Coagulation Factor Xa Activates Thrombin and Signals Ischemic Neuronal Death Via Par-1 and JNK in Ischemic Neural Tissue

Background: The coagulation factor thrombin mediates ischemic neuronal deathand, at a low concentration, induces tolerance to ischemia.We investigated its modeof activation in ischemic neural tissue using an in vitro approach to distinguish therole of circulating coagulation factors from endogenous cerebral mechanisms. Wealso studied the signalling pathway downstream of thrombin in ischemia and afterthrombin preconditioning.Methods: Rat organotypic hippocampal slice cultures to 30 minute oxygen (5%)and glucose (1 mmol/L) deprivation (OGD).Results: Selective factor Xa (FXa) inhibition by fondaparinux during and afterOGD significantly reduced neuronal death in the CA1 after 48 hours. Thrombinactivity was increased in the medium 24 hours after OGD and this increasewas prevented by fondaparinux suggesting that FXa catalyzes the conversion ofprothrombin to thrombin in neural tissue after ischemia in vitro. Treatment withSCH79797, a selective antagonist of the thrombin receptor protease activatedreceptor-1 (PAR-1), significantly decreased neuronal cell death indicating thatthrombin signals ischemic damage via PAR-1. The JNK pathway plays an importantrole in cerebral ischemia and we observed activation of the JNK substrate,c-Jun in our model. Both the FXa inhibitor, fondaparinux and the PAR-1 antagonistSCH79797, decreased the level of phospho-c-Jun Ser73. After thrombin preconditioningc-Jun was activated by phosphorylation in the nuclei of neurons of the CA1.Treatment with a synthetic thrombin receptor agonist resulted in the same c-Junactivation profile and protection against subsequent OGD indicating that thrombinalso signals via PAR-1 and c-Jun in cell protection.Conclusion: These results indicate that FXa activates thrombin in cerebral ischemia,leading via PAR-1 to the activation of the JNK pathway resulting in neuronal death.Thrombin induced tolerance also involves PAR-1 and JNK, revealing commonfeatures in cell death and survival signalling.

Dosage optimization of treatments using population pharmacokinetic modeling and simulation.

Pharmacokinetic variability in drug levels represent for some drugs a major determinant of treatment success, since sub-therapeutic concentrations might lead to toxic reactions, treatment discontinuation or inefficacy. This is true for most antiretroviral drugs, which exhibit high inter-patient variability in their pharmacokinetics that has been partially explained by some genetic and non-genetic factors. The population pharmacokinetic approach represents a very useful tool for the description of the dose-concentration relationship, the quantification of variability in the target population of patients and the identification of influencing factors. It can thus be used to make predictions and dosage adjustment optimization based on Bayesian therapeutic drug monitoring (TDM). This approach has been used to characterize the pharmacokinetics of nevirapine (NVP) in 137 HIV-positive patients followed within the frame of a TDM program. Among tested covariates, body weight, co-administration of a cytochrome (CYP) 3A4 inducer or boosted atazanavir as well as elevated aspartate transaminases showed an effect on NVP elimination. In addition, genetic polymorphism in the CYP2B6 was associated with reduced NVP clearance. Altogether, these factors could explain 26% in NVP variability. Model-based simulations were used to compare the adequacy of different dosage regimens in relation to the therapeutic target associated with treatment efficacy. In conclusion, the population approach is very useful to characterize the pharmacokinetic profile of drugs in a population of interest. The quantification and the identification of the sources of variability is a rational approach to making optimal dosage decision for certain drugs administered chronically.

Stimulus statistics shape oscillations in nonlinear recurrent neural networks.

Rhythmic activity plays a central role in neural computations and brain functions ranging from homeostasis to attention, as well as in neurological and neuropsychiatric disorders. Despite this pervasiveness, little is known about the mechanisms whereby the frequency and power of oscillatory activity are modulated, and how they reflect the inputs received by neurons. Numerous studies have reported input-dependent fluctuations in peak frequency and power (as well as couplings across these features). However, it remains unresolved what mediates these spectral shifts among neural populations. Extending previous findings regarding stochastic nonlinear systems and experimental observations, we provide analytical insights regarding oscillatory responses of neural populations to stimulation from either endogenous or exogenous origins. Using a deceptively simple yet sparse and randomly connected network of neurons, we show how spiking inputs can reliably modulate the peak frequency and power expressed by synchronous neural populations without any changes in circuitry. Our results reveal that a generic, non-nonlinear and input-induced mechanism can robustly mediate these spectral fluctuations, and thus provide a framework in which inputs to the neurons bidirectionally regulate both the frequency and power expressed by synchronous populations. Theoretical and computational analysis of the ensuing spectral fluctuations was found to reflect the underlying dynamics of the input stimuli driving the neurons. Our results provide insights regarding a generic mechanism supporting spectral transitions observed across cortical networks and spanning multiple frequency bands.

Development of Asphalt Dynamic Modulus Master Curve Using Falling Weight Deflectometer Measurements, TR-659

The asphalt concrete (AC) dynamic modulus (|E*|) is a key design parameter in mechanistic-based pavement design methodologies such as the American Association of State Highway and Transportation Officials (AASHTO) MEPDG/Pavement-ME Design. The objective of this feasibility study was to develop frameworks for predicting the AC |E*| master curve from falling weight deflectometer (FWD) deflection-time history data collected by the Iowa Department of Transportation (Iowa DOT). A neural networks (NN) methodology was developed based on a synthetically generated viscoelastic forward solutions database to predict AC relaxation modulus (E(t)) master curve coefficients from FWD deflection-time history data. According to the theory of viscoelasticity, if AC relaxation modulus, E(t), is known, |E*| can be calculated (and vice versa) through numerical inter-conversion procedures. Several case studies focusing on full-depth AC pavements were conducted to isolate potential backcalculation issues that are only related to the modulus master curve of the AC layer. For the proof-of-concept demonstration, a comprehensive full-depth AC analysis was carried out through 10,000 batch simulations using a viscoelastic forward analysis program. Anomalies were detected in the comprehensive raw synthetic database and were eliminated through imposition of certain constraints involving the sigmoid master curve coefficients. The surrogate forward modeling results showed that NNs are able to predict deflection-time histories from E(t) master curve coefficients and other layer properties very well. The NN inverse modeling results demonstrated the potential of NNs to backcalculate the E(t) master curve coefficients from single-drop FWD deflection-time history data, although the current prediction accuracies are not sufficient to recommend these models for practical implementation. Considering the complex nature of the problem investigated with many uncertainties involved, including the possible presence of dynamics during FWD testing (related to the presence and depth of stiff layer, inertial and wave propagation effects, etc.), the limitations of current FWD technology (integration errors, truncation issues, etc.), and the need for a rapid and simplified approach for routine implementation, future research recommendations have been provided making a strong case for an expanded research study.

Citrobacter rodentium Requires Intestinal Neural Wiskott-Aldrich Syndrome Protein (N-WASp) for Actin Pedestal Formation, Colonization and Epithelial Barrier Disruption In Vivo

Background: Citrobacter rodentium is a natural mouse pathogen that is genetically closelyrelated to the human enteric pathogens enteropathogenic and enterohemorrhagic E. coli.Among the repertoire of conserved virulence factors that these pathogens deliver via typeIII secretion, Tir and EspF are responsible for the formation of characteristic actin-richpedestals and disruption of tight junction integrity, respectively. There is evidence In Vitrothese effectors accomplish this, at least in part, by subverting the normal host cellularfunctions of N-WASP, a critical regulator of branched chain actin assembly. Although NWASPhas been shown to be involved in pedestal formation In Vitro, the requirements ofN-WASP-mediated actin pedestals for intestinal colonization by attaching/effacing (A/E)pathogens In Vivo is not known. Furthermore, it is not known whether N-WASP is requiredfor EspF-mediated tight junction disruption. Methods: To investigate the role of N-WASPin the gut epithelium, we generated mice with intestine-specific deletion of N-WASP(iNWKO), by mating mice homozygous for a floxed N-WASP allele (N-WASPL2L/L2L) tomice expressing Cre recombinase under the villin promoter. Separately housed groups ofWT and iNWKO mice were inoculated with 5x108 GFP-expressing C. rodentium by intragastriclavage. Stool was collected 2, 4, 7, and 12 days after infection, and recoverablecolony forming units (CFUs) of C. rodentium were quantified by plating serial dilutions ofhomogenized stool on MacConkey's agar. GFP+ colonies were counted after 24 hoursincubation at 37°C. The presence of actin pedestals was investigated by electron microscopy(EM), and tight junction morphology was assessed by immunofluorescence staining ofoccludin, ZO-1 and claudin-2. Results: C. rodentium infection did not result in mortalityin WT or iNWKO mice. Compared to controls, iNWKO mice exhibited higher levels ofbacterial shedding during the first 4 days of infection (day 4 average: WT 5.2x104 CFU/gvs. iNWKO 4.7x105 CFU/g, p=0.08), followed by a more rapid clearance of C. rodentium, (day7-12 average: WT 2x106 CFU/g vs. iNWKO 2.7x105, p=0.01). EM and immunofluorescencerevealed the complete lack of actin pedestals in iNWKO mice and no mucosa-associatedGFP+ C. rodentium by day 7. WT controls exhibited tight junction disruption, reflected byaltered distribution of ZO-1, whereas iNWKO mice had no change in the pattern of ZO-1.Conclusion: Intestinal N-WASP is required for actin pedestal formation by C. rodentium InVivo, and ablation of N-WASP is associated with more rapid bacterial clearance and decreasedability of C. rodentium to disrupt intercellular junctions.

Mobile robot experimental modeling and control strategies using sensor fusion

This research work deals with the problem of modeling and design of low level speed controller for the mobile robot PRIM. The main objective is to develop an effective educational, and research tool. On one hand, the interests in using the open mobile platform PRIM consist in integrating several highly related subjects to the automatic control theory in an educational context, by embracing the subjects of communications, signal processing, sensor fusion and hardware design, amongst others. On the other hand, the idea is to implement useful navigation strategies such that the robot can be served as a mobile multimedia information point. It is in this context, when navigation strategies are oriented to goal achievement, that a local model predictive control is attained. Hence, such studies are presented as a very interesting control strategy in order to develop the future capabilities of the system. In this context the research developed includes the visual information as a meaningful source that allows detecting the obstacle position coordinates as well as planning the free obstacle trajectory that should be reached by the robot

Reflections on Partial Least Squares Path Modeling

The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics (Rönkkö & Evermann, 2013) and proponents (Henseler et al., 2014) of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (1) can be truly characterized as a technique for structural equation modeling (SEM); (2) is able to correct for measurement error; (3) can be used to validate measurement models; (4) accommodates small sample sizes; (5) is able to provide null hypothesis tests for path coefficients; and (6) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature in order to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.

Self-potentials in partially saturated media: the importance of explicit modeling of electrode effects

Self-potential (SP) data are of interest to vadose zone hydrology because of their direct sensitivity to water flow and ionic transport. There is unfortunately little consensus in the literature about how to best model SP data under partially saturated conditions, and different approaches (often supported by one laboratory data set alone) have been proposed. We argue that this lack of agreement can largely be traced to electrode effects that have not been properly taken into account. A series of drainage and imbibition experiments were considered in which we found that previously proposed approaches to remove electrode effects were unlikely to provide adequate corrections. Instead, we explicitly modeled the electrode effects together with classical SP contributions using a flow and transport model. The simulated data agreed overall with the observed SP signals and allowed decomposing the different signal contributions to analyze them separately. After reviewing other published experimental data, we suggest that most of them include electrode effects that have not been properly taken into account. Our results suggest that previously presented SP theory works well when considering the modeling uncertainties presently associated with electrode effects. Additional work is warranted to not only develop suitable electrodes for laboratory experiments but also to assure that associated electrode effects that appear inevitable in longer term experiments are predictable, so that they can be incorporated into the modeling framework.

Exploring the rate-limiting steps in visual phototransduction recovery by bottom-up kinetic modeling

Phototransduction in vertebrate photoreceptor cells represents a paradigm of signaling pathways mediated by G-protein-coupled receptors (GPCRs), which share common modules linking the initiation of the cascade to the final response of the cell. In this work, we focused on the recovery phase of the visual photoresponse, which is comprised of several interacting mechanisms. We employed current biochemical knowledge to investigate the response mechanisms of a comprehensive model of the visual phototransduction pathway. In particular, we have improved the model by implementing a more detailed representation of the recoverin (Rec)-mediated calcium feedback on rhodopsin kinase and including a dynamic arrestin (Arr) oligomerization mechanism. The model was successfully employed to investigate the rate limiting steps in the recovery of the rod photoreceptor cell after illumination. Simulation of experimental conditions in which the expression levels of rhodospin kinase (RK), of the regulator of the G-protein signaling (RGS), of Arr and of Rec were altered individually or in combination revealed severe kinetic constraints to the dynamics of the overall network. Our simulations confirm that RGS-mediated effector shutdown is the rate-limiting step in the recovery of the photoreceptor and show that the dynamic formation and dissociation of Arr homodimers and homotetramers at different light intensities significantly affect the timing of rhodopsin shutdown. The transition of Arr from its oligomeric storage forms to its monomeric form serves to temper its availability in the functional state. Our results may explain the puzzling evidence that overexpressing RK does not influence the saturation time of rod cells at bright light stimuli. The approach presented here could be extended to the study of other GPCR signaling pathways.