Dynamic L-type CaV1.2 channel trafficking facilitates CaV1.2 clustering and cooperative gating

L-type Ca_V1.2 channels are key regulators of gene expression, cell excitability and muscle contraction. Ca_V1.2 channels organize in clusters throughout the plasma membrane. This channel organization has been suggested to contribute to the concerted activation of adjacent Ca_V1.2 channels (e.g. cooperative gating). Here, we tested the hypothesis that dynamic intracellular and perimembrane trafficking of Ca_V1.2 channels is critical for formation and dissolution of functional channel clusters mediating cooperative gating. We found that Ca_V1.2 moves in vesicular structures of circular and tubular shape with diverse intracellular and submembrane trafficking patterns. Both microtubules and actin filaments are required for dynamic movement of Ca_V1.2 vesicles. These vesicles undergo constitutive homotypic fusion and fission events that sustain Ca_V1.2 clustering, channel activity and cooperative gating. Our study suggests that Ca_V1.2 clusters and activity can be modulated by diverse and unique intracellular and perimembrane vesicular dynamics to fine-tune Ca²⁺ signals.     

Determination of propiomazine in rat plasma by direct injection on coupled liquid chromatography columns with electrochemical detection

This method describes the determination of propiomazine by direct injection of rat plasma into a chromatography system based on coupled reversed-phase columns. An extraction column, packed with porous silica particles with covalent-bound ₁-acid glycoprotein (AGP), was used to separate the plasma proteins from the analyte. After isolation the analyte was transferred to the analytical column for separation and detection. Propiomazine was detected by an electrochemical detector and the limit of quantification was 2.0 ng/ml (100 pg injected). The absolute recovery was 80.9±2.4% at 9.0 ng/ml level. The inter-day and intra-day precision was 10.9% (5.6 ng/ml) and 2.8% (9.0 ng/ml), respectively.     

Potassium Translocation into the Root Xylem

Abstract: Potassium is the most abundant cation in cells of higher plants and plays vital roles in plant growth and develop ment. Since the soil is the only source of potassium, plant roots are well adapted to exploit the soil for potassium and supply it to the leaves. Transport across the root can be divided into three stages: uptake into the root symplast, transport across the symplast and release into the xylem. Uptake kinetics of potassium have been studied extensively in the past and sug gested the presence of high and low affinity systems. Molecular and electrophysiological techniques have now confirmed the existence of discrete transporters encoded by a number of genes. Surprisingly, detailed characterisation of the transpor ters using reverse genetics and heterologous expression shows that a number of the transporters (AKT and AtKUP family) func tion both in the low (μM) and high (mM) K⁺ range. Electrophy siological studies indicate that K⁺ uptake by roots is coupled to H⁺, to drive uptake from micromolar K⁺. However, thus far only Na⁺ coupled K⁺ transport has been demonstrated (HKT1). Ion channels play a major role in the exchange of potassium be tween the symplast and the xylem. An outward rectifying chan nel (KORC) mediates potassium release. Cloning of the gene en coding this channel (SKOR) shows that it belongs to the Shaker super-family. Both electrophysiological and genetic studies demonstrate that K⁺ release through this channel is controlled by the stress hormone abscisic acid. Interestingly, xylem par enchyma cells of young barley roots also contain a number of in ward rectifying K⁺ channels that are controlled by G-proteins. The involvement of G-proteins emphasises once more that po tassium transport at the symplast/xylem boundary is under hor monal control. The role of the electrical potential difference across the symplastxylem boundary in controlling potassium release is discussed.     

Enhancement of the isolation selectivity of isoflavonoid puerarin using oligo-β-cyclodextrin coupled polystyrene-based media

The isolation selectivity of the isoflavonoid puerarin, a well-known traditional Chinese medicine, was studied when native and oligo-β-cyclodextrin (CDP) coupled polystyrene-based macroporous resins were used as adsorbents by static tests. The research results indicated that the CDP coupled resin HPD-100-CDP offered the best adsorption and desorption capacity for puerarin than others and its equilibrium adsorption data at 25 °C fit best to the Freundlich isotherm. The performance of separation of puerarin on HPD-100-CDP column in one step was evaluated. Based on the above experimental data, a novel medium PS-CDP was synthesized and its chromatographic retention behaviors were also explored. ESI-MS/MS, ¹H NMR spectroscopy and UV absorption spectrum were used for the detection and characterization of puerarin in isolated fraction. Under the optimum mobile phase, methanol/acetic acid/water = 5.0/6.6/88.4 (v/v/v), the purity and recovery of puerarin were 95.3% and 86.7%, respectively, by HPLC analysis. In conclusion, the PS-CDP medium can enhance the isolated selectivity of puerarin and it can be applied in preparative scale operations.     

Synchrony of spatial populations induced by colored environmental noise and dispersal

Spatial synchrony of oscillating populations has been observed in many ecological systems, and its influences and causes have attracted the interest of ecologists. Spatially correlated environmental noises, dispersal, and trophic interactions have been considered as the causes of spatial synchrony. In this study, we develop a spatially structured population model, which is described by coupled-map lattices and incorporates both dispersal and colored environmental noise. A method for generating time series with desired spatial correlation and color is introduced. Then, we use these generated time series to analyze the influence of noise color on synchrony in population dynamics. The noise color refers to the temporal correlation in the time series data of the noise, and is expressed as the degree of (first-order) autocorrelation for autoregressive noise. Patterns of spatial synchrony are considered for stable, periodic and chaotic population dynamics. Numerical simulations verify that environmental noise color has a major influence on the level of synchrony, which depends strongly on how noise is introduced into the model. Furthermore, the influence of noise color also depends on patterns of dispersal between local populations. In addition, the desynchronizing effect of reddened noise is always weaker than that of white noise. From our results, we notice that the role of reddened environmental noise on spatial synchrony should be treated carefully and cautiously, especially for the spatially structured populations linked by dispersal.     

Mammalian diacylglycerol kinases: Molecular interactions and biological functions of selected isoforms

The mammalian diacylglycerol kinases (DGK) are a group of enzymes having important roles in regulating many biological processes. Both the product and the substrate of these enzymes, i.e. diacylglycerol and phosphatidic acid, are important lipid signalling molecules. Each DGK isoform appears to have a distinct biological function as a consequence of its location in the cell and/or the proteins with which it associates. This review discusses three of the more extensively studied forms of this enzyme, DGKα, DGK?, and DGKζ. DGKα has an important role in immune function and its activity is modulated by several mechanisms. DGK? has several unique features among which is its specificity for arachionoyl-containing substrates, suggesting its importance in phosphatidylinositol cycling. DGKζ is expressed in many tissues and also has several mechanisms to regulate its functions. It is localized in several subcellular organelles, including the nucleus. The current state of our understanding of the properties and functions of these proteins is reviewed.     

An extended biphasic model for charged hydrated tissues with application to the intervertebral disc

Finite element models for hydrated soft biological tissue are numerous but often exhibit certain essential deficiencies concerning the reproduction of relevant mechanical and electro-chemical responses. As a matter of fact, singlephasic models can never predict the interstitial fluid flow or related effects like osmosis. Quite a few models have more than one constituent, but are often restricted to the small-strain domain, are not capable of capturing the intrinsic viscoelasticity of the solid skeleton, or do not account for a collagen fibre reinforcement. It is the goal of this contribution to overcome these drawbacks and to present a thermodynamically consistent model, which is formulated in a very general way in order to reproduce the behaviour of almost any charged hydrated tissue. Herein, the Theory of Porous Media (TPM) is applied in combination with polyconvex Ogden-type material laws describing the anisotropic and intrinsically viscoelastic behaviour of the solid matrix on the basis of a generalised Maxwell model. Moreover, other features like the deformation-dependent permeability, the possibility to include inhomogeneities like varying fibre alignment and behaviour, or osmotic effects based on the simplifying assumption of Lanir are also included. Finally, the human intervertebral disc is chosen as a representative for complex soft biological tissue behaviour. In this regard, two numerical examples will be presented with focus on the viscoelastic and osmotic capacity of the model.     

Structure-revealing data fusion

Background

Analysis of data from multiple sources has the potential to enhance knowledge discovery by capturing underlying structures, which are, otherwise, difficult to extract. Fusing data from multiple sources has already proved useful in many applications in social network analysis, signal processing and bioinformatics. However, data fusion is challenging since data from multiple sources are often (i) heterogeneous (i.e., in the form of higher-order tensors and matrices), (ii) incomplete, and (iii) have both shared and unshared components. In order to address these challenges, in this paper, we introduce a novel unsupervised data fusion model based on joint factorization of matrices and higher-order tensors.

Results

While the traditional formulation of coupled matrix and tensor factorizations modeling only shared factors fails to capture the underlying structures in the presence of both shared and unshared factors, the proposed data fusion model has the potential to automatically reveal shared and unshared components through modeling constraints. Using numerical experiments, we demonstrate the effectiveness of the proposed approach in terms of identifying shared and unshared components. Furthermore, we measure a set of mixtures with known chemical composition using both LC-MS (Liquid Chromatography - Mass Spectrometry) and NMR (Nuclear Magnetic Resonance) and demonstrate that the structure-revealing data fusion model can (i) successfully capture the chemicals in the mixtures and extract the relative concentrations of the chemicals accurately, (ii) provide promising results in terms of identifying shared and unshared chemicals, and (iii) reveal the relevant patterns in LC-MS by coupling with the diffusion NMR data.

Conclusions

We have proposed a structure-revealing data fusion model that can jointly analyze heterogeneous, incomplete data sets with shared and unshared components and demonstrated its promising performance as well as potential limitations on both simulated and real data.

Electronic supplementary material

The online version of this article (doi:10.1186/1471-2105-15-239) contains supplementary material, which is available to authorized users.     

Local and global pyrogeographic evidence that indigenous fire management creates pyrodiversity

Despite the challenges wildland fire poses to contemporary resource management, many fire‐prone ecosystems have adapted over centuries to millennia to intentional landscape burning by people to maintain resources. We combine fieldwork, modeling, and a literature survey to examine the extent and mechanism by which anthropogenic burning alters the spatial grain of habitat mosaics in fire‐prone ecosystems. We survey the distribution of Callitris intratropica, a conifer requiring long fire‐free intervals for establishment, as an indicator of long‐unburned habitat availability under Aboriginal burning in the savannas of Arnhem Land. We then use cellular automata to simulate the effects of burning identical proportions of the landscape under different fire sizes on the emergent patterns of habitat heterogeneity. Finally, we examine the global extent of intentional burning and diversity of objectives using the scientific literature. The current distribution of Callitris across multiple field sites suggested long‐unburnt patches are common and occur at fine scales (<0.5 ha), while modeling revealed smaller, patchy disturbances maximize patch age diversity, creating a favorable habitat matrix for Callitris. The literature search provided evidence for intentional landscape burning across multiple ecosystems on six continents, with the number of identified objectives ranging from two to thirteen per study. The fieldwork and modeling results imply that the occurrence of long‐unburnt habitat in fire‐prone ecosystems may be an emergent property of patch scaling under fire regimes dominated by smaller fires. These findings provide a model for understanding how anthropogenic burning alters spatial and temporal aspects of habitat heterogeneity, which, as the literature survey strongly suggests, warrant consideration across a diversity of geographies and cultures. Our results clarify how traditional fire management shapes fire‐prone ecosystems, which despite diverse objectives, has allowed human societies to cope with fire as a recurrent disturbance.     

一类混合时滞的非线性耦合神经网络的同步

主要讨论了一类混合时滞的非线性耦合神经网络的同步问题.同时,考虑随机扰动以及参数的切换由某个马尔可夫链所确定等方面对其的影响.文中通过构造新的Lyapunov-Krasovskii泛函,运用线性矩阵不等式（LMI）技术并结合Kronecker积来获得神经网络全局同步的充分性判据.由于这样得到的判据是LMI形式,因此可以由数学软件Matlab的LMI Toolbox对所获得的判据进行有效的验证和求解.此外,本文中我们对细胞激活函数做了更为一般的假设,从而使结论在LMI下可以减少保守性.