Glutamate transporter currents in Bergmann glial cells follow the time course of extrasynaptic glutamate

Glutamate transporters in the central nervous system are expressed in both neurons and glia, they mediate high affinity, electrogenic uptake of glutamate, and they are associated with an anion conductance that is stoichiometrically uncoupled from glutamate flux. Although a complete cycle of transport may require 50–100 ms, previous studies suggest that transporters can alter synaptic currents on a much faster time scale. We find that application of l-glutamate to outside-out patches from cerebellar Bergmann glia activates anion-potentiated glutamate transporter currents that activate in <1 ms, suggesting an efficient mechanism for the capture of extrasynaptic glutamate. Stimulation in the granule cell layer in cerebellar slices elicits all or none α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptor and glutamate transporter currents in Bergmann glia that have a rapid onset, suggesting that glutamate released from climbing fiber terminals escapes synaptic clefts and reaches glial membranes shortly after release. Comparison of the concentration dependence of both α-amino-3-hydroxy-5-methyl-4-isoxazolepropionate receptor and glutamate transporter kinetics in patches with the time course of climbing fiber-evoked responses indicates that the glutamate transient at Bergmann glial membranes reaches a lower concentration than attained in the synaptic cleft and remains elevated in the extrasynaptic space for many milliseconds.

Two-dimensional infrared spectroscopy of peptides by phase-controlled femtosecond vibrational photon echoes

Two-dimensional infrared spectra of peptides are introduced that are the direct analogues of two- and three-pulse multiple quantum NMR. Phase matching and heterodyning are used to isolate the phase and amplitudes of the electric fields of vibrational photon echoes as a function of multiple pulse delays. Structural information is made available on the time scale of a few picoseconds. Line narrowed spectra of acyl-proline-NH2 and cross peaks implying the coupling between its amide-I modes are obtained, as are the phases of the various contributions to the signals. Solvent-sensitive structural differences are seen for the dipeptide. The methods show great promise to measure structure changes in biology on a wide range of time scales.

Dynamical principles in biological processes: A model of charge migration in proteins and DNA

The generalized master equations (GMEs) that contain multiple time scales have been derived quantum mechanically. The GME method has then been applied to a model of charge migration in proteins that invokes the hole hopping between local amino acid sites driven by the torsional motions of the floppy backbones. This model is then applied to analyze the experimental results for sequence-dependent long-range hole transport in DNA reported by Meggers et al. [Meggers, E., Michel-Beyerle, M. E., & Giese, B. (1998) J. Am. Chem. Soc. 120, 12950–12955]. The model has also been applied to analyze the experimental results of femtosecond dynamics of DNA-mediated electron transfer reported by Zewail and co-workers [Wan, C., Fiebig, T., Kelley, S. O., Treadway, C. R., Barton, J. K. & Zewail, A. H. (1999) Proc. Natl. Acad. Sci. USA 96, 6014–6019]. The initial events in the dynamics of protein folding have begun to attract attention. The GME obtained in this paper will be applicable to this problem.

Real-time quantitative measurement of autocrine ligand binding indicates that autocrine loops are spatially localized

Autocrine ligands are important regulators of many normal tissues and have been implicated in a number of disease states, including cancer. However, because by definition autocrine ligands are synthesized, secreted, and bound to cell receptors within an intrinsically self-contained “loop,” standard pharmacological approaches cannot be used to investigate relationships between ligand/receptor binding and consequent cellular responses. We demonstrate here a new approach for measurement of autocrine ligand binding to cells, using a microphysiometer assay originally developed for investigating cell responses to exogenous ligands. This technique permits quantitative measurements of autocrine responses on the time scale of receptor binding and internalization, thus allowing investigation of the role of receptor trafficking and dynamics in cellular responses. We used this technique to investigate autocrine signaling through the epidermal growth factor receptor by transforming growth factor alpha (TGFα) and found that anti-receptor antibodies are far more effective than anti-ligand antibodies in inhibiting autocrine signaling. This result indicates that autocrine-based signals can operate in a spatially restricted, local manner and thus provide cells with information on their local microenvironment.

A joint hazard and time scaling model to compare survival curves.

To provide a more general method for comparing survival experience, we propose a model that independently scales both hazard and time dimensions. To test the curve shape similarity of two time-dependent hazards, h1(t) and h2(t), we apply the proposed hazard relationship, h12(tKt)/ h1(t) = Kh, to h1. This relationship doubly scales h1 by the constant hazard and time scale factors, Kh and Kt, producing a transformed hazard, h12, with the same underlying curve shape as h1. We optimize the match of h12 to h2 by adjusting Kh and Kt. The corresponding survival relationship S12(tKt) = [S1(t)]KtKh transforms S1 into a new curve S12 of the same underlying shape that can be matched to the original S2. We apply this model to the curves for regional and local breast cancer contained in the National Cancer Institute's End Results Registry (1950-1973). Scaling the original regional curves, h1 and S1 with Kt = 1.769 and Kh = 0.263 produces transformed curves h12 and S12 that display congruence with the respective local curves, h2 and S2. This similarity of curve shapes suggests the application of the more complete curve shapes for regional disease as templates to predict the long-term survival pattern for local disease. By extension, this similarity raises the possibility of scaling early data for clinical trial curves according to templates of registry or previous trial curves, projecting long-term outcomes and reducing costs. The proposed model includes as special cases the widely used proportional hazards (Kt = 1) and accelerated life (KtKh = 1) models.

Reconfigurable computing for Monte Carlo simulations: results and prospects of the Janus project

We describe Janus, a massively parallel FPGA-based computer optimized for the simulation of spin glasses, theoretical models for the behavior of glassy materials. FPGAs (as compared to GPUs or many-core processors) provide a complementary approach to massively parallel computing. In particular, our model problem is formulated in terms of binary variables, and floating-point operations can be (almost) completely avoided. The FPGA architecture allows us to run many independent threads with almost no latencies in memory access, thus updating up to 1024 spins per cycle. We describe Janus in detail and we summarize the physics results obtained in four years of operation of this machine; we discuss two types of physics applications: long simulations on very large systems (which try to mimic and provide understanding about the experimental non equilibrium dynamics), and low-temperature equilibrium simulations using an artificial parallel tempering dynamics. The time scale of our non-equilibrium simulations spans eleven orders of magnitude (from picoseconds to a tenth of a second). On the other hand, our equilibrium simulations are unprecedented both because of the low temperatures reached and for the large systems that we have brought to equilibrium. A finite-time scaling ansatz emerges from the detailed comparison of the two sets of simulations. Janus has made it possible to perform spin glass simulations that would take several decades on more conventional architectures. The paper ends with an assessment of the potential of possible future versions of the Janus architecture, based on state-of-the-art technology.

Neogene radiolarian datum levels in the equatorial Indian and Pacific Oceans

Fifty radiolarian events of early Pleistocene and Neogene age were identified in an E-W transect of equatorial DSDP sites, extending from the Gulf of Panama to the western Pacific and eastern Indian Oceans. Our objective was to document the degree of synchroneity or time-transgressiveness of stratigraphically-useful datum levels from this geologic time interval. We restricted our study to low latitudes within which morphological variations of individual taxa are minimal, the total assemblage diversity remains high, and stratigraphic continuity is well-documented by an independent set of criteria. Each of the five sites chosen (503, 573, 289/586, 214) was calibrated to an "absolute" time scale, using a multiple of planktonic foraminiferal, nannofossil, and diatom datum levels which have been independently correlated to the paleomagnetic polarity time scale in piston core material. With these correlations we have assigned "absolute" ages to each radiolarian event, with a precision of 0.1-0.2 m.y. and an accuracy of 0.2-0.4 m.y. On this basis we have classified each of the events as either: (a) synchronous (range of ages <0.4 m.y.); (b) time-transgressive (i.e., range of ages >1.0 m.y.); and (c) not resolvable (range of ages 0.4-1.0 m.y.). Our results show that, among the synchronous datum levels, a large majority (15 out of 19) are last occurrences. Among those events which are clearly time-transgressive, most are first appearances (10 out of 13). In many instances taxa appear to evolve first in the Indian Ocean, and subsequently in the western and eastern Pacific Ocean. This pattern is particularly unexpected in view of the strong east-to-west zonal flow in equatorial latitudes. Three of the time-transgressive events have been used to define zonal boundaries: the first appearances of Spongaster pentas, Diartus hughesi, and D. petterssoni. Our results suggest that biostratigraphic non-synchroneity may be substantial (i.e., greater than 1 m.y.) within a given latitudinal zone; one would expect this effect to be even more pronounced across oceanographic and climatic gradients. We anticipate that the extent of diachroneity may be comparable for diatom, foraminiferal, and nannofossil datum levels as well. If this proves true, global "time scales" may need to be re-formulated on the basis of a smaller number of demonstrably synchronous events.

Stable carbon isotope record and geochemistry of late Miocene-early Pliocene sediments from DSDP Site 90-590 in the Tasman Sea

Biogenic components of sediment accumulated at high rates beneath frontal zones of the Indian and Pacific oceans during the late Miocene and early Pliocene. The delta13C of bulk and foraminiferal carbonate also decreased during this time interval. Although the two observations may be causally linked, and signify a major perturbation in global biogeochemical cycling, no site beneath a frontal zone has independent records of export production and delta13C on multiple carbonate phases across the critical interval of interest. Deep Sea Drilling Project (DSDP) site 590 lies beneath the Tasman Front (TF), an eddy-generating jetstream in the southwest Pacific Ocean. To complement previous delta13C records of planktic and benthic foraminifera at this location, late Neogene records of CaCO3 mass accumulation rate (MAR), Ca/Ti, Ba/Ti, Al/Ti, and of bulk carbonate and foraminiferal delta13C were constructed at site 590. The delta13C records include bulk sediment, bulk sediment fractions (<63 µm and 5-25 µm), and the planktic foraminifera Globigerina bulloides, Globigerinoides sacculifer (with and without sac), and Orbulina universa. Using current time scales, CaCO3 MARs, Ca/Ti, Al/Ti and Ba/Ti ratios are two to three times higher in upper Miocene and lower Pliocene sediment relative to overlying and underlying units. A significant decrease also occurs in all delta13C records. All evidence indicates that enhanced export production - the 'biogenic bloom' - extended to the southwest Pacific Ocean between ca. 9 and 3.8 Ma, and this phenomenon is coupled with changes in delta13C - the 'Chron C3AR carbon shift'. However, CaCO3 MARs peak ca. 5 Ma whereas elemental ratios are highest ca. 6.5 Ma; foraminiferal delta13C starts to decrease ca. 8 Ma whereas bulk carbonate delta13C begins to drop ca. 5.6 Ma. Temporal discrepancies between the records can be explained by changes in the upwelling regime at the TF, perhaps signifying a link between changes in ocean-atmosphere circulation change and widespread primary productivity.

The problem of space in Jewish mediaeval philosophy,

Mode of access: Internet.

Dynamic, convex, and robust optimization with Bayesian learning for response-guided dosing

Thesis (Ph.D.)--University of Washington, 2016-08

Cognitive fit between conceptual schemas and internal problem representations: The case of geospatio-temporal conceptual schema comprehension

Geospatio-temporal conceptual models provide a mechanism to explicitly represent geospatial and temporal aspects of applications. Such models, which focus on both what and when/where, need to be more expressive than conventional conceptual models (e.g., the ER model), which primarily focus on what is important for a given application. In this study, we view conceptual schema comprehension of geospatio-temporal data semantics in terms of matching the external problem representation (that is, the conceptual schema) to the problem-solving task (that is, syntactic and semantic comprehension tasks), an argument based on the theory of cognitive fit. Our theory suggests that an external problem representation that matches the problem solver's internal task representation will enhance performance, for example, in comprehending such schemas. To assess performance on geospatio-temporal schema comprehension tasks, we conducted a laboratory experiment using two semantically identical conceptual schemas, one of which mapped closely to the internal task representation while the other did not. As expected, we found that the geospatio-temporal conceptual schema that corresponded to the internal representation of the task enhanced the accuracy of schema comprehension; comprehension time was equivalent for both. Cognitive fit between the internal representation of the task and conceptual schemas with geospatio-temporal annotations was, therefore, manifested in accuracy of schema comprehension and not in time for problem solution. Our findings suggest that the annotated schemas facilitate understanding of data semantics represented on the schema.

Real-time control of a Tokamak plasma using neural networks

This paper presents results from the first use of neural networks for the real-time feedback control of high temperature plasmas in a Tokamak fusion experiment. The Tokamak is currently the principal experimental device for research into the magnetic confinement approach to controlled fusion. In the Tokamak, hydrogen plasmas, at temperatures of up to 100 Million K, are confined by strong magnetic fields. Accurate control of the position and shape of the plasma boundary requires real-time feedback control of the magnetic field structure on a time-scale of a few tens of microseconds. Software simulations have demonstrated that a neural network approach can give significantly better performance than the linear technique currently used on most Tokamak experiments. The practical application of the neural network approach requires high-speed hardware, for which a fully parallel implementation of the multi-layer perceptron, using a hybrid of digital and analogue technology, has been developed.

Complex temporal patterns in molecular dynamics:a direct measure of the phase-space exploration by the trajectory at macroscopic time scales

Computer simulated trajectories of bulk water molecules form complex spatiotemporal structures at the picosecond time scale. This intrinsic complexity, which underlies the formation of molecular structures at longer time scales, has been quantified using a measure of statistical complexity. The method estimates the information contained in the molecular trajectory by detecting and quantifying temporal patterns present in the simulated data (velocity time series). Two types of temporal patterns are found. The first, defined by the short-time correlations corresponding to the velocity autocorrelation decay times (â‰0.1â€ps), remains asymptotically stable for time intervals longer than several tens of nanoseconds. The second is caused by previously unknown longer-time correlations (found at longer than the nanoseconds time scales) leading to a value of statistical complexity that slowly increases with time. A direct measure based on the notion of statistical complexity that describes how the trajectory explores the phase space and independent from the particular molecular signal used as the observed time series is introduced. © 2008 The American Physical Society.

Stock selection with full-scale optimization and differential evolution

When composing stock portfolios, managers frequently choose among hundreds of stocks. The stocks' risk properties are analyzed with statistical tools, and managers try to combine these to meet the investors' risk profiles. A recently developed tool for performing such optimization is called full-scale optimization (FSO). This methodology is very flexible for investor preferences, but because of computational limitations it has until now been infeasible to use when many stocks are considered. We apply the artificial intelligence technique of differential evolution to solve FSO-type stock selection problems of 97 assets. Differential evolution finds the optimal solutions by self-learning from randomly drawn candidate solutions. We show that this search technique makes large scale problem computationally feasible and that the solutions retrieved are stable. The study also gives further merit to the FSO technique, as it shows that the solutions suit investor risk profiles better than portfolios retrieved from traditional methods.

Contact time periods in immunological synapse

This paper resolves the long standing debate as to the proper time scale τ of the onset of the immunological synapse bond, the noncovalent chemical bond defining the immune pathways involving T cells and antigen presenting cells. Results from our model calculations show τ to be of the order of seconds instead of minutes. Close to the linearly stable regime, we show that in between the two critical spatial thresholds defined by the integrin:ligand pair (Δ2∼ 40-45 nm) and the T-cell receptor TCR:peptide-major-histocompatibility-complex pMHC bond (Δ1∼ 14-15 nm), τ grows monotonically with increasing coreceptor bond length separation δ (= Δ2-Δ1∼ 26-30 nm) while τ decays with Δ1 for fixed Δ2. The nonuniversal δ-dependent power-law structure of the probability density function further explains why only the TCR:pMHC bond is a likely candidate to form a stable synapse.