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Zishenpingchan granules for the treatment of Parkinson's disease:a randomized,double-blind,placebo-controlled clinical trial 被引量:10
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作者 Qing Ye Xiao-Lei Yuan +2 位作者 Can-Xing Yuan Hong-Zhi Zhang Xu-Ming Yang 《Neural Regeneration Research》 SCIE CAS CSCD 2018年第7期1269-1275,共7页
Levodopa preparations remain the preferred drug for Parkinson's disease.However,long-term use of levodopa may lead to a series of motor complications.Previous studies have shown that the combination of levodopa and Z... Levodopa preparations remain the preferred drug for Parkinson's disease.However,long-term use of levodopa may lead to a series of motor complications.Previous studies have shown that the combination of levodopa and Zishenpingchan granules(consisting of Radix Rehmanniae preparata,Lycium barbarum,Herba Taxilli,Rhizoma Gastrodiae,Stiff Silkorm,Curcuma phaeocaulis,Radix Paeoniae Alba,Rhizoma Arisaematis,Scorpio and Centipede) can markedly improve dyskinesia and delay the progression of Parkinson's disease,with especially dramatic improvements of non-motor symptoms.However,the efficacy of this combination has not been confirmed by randomized controlled trials.The current study was approved by the Hospital Ethics Committee and was registered in the Chinese Clinical Trial Register(registration number:Chi CTR-INR-1701194).From December 2014 to December 2016,128 patients(72 males and 56 females,mean age of 65.78 ± 6.34 years) with Parkinson's disease were recruited from the Department of Neurology of Longhua Hospital and Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine in China.Patients were equally allocated into treatment and control groups.In addition to treatment with dopamine,patients in treatment and control groups were given Zishenpingchan granules or placebo,respectively,for 24 weeks.Therapeutic efficacy was assessed using the Unified Parkinson's Disease Rating Scale,on-off phenomenon,Hoehn-Yahr grade,Scales for Outcomes in Parkinson's disease–Autonomic,Parkinson's disease sleep scale,Hamilton Anxiety Scale,Hamilton Depression Scale,Mini-Mental State Examination,and the Parkinson's Disease Quality of Life Questionnaire.Artificial neural networks were used to determine weights at which to scale these parameters.Our results demonstrated that Zishenpingchan granules significantly reduced the occurrence of motor complications,and were useful for mitigating dyskinesia and non-motor symptoms of Parkinson's disease.This combination of Chinese and Western medicine has the potential to reduce levodopa dosages,and no obvious side effects were found.These findings indicate that Zishenpingchan granules can mitigate symptoms of Parkinson's disease,reduce toxic side effects of dopaminergic agents,and exert synergistic and detoxifying effects. 展开更多
关键词 nerve regeneration levodopa motion complications non-motor symptoms traditional Chinese medicine treatment artificial neural networks Zishenpingchan granules randomized controlled trials neurodegenerative diseases neural regeneration
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Modeling effects of alloying elements and heat treatment parameters on mechanical properties of hot die steel with back-propagation artificial neural network 被引量:1
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作者 Yong Liu Jing-chuan Zhu Yong Cao 《Journal of Iron and Steel Research International》 SCIE EI CAS CSCD 2017年第12期1254-1260,共7页
Materials data deep-excavation is very important in materials genome exploration.In order to carry out materials data deep-excavation in hot die steels and obtain the relationships among alloying elements,heat treatme... Materials data deep-excavation is very important in materials genome exploration.In order to carry out materials data deep-excavation in hot die steels and obtain the relationships among alloying elements,heat treatment parameters and materials properties,a 11×12×12×4 back-propagation(BP)artificial neural network(ANN)was set up.Alloying element contents,quenching and tempering temperatures were selected as input;hardness,tensile and yield strength were set as output parameters.The ANN shows a high fitting precision.The effects of alloying elements and heat treatment parameters on the properties of hot die steel were studied using this model.The results indicate that high temperature hardness increases with increasing alloying element content of C,Si,Mo,W,Ni,V and Cr to a maximum value and decreases with further increase in alloying element content.The ANN also predicts that the high temperature hardness will decrease with increasing quenching temperature,and possess an optimal value with increasing tempering temperature.This model provides a new tool for novel hot die steel design. 展开更多
关键词 Back-propagation artificial neural network Hot die steel Alloying element Heat treatment
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