22,903 results on '"Chen Dong"'
Search Results
152. High SVR12 With 8-Week Course of Direct-Acting Antivirals in Adolescents and Children With Chronic Hepatitis C: A Comprehensive Analysis
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Zuqiang Fu, Chen Dong, Zhijun Ge, Chunhui Wang, Yun Zhang, Chao Shen, Jun Li, Chuanlong Zhu, Yan Wang, Peng Huang, and Ming Yue
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hepatitis C virus ,direct-acting antivirals regimens ,adolescents and children ,sustained virological response ,treatment duration ,Medicine (General) ,R5-920 - Abstract
Direct-acting antiviral (DAA) treatment for 8 weeks has a sustained virological response rate in adults with chronic hepatitis C. We have conducted a systematic review and meta-analysis to compare the efficacy and safety of the 8-week vs. 12/24-week DAA treatment in adolescents and children with CHC. The PubMed, Web of Science, and Cochrane databases were searched for the relevant articles from January 1, 2017 to August 28, 2020 and further screened for literature reviews on April 1, 2021. Pool proportions with 95% CIs for SVR12 were summarized with fixed/random effects models using Freeman–Tukey double arcsine transformation. Subgroup analysis was used to explore the source of heterogeneity. Thirty-six relevant publications were identified. For adolescents aged 12–17 years old, the pooled SVR12 and AE rate were 99.4% (95% CI: 98.7–99.9) and 34.7% (95% CI: 31.9–37.6). No one discontinued treatment due to drug intolerance. In addition, the SVR12 adolescents treated for 12 and 8/24 weeks were 99.3% (95% CI: 98.4–99.9) and 100%, respectively. The pooled SVR12 rate, AEs, and SAEs for children younger than 12 years were 98.9% (95% CI: 97.3–99.8), 51.6% (95% CI: 47.0–56.2), and 1.1% (95% CI: 0.4–2.5), respectively. The most common AE was fatigue (28.4%). The SVR12 was 98.8% (95% CI: 97.1–99.8) and 100% for the pediatric patients treated for 12 weeks and 8/24 weeks, respectively. Taken together, DAAs are generally effective against CHC and well-tolerated by the adolescents and children. A treatment duration of 8 weeks is equally effective and safe as 12/24 weeks in this demographic group.
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- 2021
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153. Probing the signaling requirements for naive human pluripotency by high-throughput chemical screening
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Shafqat A. Khan, Kyoung-mi Park, Laura A. Fischer, Chen Dong, Tenzin Lungjangwa, Marta Jimenez, Dominick Casalena, Brian Chew, Sabine Dietmann, Douglas S. Auld, Rudolf Jaenisch, and Thorold W. Theunissen
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naive pluripotency ,primed pluripotency ,high-throughput screening ,signal transduction ,FGFR signaling pathway ,DNA methylation ,Biology (General) ,QH301-705.5 - Abstract
Summary: Naive human embryonic stem cells (hESCs) have been isolated that more closely resemble the pre-implantation epiblast compared to conventional “primed” hESCs, but the signaling principles underlying these discrete stem cell states remain incompletely understood. Here, we describe the results from a high-throughput screen using ∼3,000 well-annotated compounds to identify essential signaling requirements for naive human pluripotency. We report that MEK1/2 inhibitors can be replaced during maintenance of naive human pluripotency by inhibitors targeting either upstream (FGFR, RAF) or downstream (ERK1/2) kinases. Naive hESCs maintained under these alternative conditions display elevated levels of ERK phosphorylation but retain genome-wide DNA hypomethylation and a transcriptional identity of the pre-implantation epiblast. In contrast, dual inhibition of MEK and ERK promotes efficient primed-to-naive resetting in combination with PKC, ROCK, and TNKS inhibitors and activin A. This work demonstrates that induction and maintenance of naive human pluripotency are governed by distinct signaling requirements.
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- 2021
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154. Genetic Variants in KIR/HLA-C Genes Are Associated With the Susceptibility to HCV Infection in a High-Risk Chinese Population
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Chao Shen, Zhijun Ge, Chen Dong, Chunhui Wang, Jianguo Shao, Weihua Cai, Peng Huang, Haozhi Fan, Jun Li, Yun Zhang, and Ming Yue
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hepatitis C virus ,killer cell immunoglobulin-like receptors ,polymorphism ,human leukocyte antigen ,infection ,Immunologic diseases. Allergy ,RC581-607 - Abstract
BackgroundKIR/HLA-C signaling pathway influences the innate immune response which is the first defense to hepatitis C virus (HCV) infection. The aim of this study was to determine the association between the genetic polymorphisms of KIR/HLA-C genes and the outcomes of HCV infection in a high-risk Chinese population.MethodsIn this case-control study, four single nucleotide polymorphisms (SNPs) of KIR/HLA-C genes (KIR2DS4/KIR2DS1/KIR2DL1 rs35440472, HLA-C rs2308557, HLA-C rs1130838, and HLA-C rs2524094) were genotyped by TaqMan assay among drug users and hemodialysis (HD) patients including 1,378 uninfected control cases, 307 subjects with spontaneous viral clearance, and 217 patients with persistent HCV infection. Bioinformatics analysis was used to functionally annotate the SNPs.ResultsAfter logistic regression analysis, the rs35440472-A and rs1130838-A alleles were found to be associated with a significantly elevated risk of HCV infection (OR = 1.562, 95% CI: 1.229–1.987, P < 0.001; OR = 2.134, 95% CI: 1.180–3.858, P = 0.012, respectively), which remained significant after Bonferroni correction (0.05/4). The combined effect of their risk alleles and risk genotypes (rs35440472-AA and rs1130838-AA) were linked to the increased risk of HCV infection in a locus-dosage manner (all Ptrend < 0.001). Based on the SNPinfo web server, rs35440472 was predicted to be a transcription factor binding site (TFBS) while rs1130838 was predicted to have a splicing (ESE or ESS) function.ConclusionKIR2DS4/KIR2DS1/KIR2DL1 rs35440472-A and HLA-C rs1130838-A variants are associated with increased susceptibility to HCV infection in a high-risk Chinese population.
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- 2021
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155. B7-H3 participates in human salivary gland epithelial cells apoptosis through NF-κB pathway in primary Sjögren’s syndrome
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Ping Li, Ying Yang, Yi Jin, Rui Zhao, Chen Dong, Wenjie Zheng, Tianyi Zhang, Jing Li, and Zhifeng Gu
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Primary Sjögren’s syndrome ,B7-H3 ,p65 ,Medicine - Abstract
Abstract Background Primary Sjögren’s syndrome (pSS) is an autoimmune disorder mainly characterized by exocrine gland injury. Costimulatory molecules play an important role in immune-regulatory networks. Although B7 family costimulatory molecules were previously discovered in human salivary gland epithelial (HSGE) cells in pSS, the effects of the B7 family member B7-H3 (CD276) have not been well elucidated. Thus, this study aimed to investigate the role and mechanism of B7-H3 in HSGE cells in pSS. Methods The expression of B7-H3, B7-H1, PD-1 in serum, saliva and salivary gland were examined by immunohistochemistry (IHC) and enzyme-linked immunosorbent assay (ELISA). Immunofluorescence was used to test the expression and distribution of B7-H3, AQP5 and CK-8 in salivary gland tissues. Flow cytometry, Cell Counting Kit 8 (CCK-8) and western blot (WB) were performed to research the apoptotic, proliferative and inflammatory effects of B7-H3 in primary HSGE cells and HSGE cell lines. Results Our results showed that the expression of PD-1, B7-H1 and B7-H3 in peripheral blood, and salivary glands in pSS patients was higher than that in healthy controls, which was positive correlation with the grade of the salivary glands. The expression of B7-H3 in saliva was higher in pSS patients than that in healthy controls, which was detected with the most significant difference of them. The expression of B7-H3 in primary HSGE cells of pSS patients was significantly higher than healthy controls. B7-H3 increased activity of NF-κB pathway and promoted inflammation of HSGE cells, decreasing the expression of AQP5. Furthermore, B7-H3 overexpression inhibited proliferation and induced apoptosis in HSGE cell lines. Conclusion B7-H3 could promote inflammation and induce apoptosis of HSGE cells by activating NF-κB pathway, which might be a promising therapeutic target for pSS.
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- 2019
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156. Seroprevalence and molecular characteristics of varicella-zoster virus infection in Chinese children
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Lin Luan, Xiaochen Shen, Jing Qiu, Yang Jing, Jingqi Zhang, Jie Wang, Jun Zhang, and Chen Dong
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Varicella-zoster virus ,Seroprevalence, vaccination ,Genotype ,Infectious and parasitic diseases ,RC109-216 - Abstract
Abstract Background Varicella-zoster virus (VZV) infection in children is an important public health problem in China. We performed the current study to explore the seroprevalence of VZV infection in Chinese children in order to provide more information for improvement of varicella vaccination in China. Methods Three thousand fourteen children were recruited from Chinese kindergarten students aged from four to six years. Anti-VZV IgG and IgM were assayed using enzyme-linked immunosorbent assay. Both ORF22 and ORF62 of VZV were amplified, sequenced, and analyzed by nested PCR. Results Among 3014 children, 43.9% of boys and 46.3% of girls were vaccinated with varicella vaccine, respectively. The seroprevalence of anti-VZV IgG was 54.4% in the children with varicella vaccination, which was significantly higher than those in unvaccinated children (49.2%) (χ2 = 8.206, P = 0.004). Among of the vaccinated children, the detection rates of VZV IgG antibody increased with age, with 49.4, 50.9 and 58.9% in 4, 5 and 6-year groups, respectively (Trend χ2 = 17.202, P = 0.002). However, there was no difference in anti-VZV IgG detection rates among those unvaccinated children in different age groups (Trend χ2 = 8.681, P = 0.070). In addition, 13 boys and 13 girls were positive for anti-VZV IgM, respectively. Among of them, eight children (0.6%) have received varicella vaccination, which was similar to those in unvaccinated children (1.1%). However, only one ORF22 sequence was isolated from an unvaccinated 5-year boy. Compared to the reference VZV sequences, the nucleotide homology was estimated to be 99.7% with genotype J. Conclusions Our study indicated that about half of Chinese children aged four to six years have a high risk of VZV infection. It should be helpful for the evaluation on the necessity of varicella immunization in China.
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- 2019
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157. Analysis of VISTA expression and function in renal cell carcinoma highlights VISTA as a potential target for immunotherapy
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Shanjuan Hong, Qing Yuan, Haizhui Xia, Genzhen Zhu, Yu Feng, Qiang Wang, Zhiyin Zhang, Wei He, Jian Lu, Chen Dong, and Ling Ni
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Cytology ,QH573-671 ,Animal biochemistry ,QP501-801 - Published
- 2019
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158. Protective Function of Mitogen‐Activated Protein Kinase Phosphatase 5 in Aging‐ and Diet‐Induced Hepatic Steatosis and Steatohepatitis
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Peng Tang, Heng Boon Low, Chin Wen Png, Federico Torta, Jaspal Kaur Kumar, Hwee Ying Lim, Yi Zhou, Henry Yang, Veronique Angeli, Asim Shabbir, E. Shyong Tai, Richard A. Flavell, Chen Dong, Markus R. Wenk, Dan Yock Yang, and Yongliang Zhang
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Diseases of the digestive system. Gastroenterology ,RC799-869 - Abstract
Nonalcoholic fatty liver disease is currently the most common liver disease and is a leading cause of liver‐related morbidity and mortality. However, its pathogenesis remains largely unclear. We previously showed that mice deficient in mitogen‐activated protein kinase (MAPK) phosphatase 5 (MKP5) spontaneously developed insulin resistance and glucose intolerance, which are associated with visceral obesity and adipose tissue inflammation. In this study, we discovered that mice deficient in MKP5 developed more severe hepatic steatosis and steatohepatitis with age or with feeding on a high‐fat diet (HFD) compared to wild‐type (WT) mice, and this was associated with increased expression of proinflammatory cytokines and collagen genes. Increased p38 activation in MKP5 knockout (KO) liver compared to that in WT liver was detected, which contributed to increased expression of lipid droplet‐associated protein cell death‐inducing DFF45‐like effector A (CIDEA) and CIDEC/fat‐specific protein 27 but not CIDEB through activating transcription factor 2 (ATF2). In addition, MKP5 KO liver had higher peroxisome proliferator‐activated receptor gamma (PPARγ) expression compared with WT liver. On the other hand, overexpression of MKP5 or inhibition of p38 activation in hepatocytes resulted in reduced expression of PPARγ. Inhibition of p38 resulted in alleviation of hepatic steatosis in KO liver in response to HFD feeding, and this was associated with reduced expression of CIDEA, CIDEC, and proinflammatory cytokines. Conclusion: MKP5 prevents the development of nonalcoholic steatohepatitis by suppressing p38–ATF2 and p38–PPARγ to reduce hepatic lipid accumulation, inflammation, and fibrosis.
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- 2019
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159. A Spectroscopic Study on Tautomerism of Selaginellins from Selaginella
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CAO Yuan, WU Yong-ping, and CHEN Dong-jun
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nuclear magnetic resonance (NMR) ,ultraviolet-visible absorption spectrum ,selaginellin ,tautomerism ,Electricity and magnetism ,QC501-766 - Abstract
Ultraviolet-visible and nuclear magnetic resonance (NMR) spectroscopy was used to investigate the effects of pH, solvent and temperature on the tautomeric equilibrium of selaginellins from Selaginella. The results demonstrated that the tautomerism of selaginellins could be catalyzed by acid, base and protic solvent. Variable-temperature 1H NMR experiments demonstrated that the tautomerism was interrupted when the temperature fell below 233 K.
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- 2019
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160. Realization of high-efficiency fluorescent organic light-emitting diodes with low driving voltage
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Amin Salehi, Chen Dong, Dong-Hun Shin, Liping Zhu, Christopher Papa, Anh Thy Bui, Felix N. Castellano, and Franky So
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Science - Abstract
Though organic light-emitting diodes (OLEDs) with electroluminescence at sub-bandgap voltages have been reported, realizing high efficiency in such a device is difficult. Here, the authors report high efficiency sub-bandgap OLEDs featuring organic molecules with large singlet-triplet splitting.
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- 2019
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161. NCR− group 3 innate lymphoid cells orchestrate IL-23/IL-17 axis to promote hepatocellular carcinoma developmentResearch in context
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Yonghao Liu, Yuan Song, Dandan Lin, Lei Lei, Yu Mei, Ziqi Jin, Huanle Gong, Ying Zhu, Bo Hu, Yinsheng Zhang, Lixiang Zhao, Huey Yee Teo, Ju Qiu, Wen Jiang, Chen Dong, Depei Wu, Yuhui Huang, and Haiyan Liu
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Medicine ,Medicine (General) ,R5-920 - Abstract
Background: Innate lymphoid cells (ILCs) are a newly discovered family of immune cells that have similar cytokine-secreting profiles as T helper cell subsets. Although ILCs are critical for host defense against infections and tissue homeostasis, their roles in tumor development are not well established. Methods: We studied the function of ILC3 cells in the liver for the development of hepatocellular carcinoma (HCC) in murine HCC models using flow cytometry, adoptive transfer, and in vitro functional assays. Findings: We found that ILC3 lacking the natural cytotoxicity-triggering receptor (NCR−ILC3) promoted the development of HCC in response to interleukin 23 (IL-23). IL-23 serum level is elevated in HCC patients and its high expression is associated with poor clinical outcomes. We found that IL-23 could promote tumor development in murine HCC tumor models. IL-23 promoted the expansion of NCR−ILC3 and its differentiation from group 1 ILCs (ILC1s). Furthermore, NCR−ILC3 initiated IL-17 production upon IL-23 stimulation and directly inhibited CD8+ T cell immunity by promoting lymphocyte apoptosis and limiting their proliferation. Interpretation: Together, our findings suggest that NCR−ILC3 initiates the IL-17-rich immunosuppressive tumor microenvironment and promotes the development of HCC, thus may serve as a promising target for future cancer immunotherapy. Fund: This work was supported by grants from National Natural Science Foundation of China (81471586, 81571556), the Priority Academic Program Development of Jiangsu Higher Education Institutions, the collaborative Innovation Center of Hematology, start-up grant from National University of Singapore, the Cancer Prevention and Research Institute of Texas CPRIT (RR180017), and the National Cancer Institute's Cancer Center Support (Core) Grant CA016672 (to The University of Texas MD Anderson Cancer Center). Keywords: IL-23, IL-17, ILC, Tumor microenvironment, HCC
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- 2019
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162. The Sensitivity Design of Piezoresistive Acceleration Sensor in Industrial IoT
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Chen Dong, Yin Ye, Ximeng Liu, Yang Yang, and Wenzhong Guo
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Industrial Internet of Things ,piezoresistive acceleration sensor ,structural sensitivity optimization ,grasshopper optimization algorithm ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Piezoresistive acceleration sensors are widely used in various fields of the industrial Internet of Things because of their lightweight, fast response, and small size. The structural sensitivity of the sensor affects the accuracy of the measurement. And the sensitivity that the traditional method designs are only a feasible solution, not an optimal solution. Due to the differences in factory processes, the optimization of structural sensitivity is an NP-hard problem. To solve the design problem of structural sensitivity, we adopt the swarm intelligence algorithm in this paper, and we design a model for the structural sensitivity of the piezoresistive acceleration sensor. In addition, an improved grasshopper optimization algorithm (CC-GOA) that combines chaos strategy and Cauchy mutation is proposed to optimize the structural sensitivity of the piezoresistive acceleration sensor, and the structure of the sensor is composed of four beams and mass block. The experiments are compared with six well-known algorithms on 16 benchmark functions to verify the algorithm performance of CC-GOA, and then, the structural sensitivity of the piezoresistive acceleration sensor is optimized by CC-GOA. The results indicate that the piezoresistive acceleration sensor is designed with high sensitivity and superiority.
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- 2019
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163. A Multi-Layer Hardware Trojan Protection Framework for IoT Chips
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Chen Dong, Guorong He, Ximeng Liu, Yang Yang, and Wenzhong Guo
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Internet of Things ,protection framework ,hardware security ,hardware Trojan ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Since integrated circuits are performed by several untrusted manufacturers, malicious circuits (hardware Trojans) can be implanted in any stage of the Internet-of-Things (IoT) devices. With the globalization of the IoT device manufacturing technologies, protecting the system-on-chip (SoC) security is always the keys issue for scientists and IC manufacturers. The existing SoC high-level synthesis approaches cannot guarantee both register-transfer-level and gate-level security, such as some formal verification and circuit characteristic analysis technologies. Based on the structural characteristics of hardware Trojans, we propose a multi-layer hardware Trojan protection framework for the Internet-of-Things perception layer called RG-Secure, which combines the third-party intellectual property trusted design strategy with the scan-chain netlist feature analysis technology. Especially at the gate level of chip design, our RG-Secure is equipped with a distributed, lightweight gradient lifting algorithm called lightGBM. The algorithm can quickly process high-dimensional circuit feature information and effectively improve the detection efficiency of hardware Trojans. In the meanwhile, a common evaluation index F-measure is used to prove the effectiveness of our method. The experiments show that RG-Secure framework can simultaneously detect register-transfer-level and gate-level hardware Trojans. For the trust-HUB benchmarks, the optimized lightGBM classifier achieves up to 100% true positive rate and 94% true negative rate; furthermore, it achieves 99.8% average F-measure and 99% accuracy, which shows a promising approach to ensure security during the design stage.
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- 2019
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164. Dual-Search Artificial Bee Colony Algorithm for Engineering Optimization
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Chen Dong, Ziqi Xiong, Ximeng Liu, Yin Ye, Yang Yang, and Wenzhong Guo
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Artificial bee colony algorithm ,dual search mechanism ,Lévy flight ,differential self-disturbance mechanism ,engineering optimization ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
With the development of science and technology, the accuracy requirements for solving engineering problems are getting stricter than before. Most structural design optimization problems in civil and mechanical engineering have proven to be the non-deterministic polynomial hard problems. The artificial bee colony (ABC) algorithm has been proven to be an effective method of design optimization problems. This paper proposes an improved ABC algorithm (DSM-ABC) combined with dual-search mechanism containing Lévy flight and differential self-perturbation and applies it to three classical structural design problems, including cantilever beam design, gear train design, and three-bar truss design. The experimental results of benchmark functions from CEC2005 reveal that the proposed DSM-ABC algorithm accelerates the convergence and improves the performance. Eventually, the obtained results of optimization structural design problems prove that the DSM-ABC algorithm has a strong superiority compared with the state-of-the-art algorithms in solving optimization engineering design problems.
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- 2019
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165. QSSA: Quantum Evolutionary Salp Swarm Algorithm for Mechanical Design
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Rongzhong Chen, Chen Dong, Yin Ye, Zhenyi Chen, and Yanhua Liu
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Evolutionary algorithm ,salp swarm optimization ,quantum behavior ,wavelet mutation ,structure design ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Salp swarm algorithm is a new meta-heuristic algorithm which has excellent advantages for solving the multidimensional optimization problem. In this paper, a hybrid model assisted evolutionary algorithm for solving engineering design optimization problems is proposed and investigated. The purpose of the optimizer is to improve the potential shortcomings of the basic salp swarm optimization, including trapping in local or deceptive optima easily. On the one hand, quantum behavior can increase an individual's searchability, which can promote the overall optimization trend. On the other hand, the elite opposition-based learning strategy is used to enhance the diversity of the population. Besides, mutation mechanism is introduced to prevent the individuals of the population from being in stagnation behavior. The proposed quantum-behaved and wavelet mutation salp swarm algorithm (QSSA) is applied on twenty-three benchmark functions and three basic constrained engineering problems. Experimental results demonstrate that the algorithm has excellent solution quality, and it can overcome the defect of the low convergence rate.
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- 2019
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166. A Locating Method for Multi-Purposes HTs Based on the Boundary Network
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Chen Dong, Fan Zhang, Ximeng Liu, Xing Huang, Wenzhong Guo, and Yang Yang
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Hardware trojan ,Integrated circuit ,boundary network ,static detection ,ML-HTCL ,Electrical engineering. Electronics. Nuclear engineering ,TK1-9971 - Abstract
Recently, there are various methods for detecting the hardware trojans (HTs) in the integrated circuits (ICs). The circuit's logic representations of different types, structures, and functional characteristics should be different. Each type of circuit has its' own performance characteristics according to its' purpose. However, the traditional HTs detection methods adopt the same approach to deal with the multi-purpose hardware trojan. At the same time, as the scale of integrated circuits growing, the structures are more complex, and the functions are more refined. The current situation makes the traditional HTs detection methods weaker and even unfeasible. Therefore, we propose an HTs classified locating method based on machine learning, named ML-HTCL, which belongs to the static detection and locating method. In ML-HTCL, different purpose HTs were represented by different features. Due to the different features, the ML-HTCL employs the multi-layer BP neural network for the control signal type HTs and the one-class SVM for the information leakage HTs, respectively. To deal with the HTs completely, the boundary nets are considered for all data set, while those were ignored by the most existing methods due to the high detection error rate. After detection, the HTs' precise locations were achieved. To evaluate the ML-HTCL, 17 gate-level netlist benchmarks are used for training and testing by leave-one-out cross-validation. From the results, the ML-HTCL reaches 85.05% of TPR and 73.91% of TNR for all kinds of HTs, which performs better than the most existing methods.
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- 2019
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167. Enhanced sintering and nonlinear dielectric properties of Ba0.6Sr0.4TiO3 ceramics with a small amount of lithium additive
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Zhang Xiao-Fei, Xie Xiao-Bin, Xu Qing, Chen Min, Chen Dong-Chu, Huang Duan-Ping, and Zhang Feng
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ba0.6sr0.4tio3 ceramics ,li2co3 additive ,sintering ,nonlinear dielectric properties ,Chemical technology ,TP1-1185 - Abstract
The powders with the nominal compositions of Ba0.6Sr0.4TiO3+x wt.% Li2CO3 (x=0 and x=1.0) were synthesized by a citrate precursor method. The sintering behavior, structure and dielectric properties of the ceramic specimens were investigated. Compared with the lithium-free specimen (x=0), the lithium-added specimen (x=1.0) showed appreciably enhanced sintering properties, achieving a relative density of 96.0% after sintering at 900°C. The enhanced sintering properties were related to a liquid-phase sintering mechanism. The origin of the liquid-phase was explained. The effects of the liquid-phase on the densification progress of the lithium-added specimen in different sintering stages were elucidated. The lithium addition was found to be beneficial to the nonlinear dielectric properties. The ceramic specimen with x=1.0 exhibited a figure-of-merit of 106 under a bias electric field of 20 kV/cm, higher by ~60% than the value (67) for the specimen with x=0.
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- 2019
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168. NtDREB-1BL1 Enhances Carotenoid Biosynthesis by Regulating Phytoene Synthase in Nicotiana tabacum
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Chen Dong, Qingdong Wang, Yubo Wang, Lili Qin, Yongchun Shi, Xiaoran Wang, and Ran Wang
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antioxidants ,carotenoid biosynthesis ,DREB ,drought stress ,phytoene synthase ,transcription factor ,Genetics ,QH426-470 - Abstract
As one of the most imperative antioxidants in higher plants, carotenoids serve as accessory pigments to harvest light for photosynthesis as well as photoprotectors for plants to adapt to high light stress. Phytoene synthase (PSY) is the entry enzyme and also the major rate-limiting enzyme in the carotenoid pathway. Here, we report a dehydration-responsive element-binding protein (DREB) transcription factor member in Nicotiana tabacum K326, NtDREB-1BL1, which regulates carotenoids biosynthesis by binding to the NtPSY promoter. The NtDREB-1BL1 transcript was widely distributed in leaves by Real-time PCR. Confocal image revealed that NtDREB-1BL1 was localized in the nucleus. The chromatin immunoprecipitation (ChIP) with the qPCR technique indicated that NtDREB-1BL1 could anchor the promoter region of NtPSY. Overexpression (NtDREB-1BL1 OE) and RNA interference (NtDREB-1BL1 RNAi) of NtDREB-1BL1 were performed to evaluate its biological function in N. tabacum. Both carotenoid and chlorophyll contents increased in transgenic plants of NtDREB-1BL1 OE compared with wild-type (WT) plants, with the augment of the genes involved in carotenoid biosynthesis. In contrast, the contents of carotenoid and chlorophyll significantly decreased in transgenic plants of NtDREB-1BL1 RNAi compared to WT, along with the decline in the expression of genes related to carotenoid biosynthesis. Moreover, transgenic plants of NtDREB-1BL1 OE exhibited enhanced tolerance under drought stress, with the weakened tolerance of drought stress in transgenic plants of NtDREB-1BL1 RNAi. In conclusion, our results illustrated the new role of transcription factor NtDREB-1BL1 in improving carotenoid biosynthesis through regulating NtPSY expression.
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- 2022
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169. Quantum Linear System Algorithm for General Matrices in System Identification
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Kai Li, Ming Zhang, Xiaowen Liu, Yong Liu, Hongyi Dai, Yijun Zhang, and Chen Dong
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system identification ,linear systems of equations ,quantum algorithm ,time complexity ,Science ,Astrophysics ,QB460-466 ,Physics ,QC1-999 - Abstract
Solving linear systems of equations is one of the most common and basic problems in classical identification systems. Given a coefficient matrix A and a vector b, the ultimate task is to find the solution x such that Ax=b. Based on the technique of the singular value estimation, the paper proposes a modified quantum scheme to obtain the quantum state |x⟩ corresponding to the solution of the linear system of equations in O(κ2rpolylog(mn)/ϵ) time for a general m×n dimensional A, which is superior to existing quantum algorithms, where κ is the condition number, r is the rank of matrix A and ϵ is the precision parameter. Meanwhile, we also design a quantum circuit for the homogeneous linear equations and achieve an exponential improvement. The coefficient matrix A in our scheme is a sparsity-independent and non-square matrix, which can be applied in more general situations. Our research provides a universal quantum linear system solver and can enrich the research scope of quantum computation.
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- 2022
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170. GaussianCube: A Structured and Explicit Radiance Representation for 3D Generative Modeling
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Zhang, Bowen, Cheng, Yiji, Yang, Jiaolong, Wang, Chunyu, Zhao, Feng, Tang, Yansong, Chen, Dong, and Guo, Baining
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Computer Science - Computer Vision and Pattern Recognition - Abstract
We introduce a radiance representation that is both structured and fully explicit and thus greatly facilitates 3D generative modeling. Existing radiance representations either require an implicit feature decoder, which significantly degrades the modeling power of the representation, or are spatially unstructured, making them difficult to integrate with mainstream 3D diffusion methods. We derive GaussianCube by first using a novel densification-constrained Gaussian fitting algorithm, which yields high-accuracy fitting using a fixed number of free Gaussians, and then rearranging these Gaussians into a predefined voxel grid via Optimal Transport. Since GaussianCube is a structured grid representation, it allows us to use standard 3D U-Net as our backbone in diffusion modeling without elaborate designs. More importantly, the high-accuracy fitting of the Gaussians allows us to achieve a high-quality representation with orders of magnitude fewer parameters than previous structured representations for comparable quality, ranging from one to two orders of magnitude. The compactness of GaussianCube greatly eases the difficulty of 3D generative modeling. Extensive experiments conducted on unconditional and class-conditioned object generation, digital avatar creation, and text-to-3D synthesis all show that our model achieves state-of-the-art generation results both qualitatively and quantitatively, underscoring the potential of GaussianCube as a highly accurate and versatile radiance representation for 3D generative modeling. Project page: https://gaussiancube.github.io/., Comment: Update for digital avatar creation and text-to-3D synthesis; Project Page: https://gaussiancube.github.io/
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- 2024
171. CodeS: Natural Language to Code Repository via Multi-Layer Sketch
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Zan, Daoguang, Yu, Ailun, Liu, Wei, Chen, Dong, Shen, Bo, Li, Wei, Yao, Yafen, Gong, Yongshun, Chen, Xiaolin, Guan, Bei, Yang, Zhiguang, Wang, Yongji, Wang, Qianxiang, and Cui, Lizhen
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Computer Science - Computation and Language ,Computer Science - Artificial Intelligence ,Computer Science - Software Engineering - Abstract
The impressive performance of large language models (LLMs) on code-related tasks has shown the potential of fully automated software development. In light of this, we introduce a new software engineering task, namely Natural Language to code Repository (NL2Repo). This task aims to generate an entire code repository from its natural language requirements. To address this task, we propose a simple yet effective framework CodeS, which decomposes NL2Repo into multiple sub-tasks by a multi-layer sketch. Specifically, CodeS includes three modules: RepoSketcher, FileSketcher, and SketchFiller. RepoSketcher first generates a repository's directory structure for given requirements; FileSketcher then generates a file sketch for each file in the generated structure; SketchFiller finally fills in the details for each function in the generated file sketch. To rigorously assess CodeS on the NL2Repo task, we carry out evaluations through both automated benchmarking and manual feedback analysis. For benchmark-based evaluation, we craft a repository-oriented benchmark, SketchEval, and design an evaluation metric, SketchBLEU. For feedback-based evaluation, we develop a VSCode plugin for CodeS and engage 30 participants in conducting empirical studies. Extensive experiments prove the effectiveness and practicality of CodeS on the NL2Repo task., Comment: https://github.com/NL2Code/CodeS
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- 2024
172. Simplified Diffusion Schr\'odinger Bridge
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Tang, Zhicong, Hang, Tiankai, Gu, Shuyang, Chen, Dong, and Guo, Baining
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Computer Science - Machine Learning ,Computer Science - Computer Vision and Pattern Recognition - Abstract
This paper introduces a novel theoretical simplification of the Diffusion Schr\"odinger Bridge (DSB) that facilitates its unification with Score-based Generative Models (SGMs), addressing the limitations of DSB in complex data generation and enabling faster convergence and enhanced performance. By employing SGMs as an initial solution for DSB, our approach capitalizes on the strengths of both frameworks, ensuring a more efficient training process and improving the performance of SGM. We also propose a reparameterization technique that, despite theoretical approximations, practically improves the network's fitting capabilities. Our extensive experimental evaluations confirm the effectiveness of the simplified DSB, demonstrating its significant improvements. We believe the contributions of this work pave the way for advanced generative modeling.
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- 2024
173. Deep-learning-assisted optical communication with discretized state space of structured light
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Zhang, Minyang, Chen, Dong-Xu, Ruan, Pengxiang, Liu, Jun, Zhao, Jun-Long, and Yang, Chui-Ping
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Physics - Optics ,Quantum Physics - Abstract
The rich structure of transverse spatial modes of structured light has facilitated their extensive applications in quantum information and optical communication. The Laguerre-Gaussian (LG) modes, which carry a well-defined orbital angular momentum (OAM), consist of a complete orthogonal basis describing the transverse spatial modes of light. The application of OAM in free-space optical communication is restricted due to the experimentally limited OAM numbers and the complex OAM recognition methods. Here, we present a novel method that uses the advanced deep learning technique for LG modes recognition. By discretizing the spatial modes of structured light, we turn the OAM state regression into classification. A proof-of-principle experiment is also performed, showing that our method effectively categorizes OAM states with small training samples and high accuracy. By assigning each category a classical information, we further apply our approach to an image transmission task, demonstrating the ability to encode large data with low OAM number. This work opens up a new avenue for achieving high-capacity optical communication with low OAM number based on structured light., Comment: 10 pages, 7 figures
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- 2024
174. SiGNN: A Spike-induced Graph Neural Network for Dynamic Graph Representation Learning
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Chen, Dong, Zheng, Shuai, Xu, Muhao, Zhu, Zhenfeng, and Zhao, Yao
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Computer Science - Neural and Evolutionary Computing ,Computer Science - Artificial Intelligence ,Computer Science - Machine Learning - Abstract
In the domain of dynamic graph representation learning (DGRL), the efficient and comprehensive capture of temporal evolution within real-world networks is crucial. Spiking Neural Networks (SNNs), known as their temporal dynamics and low-power characteristic, offer an efficient solution for temporal processing in DGRL task. However, owing to the spike-based information encoding mechanism of SNNs, existing DGRL methods employed SNNs face limitations in their representational capacity. Given this issue, we propose a novel framework named Spike-induced Graph Neural Network (SiGNN) for learning enhanced spatialtemporal representations on dynamic graphs. In detail, a harmonious integration of SNNs and GNNs is achieved through an innovative Temporal Activation (TA) mechanism. Benefiting from the TA mechanism, SiGNN not only effectively exploits the temporal dynamics of SNNs but also adeptly circumvents the representational constraints imposed by the binary nature of spikes. Furthermore, leveraging the inherent adaptability of SNNs, we explore an in-depth analysis of the evolutionary patterns within dynamic graphs across multiple time granularities. This approach facilitates the acquisition of a multiscale temporal node representation.Extensive experiments on various real-world dynamic graph datasets demonstrate the superior performance of SiGNN in the node classification task.
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- 2024
175. Performance Evaluation of Semi-supervised Learning Frameworks for Multi-Class Weed Detection
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Li, Jiajia, Chen, Dong, Yin, Xunyuan, and Li, Zhaojian
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Computer Science - Computer Vision and Pattern Recognition ,Computer Science - Machine Learning ,Electrical Engineering and Systems Science - Image and Video Processing - Abstract
Effective weed control plays a crucial role in optimizing crop yield and enhancing agricultural product quality. However, the reliance on herbicide application not only poses a critical threat to the environment but also promotes the emergence of resistant weeds. Fortunately, recent advances in precision weed management enabled by ML and DL provide a sustainable alternative. Despite great progress, existing algorithms are mainly developed based on supervised learning approaches, which typically demand large-scale datasets with manual-labeled annotations, which is time-consuming and labor-intensive. As such, label-efficient learning methods, especially semi-supervised learning, have gained increased attention in the broader domain of computer vision and have demonstrated promising performance. These methods aim to utilize a small number of labeled data samples along with a great number of unlabeled samples to develop high-performing models comparable to the supervised learning counterpart trained on a large amount of labeled data samples. In this study, we assess the effectiveness of a semi-supervised learning framework for multi-class weed detection, employing two well-known object detection frameworks, namely FCOS and Faster-RCNN. Specifically, we evaluate a generalized student-teacher framework with an improved pseudo-label generation module to produce reliable pseudo-labels for the unlabeled data. To enhance generalization, an ensemble student network is employed to facilitate the training process. Experimental results show that the proposed approach is able to achieve approximately 76\% and 96\% detection accuracy as the supervised methods with only 10\% of labeled data in CottenWeedDet3 and CottonWeedDet12, respectively. We offer access to the source code, contributing a valuable resource for ongoing semi-supervised learning research in weed detection and beyond., Comment: 11 pages, 7 figures
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- 2024
176. Drug resistance revealed by in silico deep mutational scanning and mutation tracker
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Chen, Dong, Liu, Gengzhuo, Du, Hongyan, Wee, Junjie, Wang, Rui, Chen, Jiahui, Shen, Jana, and Wei, Guo-Wei
- Subjects
Quantitative Biology - Quantitative Methods - Abstract
As COVID-19 enters its fifth year, it continues to pose a significant global health threat, with the constantly mutating SARS-CoV-2 virus challenging drug effectiveness. A comprehensive understanding of virus-drug interactions is essential for predicting and improving drug effectiveness, especially in combating drug resistance during the pandemic. In response, the Path Laplacian Transformer-based Prospective Analysis Framework (PLFormer-PAF) has been proposed, integrating historical data analysis and predictive modeling strategies. This dual-strategy approach utilizes path topology to transform protein-ligand complexes into topological sequences, enabling the use of advanced large language models for analyzing protein-ligand interactions and enhancing its reliability with factual insights garnered from historical data. It has shown unparalleled performance in predicting binding affinity tasks across various benchmarks, including specific evaluations related to SARS-CoV-2, and assesses the impact of virus mutations on drug efficacy, offering crucial insights into potential drug resistance. The predictions align with observed mutation patterns in SARS-CoV-2, indicating that the widespread use of the Pfizer drug has lead to viral evolution and reduced drug efficacy. PLFormer-PAF's capabilities extend beyond identifying drug-resistant strains, positioning it as a key tool in drug discovery research and the development of new therapeutic strategies against fast-mutating viruses like COVID-19.
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- 2024
177. Unified understanding to the rich electronic-structure evolutions of 2D black phosphorus under pressure
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Gao, Yu-Meng, Zhang, Yue-Jiao, Zhao, Xiao-Lin, Li, Xin-Yu, Wang, Shu-Hui, Jin, Chen-Dong, Zhang, Hu, Lian, Ru-Qian, Wang, Rui-Ning, Gong, Peng-Lai, Wang, Jiang-Long, and Shi, Xing-Qiang
- Subjects
Condensed Matter - Materials Science - Abstract
The electronic structure evolutions of few-layer black phosphorus (BP) under pressure shows a wealth of phenomena, such as the nonmonotonic change of direct gap at the {\Gamma} point, the layer-number dependence, and the distinct responses to normal and hydrostatic pressures. A full and unified understanding to these rich phenomena remains lacking. Here, we provide a unified understanding from the competition between interlayer quasi-bonding (QB) interactions and intralayer chemical bonding interactions. The former decreases while the latter increases the band gap under pressure and the origin can be correlated to different combinations of inter- and intra-layer antibonding or bonding interactions at the band edges. More interestingly, the interlayer QB interactions are a coexistence of two categories of interactions, namely, the coexistence of interactions between bands of the same occupancy (occupied-occupied and empty-empty interactions) and of different occupancies (occupied-empty interaction); and, the overall effect is a four-level interaction, which explains the anomalous interlayer-antibonding feature of the conduction band edge of bilayer BP. Our current study lay the foundation for the electronic structure tuning of two-dimensional (2D) BP, and, our analysis method for multi-energy-level interactions can be applied to other 2D semiconductor homo- and hetero-structures that have occupied-empty interlayer interactions.
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- 2024
178. Observation of Giant Spin Splitting and d-wave Spin Texture in Room Temperature Altermagnet RuO2
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Lin, Zihan, Chen, Dong, Lu, Wenlong, Liang, Xin, Feng, Shiyu, Yamagami, Kohei, Osiecki, Jacek, Leandersson, Mats, Thiagarajan, Balasubramanian, Liu, Junwei, Felser, Claudia, and Ma, Junzhang
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Condensed Matter - Materials Science ,Condensed Matter - Other Condensed Matter - Abstract
Recently, a novel magnetic phase called altermagnetism has been proposed, ushering in a third distinct magnetic phase beyond ferromagnetism and antiferromagnetism. It is expected that this groundbreaking phase exhibits unique physical properties such as C-paired spin-valley locking, anomalous Hall effect, nontrivial Berry phase, and giant magnetoresistance, etc. Among all the predicted candidates, several room temperature altermagnets are suggested to host significant potential applications in the near future. Nevertheless, direct evidence about the spin pattern of the room temperature altermagnet is still unrevealed. Previous studies found that RuO2 is identified as the most promising candidate for room temperature d-wave altermagnetism, exhibiting a substantial spin splitting of up to 1.4 eV. In this study, utilizing angle-resolved photoemission spectroscopy (ARPES), we report experimental observation of the spin splitting in RuO2. Furthermore, employing spin-ARPES, we directly observed the d-wave spin pattern. Our results unequivocally show that RuO2 is a perfect d-wave altermagnet with great potential for upcoming spintronic applications., Comment: 32 pages, 12 figures
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- 2024
179. EPSD: Early Pruning with Self-Distillation for Efficient Model Compression
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Chen, Dong, Liu, Ning, Zhu, Yichen, Che, Zhengping, Ma, Rui, Zhang, Fachao, Mou, Xiaofeng, Chang, Yi, and Tang, Jian
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Computer Science - Machine Learning ,Computer Science - Artificial Intelligence ,Computer Science - Computer Vision and Pattern Recognition - Abstract
Neural network compression techniques, such as knowledge distillation (KD) and network pruning, have received increasing attention. Recent work `Prune, then Distill' reveals that a pruned student-friendly teacher network can benefit the performance of KD. However, the conventional teacher-student pipeline, which entails cumbersome pre-training of the teacher and complicated compression steps, makes pruning with KD less efficient. In addition to compressing models, recent compression techniques also emphasize the aspect of efficiency. Early pruning demands significantly less computational cost in comparison to the conventional pruning methods as it does not require a large pre-trained model. Likewise, a special case of KD, known as self-distillation (SD), is more efficient since it requires no pre-training or student-teacher pair selection. This inspires us to collaborate early pruning with SD for efficient model compression. In this work, we propose the framework named Early Pruning with Self-Distillation (EPSD), which identifies and preserves distillable weights in early pruning for a given SD task. EPSD efficiently combines early pruning and self-distillation in a two-step process, maintaining the pruned network's trainability for compression. Instead of a simple combination of pruning and SD, EPSD enables the pruned network to favor SD by keeping more distillable weights before training to ensure better distillation of the pruned network. We demonstrated that EPSD improves the training of pruned networks, supported by visual and quantitative analyses. Our evaluation covered diverse benchmarks (CIFAR-10/100, Tiny-ImageNet, full ImageNet, CUB-200-2011, and Pascal VOC), with EPSD outperforming advanced pruning and SD techniques., Comment: The first two authors are with equal contributions. Paper accepted by AAAI 2024
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- 2024
180. CCA: Collaborative Competitive Agents for Image Editing
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Hang, Tiankai, Gu, Shuyang, Chen, Dong, Geng, Xin, and Guo, Baining
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Computer Science - Computer Vision and Pattern Recognition - Abstract
This paper presents a novel generative model, Collaborative Competitive Agents (CCA), which leverages the capabilities of multiple Large Language Models (LLMs) based agents to execute complex tasks. Drawing inspiration from Generative Adversarial Networks (GANs), the CCA system employs two equal-status generator agents and a discriminator agent. The generators independently process user instructions and generate results, while the discriminator evaluates the outputs, and provides feedback for the generator agents to further reflect and improve the generation results. Unlike the previous generative model, our system can obtain the intermediate steps of generation. This allows each generator agent to learn from other successful executions due to its transparency, enabling a collaborative competition that enhances the quality and robustness of the system's results. The primary focus of this study is image editing, demonstrating the CCA's ability to handle intricate instructions robustly. The paper's main contributions include the introduction of a multi-agent-based generative model with controllable intermediate steps and iterative optimization, a detailed examination of agent relationships, and comprehensive experiments on image editing. Code is available at \href{https://github.com/TiankaiHang/CCA}{https://github.com/TiankaiHang/CCA}.
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- 2024
181. Back-stepping Experience Replay with Application to Model-free Reinforcement Learning for a Soft Snake Robot
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Qi, Xinda, Chen, Dong, Li, Zhaojian, and Tan, Xiaobo
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Computer Science - Robotics ,Computer Science - Machine Learning - Abstract
In this paper, we propose a novel technique, Back-stepping Experience Replay (BER), that is compatible with arbitrary off-policy reinforcement learning (RL) algorithms. BER aims to enhance learning efficiency in systems with approximate reversibility, reducing the need for complex reward shaping. The method constructs reversed trajectories using back-stepping transitions to reach random or fixed targets. Interpretable as a bi-directional approach, BER addresses inaccuracies in back-stepping transitions through a distillation of the replay experience during learning. Given the intricate nature of soft robots and their complex interactions with environments, we present an application of BER in a model-free RL approach for the locomotion and navigation of a soft snake robot, which is capable of serpentine motion enabled by anisotropic friction between the body and ground. In addition, a dynamic simulator is developed to assess the effectiveness and efficiency of the BER algorithm, in which the robot demonstrates successful learning (reaching a 100% success rate) and adeptly reaches random targets, achieving an average speed 48% faster than that of the best baseline approach., Comment: Submitted to the IEEE for possible publication
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- 2024
182. Design and Nonlinear Modeling of a Modular Cable Driven Soft Robotic Arm
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Qi, Xinda, Mei, Yu, Chen, Dong, Li, Zhaojian, and Tan, Xiaobo
- Subjects
Computer Science - Robotics - Abstract
We propose a novel multi-section cable-driven soft robotic arm inspired by octopus tentacles along with a new modeling approach. Each section of the modular manipulator is made of a soft tubing backbone, a soft silicon arm body, and two rigid endcaps, which connect adjacent sections and decouple the actuation cables of different sections. The soft robotic arm is made with casting after the rigid endcaps are 3D-printed, achieving low-cost and convenient fabrication. To capture the nonlinear effect of cables pushing into the soft silicon arm body, which results from the absence of intermediate rigid cable guides for higher compliance, an analytical static model is developed to capture the relationship between the bending curvature and the cable lengths. The proposed model shows superior prediction performance in experiments over that of a baseline model, especially under large bending conditions. Based on the nonlinear static model, a kinematic model of a multi-section arm is further developed and used to derive a motion planning algorithm. Experiments show that the proposed soft arm has high flexibility and a large workspace, and the tracking errors under the algorithm based on the proposed modeling approach are up to 52$\%$ smaller than those with the algorithm derived from the baseline model. The presented modeling approach is expected to be applicable to a broad range of soft cable-driven actuators and manipulators., Comment: The paper has been accepted by IEEE Transactions on Mechatronics
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- 2024
183. Genetic Variants in TNFSF4 and TNFSF8 Are Associated With the Risk of HCV Infection Among Chinese High-Risk Population
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Zuqiang Fu, Weihua Cai, Jianguo Shao, Hong Xue, Zhijun Ge, Haozhi Fan, Chen Dong, Chunhui Wang, Jinwei Zhang, Chao Shen, Yun Zhang, Peng Huang, and Ming Yue
- Subjects
tumor necrosis factor superfamily ,tumor necrosis factor receptor superfamily ,hepatitis C virus ,single nucleotide polymorphisms (SNPs) ,correlation analysis ,Genetics ,QH426-470 - Abstract
BackgroundThe tumor necrosis factor superfamily (TNFSF) and TNF receptor superfamily (TNFRSF) play important roles in the immune responses to infections. The aim of this study was to determine the impact of single nucleotide polymorphisms (SNPs) of several TNFSF/TNFRSF genes on the risk of hepatitis C virus (HCV) infection in the Chinese high-risk population.MethodsThe TNFSF4-rs1234313, TNFSF4-rs7514229, TNFSF8-rs3181366, TNFSF8-rs2295800, TNFRSF8-rs2298209, and TNFRSF8-rs2230625 SNPs were genotyped in 2309 uninfected controls, 597 subjects with spontaneous HCV clearance and 784 patients with persistent HCV infection using the TaqMan-MGB assay. The putative functions of the positive SNPs were determined using online bioinformatics tools.ResultsAfter adjusting for gender, age, high-risk population, alanine transaminase (ALT), aspartate aminotransferase (AST), IL28B-rs12979860 and rs8099917 genotypes, the non-conditional logistic regression showed that rs7514229-T, rs3181366-T, and rs2295800-C were associated with an increased risk of HCV infection (all PFDR < 0.05). Combined analysis of rs7514229-T and rs3181366-T risk alleles showed that the subjects carrying 2–4 risk alleles were more susceptible to HCV infection compared with those lacking any risk allele (all P < 0.001). Furthermore, the risk of HCV infection increased with the number of risk alleles (Ptrend < 0.001). In silico analysis showed that rs7514229, rs3181366, and rs2295800 polymorphisms may affect the transcription of mRNA by regulating miRNA binding, TF binding, and promoter activation, respectively, which may have biological consequences.ConclusionTNFSF4-rs7514229, TNFSF8-rs3181366, and TNFSF8-rs2295800 are associated with increased risk of HCV infection in the Chinese high-risk population.
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- 2021
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184. Enhancing Dispersion of TiB2 Nanoparticles in Al Composites via Ultrasonic-Assisted Fast Cooling Schemes
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Chen, Jian, Geng, Jiwei, Li, Yugang, Li, Keneng, Xia, Peikang, Li, Xianfeng, Wang, Fangming, Chen, Dong, Wang, Mingliang, and Wang, Haowei
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- 2024
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185. Research on the Energy Dissipation Characteristics and Stress Wave Spectrum Analysis of Red Sandstone Subjected to Progressive Load Cyclic Impact
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Zhang, Li, Wang, Enyuan, Liu, Yubing, Yue, Weitao, and Chen, Dong
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- 2024
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186. Neutrophil-mimetic hybrid liposome with ROS cascade amplification for synergistic ferroptosis-photodynamic therapy of breast cancer
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Li, Jiaxin, Li, Jiaxin, He, Jiao, He, Xuan, Chen, Dong, Dong, Ziyan, Xiong, Lin, Bai, Wenjing, Li, Man, Guo, Rong, and He, Qin
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- 2024
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187. Context-dependent Grid-like Representations of Theta Power in Human Entorhinal Cortex
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Lv, Pengcheng, Chen, Dong, Zhang, Hui, Zhou, Wenjing, Wang, Mengyang, Grewe, Philip, Axmacher, Nikolai, and Wang, Liang
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- 2024
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188. Combination of menin and kinase inhibitors as an effective treatment for leukemia with NUP98 translocations
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Miao, Hongzhi, Chen, Dong, Ropa, James, Purohit, Trupta, Kim, EunGi, Sulis, Maria-Luisa, Ferrando, Adolfo, Cierpicki, Tomasz, and Grembecka, Jolanta
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- 2024
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189. Performance, kinetic characteristics and bacterial community of short-cut nitrification and denitrification system at different ferrous ion conditions
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Chang, Ben-ze, Zhang, Shuai, Chen, Dong-zhi, Gao, Kai-tuo, and Yang, Guang-feng
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- 2024
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190. COLEC10 inhibits the stemness of hepatocellular carcinoma by suppressing the activity of β-catenin signaling
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Cai, Mei-Na, Chen, Dong-Mei, Chen, Xin-Ru, Gu, Yu-Rong, Liao, Chun-Hong, Xiao, Le-Xin, Wang, Jia-Liang, Lin, Bing-Liang, Huang, Yue-Hua, and Lian, Yi-Fan
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- 2024
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191. Multiscale topology-enabled structure-to-sequence transformer for protein–ligand interaction predictions
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Chen, Dong, Liu, Jian, and Wei, Guo-Wei
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- 2024
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192. MQ quasi-interpolation-based level set method for structural topology optimization
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Yang, Chen-Dong, Feng, Jian-Hu, Ren, Jiong, and Shen, Ya-Dong
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- 2024
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193. Guided aggregation and disparity refinement for real-time stereo matching
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Yang, Jinlong, Wu, Cheng, Wang, Gang, and Chen, Dong
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- 2024
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194. Efficacy and Safety of Glecaprevir/Pibrentasvir in HCV Patients With Previous Direct-Acting Antiviral Therapy Failures: A Meta-Analysis
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Chao Shen, Haozhi Fan, Zhijun Ge, Weihua Cai, Jianguo Shao, Chen Dong, Hong Xue, Zuqiang Fu, Jun Li, Yun Zhang, and Ming Yue
- Subjects
pibrentasvir ,retreatment ,DAAs therapy failures ,meta-analysis ,glecaprevir ,Medicine (General) ,R5-920 - Abstract
Background: Since a greater number of hepatitis C virus (HCV) patients have access to direct-acting antiviral (DAA) based therapies, the number of patients not properly responding to prior DAA regimens is increasing. The objective of this comprehensive analysis was to assess the efficacy and safety of glecaprevir/pibrentasvir (GLE/PIB) in HCV patients who experienced previous DAA therapy failures.Methods: Bibliographic databases were systematically searched for relevant articles published by November 2020. The main endpoints were sustained viral response after 12 weeks (SVR12), adverse events (AEs; any grade) and severe adverse events (SAEs). Publication bias assessment was performed using funnel plots and the Egger's test.Results: Fourteen studies consisting of a total of 1,294 subjects were included in this study and the pooled estimate of SVR12, AEs and SAEs rates were 96.8% (95%CI: 95.1–98.2), 47.1% (95%CI: 26.0–69.3), and 1.8% (95%CI: 0.7–3.4), respectively. Subgroup analysis showed that pooled SVR12 rates were 97.9% (95%CI: 96.7–98.9) for Japan and 91.1% (95%CI: 87.3–94.3) for the United States; 95.8% (95%CI: 93.9–97.4) for genotype (GT)1 and 100.0% (95%CI: 99.6–100.0) for GT2; 95.3% (95%CI: 92.4–97.2) for cirrhosis and 96.3% (95%CI: 94.2–97.7) for non-cirrhosis cases. There was no publication bias included this study.Conclusion: This comprehensive analysis revealed that GLE/PIB is an effective and secure retreatment option for patients who did not optimally respond to DAA treatment, especially the Asian population with GT1-2.
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- 2020
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195. Analysis of the model of integration of multicultural media in the network’s space of public opinion
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Liang WANG and Chen DONG
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Distributed heterogeneity ,Information integration ,Multiculturalism ,Network environment ,Public opinion ,Museums. Collectors and collecting ,AM1-501 ,Bibliography. Library science. Information resources - Abstract
Abstract When the traditional Meta database model is used to integrate multicultural media in the network’s space of public opinion, the performance of cooperative processing of distributed heterogeneous network data is poor, the logic of integration of multicultural media information is poor, the integration time is long, and the accuracy is low. This article proposes a multicultural media integration model based on multi-agent collaboration, which combines the life cycle of multicultural media models in the network’s space of public opinion. In distributed heterogeneous network spaces of public opinion, data is obtained from the distributed multicultural media information source, transferred to the multi-agent, and the collaboration among the agents is constructed. The multicultural media integration model provides the work flow and the standard principle of the model, and shapes the integrated model’s architecture including the data layer, the middle layer, and the expression layer, so as to achieve the intelligent integration of the multicultural media information. The experimental results show that the proposed model has high practicability, high integration efficiency and accuracy, and can enhance the penetration of multicultural media brands.
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- 2020
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196. Donor γδT Cells Promote GVL Effect and Mitigate aGVHD in Allogeneic Hematopoietic Stem Cell Transplantation
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Yuan Song, Ying Zhu, Bo Hu, Yonghao Liu, Dandan Lin, Ziqi Jin, Zhinan Yin, Chen Dong, Depei Wu, and Haiyan Liu
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γδT cells ,IL-17 ,graft-versus-host disease ,graft-versus-leukemia ,hematopoietic stem cell transplantation ,Immunologic diseases. Allergy ,RC581-607 - Abstract
Disease relapse and graft-versus-host disease (GVHD) are the major complications affecting the outcomes of allogeneic hematopoietic stem cell transplantation (allo-HSCT). While the functions of αβT cells are extensively studied, the role of donor γδT cells in allo-HSCT is less well defined. Using TCRδ-/- donors lacking γδT cells, we demonstrated that donor γδT cells were critical in mediating graft-versus-leukemia (GVL) effect during allo-HSCT. In the absence of donor γδT cells, IFN-γ production by CD8+ T cells was severely impaired. Vγ4 subset was the major γδT cell subset mediating the GVL effect in vivo, which was partially dependent on IL-17A. Meanwhile, donor γδT cells could mitigate acute GVHD in a murine allo-HSCT model by suppressing CD4+ T cell activation and the major γδT cell subset that exerted this protective function was also Vγ4 γδT cells. Therefore, our findings provide evidence that donor γδT cells, especially Vγ4 subset, can enhance GVL effect and mitigate aGVHD during allo-HSCT.
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- 2020
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197. Downregulation of Squalene Synthase Broadly Impacts Isoprenoid Biosynthesis in Guayule
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Dante Placido, Niu Dong, Bashar Amer, Chen Dong, Grisel Ponciano, Talwinder Kahlon, Maureen Whalen, Edward E. K. Baidoo, and Colleen McMahan
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Parthenum argentatum ,guayule ,squalene synthase ,squalene ,natural rubber ,Microbiology ,QR1-502 - Abstract
Production of natural rubber by Parthenium argentaum (guayule) requires increased yield for economic sustainability. An RNAi gene silencing strategy was used to engineer isoprenoid biosynthesis by downregulation of squalene synthase (SQS), such that the pool of farnesyl diphosphate (FPP) substrate might instead be available to initiate natural rubber synthesis. Downregulation of SQS resulted in significantly reduced squalene and slightly increased rubber, but not in the same tissues nor to the same extent, partially due to an apparent negative feedback regulatory mechanism that downregulated mevalonate pathway isoprenoid production, presumably associated with excess geranyl pyrophosphate levels. A detailed metabolomics analysis of isoprenoid production in guayule revealed significant differences in metabolism in different tissues, including in active mevalonate and methylerythritol phosphate pathways in stem tissue, where rubber and squalene accumulate. New insights and strategies for engineering isoprenoid production in guayule were identified.
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- 2022
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198. Crown Profile Modeling and Prediction Based on Ensemble Learning
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Yuling Chen, Chen Dong, and Baoguo Wu
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crown profile model ,ensemble learning ,marginal model ,Plant ecology ,QK900-989 - Abstract
Improving prediction accuracy is a prominent modeling issue in relation to forest simulations, and ensemble learning is a new effective method for improving the precision of crown profile model simulations in order to overcome the disadvantages of statistical modeling. Background: Ensemble learning (a machine learning paradigm in which multiple learners are trained to achieve better performance) has strong nonlinear problem learning ability and flexibility in terms of analyzing longitudinal data, and it remains rarely explored so far in the field of crown profile modeling forest science. In this study, we explored the application of ensemble learning to the modeling and prediction of crown profiles. Methods: We evaluated the performance of ensemble learning procedures and marginal model in modeling crown profile using the crown profile database from China fir plantations in Fujian, in southern China. Results: The ensemble learning approach for the crown profile model appeared to have better performance and higher efficiency (R2 > 0.9). The crown equation model 18 showed an intermediate performance in its estimation, whereas GBDT (MAE = 0.3250, MSE = 0.2450) appeared to have the best performance and higher efficiency. Conclusions: The ensemble learning method can combine the advantages of multiple learners and has higher model accuracy, robustness and overall induction ability, and is thus an effective technique for crown profile modeling and prediction.
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- 2022
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199. Plasma Metabolite Signature Classifies Male LRRK2 Parkinson’s Disease Patients
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Chen Dong, Chandrashekhar Honrao, Leonardo O. Rodrigues, Josephine Wolf, Keri B. Sheehan, Matthew Surface, Roy N. Alcalay, and Elizabeth M. O’Day
- Subjects
Parkinson’s disease ,biomarker ,metabolite ,leucine ,machine learning ,Microbiology ,QR1-502 - Abstract
Parkinson’s disease (PD) is a progressive neurodegenerative disease, causing loss of motor and nonmotor function. Diagnosis is based on clinical symptoms that do not develop until late in the disease progression, at which point the majority of the patients’ dopaminergic neurons are already destroyed. While many PD cases are idiopathic, hereditable genetic risks have been identified, including mutations in the gene for LRRK2, a multidomain kinase with roles in autophagy, mitochondrial function, transcription, molecular structural integrity, the endo-lysosomal system, and the immune response. A definitive PD diagnosis can only be made post-mortem, and no noninvasive or blood-based disease biomarkers are currently available. Alterations in metabolites have been identified in PD patients, suggesting that metabolomics may hold promise for PD diagnostic tools. In this study, we sought to identify metabolic markers of PD in plasma. Using a 1H-13C heteronuclear single quantum coherence spectroscopy (HSQC) NMR spectroscopy metabolomics platform coupled with machine learning (ML), we measured plasma metabolites from approximately age/sex-matched PD patients with G2019S LRRK2 mutations and non-PD controls. Based on the differential level of known and unknown metabolites, we were able to build a ML model and develop a Biomarker of Response (BoR) score, which classified male LRRK2 PD patients with 79.7% accuracy, 81.3% sensitivity, and 78.6% specificity. The high accuracy of the BoR score suggests that the metabolomics/ML workflow described here could be further utilized in the development of a confirmatory diagnostic for PD in larger patient cohorts. A diagnostic assay for PD will aid clinicians and their patients to quickly move toward a definitive diagnosis, and ultimately empower future clinical trials and treatment options.
- Published
- 2022
- Full Text
- View/download PDF
200. Remote sensing comprehensive evaluation of land degradation based on relative rain use efficiency of vegetation
- Author
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Xing Yu, Yang Jinzhong, Sun Yaqing, Jiang Cunhao, and Chen Dong
- Subjects
Environmental sciences ,GE1-350 - Abstract
China is one of the countries with serious land degradation problems in the world. Land degradation directly threatens the food security of our country and determines the sustainable development of social economy. In this paper, the potential evapotranspiration and moisture index are calculated to divide the climatic zone of China. Based on the NPP and precipitation data, the national rRUE is obtained by the edge function. With the climate "relative benchmark", the rules of threshold analysis is used to comprehensively evaluate the land degradation in China. The results show that: excellent land is concentrated in northeast China, western Xinjiang and eastern Qinghai-Tibet Plateau; mildly degraded land is widely and sporadically distributed in the eastern plain of China; moderately degraded land and severely degraded land are concentrated in western Inner Mongolia, southern Xinjiang and northern Qinghai-Xizang Plateau.
- Published
- 2022
- Full Text
- View/download PDF
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