Background:This study aimed to construct and characterize a humanized influenza mouse model expressing hST6GAL1.Methods:Humanized fragments,consisting of the endothelial cell-specific K18 promoter,human ST6GAL1-encodi...Background:This study aimed to construct and characterize a humanized influenza mouse model expressing hST6GAL1.Methods:Humanized fragments,consisting of the endothelial cell-specific K18 promoter,human ST6GAL1-encoding gene,and luciferase gene,were microinjected into the fertilized eggs of mice.The manipulated embryos were transferred into the oviducts of pseudopregnant female mice.The offspring were identified using PCR.Mice exhibiting elevated expression of the hST6GAL1 gene were selectively bred for propagation,and in vivo analysis was performed for screening.Expression of the humanized gene was tested by performing immunohistochemical(IHC)analysis.Hematologic and biochemical analyses using the whole blood and serum of humanized hST6GAL1 mice were performed.Results:Successful integration of the human ST6GAL1 gene into the mouse genome led to the overexpression of human SiaT ST6GAL1.Seven mice were identified as carrying copies of the humanized gene,and the in vivo analysis indicated that hST6GAL1gene expression in positive mice mirrored influenza virus infection characteristics.The IHC results revealed that hST6GAL1 was expressed in the lungs of humanized mice.Moreover,the hematologic and biochemical parameters of the positive mice were within the normal range.Conclusion:A humanized influenza mouse model expressing the hST6GAL1 gene was successfully established and characterized.展开更多
Evapotranspiration is the most important expenditure item in the water balance of terrestrial ecosystems,and accurate evapotranspiration modeling is of great significance for hydrological,ecological,agricultural,and w...Evapotranspiration is the most important expenditure item in the water balance of terrestrial ecosystems,and accurate evapotranspiration modeling is of great significance for hydrological,ecological,agricultural,and water resource management.Artificial forests are an important means of vegetation restoration in the western Loess Plateau,and accurate estimates of their evapotranspiration are essential to the management and development of water use strategies for artificial forests.This study estimated the soil moisture and evapotranspiration based on the HYDRUS-1D model for the artificial Platycladus orientalis(L.)Franco forest in western mountains of Loess Plateau,China from 20 April to 31 October,2023.Moreover,the influence factors were identified by combining the correlation coefficient method and the principal component analysis(PCA)method.The results showed that HYDRUS-1D model had strong applicability in portraying hydrological processes in this area and revealed soil water surplus from 20 April to 31 October,2023.The soil water accumulation was 49.64 mm;the potential evapotranspiration(ET_(p))was 809.67 mm,which was divided into potential evaporation(E_(p);95.07 mm)and potential transpiration(T_(p);714.60 mm);and the actual evapotranspiration(ET_(a))was 580.27 mm,which was divided into actual evaporation(E_(a);68.27 mm)and actual transpiration(T_(a);512.00 mm).From April to October 2023,the ET_(p),E_(p),T_(p),ET_(a),E_(a),and T_(a) first increased and then decreased on both monthly and daily scales,exhibiting a single-peak type trend.The average ratio of T_(a)/ET_(a) was 0.88,signifying that evapotranspiration mainly stemmed from transpiration in this area.The ratio of ET_(a)/ET_(p) was 0.72,indicating that this artificial forest suffered from obvious drought stress.The ET_(p) was significantly positively correlated with ET_(a),and the R^(2) values on the monthly and daily scales were 0.9696 and 0.9635(P<0.05),respectively.Furthermore,ET_(a) was significantly positively correlated with temperature,solar radiation,and wind speed,and negatively correlated with relative humidity and precipitation(P<0.05);and temperature exhibited the highest correlation with ET_(a).Thus,ET_(p) and temperature were the decisive contributors to ET_(a) in this area.The findings provide an effective method for simulating regional evapotranspiration and theoretical reference for water management of artificial forests,and deepen understanding of effects of each influence factors on ET_(a) in arid areas.展开更多
This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations a...This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location.Our tidal modeling methodology follows an iterative process:partitioning sea surface height(SSH)observations into analysis/training and prediction/validation parts and ultimately identi-fying the set of tidal constituents that provide the best predictions at each time series location.The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea,each with its own set of tidal constituents.Verification of the developed tidal models against the sSH observations within the prediction/validation part reveals mean absolute error(MAE)values ranging from 0.0334 m to 0.1349 m,with an average MAE of 0.089 m.The same validation process is conducted on the FES2014 and EOT20 global tidal models,demonstrating that our tidal model,referred to as BT23(short for Baltic Tide 2023),outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m,respectively.In addition to providing details on the development of the time series and the tidal modeling procedure,we offer the 1256 along-track time series and their associated tidal models as supplementary materials.We encourage the satellite altimetry community to utilize these resources for further research and applications.展开更多
We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Se...We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.展开更多
Using the Faddeev-Jackiw （FJ） quantization method, this paper treats the CP^1nonlinear sigma model with ChernSimons term. The generalized FJ brackets are obtained in the framework of this quantization method, which ...Using the Faddeev-Jackiw （FJ） quantization method, this paper treats the CP^1nonlinear sigma model with ChernSimons term. The generalized FJ brackets are obtained in the framework of this quantization method, which agree with the results obtained by using the Dirac＇s method.展开更多
Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model o...Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .展开更多
In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for la...In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.展开更多
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 functio...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.展开更多
To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new ...To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM （1, 1 ） model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM （1, 1 ） model is higher than the unbiased GM （1,1） model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.展开更多
基金National Key Research and Development Program of China,Grant/Award Number:2021YFC2301403 and 2022YFF0711000。
文摘Background:This study aimed to construct and characterize a humanized influenza mouse model expressing hST6GAL1.Methods:Humanized fragments,consisting of the endothelial cell-specific K18 promoter,human ST6GAL1-encoding gene,and luciferase gene,were microinjected into the fertilized eggs of mice.The manipulated embryos were transferred into the oviducts of pseudopregnant female mice.The offspring were identified using PCR.Mice exhibiting elevated expression of the hST6GAL1 gene were selectively bred for propagation,and in vivo analysis was performed for screening.Expression of the humanized gene was tested by performing immunohistochemical(IHC)analysis.Hematologic and biochemical analyses using the whole blood and serum of humanized hST6GAL1 mice were performed.Results:Successful integration of the human ST6GAL1 gene into the mouse genome led to the overexpression of human SiaT ST6GAL1.Seven mice were identified as carrying copies of the humanized gene,and the in vivo analysis indicated that hST6GAL1gene expression in positive mice mirrored influenza virus infection characteristics.The IHC results revealed that hST6GAL1 was expressed in the lungs of humanized mice.Moreover,the hematologic and biochemical parameters of the positive mice were within the normal range.Conclusion:A humanized influenza mouse model expressing the hST6GAL1 gene was successfully established and characterized.
基金financially supported by the National Natural Science Foundation of China(42071047,41771035)the Basic Research Innovation Group Project of Gansu Province(22JR5RA129)the Excellent Doctoral Program in Gansu Province(24JRRA152).
文摘Evapotranspiration is the most important expenditure item in the water balance of terrestrial ecosystems,and accurate evapotranspiration modeling is of great significance for hydrological,ecological,agricultural,and water resource management.Artificial forests are an important means of vegetation restoration in the western Loess Plateau,and accurate estimates of their evapotranspiration are essential to the management and development of water use strategies for artificial forests.This study estimated the soil moisture and evapotranspiration based on the HYDRUS-1D model for the artificial Platycladus orientalis(L.)Franco forest in western mountains of Loess Plateau,China from 20 April to 31 October,2023.Moreover,the influence factors were identified by combining the correlation coefficient method and the principal component analysis(PCA)method.The results showed that HYDRUS-1D model had strong applicability in portraying hydrological processes in this area and revealed soil water surplus from 20 April to 31 October,2023.The soil water accumulation was 49.64 mm;the potential evapotranspiration(ET_(p))was 809.67 mm,which was divided into potential evaporation(E_(p);95.07 mm)and potential transpiration(T_(p);714.60 mm);and the actual evapotranspiration(ET_(a))was 580.27 mm,which was divided into actual evaporation(E_(a);68.27 mm)and actual transpiration(T_(a);512.00 mm).From April to October 2023,the ET_(p),E_(p),T_(p),ET_(a),E_(a),and T_(a) first increased and then decreased on both monthly and daily scales,exhibiting a single-peak type trend.The average ratio of T_(a)/ET_(a) was 0.88,signifying that evapotranspiration mainly stemmed from transpiration in this area.The ratio of ET_(a)/ET_(p) was 0.72,indicating that this artificial forest suffered from obvious drought stress.The ET_(p) was significantly positively correlated with ET_(a),and the R^(2) values on the monthly and daily scales were 0.9696 and 0.9635(P<0.05),respectively.Furthermore,ET_(a) was significantly positively correlated with temperature,solar radiation,and wind speed,and negatively correlated with relative humidity and precipitation(P<0.05);and temperature exhibited the highest correlation with ET_(a).Thus,ET_(p) and temperature were the decisive contributors to ET_(a) in this area.The findings provide an effective method for simulating regional evapotranspiration and theoretical reference for water management of artificial forests,and deepen understanding of effects of each influence factors on ET_(a) in arid areas.
文摘This research aims to optimize the utilization of long-term sea level data from the TOPEX/Poseidon,Jason1,Jason2,and Jason3 altimetry missions for tidal modeling.We generate a time series of along-track observations and apply a developed method to produce tidal models with specific tidal constituents for each location.Our tidal modeling methodology follows an iterative process:partitioning sea surface height(SSH)observations into analysis/training and prediction/validation parts and ultimately identi-fying the set of tidal constituents that provide the best predictions at each time series location.The study focuses on developing 1256 time series along the altimetry tracks over the Baltic Sea,each with its own set of tidal constituents.Verification of the developed tidal models against the sSH observations within the prediction/validation part reveals mean absolute error(MAE)values ranging from 0.0334 m to 0.1349 m,with an average MAE of 0.089 m.The same validation process is conducted on the FES2014 and EOT20 global tidal models,demonstrating that our tidal model,referred to as BT23(short for Baltic Tide 2023),outperforms both models with an average MAE improvement of 0.0417 m and 0.0346 m,respectively.In addition to providing details on the development of the time series and the tidal modeling procedure,we offer the 1256 along-track time series and their associated tidal models as supplementary materials.We encourage the satellite altimetry community to utilize these resources for further research and applications.
文摘We estimate tree heights using polarimetric interferometric synthetic aperture radar(PolInSAR)data constructed by the dual-polarization(dual-pol)SAR data and random volume over the ground(RVoG)model.Considering the Sentinel-1 SAR dual-pol(SVV,vertically transmitted and vertically received and SVH,vertically transmitted and horizontally received)configuration,one notes that S_(HH),the horizontally transmitted and horizontally received scattering element,is unavailable.The S_(HH)data were constructed using the SVH data,and polarimetric SAR(PolSAR)data were obtained.The proposed approach was first verified in simulation with satisfactory results.It was next applied to construct PolInSAR data by a pair of dual-pol Sentinel-1A data at Duke Forest,North Carolina,USA.According to local observations and forest descriptions,the range of estimated tree heights was overall reasonable.Comparing the heights with the ICESat-2 tree heights at 23 sampling locations,relative errors of 5 points were within±30%.Errors of 8 points ranged from 30%to 40%,but errors of the remaining 10 points were>40%.The results should be encouraged as error reduction is possible.For instance,the construction of PolSAR data should not be limited to using SVH,and a combination of SVH and SVV should be explored.Also,an ensemble of tree heights derived from multiple PolInSAR data can be considered since tree heights do not vary much with time frame in months or one season.
文摘Using the Faddeev-Jackiw （FJ） quantization method, this paper treats the CP^1nonlinear sigma model with ChernSimons term. The generalized FJ brackets are obtained in the framework of this quantization method, which agree with the results obtained by using the Dirac＇s method.
文摘Atmospheric models are physical equations based on the ideal gas law. Applied to the atmosphere, this law yields equations for water, vapor (gas), ice, air, humidity, dryness, fire, and heat, thus defining the model of key atmospheric parameters. The distribution of these parameters across the entire planet Earth is the origin of the formation of the climatic cycle, which is a normal climatic variation. To do this, the Earth is divided into eight (8) parts according to the number of key parameters to be defined in a physical representation of the model. Following this distribution, numerical models calculate the constants for the formation of water, vapor, ice, dryness, thermal energy (fire), heat, air, and humidity. These models vary in complexity depending on the indirect trigonometric direction and simplicity in the sum of neighboring models. Note that the constants obtained from the equations yield 275.156˚K (2.006˚C) for water, 273.1596˚K (0.00963˚C) for vapor, 273.1633˚K (0.0133˚C) for ice, 0.00365 in/s for atmospheric dryness, 1.996 in<sup>2</sup>/s for humidity, 2.993 in<sup>2</sup>/s for air, 1 J for thermal energy of fire, and 0.9963 J for heat. In summary, this study aims to define the main parameters and natural phenomena contributing to the modification of planetary climate. .
文摘In the R&D phase of Gravity-1(YL-1), a multi-domain modeling and simulation technology based on Modelica language was introduced, which was a recent attempt in the practice of modeling and simulation method for launch vehicles in China. It realizes a complex coupling model within a unified model for different domains, so that technologists can work on one model. It ensured the success of YL-1 first launch mission, supports rapid iteration, full validation, and tight design collaboration.
基金supported by Warren Alpert Foundation and Houston Methodist Academic Institute Laboratory Operating Fund(to HLC).
文摘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.
基金Supported by Science Research Project of Department of Education of Hubei Province (B20092901)~~
文摘To create a new prediction model, the unbiased GM （1,1） model is optimized by the five-point slide method in this paper. Then, based on the occurrence areas of dce blast in Enshi District during 1995 -2004, the new model and unbiased GM （1, 1 ） model are applied to predict the occurrence areas of rice blast during 2005 -2010. Predicting outcomes show that the prediction accuracy of five-point unbiased sliding optimized GM （1, 1 ） model is higher than the unbiased GM （1,1） model. Finally, combined with the prediction results, the author provides some suggestion for Enshi District in the prevention and control of rice blast in 2010.
