307 research outputs found
Regulation of metabotropic glutamate receptor subtype 7a by PDZ-domain protein PICK1
Metabotropic glutamate receptor subtype 7 (mGluR7) belongs to the family of G-protein coupled receptors. mGluR7 is widely distributed in the brain and primarily localized at presynaptic terminals, where it is thought to regulate neurotransmitter release and synaptic plasticity. Studies have shown that the intracellular C-terminal tail of mGluR7 binds a variety of proteins in addition to trimeric G-proteins. These newly identified protein interactions are believed to play a key role in the synaptic targeting and G-protein dependent signaling of mGluR7. Protein interacting with C kinase 1 (PICK1), a PDZ-domain protein, is a strong interaction partner of mGluR7a. In order to investigate the role of PICK1 in the synaptic trafficking and signaling of mGluR7a, a knock-in mouse line in which the interaction of mGluR7a and PICK1 is disrupted was generated. Analysis of the mutant mice by immunocytochemistry and immunoelectron microscopy showed that the synaptic targeting and clustering of mGluR7a was not altered, indicating that PICK1 is not required for mGluR7a receptor membrane trafficking and synaptic localization. However, when the spontaneous synaptic activity of cerebellar granule cell cultures prepared from both wild-type and knock-in mice was monitored, and L-AP4 (400μm) was found to decrease the frequency, but not the amplitude, of spontaneous excitatory currents in wild-type neurons, while no effect of L-AP4 on spontaneous synaptic activity was observed in knock-in neurons. This indicates that PICK1 binding to the C-terminal region of mGluR7a plays an essential role in mGluR7a mediated G-protein signaling. We examined the threshold sensitivity for the convulsant pentetrazole (PTZ) in knock-in mice. It was found that mGluR7a knock-in mice had a greater sensitivity to PTZ than wild-type mice. Moreover, the surface parietal cortex EEG recordings of the mutant mice revealed spontaneous synchronous oscillation, or "spike-and-wave discharges" (SWD), which displayed similar characteristics to absence-like seizures. It was also observed that the knock-in mice responded to pharmacology as human absence epilepsy. These data suggests that the knock-in mice displayed the phenotype of absencelike epilepsy. Furthermore, the behavioral analysis of the mGluR7a knock-in mice showed no deficits in motor coordination, pain sensation, anxiety as well as spatial learning and memory, thus the interaction of mGluR7a and PICK1 appears not to contribute to these physiological processes. Taken together, our data provides evidence for an important role of PICK1 in Gprotein dependent signaling of mGluR7a, whereas PICK1 is not required for synaptic targeting and clustering of mGluR7a. Our results also provide an animal model of absencelike epilepsy generated by disruption of a single mGluR7a-PDZ interaction, thus creating a novel therapeutic target against this neurological disease.Die AminosĂ€ure Glutamat ist nicht nur ein SchlĂŒsselmolekĂŒl im Stoffwechsel jeder Zelle, sondern sie fungiert auch als primĂ€rer exzitatorischer Neurotransmitter im zentralen Nervensystem von SĂ€ugetieren. Erregende Nervensignale, die durch Glutamat vermittelt werden, spielen bei vielen Prozessen im Gehirn eine Rolle, einschlieĂlich kognitiver Leistungen wie zum Beispiel Lernen und GedĂ€chtnisbildung. Glutamat bindet nach Sekretion in den synaptischen Spalt an Glutamat-Rezeptoren, wodurch eine Reihe von Signalkaskaden im nachgeschalteten Neuron aktiviert werden. Es werden zwei Klassen von Glutamat-Rezeptoren unterschieden: ionotrope Glutamatrezeptoren, zu denen die nach ihren jeweiligen Agonisten benannten NMDA-, AMPA- und Kainat-Rezeptoren zĂ€hlen, und metabotrope Glutamat-Rezeptoren (mGluR). Bei letzteren handelt es sich um G-Protein gekoppelte Rezeptoren, welche ĂŒber GTP-bindende Proteine die Aktivierung intrazellulĂ€rer Signalkaskaden vermitteln. Diesen Rezeptoren werden Aufgaben bei der Regulation verschiedener Formen neuronaler PlastizitĂ€t zugeschrieben. Es sind gegenwĂ€rtig acht Subtypen bekannt (mGluR1-8), die anhand von Sequenzhomologien und pharmakologischen Eigenschaften in drei Gruppen (I-III) eingeteilt werden. Von besonderem Interesse fĂŒr diese Doktorarbeit war die Untersuchung des zur Gruppe III zĂ€hlenden, prĂ€synaptisch lokalisierten Rezeptors mGluR7a. Es handelt sich dabei um einen sogenannten Autorezeptor, welcher nach Aktivierung durch Glutamat zu einer Verringerung der Transmitterfreisetzung in der PrĂ€synapse fĂŒhrt. Die molekularen Mechanismen dieser Form von prĂ€synaptischer Inhibition sind erst teilweise verstanden. Es wurde bereits gezeigt, daĂ die Reduktion der TransmitterausschĂŒttung mit einer Hemmung spannungsabhĂ€ngiger Kalzium-KanĂ€le in der PrĂ€synapse einhergeht. Allerdings ist noch unklar, ob diese Effekte direkt durch G-Proteine vermittelt werden oder weitere SignalmolekĂŒle involviert sind. Zur Analyse der funktionellen Regulation von mGluRs der Gruppe III wurde weltweit in verschiedenen Arbeitsgruppen gezielt nach Interaktionspartnern fĂŒr die einzelnen Rezeptoren gesucht. Es konnten einige Proteine identifiziert werden, welche mit mGluR7a interagieren, wie z.B. die G-Protein-Untereinheit bg, Calmodulin, MacMARCKS, Filamin-A u.a. Im Rahmen der vorliegenden Doktorarbeit soll die Interaktion des PKC-bindenden Proteins PICK1 mit dem Rezeptor-CTerminus genauer untersucht werden. Das Protein PICK1 verfĂŒgt ĂŒber eine PDZ DomĂ€ne, welche die Assoziation mit anderen Proteinen, auch die mit mGluR7a, mediiert. Weitere Motive sind zwei coiledcoil Motive, welche fĂŒr die Dimerisierung von PICK1 verantwortlich sind; eine azide Glutamat-Aspartat-reiche Region (E/D Motiv), die möglicherweise in Interaktionen mit weiteren Proteinen eine Rolle spielt, welche die synaptische Lokalisation des Rezeptors regulieren; sowie eine BAR DomĂ€ne, die an Membranlipide binden kann. Vorangegangene Untersuchungen zur Interaktion von PICK1 mit mGluR7a legten die Vermutung nahe, dass PICK1 entweder eine entscheidende Rolle bei der gezielten AnhĂ€ufung von mGluR7a am Ort der TransmitterausschĂŒttung spielt und/oder regulierend auf die PKC-vermittelte Signaltransduktion einwirkt. Jedoch konnte weder die eine noch fĂŒr die andere Hypothese aufgrund des Fehlens geeigneter in vivo Modelle experimentell belegt werden. Vor diesem Hintergrund ist die Generation einer geeigneten Mausmutante, in welcher die Interaktion der Rezeptor-C-Terminus von mGluR7a mit PICK1 gestört ist, das vornehmliche Ziel dieser Doktorarbeit..
The Reciprocal Relationships Among Parentsâ Expectations, Adolescentsâ Expectations, and Adolescentsâ Achievement: A Two-Wave Longitudinal Analysis of the NELS Data
Previous research has consistently demonstrated the importance of parentsâ expectations and adolescentsâ expectations on adolescentsâ academic achievement. Less is known, however, about the reciprocal relationships among these constructs. To address this issue, we analyzed two waves of data from the National Education Longitudinal Study of 1988 (NELS:88) using longitudinal cross-lagged path models. The sample consisted of 14,376 students (51.1% females; 6.5% Asian, 11.1% Hispanic, 9.2% African American, and 73.2% White). Results indicated that there was a reciprocal relationship between parentsâ expectations and adolescentsâ expectations (i.e., they had mutual influence on each other). Moreover, there was a reciprocal relationship between expectations (both parentsâ and adolescentsâ) and adolescentsâ academic achievement. Multiple-group analyses of gender and ethnicity revealed that the effects of parentsâ expectations on studentsâ expectations were stronger among males than among females. With respect to ethnic differences, the effects of adolescentsâ expectations were weakest on parentsâ expectations among African Americans as compared to the other ethnic groups (i.e., Asian, Hispanic and White). Implications of these findings are discussed
Automaticity in processing spatial-numerical associations: Evidence from a perceptual orientation judgment task of Arabic digits in frames.
Human adults are faster to respond to small/large numerals with their left/right hand when they judge the parity of numerals, which is known as the SNARC (spatial-numerical association of response codes) effect. It has been proposed that the size of the SNARC effect depends on response latencies. The current study introduced a perceptual orientation task, where participants were asked to judge the orientation of a digit or a frame surrounding the digit. The present study first confirmed the SNARC effect with native Chinese speakers (Experiment 1) using a parity task, and then examined whether the emergence and size of the SNARC effect depended on the response latencies (Experiments 2, 3, and 4) using a perceptual orientation judgment task. Our results suggested that (a) the automatic processing of response-related numerical-spatial information occurred with Chinese-speaking participants in the parity task; (b) the SNARC effect was also found when the task did not require semantic access; and (c) the size of the effect depended on the processing speed of the task-relevant dimension. Finally, we proposed an underlying mechanism to explain the SNARC effect in the perceptual orientation judgment task
All-in-one aerial image enhancement network for forest scenes
Drone monitoring plays an irreplaceable and significant role in forest firefighting due to its characteristics of wide-range observation and real-time messaging. However, aerial images are often susceptible to different degradation problems before performing high-level visual tasks including but not limited to smoke detection, fire classification, and regional localization. Recently, the majority of image enhancement methods are centered around particular types of degradation, necessitating the memory unit to accommodate different models for distinct scenarios in practical applications. Furthermore, such a paradigm requires wasted computational and storage resources to determine the type of degradation, making it difficult to meet the real-time and lightweight requirements of real-world scenarios. In this paper, we propose an All-in-one Image Enhancement Network (AIENet) that can restore various degraded images in one network. Specifically, we design a new multi-scale receptive field image enhancement block, which can better reconstruct high-resolution details of target regions of different sizes. In particular, this plug-and-play module enables it to be embedded in any learning-based model. And it has better flexibility and generalization in practical applications. This paper takes three challenging image enhancement tasks encountered in drone monitoring as examples, whereby we conduct task-specific and all-in-one image enhancement experiments on a synthetic forest dataset. The results show that the proposed AIENet outperforms the state-of-the-art image enhancement algorithms quantitatively and qualitatively. Furthermore, extra experiments on high-level vision detection also show the promising performance of our method compared with some recent baselines.Award-winningPostprint (published version
Effect of rs1344706 in the ZNF804A gene on the brain network.
ZNF804A rs1344706 (A/C) was the first SNP that reached genome-wide significance for schizophrenia. Recent studies have linked rs1344706 to functional connectivity among specific brain regions. However, no study thus far has examined the role of this SNP in the entire functional connectome. In this study, we used degree centrality to test the role of rs1344706 in the whole-brain voxel-wise functional connectome during the resting state. 52 schizophrenia patients and 128 healthy controls were included in the final analysis. In our whole-brain analysis, we found a significant interaction effect of genotype Ă diagnosis at the precuneus (PCU) (cluster size = 52 voxels, peak voxel MNI coordinates: x = 9, y = - 69, z = 63, F = 32.57, FWE corrected P < 0.001). When we subdivided the degree centrality network according to anatomical distance, the whole-brain analysis also found a significant interaction effect of genotype Ă diagnosis at the PCU with the same peak in the short-range degree centrality network (cluster size = 72 voxels, F = 37.29, FWE corrected P < 0.001). No significant result was found in the long-range degree centrality network. Our results elucidated the contribution of rs1344706 to functional connectivity within the brain network, and may have important implications for our understanding of this risk gene's role in functional dysconnectivity in schizophrenia
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