Dopamine D-3 receptors regulate GABA(A) receptor function through a phospho-dependent endocytosis mechanism in nucleus accumbens

The dopamine D-3 receptor, which is highly enriched in nucleus accumbens (NAc), has been suggested to play an important role in reinforcement and reward. To understand the potential cellular mechanism underlying D-3 receptor functions, we examined the effect of D-3 receptor activation on GABA(A) receptor (GABA(A)R)-mediated current and inhibitory synaptic transmission in medium spiny neurons of NAc. Application of PD128907 [(4aR, 10bR)-3,4a, 4,10b-tetrahydro-4-propyl-2H, 5H-[1] benzopyrano-[4,3-b]-1,4-oxazin-9-ol hydrochloride], a specific D-3 receptor agonist, caused a significant reduction of GABAAR current in acutely dissociated NAc neurons and miniature IPSC amplitude in NAc slices. This effect was blocked by dialysis with a dynamin inhibitory peptide, which prevents the clathrin/activator protein 2 (AP2)-mediated GABA(A) receptor endocytosis. In addition, the D-3 effect on GABA(A)R current was prevented by agents that manipulate protein kinase A (PKA) activity. Infusion of a peptide derived from GABA(A) beta subunits, which contains an atypical binding motif for the clathrin AP2 adaptor complex and the major PKA phosphorylation sites and binds with high affinity to AP2 only when dephosphorylated, diminished the D-3 regulation of IPSC amplitude. The phosphorylated equivalent of the peptide was without effect. Moreover, PD128907 increased GABAAR internalization and reduced the surface expression of GABA(A) receptor beta subunits in NAc slices, which was prevented by dynamin inhibitory peptide or cAMP treatment. Together, our results suggest that D-3 receptor activation suppresses the efficacy of inhibitory synaptic transmission in NAc by increasing the phospho-dependent endocytosis of GABA(A) receptors

Finding the optimal design of a passive microfluidic mixer.

The ability to thoroughly mix two fluids is a fundamental need in microfluidics. While a variety of different microfluidic mixers have been designed by researchers, it remains unknown which (if any) of these mixers are optimal (that is, which designs provide the most thorough mixing with the smallest possible fluidic resistance across the mixer). In this work, we automatically designed and rationally optimized a microfluidic mixer. We accomplished this by first generating a library of thousands of different randomly designed mixers, then using the non-dominated sorting genetic algorithm II (NSGA-II) to optimize the random chips in order to achieve Pareto efficiency. Pareto efficiency is a state of allocation of resources (e.g. driving force) from which it is impossible to reallocate so as to make any one individual criterion better off (e.g. pressure drop) without making at least one individual criterion (e.g. mixing performance) worse off. After 200 generations of evolution, Pareto efficiency was achieved and the Pareto-optimal front was found. We examined designs at the Pareto-optimal front and found several design criteria that enhance the mixing performance of a mixer while minimizing its fluidic resistance; these observations provide new criteria on how to design optimal microfluidic mixers. Additionally, we compared the designs from NSGA-II with some popular microfluidic mixer designs from the literature and found that designs from NSGA-II have lower fluidic resistance with similar mixing performance. As a proof of concept, we fabricated three mixer designs from 200 generations of evolution and one conventional popular mixer design and tested the performance of these four mixers. Using this approach, an optimal design of a passive microfluidic mixer is found and the criteria of designing a passive microfluidic mixer are established

Low-Symmetry Rhombohedral GeTe Thermoelectrics

High-symmetry thermoelectric materials usually have the advantage of very high band degeneracy, while low-symmetry thermoelectrics have the advantage of very low lattice thermal conductivity. If the symmetry breaking of band degeneracy is small, both effects may be realized simultaneously. Here we demonstrate this principle in rhombohedral GeTe alloys, having a slightly reduced symmetry from its cubic structure, to realize a record figure of merit (zT ∼ 2.4) at 600 K. This is enabled by the control of rhombohedral distortion in crystal structure for engineering the split low-symmetry bands to be converged and the resultant compositional complexity for simultaneously reducing the lattice thermal conductivity. Device ZT as high as 1.3 in the rhombohedral phase and 1.5 over the entire working temperature range of GeTe alloys make this material the most efficient thermoelectric to date. This work paves the way for exploring low-symmetry materials as efficient thermoelectrics. Thermoelectric materials enable a heat flow to be directly converted to a flow of charge carriers for generating electricity. The crystal structure symmetry is one of the most fundamental parameters determining the properties of a crystalline material including thermoelectrics. The common belief currently held is that high-symmetry materials are usually good for thermoelectrics, leading to great efforts having historically been focused on GeTe alloys in a high-symmetry cubic structure. Here we show a slight reduction of crystal structure symmetry of GeTe alloys from cubic to rhombohedral, enabling a rearrangement in electronic bands for more transporting channels of charge carriers and many imperfections for more blocking centers of heat-energy carriers (phonons). This leads to the discovery of rhombohedral GeTe alloys as the most efficient thermoelectric materials to date, opening new possibilities for low-symmetry thermoelectric materials. Cubic GeTe thermoelectrics have been historically focused on, while this work utilizes a slight symmetry-breaking strategy to converge the split valence bands, to reduce the lattice thermal conductivity and therefore realize a record thermoelectric performance, all enabled in GeTe in a rhombohedral structure. This not only promotes GeTe alloys as excellent materials for thermoelectric power generation below 800 K, but also expands low-symmetry materials as efficient thermoelectrics

Serial processing of kinematic signals by cerebellar circuitry during voluntary whisking

Purkinje cells (PCs) in Crus 1 represent whisker movement via linear changes in firing rate, but the circuit mechanisms underlying this coding scheme are unknown. Here we examine the role of upstream inputs to PCs—excitatory granule cells (GCs) and inhibitory molecular layer interneurons—in processing of whisking signals. Patch clamp recordings in GCs reveal that movement is accompanied by changes in mossy fibre input rate that drive membrane potential depolarisation and high-frequency bursting activity at preferred whisker angles. Although individual GCs are narrowly tuned, GC populations provide linear excitatory drive across a wide range of movement. Molecular layer interneurons exhibit bidirectional firing rate changes during whisking, similar to PCs. Together, GC populations provide downstream PCs with linear representations of volitional movement, while inhibitory networks invert these signals. The exquisite sensitivity of neurons at each processing stage enables faithful propagation of kinematic representations through the cerebellum

Combined overexpression of chitinase and defensin genesin transgenic tomato enhances resistance to Botrytis cinerea

The rice chitinase gene (CHI), the alfalfa defensin gene (alfAFP) and their bivalent gene (CHI-AFP) were introduced into tomato line Micro-Tom via Agrobacterium-mediated gene transfer method. Transformants were obtained and confirmed by GFP, PCR and Southern blot hybridization. One to four copies of transgene were integrated into the tomato nuclear genome. Transcription levels of chitinase, alfAFP and their bivalent gene CHI-AFP in various transgenic lines were determined using Northern blotand Western blot analysis. Performance test of resistance analyses to Botrytis cinerea with T1 generation transgenic tomato lines showed the transgenic lines exhibited higher resistance to the pathogens infected than that of the non-transgenic plants and the resistance levels were related toexpression levels of the transgene, showing dosage-effect. The transgenic tomato harboring CHI-AFP cassette showed the highest disease resistance; it suggested that co-transformation with alfAFP and chitinase gene was more effective than individual transformations on the resistance to B. cinerea. Some independent lines with high disease resistance, low variability and stable expression of transgenes could be selected for the further studies and molecular breeding

A weighted reduced basis method for parabolic PDEs with random data

This work considers a weighted POD-greedy method to estimate statistical outputs parabolic PDE problems with parametrized random data. The key idea of weighted reduced basis methods is to weight the parameter-dependent error estimate according to a probability measure in the set-up of the reduced space. The error of stochastic finite element solutions is usually measured in a root mean square sense regarding their dependence on the stochastic input parameters. An orthogonal projection of a snapshot set onto a corresponding POD basis defines an optimum reduced approximation in terms of a Monte Carlo discretization of the root mean square error. The errors of a weighted POD-greedy Galerkin solution are compared against an orthogonal projection of the underlying snapshots onto a POD basis for a numerical example involving thermal conduction. In particular, it is assessed whether a weighted POD-greedy solutions is able to come significantly closer to the optimum than a non-weighted equivalent. Additionally, the performance of a weighted POD-greedy Galerkin solution is considered with respect to the mean absolute error of an adjoint-corrected functional of the reduced solution.Comment: 15 pages, 4 figure

Effects of surface tension on the size-dependent ferroelectric characteristics of free-standing BaTiO3 nano-thin films

Intrinsic surface tension of nanoscale ferroelectric thin film tends to induce tensile stress in its surface layer, whereas the other portion of the film is subjected to compression to maintain mechanical balance. A continuum-based phase-field model accounting for such surface effect has been set up to investigate the evolution of domain structure and thickness-dependent ferroelectric properties of free-standing BaTiO 3 nano-thin films. It was observed that both remnant polarization and coercive field decrease with a decrease of film thickness and increase of surface tension, and that, for film thickness ranging from 10-20 nm, both properties decreased sharply at the surface strain 2-3ε 0 (ε 0 being the spontaneous strain). Further decrease in film thickness or increase in surface tension could result in loss of ferroelectricity. Such a critical state for the ferroelectric-to-paraelectric transition has also been established for the range of film thickness 4-20 nm. © 2011 American Institute of Physics.published_or_final_versio

Provenance analysis for instagram photos

As a feasible device fingerprint, sensor pattern noise (SPN) has been proven to be effective in the provenance analysis of digital images. However, with the rise of social media, millions of images are being uploaded to and shared through social media sites every day. An image downloaded from social networks may have gone through a series of unknown image manipulations. Consequently, the trustworthiness of SPN has been challenged in the provenance analysis of the images downloaded from social media platforms. In this paper, we intend to investigate the effects of the pre-defined Instagram images filters on the SPN-based image provenance analysis. We identify two groups of filters that affect the SPN in quite different ways, with Group I consisting of the filters that severely attenuate the SPN and Group II consisting of the filters that well preserve the SPN in the images. We further propose a CNN-based classifier to perform filter-oriented image categorization, aiming to exclude the images manipulated by the filters in Group I and thus improve the reliability of the SPN-based provenance analysis. The results on about 20, 000 images and 18 filters are very promising, with an accuracy higher than 96% in differentiating the filters in Group I and Group II

MAC Performance Analysis for Drive-Thru Internet Networks with Rayleigh Capture

© 2013 IEEE. In practical radio transmissions, channel capture is a dominating factor that affects wireless network performance. The capture effect can occur in wireless network when packets arrive with different powers. Packets with high power can effectively swamp low power packets, such that they are received successfully, when otherwise a collision would have occurred. We present a vehicular network performance-prediction model for a Rayleigh capture channel in Drive-thru Internet scenario. The model incorporates the capture effect into a 2-D Markov chain modeling the high-node mobility and distributed coordination function broadcast scheme. The performance-prediction model unveils the impacts of mobility velocity and number of vehicles on the throughput in a Rayleigh capture channel. We use a vehicular traffic flow model to predict vehicular movement on road by aggregating all vehicles into a flow. Simulation results confirm that our performance-prediction model accurately predicts the performance of traveling vehicles with Rayleigh capture channel in the Drive-thru Internet scenario. We demonstrate that using our performance-prediction model, we can obtain optimal contention window value, by which the best system throughput can be reached without wasting contention time. This is also proved by Anastasi et al