AIM:To investigate whether the axial length(AL)/total corneal refractive power(TCRP)ratio is a sensitive and simple factor that can be used for the early diagnosis of Marfan’s syndrome(MFS)in children.METHODS:The rel...AIM:To investigate whether the axial length(AL)/total corneal refractive power(TCRP)ratio is a sensitive and simple factor that can be used for the early diagnosis of Marfan’s syndrome(MFS)in children.METHODS:The relationship between the AL/TCRP ratio and the diagnosis of MFS for 192 eyes in 97 children were evaluate.The biological characteristics,including age,sex,AL,and TCRP,were collected from medical records.Receiver operating characteristic(ROC)curve analysis was performed to investigate whether the AL/TCRP ratio effectively distinguishes MFS from other subjects.The Youden index was used to re-divide the whole population into two groups according to an AL/TCRP ratio of 0.59.RESULTS:Of 96 subjects(mean age 7.46±3.28 y)evaluated,56(110 eyes)had a definite diagnosis of MFS in childhood based on the revised Ghent criteria,41(82 eyes)with diagnosis of congenital ectopia lentis(EL)were included as a control group.AL was negatively correlated with TCRP,with a linear regression coefficient of-0.36(R2=0.08).A significant correlation was found between age and the AL/TCRP ratio(P=0.023).ROC curve analysis showed that the AL/TCRP ratio distinguished MFS from the other patients at a threshold of 0.59.MFS patients were present in 24/58(41.38%)patients with an AL/TCRP ratio of≤0.59 and in 34/39(87.18%)patients with an AL/TCRP ratio of>0.59.CONCLUSION:An AL/TCRP ratio of>0.59 is significantly associated with the risk of MFS.The AL/TCRP ratio should be measured as a promising marker for the prognosis of children MFS.Changes in the AL/TCRP ratio should be monitored over time.展开更多
Mathematical modeling has become an increasingly important aspect of biological research. Computer simulations help to improve our understanding of complex systems by testing the validity of proposed mechanisms and ge...Mathematical modeling has become an increasingly important aspect of biological research. Computer simulations help to improve our understanding of complex systems by testing the validity of proposed mechanisms and generating experimentally testable hypotheses. However, significant overhead is generated by the creation, debugging, and perturbation of these computational models and their parameters, especially for researchers who are unfamiliar with programming or numerical methods. Dynetica 2.0 is a user-friendly dynamic network simulator designed to expedite this process. Models are created and visualized in an easy-to-use graphical interface, which displays all of the species and reactions involved in a graph layout. System inputs and outputs, indicators, and intermediate expressions may be incorporated into the model via the versatile ＂expression variable＂ entity. Models can also be modular, allowing for the quick construction of complex systems from simpler components. Dynetica 2.0 supports a number of deterministic and stochastic algorithms for performing time-course simulations. Additionally, Dynetica 2.0 provides built-in tools for performing sensitivity or dose response analysis for a number of different metrics. Its parameter searching tools can optimize specific objectives of the time course or dose response of the system. Systems can be translated from Dynetica 2.0 into MATLAB code or the Systems Biology Markup Language （SBML） format for further analysis or publication. Finally, since it is written in Java, Dynetica 2.0 is platform independent, allowing for easy sharing and collaboration between researchers.展开更多
基金Supported by the National Natural Science Foundation of China(No.81770908)the Shanghai Science and Technology Commission(Scientific Innovation Project,No.20Y11911000)。
文摘AIM:To investigate whether the axial length(AL)/total corneal refractive power(TCRP)ratio is a sensitive and simple factor that can be used for the early diagnosis of Marfan’s syndrome(MFS)in children.METHODS:The relationship between the AL/TCRP ratio and the diagnosis of MFS for 192 eyes in 97 children were evaluate.The biological characteristics,including age,sex,AL,and TCRP,were collected from medical records.Receiver operating characteristic(ROC)curve analysis was performed to investigate whether the AL/TCRP ratio effectively distinguishes MFS from other subjects.The Youden index was used to re-divide the whole population into two groups according to an AL/TCRP ratio of 0.59.RESULTS:Of 96 subjects(mean age 7.46±3.28 y)evaluated,56(110 eyes)had a definite diagnosis of MFS in childhood based on the revised Ghent criteria,41(82 eyes)with diagnosis of congenital ectopia lentis(EL)were included as a control group.AL was negatively correlated with TCRP,with a linear regression coefficient of-0.36(R2=0.08).A significant correlation was found between age and the AL/TCRP ratio(P=0.023).ROC curve analysis showed that the AL/TCRP ratio distinguished MFS from the other patients at a threshold of 0.59.MFS patients were present in 24/58(41.38%)patients with an AL/TCRP ratio of≤0.59 and in 34/39(87.18%)patients with an AL/TCRP ratio of>0.59.CONCLUSION:An AL/TCRP ratio of>0.59 is significantly associated with the risk of MFS.The AL/TCRP ratio should be measured as a promising marker for the prognosis of children MFS.Changes in the AL/TCRP ratio should be monitored over time.
文摘Mathematical modeling has become an increasingly important aspect of biological research. Computer simulations help to improve our understanding of complex systems by testing the validity of proposed mechanisms and generating experimentally testable hypotheses. However, significant overhead is generated by the creation, debugging, and perturbation of these computational models and their parameters, especially for researchers who are unfamiliar with programming or numerical methods. Dynetica 2.0 is a user-friendly dynamic network simulator designed to expedite this process. Models are created and visualized in an easy-to-use graphical interface, which displays all of the species and reactions involved in a graph layout. System inputs and outputs, indicators, and intermediate expressions may be incorporated into the model via the versatile ＂expression variable＂ entity. Models can also be modular, allowing for the quick construction of complex systems from simpler components. Dynetica 2.0 supports a number of deterministic and stochastic algorithms for performing time-course simulations. Additionally, Dynetica 2.0 provides built-in tools for performing sensitivity or dose response analysis for a number of different metrics. Its parameter searching tools can optimize specific objectives of the time course or dose response of the system. Systems can be translated from Dynetica 2.0 into MATLAB code or the Systems Biology Markup Language （SBML） format for further analysis or publication. Finally, since it is written in Java, Dynetica 2.0 is platform independent, allowing for easy sharing and collaboration between researchers.
