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Dive into the research topics where Hui-Jun Zhang is active.

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Featured researches published by Hui-Jun Zhang.


Chinese Medical Journal | 2016

Rapid Eye Movement Sleep Behavior Disorder Symptoms Correlate with Domains of Cognitive Impairment in Parkinson's Disease

Jin-Ru Zhang; Jing Chen; Zi-Jiao Yang; Hui-Jun Zhang; Yun-Ting Fu; Yun Shen; Pei-Cheng He; Cheng-Jie Mao; Chun-Feng Liu

Background:Rapid eye movement (REM) sleep behavior disorder (RBD) may be a risk factor for cognitive impairment in patients with Parkinsons disease (PD). However, little is known regarding the relation between the severity of RBD and the different domains of cognitive impairment. The aim of this study was: (1) to investigate the domains of cognitive impairment in patients with PD and RBD, and (2) to explore risk factors for PD-mild cognitive impairment (PD-MCI) and the relationship between RBD severity and impairment in different cognitive domains in PD. Methods:The participants were grouped as follows: PD without RBD (PD-RBD; n = 42), PD with RBD (PD + RBD; n = 32), idiopathic RBD (iRBD; n = 15), and healthy controls (HCs; n = 36). All participants completed a battery of neuropsychological assessment of attention and working memory, executive function, language, memory, and visuospatial function. The information of basic demographics, diseases and medication history, and motor and nonmotor manifestations was obtained and compared between PD-RBD and PD + RBD groups. Particular attention was paid to the severity of RBD assessed by the RBD Questionnaire-Hong Kong (RBDQ-HK) and the RBD Screening Questionnaire (RBDSQ), then we further examined associations between the severity of RBD symptoms and cognitive levels via correlation analysis. Results:Compared to PD-RBD subjects, PD + RBD patients were more likely to have olfactory dysfunction and their Epworth Sleepiness Scale scores were higher (P < 0.05). During neuropsychological testing, PD + RBD patients performed worse than PD-RBD patients, including delayed memory function, especially. The MCI rates were 33%, 63%, 33%, and 8% for PD-RBD, PD + RBD, iRBD, and HC groups, respectively. RBD was an important factor for the PD-MCI variance (odds ratio = 5.204, P = 0.018). During correlation analysis, higher RBDSQ and RBDQ-HK scores were significantly associated with poorer performance on the Trail Making Test-B (errors) and Auditory Verbal Learning Test (delayed recall) and higher RBD-HK scores were also associated with Rey–Osterrieth complex figure (copy) results. Conclusions:When PD-RBD and PD + RBD patients have equivalent motor symptoms, PD + RBD patients still have more olfactory dysfunction and worse daytime somnolence. RBD is an important risk factor for MCI, including delayed memory. Deficits in executive function, verbal delayed memory, and visuospatial function were consistently associated with more severe RBD symptoms.


Pain Practice | 2018

Pain Correlates with Sleep Disturbances in Parkinson's Disease Patients

Yun-Ting Fu; Cheng-Jie Mao; Li‐Jing Ma; Hui-Jun Zhang; Yi Wang; Jie Li; J. Huang; Jun‐Yi Liu; Chun-Feng Liu

Both sleep disorders and pain decrease quality of life in patients with Parkinsons disease (PD). However, little is known about the relationship between objective sleep disturbances and pain in patients with PD. This study aimed to (1) examine the clinical characteristics of pain in PD patients and (2) explore the correlation between pain and sleep disturbances in PD patients.


Neurobiology of Aging | 2018

Genetic analysis of LRRK2 in Parkinson's disease in Han Chinese population

Jin-Ru Zhang; Hong Jin; Kai Li; Cheng-Jie Mao; Ya-Ping Yang; Fen Wang; Chen-chen Gu; Hui-Jun Zhang; Jing Chen; Chun-Feng Liu

Mutations in Leucine-rich repeat kinase 2 (LRRK2) are recognized as the most frequent genetic factors contributing to Parkinsons disease (PD). The aim of our study was to explore LRRK2 variants in PD patients within the mainland Han Chinese population. The whole coding regions of LRRK2 from 296 PD patients were sequenced by targeted regions sequencing and exome sequencing. Eighteen rare variants were identified in 27 PD patients, and 13 of them (M100T, L153W, A459S, S722N, R792K, C925Y, R981K, S1007T, V1447M, R1677S, N2308D, N2313S, and S2350I) were firstly reported in PD. We also tried to explore the genotype-phenotype associations of LRRK2 variants in our data and found that PD with common and rare LRRK2 variants was more likely to have motor fluctuation and nonmotor symptoms. The identification of novel variants in LRRK2 suggests that this gene plays an important role in the pathogenesis and phenotype of PD in Han Chinese population, and our data also rang the alarm bell-more attention should be paid to the whole coding regions of LRRK2.


Chinese Medical Journal | 2018

Effect of Rapid Eye Movement Sleep Behavior Disorder on Obstructive Sleep Apnea Severity and Cognition of Parkinson's Disease Patients

Jie Li; Jun-Ying Huang; Jin-Ru Zhang; Yun Shen; Hui-Jun Zhang; Yu-Lan Cao; Cheng-Jie Mao; Ya-Ping Yang; Jing Chen; Chun-Feng Liu

Background: Rapid eye movement (REM) sleep behavior disorder (RBD) and obstructive sleep apnea (OSA) are the most common sleep disorders in Parkinsons disease (PD). The aim of this study was to identify whether RBD could alleviate OSA severity in PD patients and its effect on cognitive impairment. Methods: From February 2014 to May 2017, we recruited 174 PD patients from the Second Affiliated Hospital of Soochow University, all of whom underwent polysomnography (PSG). We collected clinical data, PSG results, and compared information between patients with and without RBD or OSA by analysis of covariance. We also investigated the effect of these sleep disorders on cognitive impairment using linear regression. Results: We grouped participants as follows: PD only (n = 53), PD + OSA (n = 29), PD + RBD (n = 61), and PD + RBD + OSA (n = 31). Minimum oxygen saturation (SaO2) during whole sleep and in REM sleep was higher in PD + RBD + OSA patients than that in PD + OSA patients. PD + RBD patients had worse Mini-Mental Status Examination and Montreal Cognitive Assessment (MoCA) scores than those in the PD group (P < 0.001), especially in visuospatial/executive, attention, and memory functions. The PD + OSA group performed worse than the PD group in the delayed recall domain. After adjusting for age, sex, body mass index, education, disease severity, and other sleep disorders, MoCA was negatively associated with OSA (&bgr; = −0.736, P = 0.043) and RBD (&bgr; = −2.575,P < 0.001). The severity of RBD (tonic/phasic electromyography activity) and OSA (apnea-hypopnea index/oxygen desaturation index/minimum SaO2) were also associated with MoCA. The adjusted &bgr; values of RBD-related parameters were higher than that for OSA. Conclusions: We found that RBD alleviated OSA severity; however, RBD and OSA together exacerbated PD cognitive impairment. Further studies are needed to evaluate whether OSA treatment can improve cognition in PD.


international ieee/embs conference on neural engineering | 2017

Multi-sensor wearable devices for movement monitoring in Parkinson's disease

Liang Li; Qian Yu; Baoteng Xu; Qifan Bai; Yunpeng Zhang; Hui-Jun Zhang; Cheng-Jie Mao; Chun-Feng Liu; Tianyu Shen; Shouyan Wang

Quantitative assessment of the motor symptoms in Parkinsons disease is the key to early treatment and essential for long term management over years. Wearable devices provide a new approach to quantify the motor symptoms in Parkinsons disease. Monitoring of the symptoms at multi-joints and body, on-line monitoring, quick analysis, low load and less restriction to the patients raise challenges to develop proper wearable device for patients monitoring in hospital. In this paper, multi-sensor wearable devices were developed to monitor and quantify the movement symptoms in Parkinsons disease. Five wearable sensors were used to record motion signals from patients bilateral forearms, legs and waist. A local area network based on low power Wi-Fi technology was built for wide range and long period wireless data transmission. A software was developed for motion signal recording and analyzing. The size of each sensors was 52 mm×37 mm×13 mm and the weight was 26.3 g. The sensors were rechargeable and able to run 13 hours per charge. The wireless transmission radius was over 40 m. The wearable devices were tested in patients and normal subjects. The devices were reliable and with good temporal resolution and spatial resolution for movement monitoring in hospital.


Parkinsonism & Related Disorders | 2017

Poor nighttime sleep is positively associated with dyskinesia in Parkinson's disease patients

Cheng-Jie Mao; Ya-Ping Yang; Ju-Ping Chen; Fen Wang; Jing Chen; Jin-Ru Zhang; Hui-Jun Zhang; Sheng Zhuang; Yi-tong Xiong; Chen-chen Gu; Wen Yuan; Juan-Ying Huang; Alexander Fay; Chong-ke Zhong; Chun-Feng Liu

BACKGROUND Dyskinesia is a troublesome complication of long-term dopaminergic medications in Parkinsons disease (PD) patients. Many factors are reported to be associated with dyskinesia in PD. OBJECTIVE To investigate the association between sleep quality and dyskinesia in patients with PD. METHODS Four hundred twenty-five patients with PD were enrolled in this study. Demographic information was collected. Unified Parkinsons Disease Rating Scale (UPDRS) and Hoehn and Yahr (H-Y) stage scale were also performed. Epworth Sleepiness Scale (ESS) and Pittsburgh Sleep Quality Index (PSQI) were applied to evaluate daytime sleepiness and overall nighttime sleep quality, respectively, in PD patients. RESULTS Patients with dyskinesia tended to have a longer duration of disease, higher daily levodopa-equivalent dose (LED), H-Y stage, UPDRS II and PSQI score, and a higher percentage of levodopa treatment than those without dyskinesia. After adjusting for age, sex, age at onset of PD, disease duration, UPDRS I, UPDRS II, UPDRS III, cigarette smoking, use of different antiparkinsonian drugs, phenotype, daily LED, and restless leg syndrome (RLS), PSQI score was still associated with dyskinesia, with corresponding ORs 1.111 (95% CI, 1.004-1.229) as a continuous variable, and 2.469 (95% CI, 1.051-5.800) as a categorical variable, respectively. Further analysis of PSQI components showed that subjective sleep quality and sleep latency were associated with dyskinesia in PD patients. CONCLUSIONS Our data showed that poor nighttime sleep is positively associated with dyskinesia in PD patients. Attention to the management of nighttime sleep quality may be beneficial to dyskinesia in patients with PD.


Brain and behavior | 2017

Serum sodium and chloride are inversely associated with dyskinesia in Parkinson's disease patients

Cheng-Jie Mao; Chong-ke Zhong; Yong Yang; Ya-Ping Yang; Fen Wang; Jing Chen; Jin-Ru Zhang; Hui-Jun Zhang; Hong Jin; Ling-Li Xu; Juan-Ying Huang; Chun-Feng Liu

We aim to report and evaluate the associations between serum sodium and chloride and dyskinesia in patients with Parkinsons disease. One hundred and two patients with Parkinsons disease were enrolled in this study.


international conference on signal processing | 2016

Quantitative assessment of Parkinson's disease with multiple wearable devices

Qifan Bai; Hui-Jun Zhang; Cheng-Jie Mao; Liang Li; Qian Yu; Baoteng Xu; Tianyu Shen; Chun-Feng Liu; Shouyan Wang

With the aging of the population, Parkinsons disease (PD) is increasing and severely threating to human life and health. Quantitative assessment of the symptoms in PD is the key for precise diagnosis and treatment and essential for long term management over years. Currently, the evaluation of the symptoms in PD mainly relies on Unified Parkinsons Disease Rating Scale (UPDRS), which is affected by the subjective judgment of the clinicians. In this paper, we developed a new method for quantitative assessment of the motor symptoms in PD with multiple wearable devices. The method was used in conjunction with UPDRS assessment, and movement monitoring during sleep.


Parkinsonism & Related Disorders | 2015

Quantitative and fiber-selective evaluation of pain and sensory dysfunction in patients with Parkinson's disease

Yi Chen; Cheng-Jie Mao; Si-Jiao Li; Fen Wang; Jing Chen; Hui-Jun Zhang; Ling Li; Sha-Sha Guo; Ya-Ping Yang; Chun-Feng Liu


international ieee/embs conference on neural engineering | 2017

Quantification of the motor symptoms of Parkinson's disease

Qifan Bai; Tianyu Shen; Baoteng Xu; Qian Yu; Hui-Jun Zhang; Cheng-Jie Mao; Chun-Feng Liu; Shouyan Wang

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Baoteng Xu

Chinese Academy of Sciences

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Qian Yu

Chinese Academy of Sciences

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Qifan Bai

Chinese Academy of Sciences

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Shouyan Wang

Chinese Academy of Sciences

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Tianyu Shen

Chinese Academy of Sciences

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Liang Li

Chinese Academy of Sciences

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Jue Chen

Peking Union Medical College

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Yunpeng Zhang

Chinese Academy of Sciences

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Alexander Fay

Washington University in St. Louis

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