Genetically engineered mouse models for functional studies of SKP1-CUL1-F-box-protein (SCF) E3 ubiquitin ligases

The SCF (SKP1 (S-phase-kinase-associated protein 1), Cullin-1, F-box protein) E3 ubiquitin ligases, the founding member of Cullin-RING ligases (CRLs), are the largest family of E3 ubiquitin ligases in mammals. Each individual SCF E3 ligase consists of one adaptor protein SKP1, one scaffold protein cullin-1 (the first family member of the eight cullins), one F-box protein out of 69 family members, and one out of two RING (Really Interesting New Gene) family proteins RBX1/ROC1 or RBX2/ROC2/SAG/RNF7. Various combinations of these four components construct a large number of SCF E3s that promote the degradation of many key regulatory proteins in cell-context, temporally, and spatially dependent manners, thus controlling precisely numerous important cellular processes, including cell cycle progression, apoptosis, gene transcription, signal transduction, DNA replication, maintenance of genome integrity, and tumorigenesis. To understand how the SCF E3 ligases regulate these cellular processes and embryonic development under in vivo physiological conditions, a number of mouse models with transgenic (Tg) expression or targeted deletion of components of SCF have been established and characterized. In this review, we will provide a brief introduction to the ubiquitin-proteasome system (UPS) and the SCF E3 ubiquitin ligases, followed by a comprehensive overview on the existing Tg and knockout (KO) mouse models of the SCF E3s, and discuss the role of each component in mouse embryogenesis, cell proliferation, apoptosis, carcinogenesis, as well as other pathogenic processes associated with human diseases. We will end with a brief discussion on the future directions of this research area and the potential applications of the knowledge gained to more effective therapeutic interventions of human diseases

Spin-resolved electron waiting times in a quantum dot spin valve

We study the electronic waiting time distributions (WTDs) in a non-interacting quantum dot spin valve by varying spin polarization and the noncollinear angle between the magnetizations of the leads using scattering matrix approach. Since the quantum dot spin valve involves two channels (spin up and down) in both the incoming and outgoing channels, we study three different kinds of WTDs, which are two-channel WTD, spin-resolved single-channel WTD and cross-channel WTD. We analyze the behaviors of WTDs in short times, correlated with the current behaviors for different spin polarizations and noncollinear angles. Cross-channel WTD reflects the correlation between two spin channels and can be used to characterize the spin transfer torque process. We study the influence of the earlier detection on the subsequent detection from the perspective of cross-channel WTD, and define the influence degree quantity as the cumulative absolute difference between cross-channel WTDs and first passage time distributions to quantitatively characterize the spin flip process. The influence degree shows a similar behavior with spin transfer torque and can be a new pathway to characterize spin correlation in spintronics system.Comment: 9 pages, 7 figure

Iteratively Learn Diverse Strategies with State Distance Information

In complex reinforcement learning (RL) problems, policies with similar rewards may have substantially different behaviors. It remains a fundamental challenge to optimize rewards while also discovering as many diverse strategies as possible, which can be crucial in many practical applications. Our study examines two design choices for tackling this challenge, i.e., diversity measure and computation framework. First, we find that with existing diversity measures, visually indistinguishable policies can still yield high diversity scores. To accurately capture the behavioral difference, we propose to incorporate the state-space distance information into the diversity measure. In addition, we examine two common computation frameworks for this problem, i.e., population-based training (PBT) and iterative learning (ITR). We show that although PBT is the precise problem formulation, ITR can achieve comparable diversity scores with higher computation efficiency, leading to improved solution quality in practice. Based on our analysis, we further combine ITR with two tractable realizations of the state-distance-based diversity measures and develop a novel diversity-driven RL algorithm, State-based Intrinsic-reward Policy Optimization (SIPO), with provable convergence properties. We empirically examine SIPO across three domains from robot locomotion to multi-agent games. In all of our testing environments, SIPO consistently produces strategically diverse and human-interpretable policies that cannot be discovered by existing baselines

Analysis of four achaete-scute homologs in Bombyx mori reveals new viewpoints of the evolution and functions of this gene family

<p>Abstract</p> <p>Background</p> <p><it>achaete-scute </it>complexe (<it>AS-C</it>) has been widely studied at genetic, developmental and evolutional levels. Genes of this family encode proteins containing a highly conserved bHLH domain, which take part in the regulation of the development of central nervous system and peripheral nervous system. Many <it>AS-C </it>homologs have been isolated from various vertebrates and invertebrates. Also, <it>AS-C </it>genes are duplicated during the evolution of Diptera. Functions besides neural development controlling have also been found in <it>Drosophila AS-C </it>genes.</p> <p>Results</p> <p>We cloned four <it>achaete-scute </it>homologs (<it>ASH</it>) from the lepidopteran model organism <it>Bombyx mori</it>, including three proneural genes and one neural precursor gene. Proteins encoded by them contained the characteristic bHLH domain and the three proneural ones were also found to have the C-terminal conserved motif. These genes regulated promoter activity through the Class A E-boxes <it>in vitro</it>. Though both <it>Bm-ASH </it>and <it>Drosophila AS-C </it>have four members, they are not in one by one corresponding relationships. Results of RT-PCR and real-time PCR showed that <it>Bm-ASH </it>genes were expressed in different larval tissues, and had well-regulated expressional profiles during the development of embryo and wing/wing disc.</p> <p>Conclusion</p> <p>There are four <it>achaete-scute </it>homologs in <it>Bombyx mori</it>, the second insect having four <it>AS-C </it>genes so far, and these genes have multiple functions in silkworm life cycle. <it>AS-C </it>gene duplication in insects occurs after or parallel to, but not before the taxonomic order formation during evolution.</p

Accurate Sparse-Projection Image Reconstruction via Nonlocal TV Regularization

Sparse-projection image reconstruction is a useful approach to lower the radiation dose; however, the incompleteness of projection data will cause degeneration of imaging quality. As a typical compressive sensing method, total variation has obtained great attention on this problem. Suffering from the theoretical imperfection, total variation will produce blocky effect on smooth regions and blur edges. To overcome this problem, in this paper, we introduce the nonlocal total variation into sparse-projection image reconstruction and formulate the minimization problem with new nonlocal total variation norm. The qualitative and quantitative analyses of numerical as well as clinical results demonstrate the validity of the proposed method. Comparing to other existing methods, our method more efficiently suppresses artifacts caused by low-rank reconstruction and reserves structure information better

Ultra Dual-Path Compression For Joint Echo Cancellation And Noise Suppression

Echo cancellation and noise reduction are essential for full-duplex communication, yet most existing neural networks have high computational costs and are inflexible in tuning model complexity. In this paper, we introduce time-frequency dual-path compression to achieve a wide range of compression ratios on computational cost. Specifically, for frequency compression, trainable filters are used to replace manually designed filters for dimension reduction. For time compression, only using frame skipped prediction causes large performance degradation, which can be alleviated by a post-processing network with full sequence modeling. We have found that under fixed compression ratios, dual-path compression combining both the time and frequency methods will give further performance improvement, covering compression ratios from 4x to 32x with little model size change. Moreover, the proposed models show competitive performance compared with fast FullSubNet and DeepFilterNet. A demo page can be found at hangtingchen.github.io/ultra_dual_path_compression.github.io/.Comment: Accepted by Interspeech 202

Improving the critical speeds of high-speed trains using magnetorheological technology

With the rapid development of high-speed railways, vibration control for maintaining stability, passenger comfort, and safety has become an important area of research. In order to investigate the mechanism of train vibration, the critical speeds of various DOFs with respect to suspension stiffness and damping are first calculated and analyzed based on its dynamic equations. Then, the sensitivity of the critical speed is studied by analyzing the influence of different suspension parameters. On the basis of these analyses, a conclusion is drawn that secondary lateral damping is the most sensitive suspension damper. Subsequently, the secondary lateral dampers are replaced with magnetorheological fluid (MRF) dampers. Finally, a high-speed train model with MRF dampers is simulated by a combined ADAMS and MATLAB simulation and tested in a roller rig test platform to investigate the mechanism of how the MRF damper affects the train\u27s stability and critical speed. The results show that the semi-active suspension installed with MRF dampers substantially improves the stability and critical speed of the train