Considerations for the use of porcine organ donation models in preclinical organ donor intervention research

Use of animal models in preclinical transplant research is essential to the optimization of human allografts for clinical transplantation.Animal models of organ donation and preservation help to advance and improve technical elements of solid organ recovery and facilitate research of ischemia-reperfusion injury,organ preservation strategies,and future donor-based interventions.Important considerations include cost,public opinion regarding the conduct of animal research,translational value,and relevance of the animal model for clinical practice.We present an overview of two porcine models of organ donation:donation following brain death(DBD)and donation following circulatory death(DCD).The cardiovascular anatomy and physiology of pigs closely resembles those of humans,making this species the most appropriate for pre-clinical research.Pigs are also considered a potential source of organs for human heart and kidney xenotransplantation.It is imperative to minimize animal loss during procedures that are surgically complex.We present our experience with these models and describe in detail the use cases,procedural approach,challenges,alternatives,and limitations of each model.

Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management policies.As a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different scales.However,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance.To overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in 2021.The results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on uncertainty.Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to 0.43.Forward recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(<200),whereas Boruta is recommended when there are many environmental covariates(>500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty.When the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final predictions.Given the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales,so this approach can provide more reliable references for soil conservation policy-making.

采用STAMP-24Model的多组织事故分析

安全生产事故往往由多组织交互、多因素耦合造成,事故原因涉及多个组织。为预防和遏制多组织生产安全事故的发生,基于系统理论事故建模与过程模型(Systems-Theory Accident Modeling and Process,STAMP)、24Model,构建一种用于多组织事故分析的方法,并以青岛石油爆炸事故为例进行事故原因分析。结果显示:STAMP-24Model可以分组织,分层次且有效、全面、详细地分析涉及多个组织的事故原因,探究多组织之间的交互关系;对事故进行动态演化分析,可得到各组织不安全动作耦合关系与形成的事故失效链及管控失效路径,进而为预防多组织事故提供思路和参考。

Lateral downslope transport and tentative sedimentary organic carbon box model in the southern Yap Trench,western Pacific Ocean

Sediment collapse and subsequent lateral downslope migration play important roles in shaping the habitats and regulating sedimentary organic carbon(SOC)cycling in hadal trenches.In this study,three sediment cores were collected using a human-occupied vehicle across the axis of the southern Yap Trench(SYT).The total organic carbon(TOC)and total nitrogen(TN)contents,δ13C,radiocarbon ages,specific surface areas,and grain size compositions of sediments from three cores were measured.We explored the influence of the lateral downslope transport on the dispersal of the sediments and established a tentative box model for the SOC balance.In the SYT,the surface TOC content decreased with water depth and was decoupled by the funneling effect of the V-shaped hadal trench.However,the sedimentation(0.0025 cm/a)and SOC accumulation rates(∼0.038 g/(m^(2)·a)(in terms of OC))were approximately 50%higher in the deeper hadal region than in the abyssal region(0.0016 cm/a and∼0.026 g/(m^(2)·a)(in terms of OC),respectively),indicating the occurrence of lateral downslope transport.The fluctuating variations in the prokaryotic abundances and the SOC accumulation rate suggest the periodic input of surficial sediments from the shallow region.The similar average TOC(0.31%–0.38%),TN(0.06%–0.07%)contents,and SOC compositions(terrestrial OC(11%–18%),marine phytoplanktonic OC(45%–53%),and microbial OC(32%–44%))of the three sites indicate that the lateral downslope transport has a significant mixing effect on the SOC composition.The output fluxes of the laterally transported SOC(0.44–0.56 g/(m^(2)·a)(in terms of OC))contributed approximately(47%–73%)of the total SOC input,and this proportion increased with water depth.The results of this study demonstrate the importance of lateral downslope transport in the spatial distribution and development of biomes.

Verify the Function of a Potential Growth-Regulating Gene in Marine Bivalve Using a Candidate Model Organism Mulinia lateralis

A better understanding of genetic bases of growth regulation is essential for bivalve breeding,which is helpful to improve the yield of the commercially important bivalves.While previous studies have identified some candidate genes accounting for variation in growth-related traits through genotype-phenotype association analyses,seldom of them have verified the functions of these putative,growth-related genes beyond the genomic level due to the difficulty of culturing commercial bivalves under laboratory conditions.Fortunately,dwarf surf clam Mulinia lateralis can serve as a model organism for studying marine bivalves given its short generation time,the feasibility of being grown under experimental conditions and the availability of genetic and biological information.Using dwarf surf clam as a model bivalve,we characterize E2F3,a gene that has been found to account for variation in growth in scallops by a previous genome-wide association study,and verify its function in growth regulation through RNA interference(RNAi)experiments.For the first time,E2F3 in dwarf surf clam,which is termed as MulE2F3,is characterized.The results reveal that dwarf surf clams with MulE2F3 knocked down exhibit a reduction in both shell size and soft-tissue weight,indicating the functions of MulE2F3 in positively regulating bivalve growth.More importantly,we demonstrate how dwarf surf clam can be used as a model organism to investigate gene functions in commercial bivalves,shedding light on genetic causes for variation in growth to enhance the efficiency of bivalve farming.

Quantitative characterizations of anisotropic dynamic properties in organic-rich shale with different kerogen content

Understanding the quantitative responses of anisotropic dynamic properties in organic-rich shale with different kerogen content(KC)is of great significance in hydrocarbon exploration and development.Conducting controlled experiments with a single variable is challenging for natural shales due to their high variations in components,diagenesis conditions,or pore fluid.We employed the hot-pressing technique to construct 11 well-controlled artificial shale with varying KC.These artificial shale samples were successive machined into prismatic shape for ultrasonic measurements along different directions.Observations revealed bedding perpendicular P-wave velocities are more sensitive to the increasing KC than bedding paralleling velocities due to the preferential alignments of kerogen.All elastic stiffnesses except C_(13)are generally decreasing with the increasing KC,the variation of C_(1) and C_(33)on kerogen content are more sensitive than those of C_(44)and C_(66).Apparent dynamic mechanical parameters(v and E)were found to have linear correlation with the true ones from complete anisotropic equations independent of KC,which hold value towards the interpretation of well logs consistently across formations,Anisotropic mechanical parameters(ΔE and brittlenessΔB)tend to decrease with the reducing KC,withΔB showing great sensitivity to KC variations.In the range of low KC(<10%),the V_(P)/V_(S) ratio demonstrated a linearly negative correlation with KC,and the V_(P)/V_(S) ratio magnitude of less than 1.75may serve as a significant characterization for highly organic-rich(>10%)shale,compilation of data from natural organic rich-shales globally verified the similar systematic relationships that can be empirically used to predict the fraction of KC in shales.

Exploration of the coupled lattice Boltzmann model based on a multiphase field model:A study of the solid-liquid-gas interaction mechanism in the solidification process

A multiphase field model coupled with a lattice Boltzmann(PF-LBM)model is proposed to simulate the distribution mechanism of bubbles and solutes at the solid-liquid interface,the interaction between dendrites and bubbles,and the effects of different temperatures,anisotropic strengths and tilting angles on the solidified organization of the SCN-0.24wt.%butanedinitrile alloy during the solidification process.The model adopts a multiphase field model to simulate the growth of dendrites,calculates the growth motions of dendrites based on the interfacial solute equilibrium;and adopts a lattice Boltzmann model(LBM)based on the Shan-Chen multiphase flow to simulate the growth and motions of bubbles in the liquid phase,which includes the interaction between solid-liquid-gas phases.The simulation results show that during the directional growth of columnar dendrites,bubbles first precipitate out slowly at the very bottom of the dendrites,and then rise up due to the different solid-liquid densities and pressure differences.The bubbles will interact with the dendrite in the process of flow migration,such as extrusion,overflow,fusion and disappearance.In the case of wide gaps in the dendrite channels,bubbles will fuse to form larger irregular bubbles,and in the case of dense channels,bubbles will deform due to the extrusion of dendrites.In the simulated region,as the dendrites converge and diverge,the bubbles precipitate out of the dendrites by compression and diffusion,which also causes physical phenomena such as fusion and spillage of the bubbles.These results reveal the physical mechanisms of bubble nucleation,growth and kinematic evolution during solidification and interaction with dendrite growth.

Mapping soil organic matter in cultivated land based on multi-year composite images on monthly time scales

Rapid and accurate acquisition of soil organic matter(SOM)information in cultivated land is important for sustainable agricultural development and carbon balance management.This study proposed a novel approach to predict SOM with high accuracy using multiyear synthetic remote sensing variables on a monthly scale.We obtained 12 monthly synthetic Sentinel-2 images covering the study area from 2016 to 2021 through the Google Earth Engine(GEE)platform,and reflectance bands and vegetation indices were extracted from these composite images.Then the random forest(RF),support vector machine(SVM)and gradient boosting regression tree(GBRT)models were tested to investigate the difference in SOM prediction accuracy under different combinations of monthly synthetic variables.Results showed that firstly,all monthly synthetic spectral bands of Sentinel-2 showed a significant correlation with SOM(P<0.05)for the months of January,March,April,October,and November.Secondly,in terms of single-monthly composite variables,the prediction accuracy was relatively poor,with the highest R^(2)value of 0.36 being observed in January.When monthly synthetic environmental variables were grouped in accordance with the four quarters of the year,the first quarter and the fourth quarter showed good performance,and any combination of three quarters was similar in estimation accuracy.The overall best performance was observed when all monthly synthetic variables were incorporated into the models.Thirdly,among the three models compared,the RF model was consistently more accurate than the SVM and GBRT models,achieving an R^(2)value of 0.56.Except for band 12 in December,the importance of the remaining bands did not exhibit significant differences.This research offers a new attempt to map SOM with high accuracy and fine spatial resolution based on monthly synthetic Sentinel-2 images.

Exploiting fly models to investigate rare human neurological disorders

Rare neurological diseases,while individually are rare,collectively impact millions globally,leading to diverse and often severe neurological symptoms.Often attributed to genetic mutations that disrupt protein function or structure,understanding their genetic basis is crucial for accurate diagnosis and targeted therapies.To investigate the underlying pathogenesis of these conditions,researchers often use non-mammalian model organisms,such as Drosophila(fruit flies),which is valued for their genetic manipulability,cost-efficiency,and preservation of genes and biological functions across evolutionary time.Genetic tools available in Drosophila,including CRISPR-Cas9,offer a means to manipulate gene expression,allowing for a deep exploration of the genetic underpinnings of rare neurological diseases.Drosophila boasts a versatile genetic toolkit,rapid generation turnover,and ease of large-scale experimentation,making it an invaluable resource for identifying potential drug candidates.Researchers can expose flies carrying disease-associated mutations to various compounds,rapidly pinpointing promising therapeutic agents for further investigation in mammalian models and,ultimately,clinical trials.In this comprehensive review,we explore rare neurological diseases where fly research has significantly contributed to our understanding of their genetic basis,pathophysiology,and potential therapeutic implications.We discuss rare diseases associated with both neuron-expressed and glial-expressed genes.Specific cases include mutations in CDK19 resulting in epilepsy and developmental delay,mutations in TIAM1 leading to a neurodevelopmental disorder with seizures and language delay,and mutations in IRF2BPL causing seizures,a neurodevelopmental disorder with regression,loss of speech,and abnormal movements.And we explore mutations in EMC1 related to cerebellar atrophy,visual impairment,psychomotor retardation,and gain-of-function mutations in ACOX1 causing Mitchell syndrome.Loss-of-function mutations in ACOX1 result in ACOX1 deficiency,characterized by very-long-chain fatty acid accumulation and glial degeneration.Notably,this review highlights how modeling these diseases in Drosophila has provided valuable insights into their pathophysiology,offering a platform for the rapid identification of potential therapeutic interventions.Rare neurological diseases involve a wide range of expression systems,and sometimes common phenotypes can be found among different genes that cause abnormalities in neurons or glia.Furthermore,mutations within the same gene may result in varying functional outcomes,such as complete loss of function,partial loss of function,or gain-of-function mutations.The phenotypes observed in patients can differ significantly,underscoring the complexity of these conditions.In conclusion,Drosophila represents an indispensable and cost-effective tool for investigating rare neurological diseases.By facilitating the modeling of these conditions,Drosophila contributes to a deeper understanding of their genetic basis,pathophysiology,and potential therapies.This approach accelerates the discovery of promising drug candidates,ultimately benefiting patients affected by these complex and understudied diseases.

A Semantic-Sensitive Approach to Indoor and Outdoor 3D Data Organization

Building model data organization is often programmed to solve a specific problem,resulting in the inability to organize indoor and outdoor 3D scenes in an integrated manner.In this paper,existing building spatial data models are studied,and the characteristics of building information modeling standards(IFC),city geographic modeling language(CityGML),indoor modeling language(IndoorGML),and other models are compared and analyzed.CityGML and IndoorGML models face challenges in satisfying diverse application scenarios and requirements due to limitations in their expression capabilities.It is proposed to combine the semantic information of the model objects to effectively partition and organize the indoor and outdoor spatial 3D model data and to construct the indoor and outdoor data organization mechanism of“chunk-layer-subobject-entrances-area-detail object.”This method is verified by proposing a 3D data organization method for indoor and outdoor space and constructing a 3D visualization system based on it.

Self-organized Criticality in a Modified Evolution Model on Generalized Barabasi-Albert Scale-Free Networks

generalizedBarabasi 艾伯特(GBA ) 上的自我组织的 criticality 的一个修改进化模型没有规模的网络被调查。在我们的模型，我们发现空间、时间的关联展出批评行为。更重要地，这些批评行为随着参数 b 变化，哪个重量与在 GBA 网络进化的度比较的距离。

Self-organized Criticality in an Earthquake Model on Random Network

一个随机的网络上的一个简化 Olami-Feder-Christensen 模型被学习了。我们建议一条新倒下规则—当有一个不稳定的地点，倒下时，这个地点的精力不平均随机被再分配到它的最近的邻居。当系统是保守人士，和系统的分发服从有限尺寸可伸缩的雪崩尺寸概率时，模拟结果显示模型显示自我组织的 criticality。什么时候系统 isnonconservative，模型不显示可伸缩行为。我们有不同最近的邻居 q 的模型的模拟结果 aiso 被比较，它显示空间拓扑学不改变系统的批评行为。

Predicting dynamics of soil organic carbon mineralization with a double exponential model in different forest belts of China

The dynamics of soil organic carbon （SOC） was analyzed by using laboratory incubation and double exponential model that mineralizable SOC was separated into active carbon pools and slow carbon pools in forest soils derived from Changbai and Qilian Mountain areas. By analyzing and fitting the CO2 evolved rates with SOC mineralization, the results showed that active carbon pools accounted tor 1.0% to 8.5% of SOC with an average of mean resistant times （MRTs） for 24 days, and slow carbon pools accounted for 91% to 99% of SOC with an average of MRTs for 179 years. The sizes and MRTs of slow carbon pools showed that SOC in Qilian Mountain sites was more difficult to decompose than that in Changbai Mountain sites. By analyzing the effects of temperature, soil clay content and elevation on SOC mineralization, results indicated that mineralization of SOC was directly related to temperature and that content of accumulated SOC and size of slow carbon pools from Changbai Mountain and Qilian Mountain sites increased linearly with increasing clay content, respectively, which showed temperature and clay content could make greater effect on mineralization of SOC.

Modeling Soil Organic Carbon Storage and Its Dynamics in Croplands of China

Soil organic carbon （SOC） is one of the centre issues related to not only soil fertility but also environmental safety. Assessing SOC dynamics in croplands has been a challenge in China for long due to the lack of appropriate methodologies and data sources. As an alternative approach for studying SOC dynamics, process-based models are adopted to meet the needs. In this paper, a process-based model, DeNitrification-DeComposition （DNDC）, was applied to quantify the SOC storage and the spatial distribution in croplands of China in 2003, with the support of a newly compiled county-level soil/ climate/land use database. The simulated results showed that the total SOC storage in the top layer （0-30 cm） of the 1.18 × 10^8 ha croplands of China is 4.7-5.2 Pg C in 2003 with an average value of 4.95 Pg C. The SOC storage in the northeastern provinces （1.3 Pg C） accounts for about 1/4 of the whole national totals due to their dominantly fertile soils with high organic matter content. SOC density ranges from 3.9 to 4.4 kg C m 2, with an average of 4.2 kg C m^-2, a level is much lower than the world average level. The model results also indicated that high rates of SOC losses occurred in the croplands with the most common cropping patterns in China as like single soybean 〉 maize 〉 paddy 〉 cotton 〉 winter wheat and corn rotation. The results reported in this paper showed that there was still a great potential for improving SOC status in most croplands of China by adopting proper farming practices and land-use pattern. Therefore, long-term policy to protect SOC is urgently needed.

Research proceedings on amphibian model organisms

Model organisms have long been important in biology and medicine due to their specific characteristics. Amphibians, especially Xenopus, play key roles in answering fundamental questions on developmental biology, regeneration, genetics, and toxicology due to their large and abundant eggs, as well as their versatile embryos, which can be readily manipulated and developed in vivo. Furthermore, amphibians have also proven to be of considerable benefit in human disease research due to their conserved cellular developmental and genomic organization. This review gives a brief introduction on the progress and limitations of these animal models in biology and human disease research, and discusses the potential and challenge of Microhyla fissipes as a new model organism.

Model Establishment for Simulating Soil Organic Carbon Dynamics

Assuming that decomposition of organic matter in soils follows the first-order kinetics reaction, a computer model was developed to simulate soil organic matter dynamics. Organic matter in soils is divided up into two parts that include incorporated organic carbon from crop residues or other organic fertilizer and soil intrinsic carbon. The incorporated organic carbon was assumed to consist of two components, labile-C and resistant-C. The model was represented by a differential equation of dCt/dt = Kt × fr × fw × fs × ct (i = 1, r,S) and an integral equation of Cit = Cio × EXP(Ki × fT × fw × fs × t). Effect of soil parameters of temperature, moisture and texture on the decomposition was functioned by the fT, fw and fs, respectively. Data from laboratory incubation experiments were used to determine the first-order decay rate K, and the fraction of labile-C of crop residues by employing a nonlinear method. The values of K for the components of labile-C and resistant-C and the soil intrinsic carbon were evaluated to be 0.025,0.080 X 10-2 and 0.065 X 10-3d-1, respectively. The labile-C fraction of wheat straw, wheat roots, rice straw and rice roots were 0.50, 0.25, 0.40 and 0.20, respectively. These values are related to the initial residue carbon-to-nitrogen ratio (C/N) and lignin content.

The Evolution of Organic Carbon in Chinese Mollisol Under Different Farming Systems: Validation and Prediction by Using Century Model

Soil organic carbon （SOC） is an important indicator of soil degradation process. In this study, the long-term SOC evolution in Chinese mollisol farmland was simulated and predicted by validating, analyzing, processing and assorting concerning data, based on clarifying parameters of Century model need, combined with best use of recorded data of field management, observed data of long-term experiments, climate, soil, and biology, and achieved results from Hailun Agro-Ecological Experimental Station, Chinese Academy of Sciences. The results were showed as follows： Before reclamation, SOC content was around 58.00 g kg^-1, SOC content dropped quickly in early years, and then decreased slowly after reclamation. SOC content was around 34.00 g kg^-1 with a yearly average rate of 8.91‰ decrease before long-term experiments was established. After a long-term experiment, SOC would change under different farming systems. Shift farming system changed as follows： By 20-year model simulation, SOC content decreased from 34.03 to 30.19 g kg^-1, with a yearly average rate of 5.97‰; by 100-year model simulation, SOC content decreased to 24.31 g kg^-1, with a yearly average rate of 3.36‰. Organic farming system changed as follows： By 20-year model simulation, SOC content decreased slowly from 34.03 to 33.39 g kg^-1, with a yearly average rate of 0.95‰, 5‰ less than that of shift farming system; by 100-year model simulation, SOC content decreased to 32.21 g kg^-1, with a yearly average rate of 0.55‰. ＂Petroleum＂ farming system changed as follows： By 20-year model simulation, SOC content decreased from 34.03 to 32.88 g kg^-1, with a yearly average rate of 1.72‰, much more than that of organic farming system; by 100-year model simulation, SOC content decreased to 30.89 g kg^-1, with a yearly average rate of 0.96‰. Combined ＂petroleum＂-organic farming system changed as follows： By 20-year model simulation, SOC content was increased slightly; by 100-year model simulation, SOC content increased from 34.03 to 34.41g kg^-1, with a yearly average rate of 0.11‰. The above results provided an optimal way for maintaining SOC in Chinese mollisol farmland： To increase, as much as possible within agro-ecosystem, soil organic matter returns such as crop stubble, crop litter, crop straw or stalk, and manure, besides applying chemical nitrogen and phosphorous, which increased system productivity and maintained SOC content as well. Also, the results provided a valuable methodology both for a study of CO2 sequestration capacity and for a target fertility determination in Chinese mollisol.

Human Health Risk Assessment Model of Organic Pollution in Groundwater:Shijiazhuang Industrial Zone

In this study, a risk-based management model is developed and applied to an industrial zone. The models proposed by the United States Environmental Protection Agency and Han Bing have been improved by adding a residual ratio of volatile organic compounds （VOC） after boiling and deleting the related parameters in half-life. Using this improved model, an integrated process was used to assess human health risk level in the study area. Compared with water quality analysis, the results highlight the importance of applying an integrated approach for decision making on risk levels and water protection. The results of this study demonstrated that： （1） Compared with these permissible level standards in China （GB 3838-2002） and National Primary Drinking Water Regulations of the United States, the residents＇ daily life had not been affected by the groundwater in this area （except for relative bad water quality of HB3-4 and HB3-6）; （2） The typical detected organic contaminants of all groundwater samples were chloroform, carbon tetrachloride, trichloroethylene and tetrachloroethene, and the pollution sources were mainly industrial sources by preliminary investigations; （3） As for groundwater, the non-carcinogenic risk values of all samples do not exceed the permissible level of 1.0 and the carcinogenic risk values are relatively lower than the permissible level of 1.00E-06 to 1.00E-04; （4） Drinking water pathway of trichloroethylene and tetrachloroethylene mainly contribute to increasing the health risk of residents＇ in study areas; （5） In terms of non-carcinogenic risk and carcinogenic risk, the health risk order for drinking water pathway and dermal contact pathway was： drinking water pathway 〉 dermal contact pathway.

Modeling the Impacts of Soil Organic Carbon Content of Croplands on Crop Yields in China

This study quantified the impacts of soil organic carbon （SOC） content on the grain yield of crops using a biogeochemical model （DNDC, denitrification-decomposition）. Data on climate, soil properties, and farming management regimes of cropping systems were collected from six typical agricultural zones （northeast, north, northwest, mid-south, east and southwest regions of China, respectively） and integrated into a GIS database to support the model runs. According to the model, if the initial SOC content in the cropland was increased by 1 g C kg^-1, the crop yield may be increased by 176 kg ha^-1 for maize in the northeast region, 454 kg ha^-1 for a maize-wheat rotation in the north region, 328 kg ha^-1 for maize in the northwest region, 185 kg ha^-1 for single-rice in the mid-south region, 266 kg ha^-1 for double-rice in east region, and 229 kg ha^-1 for rice and wheat rotation in southwest region. There is a great potential for enhancing the crop yield by improving the SOC content in each region of China.

Using the DSSAT model to simulate wheat yield and soil organic carbon under a wheat-maize cropping system in the North China Plain

Crop modelling can facilitate researchers＇ ability to understand and interpret experimental results, and to diagnose yield gaps. In this paper, the Decision Support Systems for Agrotechnology Transfer 4.6 （DSSAT） model together with the CENTURT soil model were employed to investigate the effect of low nitrogen （N） input on wheat （Triticum aestivum L.） yield, grain N concentration and soil organic carbon （SOC） in a long-term experiment （19 years） under a wheat-maize （Zea mays L.） rotation at Changping, Beijing, China. There were two treatments including NO （no N application） and N150 （150 kg N ha-1） before wheat and maize planting, with phosphorus （P） and potassium （K） basal fertilizers applied as 75 kg P205 ha-1 and 37.5 kg K^O ha-~, respectively. The DSSAT-CENTURY model was able to satisfactorily simulate measured wheat grain yield and grain N concentration at NO, but could not simulate these parameters at N150, or SOC in either N treatment, Model simulation and field measurement showed that N application （N150） increased wheat yield compared to no N application （NO）. The results indicated that inorganic fertilizer application at the rates used did not maintain crop yield and SOC levels. It is suggested that if the DSSAT is calibrated carefully, it can be a useful tool for assessing and predicting wheat yield, grain N concentration, and SOC trends under wheat-maize cropping systems.