Polycomb group (PcG) proteins initiate the formation of repressed chromatin domains and regulate developmental gene expression. A mammalian PcG protein, enhancer of zeste homolog 2 (Ezh2), triggers ...transcriptional repression by catalyzing the addition of methyl groups onto lysine 27 of histone H3 (H3K27me2/3). This action facilitates the binding of other PcG proteins to chromatin for purposes of transcriptional silencing. Interestingly, there exists a paralog of Ezh2, termed Ezh1, whose primary function remains unclear. Here, we provide evidence for genome-wide association of Ezh1 complex with active epigenetic mark (H3K4me3), RNA polymerase II (Pol II), and mRNA production. Ezh1 depletion reduced global Pol II occupancy within gene bodies and resulted in delayed transcriptional activation during differentiation of skeletal muscle cells. Conversely, overexpression of wild-type Ezh1 led to premature gene activation and rescued Pol II occupancy defects in Ezh1-depleted cells. Collectively, these findings reveal a role for a PcG complex in promoting mRNA transcription.
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► The majority of Ezh1-occupied genes are devoid of repressed H3K27me3+ chromatin domains ► Ezh1 occupies H3K4me3+ genes ► The majority of genes occupied by Ezh1 are transcriptionally active ► Ezh1 promotes RNA polymerase II elongation genome-wide
Automatic modulation classification is an essential and challenging topic in the development of cognitive radios, and it is the cornerstone of adaptive modulation and demodulation abilities to sense ...and learn surrounding environments and make corresponding decisions. In this paper, we propose a spectrum interference-based two-level data augmentation method in deep learning for automatic modulation classification. Since the frequency variation over time is the most important distinction between radio signals with various modulation schemes, we plan to expand samples by introducing different intensities of interference to the spectrum of radio signals. The original signal is first transformed into the frequency domain by using short-time Fourier transform, and the interference to the spectrum can be realized by bidirectional noise masks that satisfy the specific distribution. The augmented signals can be reconstructed through inverse Fourier transform based on the interfered spectrum, and then, the original and augmented signals are fed into the network. Finally, data augmentation at both training and testing stages can be used to improve the generalization performance of deep neural network. To the best of our knowledge, this is the first time that radio signals are augmented to help modulation classification by considering the frequency domain information. Moreover, we have proved that data augmentation at the test stage can be interpreted as model ensemble. By comparing with a variety of data augmentation techniques and state-of-the-art modulation classification methods on the public dataset RadioML 2016.10a, experimental results illustrate the effectiveness and advancement of proposed method.
Developing an anti-infective shape-memory hemostatic sponge able to guide in situ tissue regeneration for noncompressible hemorrhages in civilian and battlefield settings remains a challenge. Here we ...engineer hemostatic chitosan sponges with highly interconnective microchannels by combining 3D printed microfiber leaching, freeze-drying, and superficial active modification. We demonstrate that the microchannelled alkylated chitosan sponge (MACS) exhibits the capacity for water and blood absorption, as well as rapid shape recovery. We show that compared to clinically used gauze, gelatin sponge, CELOX™, and CELOX™-gauze, the MACS provides higher pro-coagulant and hemostatic capacities in lethally normal and heparinized rat and pig liver perforation wound models. We demonstrate its anti-infective activity against S. aureus and E. coli and its promotion of liver parenchymal cell infiltration, vascularization, and tissue integration in a rat liver defect model. Overall, the MACS demonstrates promising clinical translational potential in treating lethal noncompressible hemorrhage and facilitating wound healing.
Implanted scaffolds with inductive niches can facilitate the recruitment and differentiation of host cells, thereby enhancing endogenous tissue regeneration. Extracellular matrix (ECM) scaffolds ...derived from cultured cells or natural tissues exhibit superior biocompatibility and trigger favourable immune responses. However, the lack of hierarchical porous structure fails to provide cells with guidance cues for directional migration and spatial organization, and consequently limit the morpho-functional integration for oriented tissues. Here, we engineer ECM scaffolds with parallel microchannels (ECM-C) by subcutaneous implantation of sacrificial templates, followed by template removal and decellularization. The advantages of such ECM-C scaffolds are evidenced by close regulation of in vitro cell activities, and enhanced cell infiltration and vascularization upon in vivo implantation. We demonstrate the versatility and flexibility of these scaffolds by regenerating vascularized and innervated neo-muscle, vascularized neo-nerve and pulsatile neo-artery with functional integration. This strategy has potential to yield inducible biomaterials with applications across tissue engineering and regenerative medicine.
Mesenchymal stromal/stem cells (MSCs) are widely utilized in cell therapy because of their robust immunomodulatory and regenerative properties. Their paracrine activity is one of the most important ...features that contribute to their efficacy. Recently, it has been demonstrated that the production of various factors via extracellular vesicles, especially exosomes, governs the principal efficacy of MSCs after infusion in experimental models. Compared to MSCs themselves, MSC-derived exosomes (MSC-Exos) have provided significant advantages by efficiently decreasing unfavorable adverse effects, such as infusion-related toxicities. MSC-Exos is becoming a promising cell-free therapeutic tool and an increasing number of clinical studies started to assess the therapeutic effect of MSC-Exos in different diseases. In this review, we summarized the ongoing and completed clinical studies using MSC-Exos for immunomodulation, regenerative medicine, gene delivery, and beyond. Additionally, we summarized MSC-Exos production methods utilized in these studies with an emphasis on MSCs source, MSC-Exos isolation methods, characterization, dosage, and route of administration. Lastly, we discussed the current challenges and future directions of exosome utilization in different clinical studies as a novel therapeutic strategy.
Although deep convolutional neural networks (CNNs) have demonstrated remarkable performance on multiple computer vision tasks, researches on adversarial learning have shown that deep models are ...vulnerable to adversarial examples, which are crafted by adding visually imperceptible perturbations to the input images. Most of the existing adversarial attack methods only create a single adversarial example for the input, which just gives a glimpse of the underlying data manifold of adversarial examples. An attractive solution is to explore the solution space of the adversarial examples and generate a diverse bunch of them, which could potentially improve the robustness of real-world systems and help prevent severe security threats and vulnerabilities. In this paper, we present an effective method, called Hamiltonian Monte Carlo with Accumulated Momentum (HMCAM), aiming to generate a sequence of adversarial examples. To improve the efficiency of HMC, we propose a new regime to automatically control the length of trajectories, which allows the algorithm to move with adaptive step sizes along the search direction at different positions. Moreover, we revisit the reason for high computational cost of adversarial training under the view of MCMC and design a new generative method called Contrastive Adversarial Training (CAT), which approaches equilibrium distribution of adversarial examples with only few iterations by building from small modifications of the standard Contrastive Divergence (CD) and achieve a trade-off between efficiency and accuracy. Both quantitative and qualitative analysis on several natural image datasets and practical systems have confirmed the superiority of the proposed algorithm.
As a classical method to deal with nonlinear and nonstationary signals, the Hilbert⁻Huang transform (HHT) is widely used in various fields. In order to overcome the drawbacks of the Hilbert⁻Huang ...transform (such as end effects and mode mixing) during the process of empirical mode decomposition (EMD), a revised Hilbert⁻Huang transform is proposed in this article. A method called local linear extrapolation is introduced to suppress end effects, and the combination of adding a high-frequency sinusoidal signal to, and embedding a decorrelation operator in, the process of EMD is introduced to eliminate mode mixing. In addition, the correlation coefficients between the analyzed signal and the intrinsic mode functions (IMFs) are introduced to eliminate the undesired IMFs. Simulation results show that the improved HHT can effectively suppress end effects and mode mixing. To verify the effectiveness of the new HHT method with respect to fault diagnosis, the revised HHT is applied to analyze the vibration displacement signals in a rotor system collected under normal, rubbing, and misalignment conditions. The simulation and experimental results indicate that the revised HHT method is more reliable than the original with respect to fault diagnosis in a rotor system.
Using conventional and unconventional oil and gas resource evaluation methods with play as a unit, this study evaluates the oil and gas geology and resource potential of conventional oil and gas ...resources and seven types of unconventional resources in the global major oil and gas basins (excluding China). For the first time, resource evaluation data with independent intellectual property rights has been obtained. According to evaluation and calculation, the global recoverable conventional oil resources are 5 350.0×108 t, the recoverable condensate oil resources are 496.2×108 t, and the recoverable natural gas resources are 588.4×1012 m3. The remaining oil and gas 2P recoverable reserves are 4 212.6×108 t, the reserve growth of oil and gas fields are 1 531.7×108 t. The undiscovered oil and gas recoverable resources are 3 065.5×108 t. The global unconventional oil recoverable resources are 4 209.4×108 t and the unconventional natural gas recoverable resources are 195.4×1012 m3. The evaluation results show that the global conventional and unconventional oil and gas resources are still abundant.
Duvernay shale spans over 6 million acres with a total resource of 440 billion barrels' oil equivalent in the Western Canada Sedimentary Basin (WCSB). The oil recovery factors typically decrease with ...the decreasing of gas-oil ratio (GOR) in oil window of Duvernay shale. The volatile oil recovery factors are typically 5-10%. Enhanced oil recovery technologies should be applied to improve the economics of the reservoirs. In this paper, the volatile oil from the Duvernay shale was taken as an example for phase behavior study. We analyzed the nanopore confinement on phase behavior and physical properties of Duvernay shale oil. The shift of critical properties was quantified within nanopores. With the confinement of nanopores, the viscosity, density, and bubble point pressure of the oil decrease with the shrinking of the pore size. Minimum miscibility pressure (MMP) was calculated for different injected gases. The MMP from high to low is N2 > CH4 > lean gas > CO2. In the case of injecting the same gas component, the MMP decreases as the pore size decreases. The wellhead rich gas is suggested to be the main gas source for gas injection in Duvernay shale. The formation pressure should be rapidly increased to the MMP and maintained close to it, which would help to improve the effect of gas injection and enhance shale oil recovery. This paper can provide critical insights for the research of shale oil gas injection for enhanced oil recovery.
Litchi clusters in fruit groves are randomly scattered and occur irregularly, so it is difficult to detect and locate the fruit-bearing branches of multiple litchi clusters at one time. This is a ...highly challenging task related to continuous operation in the natural environment for visual-based harvesting robots to carry out. In this study, a reliable algorithm based on RGB-depth (RGB-D) cameras in the fields was developed to accurately and automatically detect and locate the fruit-bearing branches of multiple litchi clusters simultaneously in large environments. A semantics segmentation method, Deeplabv3, was employed to segment the RGB images into three categories: background, fruit and twig. A pre-processing step is proposed to align the segmented RGB images and remove the twigs that did not bear fruits. Subsequently, the twig binary map image was processed via skeleton extraction and pruning operations, which left behind only the main branches of twigs. A method for non-parametric density-based spatial clustering of application with noise was used to cluster the pixels in the three-dimensional space of the skeleton map of the branches; thus, the fruit-bearing branches belonging to the same litchi clusters were determined. Finally, a three-dimensional straight line was fitted to each cluster via principal component analysis, and the linear information corresponded to the location of the fruit-bearing branches. In the experiments, 452 pairs of RGB-D images under different illumination were collected to test the proposed algorithm. The results show that the detection accuracy of a litchi fruit-bearing branch is 83.33%, positioning accuracy is 17.29°±24.57°, and execution time for the determination of a single litchi fruit-bearing branch is 0.464s. Field experiments show that this method can effectively guide the robot to complete continuous picking tasks.