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2021 Vol. 51, No. 5

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Invited Reviews
Regulatory role of phosphorylation in NLRP3 inflammasome activation
Huang Yi, Zhou Rongbin
2021, 51(5): 345-352. doi: 10.52396/JUST-2021-0079
Article Views:471 Full article PDF
Abstract:
NLRP3 is a pattern recognition receptor localized in the cytoplasm that belongs to the NOD-like receptor family. Upon activation by a wide range of danger-associated molecular patterns (DAMPs) and pathogen-associated molecular patterns (PAMPs), NLRP3 recruits the adaptor protein ASC and the cysteine protease pro-caspase-1 to form a multiprotein complex called the NLRP3 inflammasome. The primary function of the NLRP3 inflammasome is to maintain homeostasis by facilitating the immune response to remove pathogens and danger signals. However, aberrant activation of the NLRP3 inflammasome also causes a variety of inflammatory diseases.Therefore, NLRP3 inflammasome activation must be precisely regulated. Recently, various kinases and phosphatases have been reported to control the NLRP3 inflammasome activation, suggesting that phosphorylation plays a vital role in regulating the inflammasome activation. In this review, we summarize how various kinases and phosphatases control the NLRP3 inflammasome activation and provide an overview of the regulatory role of phosphorylation in the NLRP3 inflammasome activation. Further, we discuss the potential pharmacologically compounds that target NLRP3-related kinases or phosphatases for the treatment of inflammasome-driven diseases.
Research Articles: Life Sciences and Medicine
A navigational system for investigating multi-sensory integration in Caenorhabditis elegans
Zhao Bingzhen, Luo Linjiao, Wen Quan
2021, 51(5): 353-359. doi: 10.52396/JUST-2021-0096
Article Views:238 Full article PDF
Abstract:
Animals use different sensory cues to guide their behaviors. How a nervous system performs multi-sensory integration remains an open question in neuroscience. Here, we study how the nematode Caenorhabditis elegans integrates temperature and salt stimuli, two environmental cues that are essential for survival. We report the development of a navigational system that allows stable, linear, and orthogonal temperature gradient and salt gradient to be simultaneously presented to an animal. By combining this setup with a tracking and calcium imaging system, we analyze the behavioral strategies of C. elegans and investigate the functions of two cilia sensory neurons—AFD and ASER—that attend the behavior. Our work opens a new window into interrogating the neural mechanisms for multi-sensory integration in a compact nervous system.
Carbonic anhydrase inhibitor U-104 inhibits tumor progression through CA9 and CA12 in tongue squamous cell carcinoma
Yang Zixuan, Zhang Xuehan, Shen Tao, Shi Ronghua, Wang Xiangting
2021, 51(5): 360-368. doi: 10.52396/JUST-2021-0063
Article Views:279 Full article PDF
Abstract:
U-104, an effective inhibitor of carbonic anhydrases (CAs), has been shown as a potential anti-tumor drug in several human cancer types.However, the downstream mechanisms of U-104 and its functions in tongue squamous cell carcinoma (TSCC) remain unclear. It is neither confirmed that whether the anti-tumor effects of U-104 are dependent on CA9 and CA12. In this work, we found differentially expressed genes (DEGs) and potential cellular processes regulated by U-104 through RNA sequencing. The cell death-related, cell proliferation, migration and response to drug cellular processes were among the top GO (gene ontology) processes, which were consistent with the observed biological effects upon U-104 treatment in TSCC15 cells. Furthermore, knockdown (KD) of CA9 or CA12 completely eliminated the U-104 effects on the cell migration, cell death, and the expression of critical DEGs. All together, our study suggests the regulatory mechanisms of U-104 at the transcriptome level and demonstrates the anti-tumor functions of U-104 dependent on CA9 and CA12 in TSCC. Our findings expand the current knowledge on the anti-tumor functions of U-104 and provide a potential therapeutic option for TSCC.
Research Articles: Mathematics
The stable subgroups of Sn acting on M0,n
Xia Xiaopeng
2021, 51(5): 369-373. doi: 10.52396/JUST-2021-0040
Article Views:158 Full article PDF
Abstract:
Considering the action of the symmetric group Sn on M0,n, all the possible stable subgroups were obtained.
Cycle lengths in graphs of chromatic number five and six
Huo Qingyi
2021, 51(5): 374-381. doi: 10.52396/JUST-2021-0119
Article Views:186 Full article PDF
Abstract:
A problem was proposed by Moore and West to determine whether every (k+1)-critical non-complete graph has a cycle of length 2 modulo k. We prove a stronger result that for k=4, 5, every (k+1)-critical non-complete graph contains cycles of all lengths modulo k.
A manifold extended t-process regression
Guo Shiwei, Wang Zhanfeng, Wu Yaohua
2021, 51(5): 382-389. doi: 10.52396/JUST-2021-0026
Article Views:174 Full article PDF
Abstract:
A manifold extended t-process regression (meTPR) model is developed to fit functional data with a complicated input space. A manifold method is used to transform covariate data from input space into a feature space, and then an extended t-process regression is used to map feature from feature space into observation space. An estimation procedure is constructed to estimate parameters in the model. Numerical studies are investigated with both synthetic data and real data, and results show that the proposed meTPR model performs well.
Inference of online updating approach to nonparametric smoothing of big data
Chen Ziyu, Guo Xiao
2021, 51(5): 390-403. doi: 10.52396/JUST-2021-0078
Article Views:213 Full article PDF
Abstract:
The online updating method (ONLINE) is an efficient analysis approach applied to big data. We prove the asymptotic properties and conduct statistical inference of the ONLINE models in kernel density and kernel regression. Several algorithms are proposed to solve the problems of the bandwidth selection in kernel density and regression respectively. We verify the asymptotic normality of the ONLINE density model in simulation and apply the ONLINE linear kernel regression to the Volatility Index (VIX) prediction. The empirical results show that the ONLINE linear kernel regression model achieves a comparable performance in continuously arriving option data streams prediction with significantly lower complexity than the classical local linear regression model.
Research Articles: Management Science and Engineering
Impact of COVID-19 pandemic on stock market via sparse principal component analysis
Li Ming, Wen Canhong
2021, 51(5): 404-418. doi: 10.52396/JUST-2021-0102
Article Views:276 Full article PDF
Abstract:
The COVID-19 pandemic has caused severe public health and economic consequences around the world. It is of great importance to evaluate the impact of the COVID-19 pandemic on the economy, especially the stock market. To this end, we proposed to use several state-of-art sparse principal component analysis (PCA) methods for the stock data of the CSI 300 index from February 1, 2019 to February 1, 2021. To show the influence of the outbreak of the COVID-19 pandemic, we divide this period into two periods, i.e., before and after January 1, 2020. Based on this division, we attempted to extract the principal components and construct portfolio accordingly. The results show that the proportion of principal components representing the market declined after the outbreak. For the constitution in the first two principal components, the important stock sets are substantially different after the outbreak. The stocks from the health care sector start to play an important role in the portfolio of the CSI 300 index after the outbreak. Compared with the CSI 300 index, the first two principal components from the sparse PCA methods can obtain higher returns with a much smaller set of stocks in the portfolio. In conclusion, the outbreak of the COVID-19 pandemic led to changes in both proportion and constitution of the principal component of the stocks in the CSI 300 index.
Pricing strategies of laborer-sharing platform in two transaction modes
Guan Shuhan, Sheng Jianchao, Du Shaofu
2021, 51(5): 419-430. doi: 10.52396/JUST-2021-0083
Article Views:201 Full article PDF
Abstract:
With the advancement of Internet information technology,the laborer-sharing platform plays a crucial role in promoting the full use of human resources across the whole society. At present, multiple trading modes with different pricing strategies are adopted by the laborer-sharing platform. Considering the heterogeneity of laborers’ abilities, we construct the laborer-sharing platform’s profit functions under the buyer pricing strategy and laborer pricing strategy, and analyze its optimal pricing strategy in the bidding mode.First, our analysis shows that when the mismatch degree between the service of the low-type laborer and the buyer’s task is close to that of the high-type laborer, the laborer pricing strategy is beneficial to the platform. Second,when the task mismatch degree of the low-type laborer is much lower than that of the high-type laborer, the platform’s pricing strategy depends on the buyer’s satisfaction with the completing task. Finally, we compare two transaction models: the bidding mode and the piece mode, and find that under the laborer pricing strategy, the platform’s profit in the bidding mode is not always higher than that in the piece mode.

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