2,371 research outputs found

    A novel delta current method for transport stoichiometry estimation.

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    BackgroundThe ion transport stoichiometry (q) of electrogenic transporters is an important determinant of their function. q can be determined by the reversal potential (Erev) if the transporter under study is the only electrogenic transport mechanism or a specific inhibitor is available. An alternative approach is to calculate delta reversal potential (ΔErev) by altering the concentrations of the transported substrates. This approach is based on the hypothesis that the contributions of other channels and transporters on the membrane to Erev are additive. However, Erev is a complicated function of the sum of different conductances rather than being additive.ResultsWe propose a new delta current (ΔI) method based on a simplified model for electrogenic secondary active transport by Heinz (Electrical Potentials in Biological Membrane Transport, 1981). ΔI is the difference between two currents obtained from altering the external concentration of a transported substrate thereby eliminating other currents without the need for a specific inhibitor. q is determined by the ratio of ΔI at two different membrane voltages (V1 and V2) where q = 2RT/(F(V2 -V1))ln(ΔI2/ΔI1) + 1. We tested this ΔI methodology in HEK-293 cells expressing the elctrogenic SLC4 sodium bicarbonate cotransporters NBCe2-C and NBCe1-A, the results were consistent with those obtained with the Erev inhibitor method. Furthermore, using computational simulations, we compared the estimates of q with the ΔErev and ΔI methods. The results showed that the ΔErev method introduces significant error when other channels or electrogenic transporters are present on the membrane and that the ΔI equation accurately calculates the stoichiometric ratio.ConclusionsWe developed a ΔI method for estimating transport stoichiometry of electrogenic transporters based on the Heinz model. This model reduces to the conventional reversal potential method when the transporter under study is the only electrogenic transport process in the membrane. When there are other electrogenic transport pathways, ΔI method eliminates their contribution in estimating q. Computational simulations demonstrated that the ΔErev method introduces significant error when other channels or electrogenic transporters are present and that the ΔI equation accurately calculates the stoichiometric ratio. This new ΔI method can be readily extended to the analysis of other electrogenic transporters in other tissues

    Synaptic GABA release prevents GABA transporter type-1 reversal during excessive network activity.

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    GABA transporters control extracellular GABA, which regulates the key aspects of neuronal and network behaviour. A prevailing view is that modest neuronal depolarization results in GABA transporter type-1 (GAT-1) reversal causing non-vesicular GABA release into the extracellular space during intense network activity. This has important implications for GABA uptake-targeting therapies. Here we combined a realistic kinetic model of GAT-1 with experimental measurements of tonic GABAA receptor currents in ex vivo hippocampal slices to examine GAT-1 operation under varying network conditions. Our simulations predict that synaptic GABA release during network activity robustly prevents GAT-1 reversal. We test this in the 0 Mg(2+) model of epileptiform discharges using slices from healthy and chronically epileptic rats and find that epileptiform activity is associated with increased synaptic GABA release and is not accompanied by GAT-1 reversal. We conclude that sustained efflux of GABA through GAT-1 is unlikely to occur during physiological or pathological network activity

    A Proposal for a Three Detector Short-Baseline Neutrino Oscillation Program in the Fermilab Booster Neutrino Beam

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    A Short-Baseline Neutrino (SBN) physics program of three LAr-TPC detectors located along the Booster Neutrino Beam (BNB) at Fermilab is presented. This new SBN Program will deliver a rich and compelling physics opportunity, including the ability to resolve a class of experimental anomalies in neutrino physics and to perform the most sensitive search to date for sterile neutrinos at the eV mass-scale through both appearance and disappearance oscillation channels. Using data sets of 6.6e20 protons on target (P.O.T.) in the LAr1-ND and ICARUS T600 detectors plus 13.2e20 P.O.T. in the MicroBooNE detector, we estimate that a search for muon neutrino to electron neutrino appearance can be performed with ~5 sigma sensitivity for the LSND allowed (99% C.L.) parameter region. In this proposal for the SBN Program, we describe the physics analysis, the conceptual design of the LAr1-ND detector, the design and refurbishment of the T600 detector, the necessary infrastructure required to execute the program, and a possible reconfiguration of the BNB target and horn system to improve its performance for oscillation searches.Comment: 209 pages, 129 figure

    Computational fluid dynamic simulations of maternal circulation : wall shear stress in the human placenta and its biological implications

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    Introduction In the human placenta the maternal blood circulates in the intervillous space (IVS). The syncytiotrophoblast (STB) is in direct contact with maternal blood. The wall shear stress (WSS) exerted by the maternal blood flow on the STB has not been evaluated. Our objective was to determine the physiological WSS exerted on the surface of the STB during the third trimester of pregnancy. Material and Methods To gain insight into the shear stress levels that the STB is expected to experience in vivo, we have formulated three different computational models of varying levels of complexity that reflect different physical representations of the IVS. Computations of the flow fields in all models were performed using the CFD module of the finite element code COMSOL Multi-physics 4.4. The mean velocity of maternal blood in the IVS during the third trimester was measured in vivo with dynamic MRI (0.94 +/- 0.14 mm.s(-1)). To investigate if the in silico results are consistent with physiological observations, we studied the cytoadhesion of human parasitized (Plasmodium falciparum) erythrocytes to primary human STB cultures, in flow conditions with different WSS values. Results The WSS applied to the STB is highly heterogeneous in the IVS. The estimated average values are relatively low (0.5 +/- 0.2 to 2.3 +/- 1.1 dyn.cm(-2)). The increase of WSS from 0.15 to 5 dyn.cm(-2) was associated with a significant decrease of infected erythrocyte cytoadhesion. No cytoadhesion of infected erythrocytes was observed above 5 dyn.cm(-2) applied for one hour. Conclusion Our study provides for the first time a WSS estimation in the maternal placental circulation. In spite of high maternal blood flow rates, the average WSS applied at the surface of the chorionic villi is low (<5 dyn.cm(-2)). These results provide the basis for future physiologicallyrelevant in vitro studies of the biological effects of WSS on the STB

    Information recovery in the biological sciences : protein structure determination by constraint satisfaction, simulation and automated image processing

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    Regardless of the field of study or particular problem, any experimental science always poses the same question: ÒWhat object or phenomena generated the data that we see, given what is known?Ó In the field of 2D electron crystallography, data is collected from a series of two-dimensional images, formed either as a result of diffraction mode imaging or TEM mode real imaging. The resulting dataset is acquired strictly in the Fourier domain as either coupled Amplitudes and Phases (as in TEM mode) or Amplitudes alone (in diffraction mode). In either case, data is received from the microscope in a series of CCD or scanned negatives of images which generally require a significant amount of pre-processing in order to be useful. Traditionally, processing of the large volume of data collected from the microscope was the time limiting factor in protein structure determination by electron microscopy. Data must be initially collected from the microscope either on film-negatives, which in turn must be developed and scanned, or from CCDs of sizes typically no larger than 2096x2096 (though larger models are in operation). In either case, data are finally ready for processing as 8-bit, 16-bit or (in principle) 32-bit grey-scale images. Regardless of data source, the foundation of all crystallographic methods is the presence of a regular Fourier lattice. Two dimensional cryo-electron microscopy of proteins introduces special challenges as multiple crystals may be present in the same image, producing in some cases several independent lattices. Additionally, scanned negatives typically have a rectangular region marking the film number and other details of image acquisition that must be removed prior to processing. If the edges of the images are not down-tapered, vertical and horizontal ÒstreaksÓ will be present in the Fourier transform of the image --arising from the high-resolution discontinuities between the opposite edges of the image. These streaks can overlap with lattice points which fall close to the vertical and horizontal axes and disrupt both the information they contain and the ability to detect them. Lastly, SpotScanning (Downing, 1991) is a commonly used process where-by circular discs are individually scanned in an image. The large-scale regularity of the scanning patter produces a low frequency lattice which can interfere and overlap with any protein crystal lattices. We introduce a series of methods packaged into 2dx (Gipson, et al., 2007) which simultaneously addresses these problems, automatically detecting accurate crystal lattice parameters for a majority of images. Further a template is described for the automation of all subsequent image processing steps on the road to a fully processed dataset. The broader picture of image processing is one of reproducibility. The lattice parameters, for instance, are only one of hundreds of parameters which must be determined or provided and subsequently stored and accessed in a regular way during image processing. Numerous steps, from correct CTF and tilt-geometry determination to the final stages of symmetrization and optimal image recovery must be performed sequentially and repeatedly for hundreds of images. The goal in such a project is then to automatically process as significant a portion of the data as possible and to reduce unnecessary, repetitive data entry by the user. Here also, 2dx (Gipson, et al., 2007), the image processing package designed to automatically process individual 2D TEM images is introduced. This package focuses on reliability, ease of use and automation to produce finished results necessary for full three-dimensional reconstruction of the protein in question. Once individual 2D images have been processed, they contribute to a larger project-wide 3-dimensional dataset. Several challenges exist in processing this dataset, besides simply the organization of results and project-wide parameters. In particular, though tilt-geometry, relative amplitude scaling and absolute orientation are in principle known (or obtainable from an individual image) errors, uncertainties and heterogeneous data-types provide for a 3D-dataset with many parameters to be optimized. 2dx_merge (Gipson, et al., 2007) is the follow-up to the first release of 2dx which had originally processed only individual images. Based on the guiding principles of the earlier release, 2dx_merge focuses on ease of use and automation. The result is a fully qualified 3D structure determination package capable of turning hundreds of electron micrograph images, nearly completely automatically, into a full 3D structure. Most of the processing performed in the 2dx package is based on the excellent suite of programs termed collectively as the MRC package (Crowther, et al., 1996). Extensions to this suite and alternative algorithms continue to play an essential role in image processing as computers become faster and as advancements are made in the mathematics of signal processing. In this capacity, an alternative procedure to generate a 3D structure from processed 2D images is presented. This algorithm, entitled ÒProjective Constraint OptimizationÓ (PCO), leverages prior known information, such as symmetry and the fact that the protein is bound in a membrane, to extend the normal boundaries of resolution. In particular, traditional methods (Agard, 1983) make no attempt to account for the Òmissing coneÓ a vast, un-sampled, region in 3D Fourier space arising from specimen tilt limitations in the microscope. Provided sufficient data, PCO simultaneously refines the dataset, accounting for error, as well as attempting to fill this missing cone. Though PCO provides a near-optimal 3D reconstruction based on data, depending on initial data quality and amount of prior knowledge, there may be a host of solutions, and more importantly pseudo-solutions, which are more-or-less consistent with the provided dataset. Trying to find a global best-fit for known information and data can be a daunting challenge mathematically, to this end the use of meta-heuristics is addressed. Specifically, in the case of many pseudo-solutions, so long as a suitably defined error metric can be found, quasi-evolutionary swarm algorithms can be used that search solution space, sharing data as they go. Given sufficient computational power, such algorithms can dramatically reduce the search time for global optimums for a given dataset. Once the structure of a protein has been determined, many questions often remain about its function. Questions about the dynamics of a protein, for instance, are not often readily interpretable from structure alone. To this end an investigation into computationally optimized structural dynamics is described. Here, in order to find the most likely path a protein might take through Òconformation spaceÓ between two conformations, a graphics processing unit (GPU) optimized program and set of libraries is written to speed of the calculation of this process 30x. The tools and methods developed here serve as a conceptual template as to how GPU coding was applied to other aspects of the work presented here as well as GPU programming generally. The final portion of the thesis takes an apparent step in reverse, presenting a dramatic, yet highly predictive, simplification of a complex biological process. Kinetic Monte Carlo simulations idealize thousands of proteins as interacting agents by a set of simple rules (i.e. react/dissociate), offering highly-accurate insights into the large-scale cooperative behavior of proteins. This work demonstrates that, for many applications, structure, dynamics or even general knowledge of a protein may not be necessary for a meaningful biological story to emerge. Additionally, even in cases where structure and function is known, such simulations can help to answer the biological question in its entirety from structure, to dynamics, to ultimate function

    VIOLA - A multi-purpose and web-based visualization tool for neuronal-network simulation output

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    Neuronal network models and corresponding computer simulations are invaluable tools to aid the interpretation of the relationship between neuron properties, connectivity and measured activity in cortical tissue. Spatiotemporal patterns of activity propagating across the cortical surface as observed experimentally can for example be described by neuronal network models with layered geometry and distance-dependent connectivity. The interpretation of the resulting stream of multi-modal and multi-dimensional simulation data calls for integrating interactive visualization steps into existing simulation-analysis workflows. Here, we present a set of interactive visualization concepts called views for the visual analysis of activity data in topological network models, and a corresponding reference implementation VIOLA (VIsualization Of Layer Activity). The software is a lightweight, open-source, web-based and platform-independent application combining and adapting modern interactive visualization paradigms, such as coordinated multiple views, for massively parallel neurophysiological data. For a use-case demonstration we consider spiking activity data of a two-population, layered point-neuron network model subject to a spatially confined excitation originating from an external population. With the multiple coordinated views, an explorative and qualitative assessment of the spatiotemporal features of neuronal activity can be performed upfront of a detailed quantitative data analysis of specific aspects of the data. Furthermore, ongoing efforts including the European Human Brain Project aim at providing online user portals for integrated model development, simulation, analysis and provenance tracking, wherein interactive visual analysis tools are one component. Browser-compatible, web-technology based solutions are therefore required. Within this scope, with VIOLA we provide a first prototype.Comment: 38 pages, 10 figures, 3 table

    Somatosensory neurons integrate the geometry of skin deformation and mechanotransduction channels to shape touch sensing.

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    Touch sensation hinges on force transfer across the skin and activation of mechanosensitive ion channels along the somatosensory neurons that invade the skin. This skin-nerve sensory system demands a quantitative model that spans the application of mechanical loads to channel activation. Unlike prior models of the dynamic responses of touch receptor neurons in Caenorhabditis elegans (Eastwood et al., 2015), which substituted a single effective channel for the ensemble along the TRNs, this study integrates body mechanics and the spatial recruitment of the various channels. We demonstrate that this model captures mechanical properties of the worm's body and accurately reproduces neural responses to simple stimuli. It also captures responses to complex stimuli featuring non-trivial spatial patterns, like extended or multiple contacts that could not be addressed otherwise. We illustrate the importance of these effects with new experiments revealing that skin-neuron composites respond to pre-indentation with increased currents rather than adapting to persistent stimulation

    Asymmetric Interplay Between K+ and Blocker and Atomistic Parameters From Physiological Experiments Quantify K+ Channel Blocker Release

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    Modulating the activity of ion channels by blockers yields information on both the mode of drug action and on the biophysics of ion transport. Here we investigate the interplay between ions in the selectivity filter (SF) of K+ channels and the release kinetics of the blocker tetrapropylammonium in the model channel KcvNTS. A quantitative expression calculates blocker release rate constants directly from voltage-dependent ion occupation probabilities in the SF. The latter are obtained by a kinetic model of single-channel currents recorded in the absence of the blocker. The resulting model contains only two adjustable parameters of ion-blocker interaction and holds for both symmetric and asymmetric ionic conditions. This data-derived model is corroborated by 3D reference interaction site model (3D RISM) calculations on several model systems, which show that the K+ occupation probability is unaffected by the blocker, a direct consequence of the strength of the ion-carbonyl attraction in the SF, independent of the specific protein background. Hence, KcvNTS channel blocker release kinetics can be reduced to a small number of system-specific parameters. The pore-independent asymmetric interplay between K+ and blocker ions potentially allows for generalizing these results to similar potassium channels

    Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors

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    Patient-specific computational modeling of subendothelial LDL accumulation in a stenosed right coronary artery: effect of hemodynamic and biological factors. Am J Physiol Heart Circ Physiol 304: H1455-H1470, 2013. First published March 15, 2013; doi:10.1152/ajpheart.00539.2012.-Atherosclerosis is a systemic disease with local manifestations. Low-density lipoprotein (LDL) accumulation in the subendothelial layer is one of the hallmarks of atherosclerosis onset and ignites plaque development and progression. Blood flow-induced endothelial shear stress (ESS) is causally related to the heterogenic distribution of atherosclerotic lesions and critically affects LDL deposition in the vessel wall. In this work we modeled blood flow and LDL transport in the coronary arterial wall and investigated the influence of several hemodynamic and biological factors that may regulate LDL accumulation. We used a three-dimensional model of a stenosed right coronary artery reconstructed from angiographic and intravascular ultrasound patient data. We also reconstructed a second model after restoring the patency of the stenosed lumen to its nondiseased state to assess the effect of the stenosis on LDL accumulation

    A Rac switch regulates random versus directionally persistent cell migration

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    Directional migration moves cells rapidly between points, whereas random migration allows cells to explore their local environments. We describe a Rac1 mechanism for determining whether cell patterns of migration are intrinsically random or directionally persistent. Rac activity promoted the formation of peripheral lamellae that mediated random migration. Decreasing Rac activity suppressed peripheral lamellae and switched the cell migration patterns of fibroblasts and epithelial cells from random to directionally persistent. In three-dimensional rather than traditional two-dimensional cell culture, cells had a lower level of Rac activity that was associated with rapid, directional migration. In contrast to the directed migration of chemotaxis, this intrinsic directional persistence of migration was not mediated by phosphatidylinositol 3′-kinase lipid signaling. Total Rac1 activity can therefore provide a regulatory switch between patterns of cell migration by a mechanism distinct from chemotaxis
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