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The survival of motor neuron (SMN) protein is a major component of the pre-mRNA splicing machinery and is required for RNA metabolism. Although SMN has been considered a fundamental gene for the central nervous system, due to its relationship with neuromuscular diseases, such as spinal muscular atrophy, recent studies have also revealed the requirement of SMN in non-neuronal cells in the peripheral regions. Here, we report that the fibro-adipogenic progenitor subpopulation expressing Dpp4 (Dpp4+ FAPs) is required for the neuromuscular system. Furthermore, we also reveal that BRCA1-associated protein-1 (Bap1) is crucial for the stabilization of SMN in FAPs by preventing its ubiquitination-dependent degradation. Inactivation of Bap1 in FAPs decreased SMN levels and accompanied degeneration of the neuromuscular junction, leading to loss of motor neurons and muscle atrophy. Overexpression of the ubiquitination-resistant SMN variant, SMNK186R, in Bap1-null FAPs completely prevented neuromuscular degeneration. In addition, transplantation of Dpp4+ FAPs, but not Dpp4– FAPs, completely rescued neuromuscular defects. Our data reveal the crucial role of Bap1-mediated SMN stabilization in Dpp4+ FAPs for the neuromuscular system and provide the possibility of cell-based therapeutics to treat neuromuscular diseases.

While many researchers attempt to build up different kinds of ontologies by means of Wikipedia, the possibility of deriving high-quality domain specific subset of Wikipedia using its own category structure still remains undervalued. We prove the necessity of such processing in this paper and also propose an appropriate technique. As a result, the size of knowledge base for our text processing framework has been reduced by more than order, while the precision of disambiguating musical metadata (ID3 tags) has decreased from 98% to 64%.

Activated Foxp3+ regulatory T (Treg) cells differentiate into effector Treg (eTreg) cells to maintain peripheral immune homeostasis and tolerance. T cell receptor (TCR)-mediated induction and regulation of store-operated Ca2+ entry (SOCE) is essential for eTreg cell differentiation and function. However, SOCE regulation in Treg cells remains unclear. Here, we show that inositol polyphosphate multikinase (IPMK), which generates inositol tetrakisphosphate and inositol pentakisphosphate, is a pivotal regulator of Treg cell differentiation downstream of TCR signaling. IPMK is highly expressed in TCR-stimulated Treg cells and promotes a TCR-induced Treg cell program. IPMK-deficient Treg cells display aberrant T cell activation and impaired differentiation into RORγt+ Treg cells and tissue-resident Treg cells. Mechanistically, IPMK controls the generation of higher-order inositol phosphates, thereby promoting Ca2+ mobilization and Treg cell effector functions. Our findings identify IPMK as a critical regulator of TCR-mediated Ca2+ influx and highlight the importance of IPMK in Treg cell-mediated immune homeostasis. [ABSTRACT FROM AUTHOR]

Abstract  This paper proposes a new play segmentation algorithm using a local adaptive model for each sports game, in which the play start shots (PSS) that represent the start of each play segment are detected by comparing all of keyframes with the PSS model. The PSS model is calculated on the fly using generic clustering algorithm and a repetitive characteristic of the PSS. The end of each play segment (the play end shot (PES)) is determined by detecting close up shots using the field color extracted from the play start shots since the camera will focus on the players or the audience with close up view. Experimental results with 28 baseball videos show that good performance can be obtained with the proposed algorithm compared to other algorithms. [ABSTRACT FROM AUTHOR]

Time-shift is a crucial function of interactive Televisions as like DVR and internet TV broadcasting services. Automatic important event detection allows users utilize time- shift function conveniently. In this paper, we propose a method to extract important events in baseball videos. In the proposed method, we first detect play scenes and audio events separately from video and audio tracks. For robust play scene extraction, we proposed off-line learning model having local adaptation based on ongoing analyzed video. And we implemented the audio event detection with a SVM-based classifier. Final important events are determined by a combination of each audio-visual detection results in real time. We evaluated our method with a baseball database of Korean and Major League games. Experimental results show that the implemented system runs in real time and achieves a remarkable performance of 0.85 recall and 0.97 precision rates. [ABSTRACT FROM AUTHOR]