Latest Research

Article  |  2020-11-30

Temporal Integrative Omics Reveals an Increase in Nondegradative Ubiquitylation during Primary Hepatocyte Dedifferentiation

Primary hepatocytes (PHCs) are widely used in various fields, but the progressive deterioration of liver-specific features in vitro significantly limits their application. While the transcriptional regulation and whole cell proteome (WCP) of PHCs have been extensively studied, only a small number of studies have addressed the role of posttranslational modifications in this process. To elucidate the underlying mechanisms that induce dedifferentiation, we carried out parallel quantifications of the transcriptome, WCP, ubiquitinome, and phosphoproteome of rat PHCs after 0, 6, 12, 24, and 48 h of in vitro culture. Our data constitute a detailed proteomic analysis of dedifferentiated PHCs including 2196 proteins, 2056 ubiquitinated sites, and 4932 phosphorylated peptides. We revealed a low correlation between the transcriptome and WCP during dedifferentiation. A combined analysis of the ubiquitinome with the corresponding WCP indicated that the dedifferentiation of PHCs led to an increase in nondegradative K27 ubiquitination. Functional analysis of the altered phosphoproteins suggested a significant enrichment in ferroptosis. In all, 404 proteins with both ubiquitination and phosphorylation were identified to be involved in critical metabolic events. Furthermore, Ptbp1, Hnrpd, Hnrnpu, and Srrm2 were identified as hub genes. Taken together, our data provide new insights into proteome dynamics during PHC dedifferentiation and potential targets to inhibit the dedifferentiation process.

Zhengyi Jiang ,   Zeyu Sun   et al.

Article  |  2020-11-30

Challenges and Solutions for the Additive Manufacturing of Biodegradable Magnesium Implants

Due to their capability of fabricating geometrically complex structures, additive manufacturing (AM) techniques have provided unprecedented opportunities to produce biodegradable metallic implants— especially using Mg alloys, which exhibit appropriate mechanical properties and outstanding biocompatibility. However, many challenges hinder the fabrication of AM-processed biodegradable Mg-based implants, such as the difficulty of Mg powder preparation, powder splash, and crack formation during the AM process. In the present work, the challenges of AM-processed Mg components are analyzed and solutions to these challenges are proposed. A novel Mg-based alloy (JDBM) powder with a smooth surface and good roundness was first synthesized successfully, and the AM parameters for Mg-based alloys were optimized. Based on the optimized parameters, porous JDBM scaffolds with three different architectures (biomimetic, diamond, and gyroid) were then fabricated by selective laser melting (SLM), and their mechanical properties and degradation behavior were evaluated. Finally, the gyroid scaffolds with the best performance were selected for dicalcium phosphate dihydrate (DCPD) coating treatment, which greatly suppressed the degradation rate and increased the cytocompatibility, indicating a promising prospect for clinical application as bone tissue engineering scaffolds.

Yinchuan Wang ,   Penghuai Fu   et al.

Article  |  2020-10-14

Artificial intelligence and wireless communications

The applications of (AI) and (ML) technologies in have drawn significant attention recently. AI has demonstrated real success in speech understanding, image identification, and natural language processing domains, thus exhibiting its great potential in solving problems that cannot be easily modeled. AI techniques have become an enabler in to fulfill the increasing and diverse requirements across a large range of application scenarios. In this paper, we elaborate on several typical wireless scenarios, such as channel modeling, channel decoding and signal detection, and channel coding design, in which AI plays an important role in . Then, AI and information theory are discussed from the viewpoint of the information bottleneck. Finally, we discuss some ideas about how AI techniques can be deeply integrated with wireless communication systems.

Jun Wang ,   Rong Li   et al.

Article  |  2020-10-14

Multi-dimensional optimization for approximate near-threshold computing

The demise of Dennard’s scaling has created both power and utilization wall challenges for computer systems. As transistors operating in the near-threshold region are able to obtain flexible trade-offs between power and , it is regarded as an alternative solution to the scaling challenge. A reduction in supply voltage will nevertheless generate significant reliability challenges, while maintaining an error-free system that generates high costs in both and consumption. The main purpose of research on computer architecture has therefore shifted from improvement to complex multi-objective optimization. In this paper, we propose a three-dimensional optimization approach which can effectively identify the best system configuration to establish a balance among , , and reliability. We use a dynamic programming algorithm to determine the proper voltage and approximate level based on three predictors: system , consumption, and output quality. We propose an which uses a hardware/software co-design fault injection platform to evaluate the impact of the error on output quality under (NTC). Evaluation results demonstrate that our approach can lead to a 28% improvement in output quality with a 10% drop in overall efficiency; this translates to an approximately 20% average improvement in accuracy, power, and .

Jing Wang ,   Wei-wei Liang   et al.

Article  |  2020-10-14

A low-overhead asynchronous consensus framework for distributed bundle adjustment

Generally, the (DBA) method uses multiple worker nodes to solve the bundle adjustment problems and overcomes the computation and memory storage limitations of a single computer. However, the performance considerably degrades owing to the introduced by the additional block partitioning step and synchronous waiting. Therefore, we propose a low- consensus framework. A based asynchronous method is proposed to early achieve consensus with respect to the faster worker nodes to avoid waiting for the slower ones. A scene summarization procedure is designed and integrated into the block partitioning step to ensure that clustering can be performed on the small summarized scene. Experiments conducted on public datasets show that our method can improve the worker node utilization rate and reduce the block partitioning time. Also, sample applications are demonstrated using our large-scale culture heritage datasets.

Zhuo-hao Liu ,   Chang-yu Diao   et al.

Article  |  2020-10-14

Automatic synthesis of advertising images according to a specified style

Images are widely used by companies to advertise their products and promote awareness of their brands. The automatic synthesis of advertising images is challenging because the advertising message must be clearly conveyed while complying with the style required for the product, brand, or target audience. In this study, we proposed a to capture individual design attributes and the relationships between elements in advertising images with the aim of automatically synthesizing the input of elements into an advertising image according to a specified style. To achieve this multi-format advertisement design, we created a dataset containing 13 280 advertising images with rich annotations that encompassed the outlines and colors of the elements, in addition to the classes and goals of the advertisements. Using our probabilistic models, users guided the style of synthesized advertisements via additional constraints (e.g., context-based keywords). We applied our method to a variety of design tasks, and the results were evaluated in several perceptual studies, which showed that our method improved users’ satisfaction by 7.1% compared to designs generated by nonprofessional students, and that more users preferred the coloring results of our designs to those generated by the color harmony model and Colormind.

Wei-tao You ,   Hao Jiang   et al.