Analyses of associations between three positionally cloned asthma candidate genes and asthma or asthma-related phenotypes in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Six asthma candidate genes, ADAM33, NPSR1, PHF11, DPP10, HLA-G, and CYFIP2, located at different chromosome regions have been positionally cloned following the reported linkage studies. For ADAM33, NPSR1, and CYFIP2, the associations with asthma or asthma-related phenotypes have been studied in East Asian populations such as Chinese and Japanese. However, for PHF11, DPP10, and HLA-G, none of the association studies have been conducted in Asian populations. Therefore, the aim of the present study is to test the associations between these three positionally cloned genes and asthma or asthma-related phenotypes in a Chinese population.</p> <p>Methods</p> <p>Two, five, and two single nucleotide polymorphisms (SNPs) in the identified top regions of PHF11, DPP10, and HLA-G, respectively, were genotyped in 1183 independent samples. The study samples were selected based on asthma affectation status and extreme values in at least one of the following three asthma-related phenotypes: total serum immunoglobulin E levels, bronchial responsiveness test, and skin prick test. Both single SNP and haplotype analyses were performed.</p> <p>Results</p> <p>We found that DPP10 was significantly associated with bronchial hyperresponsiveness (BHR) and BHR asthma after the adjustment for multiple testing; while the associations of PHF11 with positive skin reactions to antigens and the associations of HLA-G with BHR asthma were only nominally significant.</p> <p>Conclusion</p> <p>Our study is the first one to provide additional evidence that supports the roles of DPP10 in influencing asthma or BHR in a Chinese population.</p

Incorporation of DPP6a and DPP6K Variants in Ternary Kv4 Channel Complex Reconstitutes Properties of A-type K Current in Rat Cerebellar Granule Cells

Dipeptidyl peptidase-like protein 6 (DPP6) proteins co-assemble with Kv4 channel α-subunits and Kv channel-interacting proteins (KChIPs) to form channel protein complexes underlying neuronal somatodendritic A-type potassium current (ISA). DPP6 proteins are expressed as N-terminal variants (DPP6a, DPP6K, DPP6S, DPP6L) that result from alternative mRNA initiation and exhibit overlapping expression patterns. Here, we study the role DPP6 variants play in shaping the functional properties of ISA found in cerebellar granule (CG) cells using quantitative RT-PCR and voltage-clamp recordings of whole-cell currents from reconstituted channel complexes and native ISA channels. Differential expression of DPP6 variants was detected in rat CG cells, with DPP6K (41±3%)>DPP6a (33±3%)>>DPP6S (18±2%)>DPP6L (8±3%). To better understand how DPP6 variants shape native neuronal ISA, we focused on studying interactions between the two dominant variants, DPP6K and DPP6a. Although previous studies did not identify unique functional effects of DPP6K, we find that the unique N-terminus of DPP6K modulates the effects of KChIP proteins, slowing recovery and producing a negative shift in the steady-state inactivation curve. By contrast, DPP6a uses its distinct N-terminus to directly confer rapid N-type inactivation independently of KChIP3a. When DPP6a and DPP6K are co-expressed in ratios similar to those found in CG cells, their distinct effects compete in modulating channel function. The more rapid inactivation from DPP6a dominates during strong depolarization; however, DPP6K produces a negative shift in the steady-state inactivation curve and introduces a slow phase of recovery from inactivation. A direct comparison to the native CG cell ISA shows that these mixed effects are present in the native channels. Our results support the hypothesis that the precise expression and co-assembly of different auxiliary subunit variants are important factors in shaping the ISA functional properties in specific neuronal populations

A theory of how active behavior stabilises neural activity: neural gain modulation by closed-loop environmental feedback

During active behaviours like running, swimming, whisking or sniffing, motor actions shape sensory input and sensory percepts guide future motor commands. Ongoing cycles of sensory and motor processing constitute a closed-loop feedback system which is central to motor control and, it has been argued, for perceptual processes. This closed-loop feedback is mediated by brainwide neural circuits but how the presence of feedback signals impacts on the dynamics and function of neurons is not well understood. Here we present a simple theory suggesting that closed-loop feedback between the brain/body/environment can modulate neural gain and, consequently, change endogenous neural fluctuations and responses to sensory input. We support this theory with modeling and data analysis in two vertebrate systems. First, in a model of rodent whisking we show that negative feedback mediated by whisking vibrissa can suppress coherent neural fluctuations and neural responses to sensory input in the barrel cortex. We argue this suppression provides an appealing account of a brain state transition (a marked change in global brain activity) coincident with the onset of whisking in rodents. Moreover, this mechanism suggests a novel signal detection mechanism that selectively accentuates active, rather than passive, whisker touch signals. This mechanism is consistent with a predictive coding strategy that is sensitive to the consequences of motor actions rather than the difference between the predicted and actual sensory input. We further support the theory by re-analysing previously published two-photon data recorded in zebrafish larvae performing closed-loop optomotor behaviour in a virtual swim simulator. We show, as predicted by this theory, that the degree to which each cell contributes in linking sensory and motor signals well explains how much its neural fluctuations are suppressed by closed-loop optomotor behaviour. More generally we argue that our results demonstrate the dependence of neural fluctuations, across the brain, on closed-loop brain/body/environment interactions strongly supporting the idea that brain function cannot be fully understood through open-loop approaches alone

Towards neuro-inspired symbolic models of cognition: linking neural dynamics to behaviors through asynchronous communications

A computational architecture modeling the relation between perception and action is proposed. Basic brain processes representing synaptic plasticity are first abstracted through asynchronous communication protocols and implemented as virtual microcircuits. These are used in turn to build mesoscale circuits embodying parallel cognitive processes. Encoding these circuits into symbolic expressions gives finally rise to neuro-inspired programs that are compiled into pseudo-code to be interpreted by a virtual machine. Quantitative evaluation measures are given by the modification of synapse weights over time. This approach is illustrated by models of simple forms of behaviors exhibiting cognition up to the third level of animal awareness. As a potential benefit, symbolic models of emergent psychological mechanisms could lead to the discovery of the learning processes involved in the development of cognition. The executable specifications of an experimental platform allowing for the reproduction of simulated experiments are given in “Appendix”

Autonomous Particles for Interactive Flow Visualization

We present an interactive approach to analyse flow fields using a new type of particle system, which is composed of autonomous particles exploring the flow. While particles provide a very intuitive way to visualize flows, it is a challenge to capture the important features with such systems. Particles tend to cluster in regions of low velocity and regions of interest are often sparsely populated. To overcome these disadvantages, we propose an automatic adaption of the particle density with respect to local importance measures. These measures are user defined and the systems sensitivity to them can be adjusted interactively. Together with the particle history, these measures define a probability for particles to multiply or die, respectively. There is no communication between the particles and no neighbourhood information has to be maintained. Thus, the particles can be handled in parallel and support a real‐time investigation of flow fields. To enhance the visualization, the particles' properties and selected field measures are also used to specify the systems rendering parameters, such as colour and size. We demonstrate the effectiveness of our approach on different simulated vector fields from technical and medical applications.Funding agencies: Stiftelsen for Strategisk Forskning Sweden (SSF) [BD15-0082]; Excellence Center at Linkoping and Lund in Information Technology (ELLIIT); Swedish e-Science Research Centre (SeRC)</p

Implementation of a Portable Nested Data-Parallel Language

This paper gives an overview of the implementation of NESL, a portable nested data-parallel language. This language and its implementation are the first to fully support nested data structures as well as nested data-parallel function calls. These features allow the concise description of parallel algorithms on irregular data structures, such as sparse matrices and graphs. In addition, they maintain the advantages of data-parallel languages: a simple programming model and portability. The current NESL implementation is based on an intermediate language called VCODE and a library of vector routines called CVL. It runs on the Connection Machines CM-2 and CM-5, the Cray C90, and serial workstations. We compare initial benchmark results of NESL with those of machine-specific code on these machines for three algorithms: least-squares linefitting, median finding, and a sparse-matrix vector product. These results show that NESL&apos;s performance is competitive with that of machine-specific code for regular dense data, and is often superior for irregular data

K+ Channels at the Axon Initial Segment Dampen Near-Threshold Excitability of Neocortical Fast-Spiking GABAergic Interneurons

Fast-spiking cells (FS cells) are a prominent subtype of neocortical GABAergic interneurons with important functional roles. Multiple FS cell properties are coordinated for rapid response. Here, we describe an FS cell feature that serves to gate the powerful inhibition produced by FS cell activity. We show that FS cells in layer 2/3 barrel cortex possess a dampening mechanism mediated by Kv1.1-containing potassium channels localized to the axon initial segment. These channels powerfully regulate action potential threshold and allow FS cells to respond preferentially to large inputs that are fast enough to outrun Kv1 activation. In addition, Kv1.1 channel blockade converts the delay-type discharge pattern of FS cells to one of continuous fast spiking without influencing the high-frequency firing that defines FS cells. Thus, Kv1 channels provide a key counterbalance to the established rapid-response characteristics of FS cells, regulating excitability through a unique combination of electrophysiological properties and discrete subcellular localization

K+ Channels at the Axon Initial Segment Dampen Near-Threshold Excitability of Neocortical Fast-Spiking GABAergic Interneurons

Fast-spiking cells (FS cells) are a prominent subtype of neocortical GABAergic interneurons with important functional roles. Multiple FS cell properties are coordinated for rapid response. Here, we describe an FS cell feature that serves to gate the powerful inhibition produced by FS cell activity. We show that FS cells in layer 2/3 barrel cortex possess a dampening mechanism mediated by Kv1.1-containing potassium channels localized to the axon initial segment. These channels powerfully regulate action potential threshold and allow FS cells to respond preferentially to large inputs that are fast enough to outrun Kv1 activation. In addition, Kv1.1 channel blockade converts the delay-type discharge pattern of FS cells to one of continuous fast spiking without influencing the high-frequency firing that defines FS cells. Thus, Kv1 channels provide a key counterbalance to the established rapid-response characteristics of FS cells, regulating excitability through a unique combination of electrophysiological properties and discrete subcellular localization