2017
DOI: 10.1073/pnas.1618213114
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Transmembrane protein 108 is required for glutamatergic transmission in dentate gyrus

Abstract: Neurotransmission in dentate gyrus (DG) is critical for spatial coding, learning memory, and emotion processing. Although DG dysfunction is implicated in psychiatric disorders, including schizophrenia, underlying pathological mechanisms remain unclear. Here we report that transmembrane protein 108 (Tmem108), a novel schizophrenia susceptibility gene, is highly enriched in DG granule neurons and its expression increased at the postnatal period critical for DG development. Tmem108 is specifically expressed in th… Show more

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Cited by 24 publications
(42 citation statements)
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“…These SNPs were nominally associated with several other cellular signatures including one for activated dendritic cells and one for the fraction of NK cells. TMEM108 is not known to have an effect on interferon signaling, but may signal through the WNT-Beta Catenin pathway (Jiao et al, 2017). TMEM108 is also a cancer-testis (CT) antigen.…”
Section: Tcga Only Includes Common Variant Germline Data and Not Wholmentioning
confidence: 99%
“…These SNPs were nominally associated with several other cellular signatures including one for activated dendritic cells and one for the fraction of NK cells. TMEM108 is not known to have an effect on interferon signaling, but may signal through the WNT-Beta Catenin pathway (Jiao et al, 2017). TMEM108 is also a cancer-testis (CT) antigen.…”
Section: Tcga Only Includes Common Variant Germline Data and Not Wholmentioning
confidence: 99%
“…Similar to other optimization-based approaches like simulated annealing [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], the goal of deep learningbased method is to minimize the loss function, which is used to evaluate the discrepancy between network prediction and target. On the basis of Eq.…”
Section: Loss Functionmentioning
confidence: 99%
“…During the past decades, various reconstruction methods have been developed , and popular algorithms include optimization-based method [7][8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23], multi-point statistics (MPS) [24][25][26], direct sampling (DS) [27], CC-SIM [28][29][30][31][32], machine learning and deep learning based method [33][34][35][36][37][38][39][40][41], and superdimension method recently proposed [42,43]. It is well known that generally the prerequisite of this reconstruction methodology is that the 2D training image (TI) needs to meet the requirements of stationarity and ergodicity, in other words, 2D image is able to statistically represent the main characteristic of the entire 3D structure.…”
Section: Introductionmentioning
confidence: 99%
“…Recently, the two-point correlation and lineal path functions have been discussed from the point of view of their efficiency and accuracy of microstructure reconstruction [12]. Within the SA approach, particularly efficient is the hybrid pair of the standard two-point correlation function, S 2 , providing information about the distribution of pair separations and the cluster one, C 2 , sensitive to topological connectedness information [13]. These functions may be equivalently treated as spatial correlation descriptors.…”
Section: Introductionmentioning
confidence: 99%
“…One of them is Co/C thin film evolving along temperature [25] while a concrete sample cross-section considered in Ref. [13] is the second one. Now, instead of the total number N t we prefer to use the number N a of the accepted MC steps.…”
Section: Introductionmentioning
confidence: 99%