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| 1 | Nitric oxide suppresses NLRP3 inflammasome activation and protects against LPS-induced septic shock显示文摘Inflammasomes 是触发 caspase-1 的激活和 interleukin-1β 的成熟的多蛋白质建筑群;(IL-1β) ,然而,这些建筑群的规定仍然保持糟糕描绘了。这里,我们显示出那氮的氧化物(没有) 禁止了调停 NLRP3 的 ASC pyroptosome 形成, caspase-1 激活和 IL-1β在从老鼠和人的 myeloid 房间的分泌物。同时,内长不否定地也源于 iNOS (没有 synthase 的可诱导的形式) 调整 NLRP3 inflammasome 激活。iNOS 的弄空响应 LPS 和 ATP 导致了不正常的线粒体的增加的累积,它为增加的 IL-1β 负责;生产和 caspase-1 激活。没有生产的 iNOS 缺乏或药理学抑制在 vivo 提高了 NLRP3 依赖的 cytokine 生产,因此在老鼠从导致 LPS 的败血增加死亡,它被 NLRP3 阻止缺乏。我们的结果因此经由线粒体的稳定作为 NLRP3 inflammasome 的一个批评否定管理者不识别。这研究有重要含意让新策略的设计控制 NLRP3 相关的疾病。 | Kairui Mao Shuzhen Chen Mingkuan Chen Yonglei Ma Yan Wang Bo Huang Zhengyu He Yan Zeng Yu Htl Shuhui Sun Jing Li Xiaodong Wu Xiangrui Wang Warren Strober Chang Chen Guangxun Meng Bing Sun | 2013 | Cell Research2013，23，2： | 59 |
| 2 | Effects of different machine transplanting methods on the physiological and yield characteristics of late rice in China显示文摘To address problems caused by rice machine transplanting such as injury to the seedlings and recovery period that extend growth period,this study explored the effects of different machine transplanting methods on the physiological and yield characteristics of late rice in China,and determine the appropriate machine transplanting method for late rice,which was expected to provide a basis for high-yield and high-efficient cultivation of machine-transplanted late rice.Hybrid indica rice Taiyou 398 and conventional indica rice Jing Gangruanzhan were selected as the research objects,and large-pot carpet seedling machine transplanting(M1),conventional pot carpet seedling machine transplanting(M2)and ordinary carpet seedling machine transplanting(M3)were adopted respectively to analyze their effects on seedling quality,population physiological characteristics,yield and its components and economic benefits of late rice.The results showed that compared with M2 and M3,M1 achieved higher seedling quality,showing significant advantages in the early stage despite average root entwining force that met the requirement of machine transplanting.The seedlings transplanted using M1 had shorter recovery period after mechanical transplanting,with earlier tillering,earlier peak seedling,and slower declining of stems and tillers in the late stage;the peak seedling number was not high,but the effective tiller number and earbearing tiller percentage were significantly higher than those achieved by the other two machine transplanting methods.Also,M1 achieved stronger photosynthetic capacity of flag leaves before HS,with more photosynthetic products in stems and leaves transported to panicles and more efficiently after HS.Compared with seedlings transplanted using M2 and M3,the recovery period of those transplanted using M1 was shortened by 3 and 5 d,the heading stage(HS),and maturity stage(MS)were advanced,which effectively reduced the risk and impact of“cold dew wind”on machine-transplanted late rice.M1 had significant yield increase advantage and economic benefit,with better grain maturity,and“larger panicles,more panicles,more and fuller grains”.M1 achieved an average yield increase of 10.31%-11.10%,20.67%-25.10%in 2 years,and an average income increase of 18.65%-131.06%and 62.85%-323.78%,respectively.Therefore,vigorously developing M1 is the key to the high-yield and high-efficient cultivation of machine-transplanted late rice in China. | Xuan Jia Yonglei Li Jiannong Song Cailing Liu Xiaolin Cao Licai Chen Lipengcheng Wan Xiang Ma | 2023 | International Journal of Agricultural and Biological Engineering2023，16，6： | 0 |
| 3 | Estimation of Potato Biomass and Yield Based on Machine Learning from Hyperspectral Remote Sensing Data显示文摘The estimation of potato biomass and yield can optimize the planting pattern and tap the production potential.Based on partial least square(PLSR),multiple linear regression(MLR),support vector machine(SVM),random forest(RF),BP neural network and other machine learning algorithms,the biomass estimation model of potato in different growth stages is constructed by using single variables such as original spectrum,first-order differential spectrum,combined spectrum index and vegetation index(VI)and their coupled combination variables.The accuracy of the models is compared and analyzed,and the best modeling method of biomass in different growth stages is selected.Based on the optimized modeling method,the biomass of each growth stage is estimated,and the yield estimation model of different growth stages is constructed based on the estimation results and the linear regression analysis method,and the accuracy of the model is verified.The results showed that in tuber formation stage,starch accumulation stage and maturity stage,the biomass estimation accuracy based on combination variable was the highest,the best modeling method was MLR and SVM,in tuber growth stage,the best modeling method was MLR,the effect of yield estimation is good.It provides a reference for the algorithm selection of crop biomass and yield models based on machine learning. | Changchun Li Chunyan Ma Haojie Pei Haikuan Feng Jinjin Shi Yilin Wang Weinan Chen Yacong Li Xiaowei Feng Yonglei Shi | 2020 | Journal of Agricultural Science and Technology(B)2020，10，4： | 0 |
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