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| 1 | Targeting of Vacuolar Membrane Localized Members of the TPK Channel Family显示文摘Arabidopsis thaliana 的双人脚踏车毛孔钾隧道家庭的四个成员(TPK1, 2, 3,和 5 ) 居住在 vacuolar 膜,而 TPK4 是一条血浆膜 K+ 隧道。由构造在 TPK1 和 TPK4 之间的怪物,我们试图识别涉及 trafficking 进程并且发现 TPK1 细胞质的 C 终端域(CT ) 为 ER-是批评的隧道域 -- 象排序 Golgi 步一样。后面的指导地点的 mutagenesis,我们识别了为 TPK1 的嗯出口要求的一个 diacidic 主题(DLE ) 。然而,在 C 终点的这个 diacidic 主题没在 TPK 家庭的另外的成员之中被保存,并且排序的 TPK3 独立于它的 CT。而且, TPK1 的 14-3-3 绑定地点,为隧道激活必要,不涉及隧道排序。 | Marcel Dunkel Andreas Latz Karin Schumacher Thomas Muller Dirk Becker Rainer Hedrich | 2008 | Molecular Plant2008，1，6： | 5 |
| 2 | Targeting of the pro-apoptotic VDAC-like porin (PorB) of Neisseria gonorrhoeae to mitochondria of infected cells显示文摘 | Anne Muller Dirk Gunther Volker Brinkmann | 2000 | The EMBO Journal2000，19，20： | 1 |
| 3 | Cost-effectiven-ess of different strategies for selecting and treating individuals at increased risk of osteoporosis or osteopenia:a syetematic review显示文摘 | Dirk Muller Tannis Pulm Health Econl | 2012 | Value Health2012，15，2： | 1 |
| 4 | The value of reoperation for recurrent glioblastoma 显示文摘 | Dirks P Bernstein M Muller PJ | 1993 | Can J Surg1993，36，3： | 1 |
| 5 | Osteomodulin downregulation is associated with osteoarthritis development显示文摘Abnormal subchondral bone remodeling leading to sclerosis is a main feature of osteoarthritis(OA), and osteomodulin(OMD), a proteoglycan involved in extracellular matrix mineralization, is associated with the sclerotic phenotype. However, the functions of OMD remain poorly understood, specifically in vivo. We used Omd knockout and overexpressing male mice and mutant zebrafish to study its roles in bone and cartilage metabolism and in the development of OA. The expression of Omd is deeply correlated with bone and cartilage microarchitectures affecting the bone volume and the onset of subchondral bone sclerosis and spontaneous cartilage lesions. Mechanistically, OMD binds to RANKL and inhibits osteoclastogenesis, thus controlling the balance of bone remodeling. In conclusion, OMD is a key factor in subchondral bone sclerosis associated with OA. It participates in bone and cartilage homeostasis by acting on the regulation of osteoclastogenesis. Targeting OMD may be a promising new and personalized approach for OA. | Jérémie Zappia Qiao Tong Renée Van der Cruyssen Frederique MFCornelis Cécile Lambert Tiago Pinto Coelho Juliane Grisart Erika Kague Rik JLories Marc Muller Dirk Elewaut Chrissy LHammond Christelle Sanchez Yves Henrotin | 2023 | Bone Research2023，11，4： | 0 |
| 6 | Safe operation of online learning data driven model predictive control of building energy systems显示文摘Model predictive control is a promising approach to reduce the CO 2 emissions in the building sector.However,the vast modeling effort hampers the widescale practical application.Here,data-driven process models,like artificial neural networks,are well-suited to automatize the modeling.However,the underlying data set strongly determines the quality and reliability of artificial neural networks.In general,the validity domain of a machine learning model is limited to the data that was used to train it.Predictions based on system states outside that domain,so-called extrapolations,are unreliable and can negatively influence the control quality.We present a safe operation approach combined with online learning to deal with extrapolation in data-driven model predictive control.Here,the k-nearest neighbor algorithm is used to detect extrapolation to switch to a robust fallback controller.By continuously retraining the artificial neural networks during operation,we successively increase the validity domain of the artificial neural networks and the control quality.We apply the approach to control a building energy system provided by the BOPTEST framework.We compare controllers based on two data sets,one with extensive system excitation and one with baseline operation.The system is controlled to a fixed temperature set point in baseline operation.Therefore,the artificial neural networks trained on this data set tend to extrapolate in other operating points.We show that safe operation in combination with online learning significantly improves performance. | Phillip Stoffel Patrick Henkel Martin Ratz Alexander Kumpel Dirk Muller | 2023 | Energy and AI2023，14，4： | 0 |
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