The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which li...The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobodyeantigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.展开更多
为在预警监视系统中对多目标的检测、跟踪、识别过程进行统一处理,提出一种基于跳转马尔可夫系统模型高斯混合概率假设密度滤波(jump Markov system model Gaussian mixture probability hypothesis density filtering,JMS-GMPHDF)算法...为在预警监视系统中对多目标的检测、跟踪、识别过程进行统一处理,提出一种基于跳转马尔可夫系统模型高斯混合概率假设密度滤波(jump Markov system model Gaussian mixture probability hypothesis density filtering,JMS-GMPHDF)算法的雷达、电子支援措施(electronic support measures,ESM)综合多目标检测、跟踪与识别方法。该方法首先根据不同类别目标设计各自的多目标多模型高斯混合概率假设密度滤波器,并在各滤波器处理过程中同时对高斯项进行编号;然后,根据目标速度与加速度模型信息进行高斯项综合与类别判决,同时根据ESM测量信息进行型号判决;最后,通过航迹综合管理,形成具有运动状态信息以及类别、型号、航迹编号信息的确定航迹。仿真实验验证了该方法能够有效综合雷达、ESM测量数据,在进行多目标检测、跟踪的同时进行正确的类别、型号判决,并形成确定航迹。展开更多
地球系统模式是研究气候变化、进行地球系统建模的重要软件.中科院地球系统模式CAS-ESM (Chinese Academy of Sciences-Earth System Model)是中科院大气所发展的进行地球系统模拟的高性能计算应用软件,目前已经发布了2.0版本,其模拟性...地球系统模式是研究气候变化、进行地球系统建模的重要软件.中科院地球系统模式CAS-ESM (Chinese Academy of Sciences-Earth System Model)是中科院大气所发展的进行地球系统模拟的高性能计算应用软件,目前已经发布了2.0版本,其模拟性能一直是制约其发展的关键因素之一.为了对CAS-ESM 2.0进行性能评估和分析,将CAS-ESM 2.0移植到中科院高性能计算系统"元"和"地球系统数值模拟装置"原型系统这两大高性能计算平台上,开展了耦合数值模拟试验.试验结果显示, CAS-ESM 2.0存在受平台影响的性能差异,大气模式的运行时间占比最高,超过了其他分模式的总和,部分分模式存在可扩展性问题.然后对试验结果进行了进一步的分析,发现大气模式的性能瓶颈主要是由通信造成的.因而对CAS-ESM 2.0的后续研发发展工作中, CAS-ESM的跨平台优化、大气模式的性能优化与并行算法改进、分模式的可扩展性应该是研究的重点之一.展开更多
主要评估了美国国家大气研究中心的NCAR CESM(Community Earth System Model,NCAR)和中国科学院的CAS ESM(Earth System Model,Chinese Academy of Sciences)两个地球系统模式对亚洲东部夏季气候态的模拟性能。使用NCAR CESM和CAS ESM...主要评估了美国国家大气研究中心的NCAR CESM(Community Earth System Model,NCAR)和中国科学院的CAS ESM(Earth System Model,Chinese Academy of Sciences)两个地球系统模式对亚洲东部夏季气候态的模拟性能。使用NCAR CESM和CAS ESM各两种不同的水平分辨率,一共进行了4组长达19年(1998~2016年)的数值积分试验,并通过对2 m气温、降水强度和降水日变化等的分析,比较了这两个模式在亚洲东部的模拟性能。结果表明,CAS ESM和NCAR CESM均能模拟出夏季2 m气温和降水强度的大尺度分布特征,但整体上模拟得到的地表面气温偏暖、降水强度偏弱。对于降水日变化而言,观测的日降水峰值在陆地上主要发生在下午到傍晚时段,在海洋上则出现在午夜到凌晨时段。两组低分辨率试验模拟的陆地降水峰值出现过早,且无法模拟出四川盆地的夜间降水峰值和部分海洋地区凌晨或上午的降水峰值。提高分辨率对模式的模拟性能有显著的提升作用。高分辨率下,NCAR CESM和CAS ESM对陆地和海洋的降水日变化模拟性能都明显提高。对降水日变化的定量化分析表明,高分辨率CAS ESM模式对整个亚洲东部降水日变化的模拟最优。目前模式对海陆风的模拟还不太理想,未来要进一步提高模式模拟性能,需要重点完善与气温、降水过程相关的物理参数化方案。展开更多
耦合器是地球系统模式(earth system model,ESM)的重要组成部分,用于连接各个分量模式。针对地球系统模式中的耦合接口进行编程操作,使得分量模式的代码从耦合系统中分离出来,从而使得模式专家只需要了解耦合接口而不再需要了解耦合器...耦合器是地球系统模式(earth system model,ESM)的重要组成部分,用于连接各个分量模式。针对地球系统模式中的耦合接口进行编程操作,使得分量模式的代码从耦合系统中分离出来,从而使得模式专家只需要了解耦合接口而不再需要了解耦合器的复杂内部实现。为此提出了两种耦合接口技术:一是耦合接口代码复用技术,将各个分量模式形式相似的代码段复用为统一的接口;二是耦合接口代码自动生成技术,根据统一的模板文件,模式专家只需要在配置文件中提供相应的变量信息,便可通过模板文件自动生成分量模式的代码。基于以上工作,将改写耦合接口后的地球系统模式部署到中科院超级计算机"元"上,结果表明经过代码复用及自动生成后的耦合接口与原来代码模拟结果一致。展开更多
Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC ...Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.展开更多
The ocean could profoundly modulate the ever-increasing atmospheric CO_(2) by air-sea CO_(2) exchange process,which is also able to cause signifi cant changes of physical and biogeochemical properties in return.In thi...The ocean could profoundly modulate the ever-increasing atmospheric CO_(2) by air-sea CO_(2) exchange process,which is also able to cause signifi cant changes of physical and biogeochemical properties in return.In this study,we assessed the long-term average and spatial-temporal variability of global air-sea CO_(2) exchange fl ux(F CO_(2))since 1980s basing on the results of 18 Coupled Model Intercomparison Project Phase 6(CMIP6)Earth System Models(ESMs).Our fi ndings indicate that the CMIP6 ESMs simulated global CO_(2) sink in recent three decades ranges from 1.80 to 2.24 Pg C/a,which is coincidence with the results of cotemporaneous observations.What’s more,the CMIP6 ESMs consistently show that the global oceanic CO_(2) sink has gradually intensifi ed since 1980s as well as the observations.This study confi rms the simulated F CO_(2) could reach agreements with the observations in the aspect of primary climatological characteristics,however,the simulation skills of CIMP6 ESMs in diverse open-sea biomes are unevenness.None of the 18 CMIP6 ESMs could reproduce the observed F CO_(2) increasement in the central-eastern tropical Pacifi c and the midlatitude Southern Ocean.Defi ciencies of some CMIP6 ESMs in reproducing the atmospheric pressure systems of the Southern Hemisphere and the El Niño-Southern Oscillation(ENSO)mode of the tropical Pacifi c are probably the major causes.展开更多
基金supported by the National Natural Science Foundation of China(Grant Nos.:92477103,22273023,12474285 and 22373116)the National Key R&D Program of China(Grant No.:2019YFA0905200)+5 种基金Shanghai Municipal Natural Science Foundation(Grant No.:23ZR1418200)Natural Science Foundation of Chongqing,China(Grant No.:CSTB2023NSCQ-MSX0616)Shanghai Frontiers Science Center of Molecule Intelligent SynthesesShanghai Future Discipline Program(Quantum Science and Tech-nology)Shanghai Municipal Education Commission’s“Artificial Intelligence-Driven Research Paradigm Reform and Discipline Advancement Program”the Fundamental Research Funds for the Central Universities.
文摘The identification and optimization of mutations in nanobodies are crucial for enhancing their thera-peutic potential in disease prevention and control.However,this process is often complex and time-consuming,which limit its widespread application in practice.In this study,we developed a work-flow,named Evolutionary-Nanobody(EvoNB),to predict key mutation sites of nanobodies by combining protein language models(PLMs)and molecular dynamic(MD)simulations.By fine-tuning the ESM2 model on a large-scale nanobody dataset,the ability of EvoNB to capture specific sequence features of nanobodies was significantly enhanced.The fine-tuned EvoNB model demonstrated higher predictive accuracy in the conserved framework and highly variable complementarity-determining regions of nanobodies.Additionally,we selected four widely representative nanobodyeantigen complexes to verify the predicted effects of mutations.MD simulations analyzed the energy changes caused by these mu-tations to predict their impact on binding affinity to the targets.The results showed that multiple mu-tations screened by EvoNB significantly enhanced the binding affinity between nanobody and its target,further validating the potential of this workflow for designing and optimizing nanobody mutations.Additionally,sequence-based predictions are generally less dependent on structural absence,allowing them to be more easily integrated with tools for structural predictions,such as AlphaFold 3.Through mutation prediction and systematic analysis of key sites,we can quickly predict the most promising variants for experimental validation without relying on traditional evolutionary or selection processes.The EvoNB workflow provides an effective tool for the rapid optimization of nanobodies and facilitates the application of PLMs in the biomedical field.
文摘为在预警监视系统中对多目标的检测、跟踪、识别过程进行统一处理,提出一种基于跳转马尔可夫系统模型高斯混合概率假设密度滤波(jump Markov system model Gaussian mixture probability hypothesis density filtering,JMS-GMPHDF)算法的雷达、电子支援措施(electronic support measures,ESM)综合多目标检测、跟踪与识别方法。该方法首先根据不同类别目标设计各自的多目标多模型高斯混合概率假设密度滤波器,并在各滤波器处理过程中同时对高斯项进行编号;然后,根据目标速度与加速度模型信息进行高斯项综合与类别判决,同时根据ESM测量信息进行型号判决;最后,通过航迹综合管理,形成具有运动状态信息以及类别、型号、航迹编号信息的确定航迹。仿真实验验证了该方法能够有效综合雷达、ESM测量数据,在进行多目标检测、跟踪的同时进行正确的类别、型号判决,并形成确定航迹。
文摘地球系统模式是研究气候变化、进行地球系统建模的重要软件.中科院地球系统模式CAS-ESM (Chinese Academy of Sciences-Earth System Model)是中科院大气所发展的进行地球系统模拟的高性能计算应用软件,目前已经发布了2.0版本,其模拟性能一直是制约其发展的关键因素之一.为了对CAS-ESM 2.0进行性能评估和分析,将CAS-ESM 2.0移植到中科院高性能计算系统"元"和"地球系统数值模拟装置"原型系统这两大高性能计算平台上,开展了耦合数值模拟试验.试验结果显示, CAS-ESM 2.0存在受平台影响的性能差异,大气模式的运行时间占比最高,超过了其他分模式的总和,部分分模式存在可扩展性问题.然后对试验结果进行了进一步的分析,发现大气模式的性能瓶颈主要是由通信造成的.因而对CAS-ESM 2.0的后续研发发展工作中, CAS-ESM的跨平台优化、大气模式的性能优化与并行算法改进、分模式的可扩展性应该是研究的重点之一.
文摘主要评估了美国国家大气研究中心的NCAR CESM(Community Earth System Model,NCAR)和中国科学院的CAS ESM(Earth System Model,Chinese Academy of Sciences)两个地球系统模式对亚洲东部夏季气候态的模拟性能。使用NCAR CESM和CAS ESM各两种不同的水平分辨率,一共进行了4组长达19年(1998~2016年)的数值积分试验,并通过对2 m气温、降水强度和降水日变化等的分析,比较了这两个模式在亚洲东部的模拟性能。结果表明,CAS ESM和NCAR CESM均能模拟出夏季2 m气温和降水强度的大尺度分布特征,但整体上模拟得到的地表面气温偏暖、降水强度偏弱。对于降水日变化而言,观测的日降水峰值在陆地上主要发生在下午到傍晚时段,在海洋上则出现在午夜到凌晨时段。两组低分辨率试验模拟的陆地降水峰值出现过早,且无法模拟出四川盆地的夜间降水峰值和部分海洋地区凌晨或上午的降水峰值。提高分辨率对模式的模拟性能有显著的提升作用。高分辨率下,NCAR CESM和CAS ESM对陆地和海洋的降水日变化模拟性能都明显提高。对降水日变化的定量化分析表明,高分辨率CAS ESM模式对整个亚洲东部降水日变化的模拟最优。目前模式对海陆风的模拟还不太理想,未来要进一步提高模式模拟性能,需要重点完善与气温、降水过程相关的物理参数化方案。
文摘耦合器是地球系统模式(earth system model,ESM)的重要组成部分,用于连接各个分量模式。针对地球系统模式中的耦合接口进行编程操作,使得分量模式的代码从耦合系统中分离出来,从而使得模式专家只需要了解耦合接口而不再需要了解耦合器的复杂内部实现。为此提出了两种耦合接口技术:一是耦合接口代码复用技术,将各个分量模式形式相似的代码段复用为统一的接口;二是耦合接口代码自动生成技术,根据统一的模板文件,模式专家只需要在配置文件中提供相应的变量信息,便可通过模板文件自动生成分量模式的代码。基于以上工作,将改写耦合接口后的地球系统模式部署到中科院超级计算机"元"上,结果表明经过代码复用及自动生成后的耦合接口与原来代码模拟结果一致。
基金supported by the CAS Strategic Priority Research Program(Grant No.XDA05110303)the"973"programs(Grant Nos.2012CB417203 and 2010CB950404)+1 种基金the"863"program(Grant No.2010AA012305)the National Science Foundation of China(Grant Nos.41023002 and 40805038)
文摘Earth System Models （ESMs） are fundamental tools for understanding climate-carbon feedback. An ESM version of the Flexible Global Ocean-Atmosphere-Land System model （FGOALS） was recently developed within the IPCC AR5 Coupled Model Intercomparison Project Phase 5 （CMIP5） modeling framework, and we describe the development of this model through the coupling of a dynamic global vegetation and terrestrial carbon model with FGOALS-s2. The performance of the coupled model is evaluated as follows. The simulated global total terrestrial gross primary production （GPP） is 124.4 PgC yr-I and net pri- mary production （NPP） is 50.9 PgC yr-1. The entire terrestrial carbon pools contain about 2009.9 PgC, comprising 628.2 PgC and 1381.6 PgC in vegetation and soil pools, respectively. Spatially, in the tropics, the seasonal cycle of NPP and net ecosystem production （NEP） exhibits a dipole mode across the equator due to migration of the monsoon rainbelt, while the seasonal cycle is not so significant in Leaf Area Index （LAI）. In the subtropics, especially in the East Asian monsoon region, the seasonal cycle is obvious due to changes in temperature and precipitation from boreal winter to summer. Vegetation productivity in the northern mid-high latitudes is too low, possibly due to low soil moisture there. On the interannual timescale, the terrestrial ecosystem shows a strong response to ENSO. The model- simulated Nifio3.4 index and total terrestrial NEP are both characterized by a broad spectral peak in the range of 2-7 years. Further analysis indicates their correlation coefficient reaches -0.7 when NEP lags the Nifio3.4 index for about 1-2 months.
基金Supported by the National Natural Science Foundation of China(No.41806133)the Marine S&T Fund of Shandong Province for the Pilot National Laboratory for Marine Science and Technology(Qingdao)(No.2022QNLM040003-1)+1 种基金the National Key Research and Development Program of China(No.2017YFA0603204)the Fund of Key Laboratory of Global Change and Marine-Atmospheric Chemistry,MNR(No.GCMAC1905)。
文摘The ocean could profoundly modulate the ever-increasing atmospheric CO_(2) by air-sea CO_(2) exchange process,which is also able to cause signifi cant changes of physical and biogeochemical properties in return.In this study,we assessed the long-term average and spatial-temporal variability of global air-sea CO_(2) exchange fl ux(F CO_(2))since 1980s basing on the results of 18 Coupled Model Intercomparison Project Phase 6(CMIP6)Earth System Models(ESMs).Our fi ndings indicate that the CMIP6 ESMs simulated global CO_(2) sink in recent three decades ranges from 1.80 to 2.24 Pg C/a,which is coincidence with the results of cotemporaneous observations.What’s more,the CMIP6 ESMs consistently show that the global oceanic CO_(2) sink has gradually intensifi ed since 1980s as well as the observations.This study confi rms the simulated F CO_(2) could reach agreements with the observations in the aspect of primary climatological characteristics,however,the simulation skills of CIMP6 ESMs in diverse open-sea biomes are unevenness.None of the 18 CMIP6 ESMs could reproduce the observed F CO_(2) increasement in the central-eastern tropical Pacifi c and the midlatitude Southern Ocean.Defi ciencies of some CMIP6 ESMs in reproducing the atmospheric pressure systems of the Southern Hemisphere and the El Niño-Southern Oscillation(ENSO)mode of the tropical Pacifi c are probably the major causes.
