget's Thesaurus) that real-world networks have statistical relations compatible with those obtained using regression models

Status of the GEO600 gravitational wave detector

The GEO600 laser interferometric gravitational wave detector is approaching the end of its commissioning phase which started in 1995.During a test run in January 2002 the detector was operated for 15 days in a power-recycled michelson configuration. The detector and environmental data which were acquired during this test run were used to test the data analysis code. This paper describes the subsystems of GEO600, the status of the detector by August 2002 and the plans towards the first science run