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| 1 | Ubiquitylation of p62/sequestosome1 activates its autophagy receptor function and controls selective autophagy upon ubiquitin stress显示文摘在细胞的 ubiquitin (Ub ) 的改变动态平衡,作为 Ub 知道强调,展示并且影响处于多重条件的细胞的回答,然而,内在的机制不完全地被理解。这里,我们报导 autophagy 受体 p62/sequestosome-1 与结合酶, UBE2D2 和 UBE2D3 的 E2 Ub 交往。内长的 p62 在 Ub 动态平衡的 upregulation 期间经历 E2 依赖的 ubiquitylation,一个条件作为 Ub + 应力称为,那对由 bortezomib 的 Ub overexpression,热吃惊或延长 proteasomal 抑制内在,化学疗法的药。p62 的 Ubiquitylation 破坏 p62 的 UBA 领域的 dimerization,解放它的能力认出为选择 autophagy 的 polyubiquitylated 货物。我们进一步证明这机制可能为在 Ub + 压力条件之上的 autophagy 激活是批评的。机制的描述和在察觉到 Ub 应力并且控制选择 autophagy 的 p62 的规章的角色能帮助理解并且调制细胞的回答到许多内长、环境的挑战,潜在地对 autophagy 相关的病为治疗学的策略的发展打开一条新大街。 | Hong Peng Jiao Yang Guangyi Li Qing You Wen Han Tianrang Li Darning Gao Xiaoduo Xie Byung-Hoon Lee Juan Du Jian Hou Tao Zhang Hai Rao Ying Huang Qinrun Li Rong Zeng Lijian Hui Hongyan Wang Qin Xia Xuemin Zhang Yongning He Masaaki Komatsu Ivan Dikic Daniel Finley Ronggui Hu | 2017 | Cell Research2017，27，5： | 9 |
| 2 | A New Family of Galeaspids(Jawless Stem-Gnathostomata) from the Early Silurian of Chongqing, Southwestern China显示文摘A new genus and species of agnathan Eugaleaspidiformes(Galeaspida), Yongdongaspis littoralis gen. et sp. nov., is described from the Llandovery(lower Silurian) Huixingshao Formation at Yongdong Town, Xiushan County, Chongqing, southwestern China. This new Telychian taxon morphologically exhibits some transitional states between Sinogaleaspidae and a cluster of higher eugaleaspidiforms containing Tridensaspidae, Eugaleaspidae, Yunnanogaleaspis, and Nochelaspis, which we term here as the ’eugaleaspid cluster’. Phylogenetic analysis of an extended character matrix of Galeaspida reveals Yongdongaspis, on which Yongdongaspidae fam. nov. is erected, as the sister taxon of this ’eugaleaspid cluster’, supported by two synapomorphies, the presence of one median transverse canal, and two lateral transverse canals leaving from the infraorbital canal. As the first fish described from the Llandovery Huixingshao Formation in Chongqing, Yongdongaspis provides new fossil evidence for the subdivision and correlation of the Upper Red Beds in South China. | CHEN Yang GAI Zhikun LI Qiang WANG Jianhua PENG Lijian WEI Guangbiao ZHU Min | 2022 | Acta Geologica Sinica(English Edition)2022，96，2： | 2 |
| 3 | Fiber-Optic Raman Spectrum Sensor for Fast Diagnosis of Esophageal Cancer显示文摘A fiber-optic Raman spectrum sensor system is used for the fast diagnosis of esophageal cancer during clinical endoscopic examination.The system contains a 785nm exciting laser,a Raman fiber-optic probe with 7 large core fibers and a focus lens,and a highly sensitive spectrum meter.The Raman spectrum of the tissue could be obtained within 1 second by using such a system. A signal baseline removal and denoising technology is used to improve the signal quality.A novel signal feature extraction method for differentiating the normal and esophageal cancer tissues is proposed,based on the differences in half-height width(HHW)in 1200cm^-1 to 1400cm^-1 frequency band and the ratios of the spectral integral energy between 1600cm^-1-1700cm^-1 and 1500cm^-1- 1600cm^-1 band.It shows a high specificity and effectivity for the diagnosis of esophageal cancer. | Jianhua DAI Xiu HE Zhuoyue LI Kang LI Tingting YANG Zengling RAN Lijian YIN Yao CHEN Xiang ZOU Dianchun FANG Guiyong PENG | 2019 | Photonic Sensors2019，9，1： | 2 |
| 4 | The antihepatic fibrotic effects of fluorofenidone via MAPK signalling pathways显示文摘 | Yu Peng Huixiang Yang Tingting Zhu Menghua Zhao Yuexia Deng Bin Liu Hong Shen Gaoyun Hu Zhaohe Wang Lijian Tao | 2013 | Eur J Clin Invest2013，，4： | 1 |
| 5 | Opportunities and challenges of using big data for global health显示文摘The past two decades have witnessed the burgeoning of enormous digital technologies and data collected via countless channels.They are combined in numerous ways in different fields,including epidemiology,mHealth and modeling of health systems,with the intention to improve human health(e.g.,clinical decision support,electronic medical record management)[1-6].However,this is a new interdisciplinary area where no single scientific discipline knows how to take full advantage of these data and technologies to solve health problems[1]. | Peng Jia Hong Xue Shiyong Liu Hao Wang Lijian Yang Therese Hesketh Lu Ma Hongwei Cai Xin Liu Yaogang Wang Youfa Wang | 2019 | Science Bulletin2019，64，22： | 1 |
| 6 | Fluorofenidone Attenuates Inflammation by Inhibiting the NF-кB Pathway显示文摘 | Ling Huang Fangfang Zhang Yiting Tang Jiao Qin Yu Peng Lin Wu Fang Wang Qiongjing Yuan Zhangzhe Peng Jishi Liu Jie Meng Lijian Tao | 2014 | The American Journal of the Medical Sciences2014，，1： | 1 |
| 7 | The antihepatic fibrotic effects of fluorofenidone via MAPK signalling pathways显示文摘 | Yu Peng Huixiang Yang Tingting Zhu Menghua Zhao Yuexia Deng Bin Liu Hong Shen Gaoyun Hu Zhaohe Wang Lijian Tao | 2013 | Eur J Clin Invest2013，，4： | 1 |
| 8 | Fluorofenidone Attenuates Tubulointerstitial Fibrosis by Inhibiting TGF-[beta]1-Induced Fibroblast Activation显示文摘 | Yuan Qiongjing Wang Rui Peng Yu Fu Xiao Wang Wei Wang Linghao Zhang Fangfang Peng Zhangzhe Ning Wangbin Hu Gaoyun Wang Zhaohe Tao Lijian | 2011 | EN2011，，2： | 1 |
| 9 | The preoperative neutrophil-to-lymphocyte ratio predicts the outcomes of patients with hepatocellular carcinoma and cirrhosis after hepatectomy显示文摘Objective The aim of the study was to investigate the prognostic value of the preoperative peripheral neutrophil-to-lymphocyte ratio(NLR) in patients with hepatocellular cancer(HCC) and cirrhosis after hepatectomy. Methods This retrospective study included 321 patients with HCC who underwent resection. The NLR was calculated using the neutrophil and lymphocyte counts in routine preoperative blood tests. Receiver operating characteristic curve analysis was performed to select the most appropriate NLR cutoff value. The preoperative NLR, patient demographics, and clinical and pathological data, including disease-free survival(DFS) and overall survival(OS), were analyzed. Results The NLR was correlated with alpha-fetoprotein levels(χ2 = 5.876, P = 0.015), tumor size(χ2 = 32.046, P < 0.001), portal vein tumor thrombus(PVTT; χ2 = 4.930, P = 0.026), tumor encapsulation(χ2 = 7.243, P = 0.007), and recurrence(χ2 = 7.717, P = 0.005). Multivariate analyses illustrated that the number of tumors, PVTT, tumor size, and the NLR were independent factors for predicting DFS and OS. In patients with HCC and cirrhosis, but not among those without cirrhosis, a larger NLR predicted poorer postoperative DFS and OS(both P < 0.001). Conclusion As a simple, effective independent predictor for patients with HCC, the preoperative NLR plays an important role in accurately predicting the postoperative outcomes of patients with HCC and cirrhosis, but not those of patients without cirrhosis. | Yunpeng Hua Fei Ji Shunjun Fu Shunli Shen Shaoqiang Li Lijian Liang Baogan Peng | 2015 | Oncology and Translational Medicine2015，1，6： | 1 |
| 10 | Selective preparation for biofuels and high value chemicals based on biochar catalysts显示文摘The reuse of biomass wastes is crucial toward today’s energy and environmental crisis,among which,biomass-based biochar as catalysts for biofuel and high value chemical production is one of the most clean and economical solutions.In this paper,the recent advances in biofuels and high chemicals for selective production based on biochar catalysts from different biomass wastes are critically summarized.The topics mainly include the modification of biochar catalysts,the preparation of energy products,and the mechanisms of other high-value products.Suitable biochar catalysts can enhance the yield of biofuels and higher-value chemicals.Especially,the feedstock and reaction conditions of biochar catalyst,which affect the efficiency of energy products,have been the focus of recent attentions.Mechanism studies based on biochar catalysts will be helpful to the controlled products.Therefore,the design and advancement of the biochar catalyst based on mechanism research will be beneficial to increase biofuels and the conversion efficiency of chemicals into biomass.The advanced design of biochar catalysts and optimization of operational conditions based on the biomass properties are vital for the selective production of high-value chemicals and biofuels.This paper identifies the latest preparation for energy products and other high-value chemicals based on biochar catalysts progresses and offers insights into improving the yield of high selectivity for products as well as the high recyclability and low toxicity to the environment in future applications. | Hui LI Changlan HOU Yunbo ZHAI Mengjiao TAN Zhongliang HUANG Zhiwei WANG Lijian LENG Peng LIU Tingzhou LEI Changzhu LI | 2023 | Frontiers in Energy2023，17，5： | 0 |
| 11 | Machine learning predicting and engineering the yield,N content,and specific surface area of biochar derived from pyrolysis of biomass显示文摘Biochar produced from pyrolysis of biomass has been developed as a platform carbonaceous material that can be used in various applications.The specific surface area(SSA)and functionalities such as N-containing functional groups of biochar are the most significant properties determining the application performance of biochar as a carbon material in various areas,such as removal of pollutants,adsorption of CO_(2)and H2,catalysis,and energy storage.Producing biochar with preferable SSA and N functional groups is among the frontiers to engineer biochar materials.This study attempted to build machine learning models to predict and optimize specific surface area of biochar(SSA-char),N content of biochar(N-char),and yield of biochar(Yield-char)individually or simultaneously,by using elemental,proximate,and biochemical compositions of biomass and pyrolysis conditions as input variables.The predictions of Yield-char,N-char,and SSA-char were compared by using random forest(RF)and gradient boosting regression(GBR)models.GBR outperformed RF for most predictions.When input parameters included elemental and proximate compositions as well as pyrolysis conditions,the test R^(2) values for the single-target and multi-target GBR models were 0.90-0.95 except for the two-target prediction of Yield-char and SSA-char which had a test R^(2) of 0.84 and the three-target prediction model which had a test R^(2) of 0.81.As indicated by the Pearson correlation coefficient between variables and the feature importance of these GBR models,the top influencing factors toward predicting three targets were specified as follows:pyrolysis temperature,residence time,and fixed carbon for Yield-char;N and ash for N-char;ash and pyrolysis temperature for SSA-char.The effects of these parameters on three targets were different,but the trade-offs of these three were balanced during multi-target ML prediction and optimization.The optimum solutions were then experimentally verified,which opens a new way for designing smart biochar with target properties and oriented application potential. | Lijian Leng Lihong Yang Xinni Lei Weijin Zhang Zejian Ai Zequn Yang Hao Zhan Jianping Yang Xingzhong Yuan Haoyi Peng Hailong Li | 2022 | Biochar2022，4，1： | 0 |
| 12 | Improving the precision of optical metrology by detecting fewer photons with biased weak measurement显示文摘In optical metrological protocols to measure physical quantities,it is,in principle,always beneficial to in crease photon number n to improve measurement precision.However,practical constraints prevent the arbitrary increase of n due to the imperfections of a practical detector,especially when the detector response is dominated by the saturation effect.In this work,we show that a modified weak measurement protocol,namely,biased weak measurement significantly improves the precision of optical metrology in the presence of saturation effect.This method detects an ultra-small fraction of photons while main tains a considerable amount of metrological information.The biased pre-coupling leads to an additi onal reduction of photons in the post-selection and gene rates an extinction point in the spectrum distribution,which is extremely sensitive to the estimated parameter and difficult to be saturated.Therefore,the Fisher information can be persistently enhanced by increasing the photon number.In our magnetic-sensing experiment,biased weak measurement achieves precision approximately one order of magnitude better than those of previously used methods.The proposed method can be applied in various optical measurement schemes to remarkably mitigate the detector saturation effect with low-cost apparatuses. | Peng Yin Wen-Hao Zhang Liang Xu Ze-Gang Liu Wei-Feng Zhuang Lei Chen Ming Gong Yu Ma Xing-Xia ng Peng Gong-Chu Li Jin-Shi Xu Zong-Quan Zhou Lijian Zhang Geng Chen Chuan-Feng Li Guang-Can Guo | 2021 | Light(Science & Applications)2021，10，6： | 0 |
| 13 | Single-cell landscape analysis reveals distinct regression trajectories and novel prognostic biomarkers in primary neuroblastoma显示文摘Neuroblastoma(NB),which is the most common pediatric extracranial solid tumor,varies widely in its clinical presentation and outcome.NB has a unique ability to spontaneously differentiate and regress,suggesting a potential direction for therapeutic intervention.However,the underlying mechanisms of regression remain largely unknown,and more reliable prognostic biomarkers are needed for predicting trajectories for NB.We performed scRNAseq analysis on 17 NB clinical samples and three peritumoral adrenal tissues.Primary NB displayed varied cell constitution,even among tumors of the same pathological subtype.Copy number variation patterns suggested that neuroendocrine cells represent the malignant cell type.Based on the differential expression of sets of related marker genes,a subgroup of neuroendocrine cells was identified and projected to differentiate into a subcluster of benign fibroblasts with highly expressed CCL2 and ZFP36,supporting a progressive pathway of spontaneous NB regression.We also identified prognostic markers(STMN2,TUBA1A,PAGE5,and ETV1)by evaluating intra-tumoral heterogeneity.Lastly,we determined that ITGB1 in M2-like macrophages was associated with favorable prognosis and may serve as a potential diagnostic marker and therapeutic target.In conclusion,our findings reveal novel mechanisms underlying regression and potential prognostic markers and therapeutic targets of NB. | Qingqing Liu Zhenni Wang Yan Jiang Fengling Shao Yue Ma Mingzhao Zhu Qing Luo Yang Bi Lijian Cao Liang Peng Jianwu Zhou Zhenzhen Zhao Xiaobin Deng Tong-Chuan He Shan Wang | 2022 | Genes & Diseases2022，9，6： | 0 |
| 14 | Research on intelligent recognition method for self-blast state of glass insulator based on mixed data augmentation显示文摘Automatically and accurately detecting the self-blast state of glass insulators is of great significance to operation and maintenance of transmission lines.To solve the shortcomings of the existing open-loop cognitive models to detect the self-blast state of glass insulators,this study explores a mixed data augmentation-based intelligent recognition method to detect the self-blast state of the glass insulator,by imitating the human cognitive mode.Firstly,generative adversarial network is utilised to obtain the highquality generative self-blast samples of the glass insulator,and the non-generative data augmentation techniques is used to obtain rich sample features.Secondly,considering the characteristics of aerial images such as large scale variations,variable shooting angles and complex backgrounds,feature maps with strong semantics and adaptive multi-scale fusion are extracted using the feature pyramid network with adaptive hierarchy and the multi-deformable convolutional network.Then,the extracted feature maps are transmitted to a two-dimensional stochastic configuration network that can adaptively generate hidden nodes and basis functions so as to develop the self-blast state classification criteria with universal approximation capability.Thirdly,based on the generalised error and entropy theory,the semantic error entropy evaluation indices of recognition results are defined to evaluate in real time,the credibility of the uncertain recognition results for the self-blast state of the glass insulator.Then,based on transfer learning and the established self-optimising feedback mechanism for feature pyramid network,the self-optimising adjustment and reconstruction of the feature map space with strong semantics and multi-scale fusion and its classification criteria are realised.Finally,the stacking method is applied to integrate the recognition results of the feature pyramid network with adaptive hierarchy and multi-channel deformable convolutional networks to improve the robustness of the recognition model.Results of experimental comparison with other machine learning and deep learning methods verify the feasibility and effectiveness of the proposed method. | Siyao Peng Lijian Ding Weitao Li Wei Sun Qiyue Li | 2023 | High Voltage2023，8，4： | 0 |
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