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Dopamine and Methamphetamine Differentially Affect Electron Transport Chain Complexes and Parkin in Rat Striatum: New Insight into Methamphetamine Neurotoxicity
No full textMethamphetamine (METH) is a highly abused psychostimulant that is neurotoxic to dopaminergic (DAergic) nerve terminals in the striatum and increases the risk of developing Parkinson's disease (PD). In vivo, METH-mediated DA release, followed by DA-mediated oxidative stress and mitochondrial dysfunction in pre- and postsynaptic neurons, mediates METH neurotoxicity. METH-triggered oxidative stress damages parkin, a neuroprotective protein involved in PD etiology via its involvement in the maintenance of mitochondria. It is not known whether METH itself contributes to mitochondrial dysfunction and whether parkin regulates complex I, an enzymatic complex downregulated in PD. To determine this, we separately assessed the effects of METH or DA alone on electron transport chain (ETC) complexes and the protein parkin in isolated striatal mitochondria. We show that METH decreases the levels of selected complex I, II, and III subunits (NDUFS3, SDHA, and UQCRC2, respectively), whereas DA decreases the levels only of the NDUFS3 subunit in our preparations. We also show that the selected subunits are not decreased in synaptosomal mitochondria under similar experimental conditions. Finally, we found that parkin overexpression does not influence the levels of the NDUFS3 subunit in rat striatum. The presented results indicate that METH itself is a factor promoting dysfunction of striatal mitochondria; therefore, it is a potential drug target against METH neurotoxicity. The observed decreases in ETC complex subunits suggest that DA and METH decrease activities of the ETC complexes via oxidative damage to their subunits and that synaptosomal mitochondria may be somewhat "resistant" to DA- and METH-induced disruption in mitochondrial ETC complexes than perikaryal mitochondria. The results also suggest that parkin does not regulate NDUFS3 turnover in rat striatum.PTBT
Modeling of the Frozen Mode Phenomenon and its Sensitivity Using Discontinuous Galerkin Methods
No full textWeinvestigatethebehaviorandsensitivityofthefrozenmodephenomenon in finite structures with anisotropic materials, including both magnetic materials and non-normal incidence. The studies are done by using a high-order accurate discontin- uous Galerkin method for solving Maxwells equations in the time domain. We confirm the existence of the phenomenon also in the time-domain and study carefully the im- pact of the finite crystal on the frozen mode. This sets the stage for a thorough study of the robustness of the frozen mode phenomenon, resulting in guidelines for which design parameters are most sensitive and acceptable tolerances.MCS
Generalised Gibbs ensemble for spherically constrained harmonic models
No full textWe build and analytically calculate the Generalised Gibbs Ensemble partition function of the integrable Soft Neumann Model. This is the model of a classical particle which is constrained to move, on average over the initial conditions, on an N dimensional sphere, and feels the effect of anisotropic harmonic potentials. We derive all relevant averaged static observables in the (thermodynamic) N -> infinity limit. We compare them to their long-term dynamic averages finding excellent agreement in all phases of a non-trivial phase diagram determined by the characteristics of the initial conditions and the amount of energy injected or extracted in an instantaneous quench. We discuss the implications of our results for the proper Neumann model in which the spherical constraint is imposed strictly.Superscript/Subscript Available</commentIDEPHICS
Short period of delayed loading can increase the final bone volume inside tissue engineering scaffold
No full textLB
Comment on "Formation of twin boundaries in commercial purity aluminum with addition of Ti refiner" by Zhongwei Chen, Jianping Gao, Kang Yan
No full textLSM
Correction of surface error occurring in microlenses characterization performed by optical profilers
No full textCharacterizing the surface of microlenses by optical profilers has the important advantages of measurement speed, flexibility and automation. Nevertheless, the accuracy of such characterization is limited by error occurring in non-flat measurements. Here, we propose a method that uses multiple measurements of a single reference ball combined with a machine learning algorithm that fits the experimental data to correct the measurements. The success of the method is demonstrated by showing that the residual error after correction reaches 20nm RMS. Such results extend greatly the quality of microlens characterization by optical profilers.NA
