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Parkinson's disease (PD) is a neurodegenerative disorder in which genetic and environmental factors synergistically lead to loss of midbrain dopamine (DA) neurons. Mutation of leucine-rich repeated kinase2 (Lrrk2) genes is responsible for the majority of inherited familial cases of PD and can also be found in sporadic cases. The pathophysiological role of this kinase has to be fully understood yet. Hyperactivation of Lrrk2 kinase domain might represent a predisposing factor for both enhanced striatal glutamatergic release and mitochondrial vulnerability to environmental factors that are observed in PD. To investigate possible alterations of striatal susceptibility to mitochondrial dysfunction, we performed electrophysiological recordings from the nucleus striatum of a G2019S Lrrk2 mouse model of PD, as well as molecular and morphological analyses of G2019S Lrrk2-expressing SH-SY5Y neuroblastoma cells. In G2019S mice, we found reduced striatal DA levels, according to the hypothesis of alteration of dopaminergic transmission, and increased loss of field potential induced by the mitochondrial complex I inhibitor rotenone. This detrimental effect is reversed by the D2 DA receptor agonist quinpirole via the inhibition of the cAMP/PKA intracellular pathway. Analysis of mitochondrial functions in G2019S Lrrk2-expressing SH-SY5Y cells revealed strong rotenone-induced oxidative stress characterized by reduced Ca2+ buffering capability and ATP synthesis, production of reactive oxygen species, and increased mitochondrial fragmentation. Importantly, quinpirole was able to prevent all these changes. We suggest that the G2019S-Lrrk2 mutation is a predisposing factor for enhanced striatal susceptibility to mitochondrial dysfunction induced by exposure to mitochondrial environmental toxins and that the D2 receptor stimulation is neuroprotective on mitochondrial function, via the inhibition of cAMP/PKA intracellular pathway. We suggest new possible neuroprotective strategies for pat

Among genetic abnormalities identified in Parkinson's disease (PD), mutations of the leucine-rich repeat kinase2 (LRRK2) gene, such as the G2019S missense mutation linked to enhanced kinase activity, are the most common. While the complex role of LRRK2 has not been fully elucidated, evidence that mutated kinase activity affects synaptic transmission has been reported. Thus, our aim was to explore possible early alterations of neurotransmission produced by the G2019S LRRK2 mutation in PD. We performed electrophysiological patch-clamp recordings of striatal spiny projection neurons (SPNs) in the G2019S-Lrrk2 knock-in (KI) mouse model of PD, in D1994S kinase-dead (KD), Lrrk2 knock-out (KO) and wild-type (WT) mice. In G2019S Lrrk2 KI mice, basal spontaneous glutamatergic transmission, synaptic facilitation, and NMDA/AMPA ratios were unchanged, whereas the stimulation of dopamine (DA) D2 receptor by quinpirole reduced the spontaneous and evoked excitatory postsynaptic currents (EPSC). Quinpirole reduced the EPSC amplitude of SPNs in KI but not in KD, KO and WT mice, suggesting that the enhanced LRRK2 kinase activity induced by the G2019S mutation is associated with the observed functional alteration of SPNs synaptic transmission. The effect of quinpirole was mediated by a phospholipase C (PLC)-dependent release of endocannabinoid, with subsequent activation of presynaptic cannabinoid receptor 1 and reduced release of glutamate. The key role of DA D2 receptor in reducing glutamatergic output in our LRRK2 genetic model of PD further supports the use of DA agonists in the treatment of early PD patients with LRRK2 mutations to counteract the disease progression.

Contains fulltext : 176656.pdf (publisher's version ) (Closed access), Visually guided finger movements include online feedback of current effector position to guide target approach. This visual feedback may be scaled or otherwise distorted by unpredictable perturbations. Although adjustments to visual feedback scaling have been studied before, the underlying brain activation differences between upscaling (visual feedback larger than real movement) and downscaling (feedback smaller than real movement) are currently unknown. Brain activation differences between upscaling and downscaling might be expected because within-trial adjustments during upscaling require corrective backwards accelerations, whereas correcting for downscaling requires forward accelerations. In this behavioural and fMRI study we investigated adjustments during up- and downscaling in a target-directed finger flexion-extension task with real-time visual feedback. We found that subjects made longer and more complete within-trial corrections for downscaling perturbations than for upscaling perturbations. The finger task activated primary motor (M1) and somatosensory (S1) areas, premotor and parietal regions, basal ganglia, and cerebellum. General scaling effects were seen in the right pre-supplementary motor area, dorsal anterior cingulate cortex, inferior parietal lobule, and dorsolateral prefrontal cortex. Stronger activations for down- than for upscaling were observed in M1, supplementary motor area (SMA), S1 and anterior cingulate cortex. We argue that these activation differences may reflect differing online correction for upscaling versus downscaling during finger flexion-extension.

Recent tools for control and analysis of hybrid systems are applied to an AC-DC converter. The topology poses particularly challenging problems since it is unusually complex and the circuit parameters are such that the dynamic coupling between the AC and DC sides cannot be ignored. The paper proposes a model predictive control scheme for direct voltage control which circumvents the bandwidth limitations associated with classical cascade control. The stability and harmonic properties of the resulting closed loop system are investigated using new tools for the analysis of switched systems., QC 20150529

Irrigation canals transport water from water sources (such as large rivers and lakes) to water users (such as farmers). Irrigation canals are typically very large in nature, covering vast geographical areas, and involving a significant number of control actuators, such as pumps, gates, and locks. The control of such canals is aimed at guaranteeing the adequate delivery of water with minimal water spillage and with minimal control structure usage. To take into account forecasts on, e.g., water consumption and weather, model predictive control (MPC) can be used to determine which actions to take. For large-scale systems, in which different parts of the canal are owned by different parties, distributed MPC control could then be employed. Although iterative distributed MPC approaches proposed earlier in the literature may yield overall optimal performance, the amount of iterations required before achieving this performance may be large, and thus require a significant amount of time. In this paper, the structure of systems consisting of serially interconnected subsystems is exploited to obtain an efficient non-iterative, cascaded MPC scheme. Simulation studies on a 7-reach irrigation canal illustrate the performance of this non-iterative scheme in comparison with an iterative scheme., Delft Center for Systems and Control, Mechanical, Maritime and Materials Engineering

Several recent techniques from hybrid and optimal control are evaluated on a power electronics benchmark problem. The benchmark involves a number of practically interesting operating scenarios for a fixed-frequency step-up dc-dc converter. The specifications are defined such that good performance can only be obtained if the switched and nonlinear nature of the problem is respected during the design phase., QC 20141127

Several recent techniques from hybrid and optimal control are evaluated on a power electronics benchmark problem. The benchmark involves a number of practically interesting operating scenarios for a fixed-frequency synchronous step-down dc-dc converter. The specifications are defined such that good performance only can be obtained if the switched and nonlinear nature of the problem is respected during the design phase., QC 20141126

Emergency voltage control problems in electric power networks have stimulated the interest for the implementation of online optimal control techniques. Briefly stated, voltage instability stems from the attempt of load dynamics to restore power consumption beyond the capability of the transmission and generation system. Typically, this situation occurs after the outage of one or more components in the network, such that the system cannot satisfy the load demand with the given inputs at a physically sustainable voltage profile. For a particular network, a supervisory control strategy based on model predictive control is proposed, which provides at discrete time steps inputs and set-points to lower-layer primary controllers based on the predicted behavior of a model featuring hybrid dynamics of the loads and the generation system., Delft Center for Systems and Control, Mechanical, Maritime and Materials Engineering