An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical react...An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical reaction equations was developed, validated, and used for studying the ozone concentrations, distribution and peak of the layer, ozone depletion and total ozone abundance in the stratosphere. The calculated ozone concentrations and profile at both the Equator and a 60˚N location were found to follow closely with the measured data. The calculated average ozone concentration was within 1% of the measured average, and the deviation of ozone profiles was within 14%. The monthly evolution of stratospheric ozone concentrations and distribution above the Equator was studied with results discussed in details. The influences of slow air movement in both altitudinal and radial directions on ozone concentrations and profile in the stratosphere were explored and discussed. Parametric studies of the influences of gas diffusivities of ozone D<sub>O3</sub> and active atomic oxygen D<sub>O</sub> on ozone concentrations and distributions were also studied and delineated. Having both influences through physical diffusion and chemical reactions, the diffusivity (and diffusion) of atomic oxygen D<sub>O</sub> was found to be more sensitive and important than that of ozone D<sub>O3</sub> on ozone concentrations and distribution. The 2-D ozone model present in this paper for stratospheric ozone and its layer and depletion is shown to be robust, convenient, efficient, and executable for analyzing the complex ozone phenomena in the stratosphere. .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
Severe acute respiratory syndrome coronavirus 2(SARSCo V-2)infection can result in more severe syndromes and poorer outcomes in patients with diabetes and obesity.However,the precise mechanisms responsible for the com...Severe acute respiratory syndrome coronavirus 2(SARSCo V-2)infection can result in more severe syndromes and poorer outcomes in patients with diabetes and obesity.However,the precise mechanisms responsible for the combined impact of coronavirus disease 2019(COVID-19)and diabetes have not yet been elucidated,and effective treatment options for SARS-Co V-2-infected diabetic patients remain limited.To investigate the disease pathogenesis,K18-h ACE2 transgenic(h ACE2^(Tg))mice with a leptin receptor deficiency(h ACE2-Lepr^(-/-))and high-fat diet(h ACE2-HFD)background were generated.The two mouse models were intranasally infected with a 5×10^(5) median tissue culture infectious dose(TCID_(50))of SARSCo V-2,with serum and lung tissue samples collected at 3days post-infection.The h ACE2-Lepr^(-/-)mice were then administered a combination of low-molecular-weight heparin(LMWH)(1 mg/kg or 5 mg/kg)and insulin via subcutaneous injection prior to intranasal infection with1×10^(4) TCID_(50)of SARS-Co V-2.Daily drug administration continued until the euthanasia of the mice.Analyses of viral RNA loads,histopathological changes in lung tissue,and inflammation factors were conducted.Results demonstrated similar SARS-Co V-2 susceptibility in h ACE2^(Tg)mice under both lean(chow diet)and obese(HFD)conditions.However,compared to the h ACE2-Lepr^(+/+)mice,h ACE2-Lepr^(-/-)mice exhibited more severe lung injury,enhanced expression of inflammatory cytokines and hypoxia-inducible factor-1α(HIF-1α),and increased apoptosis.Moreover,combined LMWH and insulin treatment effectively reduced disease progression and severity,attenuated lung pathological changes,and mitigated inflammatory responses.In conclusion,preexisting diabetes can lead to more severe lung damage upon SARS-Co V-2 infection,and LMWH may be a valuable therapeutic approach for managing COVID-19patients with diabetes.展开更多
BACKGROUND Type 2 diabetes mellitus(T2DM)is associated with periodontitis.Currently,there are few studies proposing predictive models for periodontitis in patients with T2DM.AIM To determine the factors influencing pe...BACKGROUND Type 2 diabetes mellitus(T2DM)is associated with periodontitis.Currently,there are few studies proposing predictive models for periodontitis in patients with T2DM.AIM To determine the factors influencing periodontitis in patients with T2DM by constructing logistic regression and random forest models.METHODS In this a retrospective study,300 patients with T2DM who were hospitalized at the First People’s Hospital of Wenling from January 2022 to June 2022 were selected for inclusion,and their data were collected from hospital records.We used logistic regression to analyze factors associated with periodontitis in patients with T2DM,and random forest and logistic regression prediction models were established.The prediction efficiency of the models was compared using the area under the receiver operating characteristic curve(AUC).RESULTS Of 300 patients with T2DM,224 had periodontitis,with an incidence of 74.67%.Logistic regression analysis showed that age[odds ratio(OR)=1.047,95%confidence interval(CI):1.017-1.078],teeth brushing frequency(OR=4.303,95%CI:2.154-8.599),education level(OR=0.528,95%CI:0.348-0.800),glycosylated hemoglobin(HbA1c)(OR=2.545,95%CI:1.770-3.661),total cholesterol(TC)(OR=2.872,95%CI:1.725-4.781),and triglyceride(TG)(OR=3.306,95%CI:1.019-10.723)influenced the occurrence of periodontitis(P<0.05).The random forest model showed that the most influential variable was HbA1c followed by age,TC,TG, education level, brushing frequency, and sex. Comparison of the prediction effects of the two models showedthat in the training dataset, the AUC of the random forest model was higher than that of the logistic regressionmodel (AUC = 1.000 vs AUC = 0.851;P < 0.05). In the validation dataset, there was no significant difference in AUCbetween the random forest and logistic regression models (AUC = 0.946 vs AUC = 0.915;P > 0.05).CONCLUSION Both random forest and logistic regression models have good predictive value and can accurately predict the riskof periodontitis in patients with T2DM.展开更多
The rapid spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) in recent years not only caused a global pandemic but resulted in enormous social,economic,and health burdens worldwide.Despite considera...The rapid spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) in recent years not only caused a global pandemic but resulted in enormous social,economic,and health burdens worldwide.Despite considerable efforts to combat coronavirus disease 2019(COVID-19),various SARS-CoV-2 variants have emerged,and their underlying mechanisms of pathogenicity remain largely unknown.Furthermore,effective therapeutic drugs are still under development.Thus,an ideal animal model is crucial for studying the pathogenesis of COVID-19 and for the preclinical evaluation of vaccines and antivirals against SARS-CoV-2 and variant infections.Currently,several animal models,including mice,hamsters,ferrets,and nonhuman primates(NHPs),have been established to study COVID-19.Among them,ferrets are naturally susceptible to SARS-CoV-2 infection and are considered suitable for COVID-19 study.Here,we summarize recent developments and application of SARS-CoV-2 ferret models in studies on pathogenesis,therapeutic agents,and vaccines,and provide a perspective on the role of these models in preventing COVID-19 spread.展开更多
Considering phase changes associated with a high-temperature molten material cooled down from the outside,this work presents an improvement of the modelling and the numerical simulation of such processes for an applic...Considering phase changes associated with a high-temperature molten material cooled down from the outside,this work presents an improvement of the modelling and the numerical simulation of such processes for an application pertaining to the safety of light water nuclear reactors.Postulating a core meltdown accident,the behaviour of the core melt(aka corium)into a steel vessel is of tremendous importance when evaluating the vessel integrity.Evaluating correctly the heat fluxes requires the numerical simulation of the interaction between the liquid material and its solid counterpart which forms during the solidification process,but also may melt back.To simulate this configuration,encoun-tered in various industrial applications,one considers a bi-phase model constituted by a liquid phase in contact and interaction with its solid phase.The liquid phase may solidify in presence of low energetic source,while the solid phase may melt due to an intense heat flux from the high-temperature liquid.In the frame of the in-house legacy code,several simplifying assumptions(0D multi-layer discretization,instantaneous heat transfer via a quadratic temperature profile in solids)are made for the modelling of such phase changes.In the present work,these shortcomings are illustrated and further overcome by solving a 2D heat conduction model in the solid by a mixed Raviart-Thomas finite element method coupled to the liquid phase due to heat and mass exchanges through Stefan condition.The liquid phase is modeled with a 0D multi-layer approach.The 0D-liquid and 2D-solid mod-els are coupled by a Stefan like phase change interface model.Several sanity checks are performed to assess the validity of the approach on 1D and 2D academical configurations for which exact or reference solutions are available.Then more advanced situations(genu-ine multi-dimensional phase changes and an"industrial-like scenario")are simulated to verify the appropriate behavior of the obtained coupled simulation scheme.展开更多
文摘An engineering system approach of 2-D cylindrical model of transient mass balance calculations of ozone and other concerned chemicals along with fourteen photolysis, ozone-generating and ozone-depleting chemical reaction equations was developed, validated, and used for studying the ozone concentrations, distribution and peak of the layer, ozone depletion and total ozone abundance in the stratosphere. The calculated ozone concentrations and profile at both the Equator and a 60˚N location were found to follow closely with the measured data. The calculated average ozone concentration was within 1% of the measured average, and the deviation of ozone profiles was within 14%. The monthly evolution of stratospheric ozone concentrations and distribution above the Equator was studied with results discussed in details. The influences of slow air movement in both altitudinal and radial directions on ozone concentrations and profile in the stratosphere were explored and discussed. Parametric studies of the influences of gas diffusivities of ozone D<sub>O3</sub> and active atomic oxygen D<sub>O</sub> on ozone concentrations and distributions were also studied and delineated. Having both influences through physical diffusion and chemical reactions, the diffusivity (and diffusion) of atomic oxygen D<sub>O</sub> was found to be more sensitive and important than that of ozone D<sub>O3</sub> on ozone concentrations and distribution. The 2-D ozone model present in this paper for stratospheric ozone and its layer and depletion is shown to be robust, convenient, efficient, and executable for analyzing the complex ozone phenomena in the stratosphere. .
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. .
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (CAS) (XDB29010102)National Natural Science Foundation of China (NSFC) (91957124,82161148010,32041010)+4 种基金Self-supporting Program of Guangzhou Laboratory (SRPG22-001)National Science and Technology Infrastructure of China (National Pathogen Resource Center-NPRC-32)Management Strategy of the Tertiary Prevention and Treatment of Diabetes Based on DIP system (supported by China Health Promotion Foundation)supported by the Youth Innovation Promotion Association of CAS (Y2021034)Innovation Team and Talents Cultivation Program of the National Administration of Traditional Chinese Medicine (ZYYCXTD-D-202208)。
文摘Severe acute respiratory syndrome coronavirus 2(SARSCo V-2)infection can result in more severe syndromes and poorer outcomes in patients with diabetes and obesity.However,the precise mechanisms responsible for the combined impact of coronavirus disease 2019(COVID-19)and diabetes have not yet been elucidated,and effective treatment options for SARS-Co V-2-infected diabetic patients remain limited.To investigate the disease pathogenesis,K18-h ACE2 transgenic(h ACE2^(Tg))mice with a leptin receptor deficiency(h ACE2-Lepr^(-/-))and high-fat diet(h ACE2-HFD)background were generated.The two mouse models were intranasally infected with a 5×10^(5) median tissue culture infectious dose(TCID_(50))of SARSCo V-2,with serum and lung tissue samples collected at 3days post-infection.The h ACE2-Lepr^(-/-)mice were then administered a combination of low-molecular-weight heparin(LMWH)(1 mg/kg or 5 mg/kg)and insulin via subcutaneous injection prior to intranasal infection with1×10^(4) TCID_(50)of SARS-Co V-2.Daily drug administration continued until the euthanasia of the mice.Analyses of viral RNA loads,histopathological changes in lung tissue,and inflammation factors were conducted.Results demonstrated similar SARS-Co V-2 susceptibility in h ACE2^(Tg)mice under both lean(chow diet)and obese(HFD)conditions.However,compared to the h ACE2-Lepr^(+/+)mice,h ACE2-Lepr^(-/-)mice exhibited more severe lung injury,enhanced expression of inflammatory cytokines and hypoxia-inducible factor-1α(HIF-1α),and increased apoptosis.Moreover,combined LMWH and insulin treatment effectively reduced disease progression and severity,attenuated lung pathological changes,and mitigated inflammatory responses.In conclusion,preexisting diabetes can lead to more severe lung damage upon SARS-Co V-2 infection,and LMWH may be a valuable therapeutic approach for managing COVID-19patients with diabetes.
基金the First People’s Hospital of Wenling(approval No.KY-2023-2035-01).
文摘BACKGROUND Type 2 diabetes mellitus(T2DM)is associated with periodontitis.Currently,there are few studies proposing predictive models for periodontitis in patients with T2DM.AIM To determine the factors influencing periodontitis in patients with T2DM by constructing logistic regression and random forest models.METHODS In this a retrospective study,300 patients with T2DM who were hospitalized at the First People’s Hospital of Wenling from January 2022 to June 2022 were selected for inclusion,and their data were collected from hospital records.We used logistic regression to analyze factors associated with periodontitis in patients with T2DM,and random forest and logistic regression prediction models were established.The prediction efficiency of the models was compared using the area under the receiver operating characteristic curve(AUC).RESULTS Of 300 patients with T2DM,224 had periodontitis,with an incidence of 74.67%.Logistic regression analysis showed that age[odds ratio(OR)=1.047,95%confidence interval(CI):1.017-1.078],teeth brushing frequency(OR=4.303,95%CI:2.154-8.599),education level(OR=0.528,95%CI:0.348-0.800),glycosylated hemoglobin(HbA1c)(OR=2.545,95%CI:1.770-3.661),total cholesterol(TC)(OR=2.872,95%CI:1.725-4.781),and triglyceride(TG)(OR=3.306,95%CI:1.019-10.723)influenced the occurrence of periodontitis(P<0.05).The random forest model showed that the most influential variable was HbA1c followed by age,TC,TG, education level, brushing frequency, and sex. Comparison of the prediction effects of the two models showedthat in the training dataset, the AUC of the random forest model was higher than that of the logistic regressionmodel (AUC = 1.000 vs AUC = 0.851;P < 0.05). In the validation dataset, there was no significant difference in AUCbetween the random forest and logistic regression models (AUC = 0.946 vs AUC = 0.915;P > 0.05).CONCLUSION Both random forest and logistic regression models have good predictive value and can accurately predict the riskof periodontitis in patients with T2DM.
基金supported by the S&T Program of Hebei(20277705D and 20372601D)Natural Science Foundation of Hebei Province,China (H2020206352)+2 种基金Science and Technology Project of Hebei Education Department (QN2018150)Hebei Medical Science Research Project (20220973)Chinese Medicine Research Program of Hebei Province (2021119)。
文摘The rapid spread of severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) in recent years not only caused a global pandemic but resulted in enormous social,economic,and health burdens worldwide.Despite considerable efforts to combat coronavirus disease 2019(COVID-19),various SARS-CoV-2 variants have emerged,and their underlying mechanisms of pathogenicity remain largely unknown.Furthermore,effective therapeutic drugs are still under development.Thus,an ideal animal model is crucial for studying the pathogenesis of COVID-19 and for the preclinical evaluation of vaccines and antivirals against SARS-CoV-2 and variant infections.Currently,several animal models,including mice,hamsters,ferrets,and nonhuman primates(NHPs),have been established to study COVID-19.Among them,ferrets are naturally susceptible to SARS-CoV-2 infection and are considered suitable for COVID-19 study.Here,we summarize recent developments and application of SARS-CoV-2 ferret models in studies on pathogenesis,therapeutic agents,and vaccines,and provide a perspective on the role of these models in preventing COVID-19 spread.
基金funded by CEA,EDF and Framatomefinancial and scientific support of CEA Cadarache.
文摘Considering phase changes associated with a high-temperature molten material cooled down from the outside,this work presents an improvement of the modelling and the numerical simulation of such processes for an application pertaining to the safety of light water nuclear reactors.Postulating a core meltdown accident,the behaviour of the core melt(aka corium)into a steel vessel is of tremendous importance when evaluating the vessel integrity.Evaluating correctly the heat fluxes requires the numerical simulation of the interaction between the liquid material and its solid counterpart which forms during the solidification process,but also may melt back.To simulate this configuration,encoun-tered in various industrial applications,one considers a bi-phase model constituted by a liquid phase in contact and interaction with its solid phase.The liquid phase may solidify in presence of low energetic source,while the solid phase may melt due to an intense heat flux from the high-temperature liquid.In the frame of the in-house legacy code,several simplifying assumptions(0D multi-layer discretization,instantaneous heat transfer via a quadratic temperature profile in solids)are made for the modelling of such phase changes.In the present work,these shortcomings are illustrated and further overcome by solving a 2D heat conduction model in the solid by a mixed Raviart-Thomas finite element method coupled to the liquid phase due to heat and mass exchanges through Stefan condition.The liquid phase is modeled with a 0D multi-layer approach.The 0D-liquid and 2D-solid mod-els are coupled by a Stefan like phase change interface model.Several sanity checks are performed to assess the validity of the approach on 1D and 2D academical configurations for which exact or reference solutions are available.Then more advanced situations(genu-ine multi-dimensional phase changes and an"industrial-like scenario")are simulated to verify the appropriate behavior of the obtained coupled simulation scheme.
