Diet/sugar-free soft drinks are considered to be healthier than regular soft drinks.However,few studies have examined the relationship between the types of soft drinks(regular and diet/sugar-free)and lung cancer(LC)/a...Diet/sugar-free soft drinks are considered to be healthier than regular soft drinks.However,few studies have examined the relationship between the types of soft drinks(regular and diet/sugar-free)and lung cancer(LC)/all-cancer(AC)risk.In this study,we comprehensively assessed the influence of the type of soft drink consumption on LC/AC risk based on the Prostate,Lung,Colorectal,and Ovarian(PLCO)Cancer Screening Trial.Multivariable Cox proportional hazards and competing risks Fine-Gray regression models adjusted for relevant confounders were used to estimate hazard ratios(HRs)and subdistribution HRs for different types of soft drink consumption.In the PLCO population,female subgroup,and the ever/current smoker subgroup,consumption of both regular and diet soft drinks was associated with a significantly reduced risk of LC compared with no soft drinks at all.For the non-lung cancer(NLC)risk,consumption of only diet soft drinks had a significant positive association for the total population and female subgroup.Based on our findings,it was suggested that partial replacement of regular soft drinks with diet soft drinks might be beneficial to LC prevention,especially for females and ever/current smokers.Additionally,completely replacing regular soft drinks with diet soft drinks might be detrimental to NLC prevention,especially for females.展开更多
Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochast...Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.展开更多
Major depressive disorder(MDD) is the most common mental disorder. Over 95 million people in China suffer from MDD(Huang et al.,2019). Currently available antidepressants have delayed onset and a low cure rate(Malhi a...Major depressive disorder(MDD) is the most common mental disorder. Over 95 million people in China suffer from MDD(Huang et al.,2019). Currently available antidepressants have delayed onset and a low cure rate(Malhi and Mann, 2018). Genetic and psychosocial factors, as well as their interactions, play an important role in the response to antidepressants for MDD patients(Uher, 2011;Gonda et al., 2019;Musci et al., 2019). Understanding the underlying associations and mechanisms may help to improve the first-episode cure rate in MDD patients.展开更多
基金supported by the National Natural Science Foundation of China (Projects No. 82173620to Y.Z. and 82204156 to D.Y.)Priority Academic Program Development of Jiangsu Higher Education Institution
文摘Diet/sugar-free soft drinks are considered to be healthier than regular soft drinks.However,few studies have examined the relationship between the types of soft drinks(regular and diet/sugar-free)and lung cancer(LC)/all-cancer(AC)risk.In this study,we comprehensively assessed the influence of the type of soft drink consumption on LC/AC risk based on the Prostate,Lung,Colorectal,and Ovarian(PLCO)Cancer Screening Trial.Multivariable Cox proportional hazards and competing risks Fine-Gray regression models adjusted for relevant confounders were used to estimate hazard ratios(HRs)and subdistribution HRs for different types of soft drink consumption.In the PLCO population,female subgroup,and the ever/current smoker subgroup,consumption of both regular and diet soft drinks was associated with a significantly reduced risk of LC compared with no soft drinks at all.For the non-lung cancer(NLC)risk,consumption of only diet soft drinks had a significant positive association for the total population and female subgroup.Based on our findings,it was suggested that partial replacement of regular soft drinks with diet soft drinks might be beneficial to LC prevention,especially for females and ever/current smokers.Additionally,completely replacing regular soft drinks with diet soft drinks might be detrimental to NLC prevention,especially for females.
基金supported by the National Natural Science Foundation of China(Grant Nos.82173620 to Yang Zhao and 82041024 to Feng Chen)partially supported by the Bill&Melinda Gates Foundation(Grant No.INV-006371 to Feng Chen)Priority Academic Program Development of Jiangsu Higher Education Institutions.
文摘Deterministic compartment models(CMs)and stochastic models,including stochastic CMs and agent-based models,are widely utilized in epidemic modeling.However,the relationship between CMs and their corresponding stochastic models is not well understood.The present study aimed to address this gap by conducting a comparative study using the susceptible,exposed,infectious,and recovered(SEIR)model and its extended CMs from the coronavirus disease 2019 modeling literature.We demonstrated the equivalence of the numerical solution of CMs using the Euler scheme and their stochastic counterparts through theoretical analysis and simulations.Based on this equivalence,we proposed an efficient model calibration method that could replicate the exact solution of CMs in the corresponding stochastic models through parameter adjustment.The advancement in calibration techniques enhanced the accuracy of stochastic modeling in capturing the dynamics of epidemics.However,it should be noted that discrete-time stochastic models cannot perfectly reproduce the exact solution of continuous-time CMs.Additionally,we proposed a new stochastic compartment and agent mixed model as an alternative to agent-based models for large-scale population simulations with a limited number of agents.This model offered a balance between computational efficiency and accuracy.The results of this research contributed to the comparison and unification of deterministic CMs and stochastic models in epidemic modeling.Furthermore,the results had implications for the development of hybrid models that integrated the strengths of both frameworks.Overall,the present study has provided valuable epidemic modeling techniques and their practical applications for understanding and controlling the spread of infectious diseases.
基金partly supported by the National Key R&D Program of China(2016YFC1306700)the Key Projects of National Natural Science Foundation of China(81830040 and 82130042)+2 种基金the Science and Technology Program of Guangdong,China(2018B030334001)the Program of Excellent Talents in Medical Science of Jiangsu Province,China(JCRCA2016006)the Social Science Foundation of Jiangsu Province,China(19GLB025)。
文摘Major depressive disorder(MDD) is the most common mental disorder. Over 95 million people in China suffer from MDD(Huang et al.,2019). Currently available antidepressants have delayed onset and a low cure rate(Malhi and Mann, 2018). Genetic and psychosocial factors, as well as their interactions, play an important role in the response to antidepressants for MDD patients(Uher, 2011;Gonda et al., 2019;Musci et al., 2019). Understanding the underlying associations and mechanisms may help to improve the first-episode cure rate in MDD patients.
