Background Adolescents’subjective well-being(SWB)is strongly linked to mental health,academic achievement,social relationships,and quality of life,and is a key predictor of life outcomes in adulthood.Mental health an...Background Adolescents’subjective well-being(SWB)is strongly linked to mental health,academic achievement,social relationships,and quality of life,and is a key predictor of life outcomes in adulthood.Mental health and addictive behaviors are the two main factors influencing SWB.This study aimed to identify key mental health and addictive behavior factors associated with adolescent SWB through machine learning models.Methods The data for this study comes from the Health Behaviour in School-aged Children(HBSC)survey 2017/18.The study data contains health data from 60,450 adolescents aged 10–16 years.The study used the XGBoost machine learning model to analyze the impact of mental health and addictive behaviors on adolescent SWB.Gain was used to analyze the significance of the variables.The direction of action of the variables and the interaction between the variables were analyzed using the SHapley Additive exPlanations(SHAP)method.Results The model in this study has an accuracy of 86.7%and an AUC value of 0.85,showing its good predictive performance.Six key variables were filtered through Gain analysis.Feeling low and health as the two most important factors affecting SWB,with these two variables contributing 51.38%and 19.65%,respectively.Friends and thinking body as major factors influencing SWB in mental health.Smoking lifetime and sweets as major factors influencing SWB in addictive behaviors.The interactions and characteristic dependencies between these variables were further analyzed.The results showed that feeling low,friends,and sweets had a positive effect on SWB,while health and smoking lifetime showed a negative effect.In addition,a moderate thinking body contributes to SWB,whereas being too fat and too thin are both associated with decreased levels of SWB.Conclusion Mental health and addictive behavioral factors such as feeling low,friends,sweets,and smoking lifetime were significant factors influencing SWB.This provides a scientific basis for the development of public health policies and interventions aimed at enhancing adolescent well-being.展开更多
The over-expression of α-synuclein is a major factor in the death of dopaminergic neurons in a methamphetamine-induced model of Parkinson’s disease. In the present study, α-synuclein knockdown rats were created by ...The over-expression of α-synuclein is a major factor in the death of dopaminergic neurons in a methamphetamine-induced model of Parkinson’s disease. In the present study, α-synuclein knockdown rats were created by injecting α-synuclein-shRNA lentivirus stereotaxically into the right striatum of experimental rats. At 2 weeks post-injection, the rats were injected intraper-itoneally with methamphetamine to establish the model of Parkinson’s disease. Expression of α-synuclein mRNA and protein in the right striatum of the injected rats was significantly down-regulated. Food intake and body weight were greater in α-synuclein knockdown rats, and water intake and stereotyped behavior score were lower than in model rats. Striatal dopamine and tyrosine hydroxylase levels were significantly elevated in α-synuclein knockdown rats. Moreover, superoxide dismutase activity was greater in α-synuclein knockdown rat striatum, but the levels of reactive oxygen species, malondialdehyde, nitric oxide synthase and nitrogen monoxide were lower compared with model rats. We also found that α-synuclein knockdown inhibited metham-phetamine-induced neuronal apoptosis. These results suggest that α-synuclein has the capacity to reverse methamphetamine-induced apoptosis of dopaminergic neurons in the rat striatum by inhibiting oxidative stress and improving dopaminergic system function.展开更多
基金funded by the National Social Science Fund of China(GrantNo.24CTJ019).
文摘Background Adolescents’subjective well-being(SWB)is strongly linked to mental health,academic achievement,social relationships,and quality of life,and is a key predictor of life outcomes in adulthood.Mental health and addictive behaviors are the two main factors influencing SWB.This study aimed to identify key mental health and addictive behavior factors associated with adolescent SWB through machine learning models.Methods The data for this study comes from the Health Behaviour in School-aged Children(HBSC)survey 2017/18.The study data contains health data from 60,450 adolescents aged 10–16 years.The study used the XGBoost machine learning model to analyze the impact of mental health and addictive behaviors on adolescent SWB.Gain was used to analyze the significance of the variables.The direction of action of the variables and the interaction between the variables were analyzed using the SHapley Additive exPlanations(SHAP)method.Results The model in this study has an accuracy of 86.7%and an AUC value of 0.85,showing its good predictive performance.Six key variables were filtered through Gain analysis.Feeling low and health as the two most important factors affecting SWB,with these two variables contributing 51.38%and 19.65%,respectively.Friends and thinking body as major factors influencing SWB in mental health.Smoking lifetime and sweets as major factors influencing SWB in addictive behaviors.The interactions and characteristic dependencies between these variables were further analyzed.The results showed that feeling low,friends,and sweets had a positive effect on SWB,while health and smoking lifetime showed a negative effect.In addition,a moderate thinking body contributes to SWB,whereas being too fat and too thin are both associated with decreased levels of SWB.Conclusion Mental health and addictive behavioral factors such as feeling low,friends,sweets,and smoking lifetime were significant factors influencing SWB.This provides a scientific basis for the development of public health policies and interventions aimed at enhancing adolescent well-being.
基金supported by the National Natural Science Foundation of China,No.81072506
文摘The over-expression of α-synuclein is a major factor in the death of dopaminergic neurons in a methamphetamine-induced model of Parkinson’s disease. In the present study, α-synuclein knockdown rats were created by injecting α-synuclein-shRNA lentivirus stereotaxically into the right striatum of experimental rats. At 2 weeks post-injection, the rats were injected intraper-itoneally with methamphetamine to establish the model of Parkinson’s disease. Expression of α-synuclein mRNA and protein in the right striatum of the injected rats was significantly down-regulated. Food intake and body weight were greater in α-synuclein knockdown rats, and water intake and stereotyped behavior score were lower than in model rats. Striatal dopamine and tyrosine hydroxylase levels were significantly elevated in α-synuclein knockdown rats. Moreover, superoxide dismutase activity was greater in α-synuclein knockdown rat striatum, but the levels of reactive oxygen species, malondialdehyde, nitric oxide synthase and nitrogen monoxide were lower compared with model rats. We also found that α-synuclein knockdown inhibited metham-phetamine-induced neuronal apoptosis. These results suggest that α-synuclein has the capacity to reverse methamphetamine-induced apoptosis of dopaminergic neurons in the rat striatum by inhibiting oxidative stress and improving dopaminergic system function.
