| 1 | How are MCPIP1 and cytokines mutually regulated in cancer-related immunity?显示文摘Cytokines are secreted by various cell types and act as critical mediators in many physiological processes,including immune response and tumor progression.Cytokines production is precisely and timely regulated by multiple mechanisms at different levels,ranging from transcriptional to post-transcriptional and posttranslational processes.Monocyte chemoattractant protein-1 induced protein 1(MCPIP1),a potent immunosuppressive protein,was first described as a transcription factor in monocytes treated with monocyte chemoattractant protein-1(MCP-1)and subsequently found to possess intrinsic RNase and deubiquitinase activities.MCPIP1 tightly regulates cytokines expression via various functions.Furthermore,cytokines such as interleukin 1 beta(IL-1B)and MCP-1 and inflammatory cytokines inducer lipopolysaccharide(LPS)strongly induce MCPIP1 expression.Mutually regulated MCPIP1 and cytokines form a complicated network in the tumor environment.In this review,we summarize how MCPIP1 and cytokines reciprocally interact and elucidate the effect of the network formed by these components in cancer-related immunity with aim of exploring potential clinical benefits of their mutual regulation. | Ruyi Xu Yi Li Yang Liu Jianwei Qu Wen Cao Enfan Zhang Jingsong He Zhen Cai | 2020 | Protein & Cell2020，11，12： | 2 |
| 2 | Research on Freezing of Gait Recognition Method Based on Variational Mode Decomposition显示文摘Freezing of Gait(FOG)is the most common and disabling gait disorder in patients with Parkinson’s Disease(PD),which seriously affects the life quality and social function of patients.This paper proposes a FOG recognition method based on the Variational Mode Decomposition(VMD).Firstly,VMD instead of the traditional time-frequency analysis method to complete adaptive decomposition to the FOG signal.Secondly,to improve the accuracy and speed of the recognition algorithm,use the CART model as the base classifier and perform the feature dimension reduction.Then use the RUSBoost ensemble algorithm to solve the problem of unbalanced sample size and considerable limitations of a single classifier.Finally,the hyperparam-eters of the ensemble classifier are optimized by Bayesian optimization,and the experiment proves that the RUSBoost algorithm can complete the gait recognition task well.Compared with the Adaboost,Tomeklinks-Adaboost and ROS-Adaboost ensemble algorithms,the RUSBoost ensemble algorithm can complete the FOG recognition task more efficiently.When the maximum number of splits is 1023,and the number of base classifiers is 100,the performance of the RUSBoost ensemble algorithm can reach the best.The accuracy of the time recognition algorithm was 87.8%,the sensitivity was 89.7%,and the specificity was 87.5%. | Shoutao Li Ruyi Qu Yu Zhang Dingli Yu | 2023 | Intelligent Automation & Soft Computing2023，37，9： | 0 |
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