A comparative study on the effects of the benzodiazepine midazolam and the dopamine agents, apomorphine and sulpiride, on rat behavior in the two-way avoidance test

In recent years. studies in behavioral pharmacology have shown the involvement of dopaminergic mechanisms in avoidance behavior as assessed by the two-way active avoidance test (CAR). Changes in dopaminergic transmission also occur in response to particularly threatening challenges. However, studies on the effects of benzodiazepine (BZD) drugs ill this test are still unclear. Given the interplay of dopamine and other neurotransmitters in the neurobiology of anxiety and schizophrenia the aim of this work was to evaluate the effects of systemic administration of midazolam, the dopaminergic agonist apomorphine, and the D(2) receptor antagonist sulpiride using the CAR, a test that shows good sensitivity to typical neuroleptic drugs. Whereas midazolam did not alter the avoidance response. apomorphine increased and sulpiride reduced them in this test. Escape was not affected by any drug treatments. Heightened avoidance was not associated with the increased motor activity caused by apomorphine. In contrast with the benzodiazepine midazolam, activation of post-synaptic D(2) receptors with apomorphine facilitates, whereas the D(2) receptor antagonism with sulpiride inhibited the acquisition of the avoidance behavior. Together, these results bring additional evidence for a role of D(2) mechanisms in the acquisition of the active avoidance. (C) 2009 Elsevier Inc. All rights reserved.

Black-box decomposition approach for computational hemodynamics: One-dimensional models

Increasing efforts exist in integrating different levels of detail in models of the cardiovascular system. For instance, one-dimensional representations are employed to model the systemic circulation. In this context, effective and black-box-type decomposition strategies for one-dimensional networks are needed, so as to: (i) employ domain decomposition strategies for large systemic models (1D-1D coupling) and (ii) provide the conceptual basis for dimensionally-heterogeneous representations (1D-3D coupling, among various possibilities). The strategy proposed in this article works for both of these two scenarios, though the several applications shown to illustrate its performance focus on the 1D-1D coupling case. A one-dimensional network is decomposed in such a way that each coupling point connects two (and not more) of the sub-networks. At each of the M connection points two unknowns are defined: the flow rate and pressure. These 2M unknowns are determined by 2M equations, since each sub-network provides one (non-linear) equation per coupling point. It is shown how to build the 2M x 2M non-linear system with arbitrary and independent choice of boundary conditions for each of the sub-networks. The idea is then to solve this non-linear system until convergence, which guarantees strong coupling of the complete network. In other words, if the non-linear solver converges at each time step, the solution coincides with what would be obtained by monolithically modeling the whole network. The decomposition thus imposes no stability restriction on the choice of the time step size. Effective iterative strategies for the non-linear system that preserve the black-box character of the decomposition are then explored. Several variants of matrix-free Broyden`s and Newton-GMRES algorithms are assessed as numerical solvers by comparing their performance on sub-critical wave propagation problems which range from academic test cases to realistic cardiovascular applications. A specific variant of Broyden`s algorithm is identified and recommended on the basis of its computer cost and reliability. (C) 2010 Elsevier B.V. All rights reserved.