Parkinson’s disease is a common chronic progressive neurodegenerative disease, and its main pathological change is the degeneration and loss of dopaminergic neurons in substantia nigra striatum. Vitamin D receptors are widely distributed in neurons and glial cells, and the normal function of substantia nigra striatum system depends on the level of vitamin D and the normal expression of vitamin D receptors. In recent years, from basic to clinical research, there are some differences in the conclusion of the correlation of vitamin D and its receptor gene polymorphism with Parkinson’s disease. This paper aims to review the research on the correlation of vitamin D and vitamin D receptor gene polymorphism with Parkinson’s disease, and discuss the future research direction in this field.
1-methyl-6,7-dihydroxy-1,2,3,4-tetrahydroisoquinoline (Sal) is a kind of catechol isoquinoline compound, which mainly exists in mammalian brain and performs a variety of biological functions. Through in vivo metabolism, Sal can be transformed into endogenous neurotoxins and can participate the occurrence of Parkinson’s disease (PD). This has attracted widespread concern of researchers. Recently, many research works have shown that Sal may lead to alcohol addiction and regulate hormone release of the neuroendocrine system, which indicated that it is a potential regulator of dopaminergic neurons. In this paper, we discuss the neural functions of Sal on the above aspects, and wish to provide some theoretical supports for further research on its mechanism.
At present, the incidence of Parkinson’s disease (PD) is gradually increasing. This seriously affects the quality of life of patients, and the burden of diagnosis and treatment is increasing. However, the disease is difficult to intervene in early stage as early monitoring means are limited. Aiming to find an effective biomarker of PD, this work extracted correlation between each pair of electroencephalogram (EEG) channels for each frequency band using weighted symbolic mutual information and k-means clustering. The results showed that State1 of Beta frequency band (P = 0.034) and State5 of Gamma frequency band (P = 0.010) could be used to differentiate health controls and off-medication Parkinson’s disease patients. These findings indicated that there were significant differences in the resting channel-wise correlation states between PD patients and healthy subjects. However, no significant differences were found between PD-on and PD-off patients, and between PD-on patients and healthy controls. This may provide a clinical diagnosis reference for Parkinson’s disease.
At present the parkinsonian rigidity assessment depends on subjective judgment of neurologists according to their experience. This study presents a parkinsonian rigidity quantification system based on the electromechanical driving device and mechanical impedance measurement method. The quantification system applies the electromechanical driving device to perform the rigidity clinical assessment tasks (flexion-extension movements) in Parkinson’s disease (PD) patients, which captures their motion and biomechanical information synchronously. Qualified rigidity features were obtained through statistical analysis method such as least-squares parameter estimation. By comparing the judgments from both the parkinsonian rigidity quantification system and neurologists, correlation analysis was performed to find the optimal quantitative feature. Clinical experiments showed that the mechanical impedance has the best correlation (Pearson correlation coefficient r = 0.872, P < 0.001) with the clinical unified Parkinson’s disease rating scale (UPDRS) rigidity score. Results confirmed that this measurement system is capable of quantifying parkinsonian rigidity with advantages of simple operation and effective assessment. In addition, the mechanical impedance can be adopted to help doctors to diagnose and monitor parkinsonian rigidity objectively and accurately.
Objective To assess the changes in depression symptoms in patients with Parkinson’s disease (PD) receiving combined treatment of deep brain stimulation (DBS) and antiparkinsonian drug therapy (DT) compared with under DT alone. Methods Related literature was retrieved from electronic databases, including PubMed, Cochrane Library, Embase, China National Knowledge Infrastructure, Wanfang Data, and VIP databases. Stata 14.0 software was used for statistical analysis. Network meta-analysis was performed using frequentist model to compare different interventions with each other. Results Five cohort studies and seven randomized controlled trials (RCTs) were included. The total number of participants was 1241. Assessed by the Beck Depression Inventory (BDI) score as the primary outcome, patients who received DT alone showed worse outcome in depression as compared to those who received subthalamic nucleus (STN)-DBS plus DT [standardized mean difference (SMD)=0.30, 95% confidence interval (CI) (0.01, 0.59), P<0.05], and there was no significant difference between the patients receiving globus pallidus interna (GPi)-DBS plus DT and those receiving STN-DBS plus DT [SMD=–0.12, 95%CI (–0.41, 0.16), P>0.05] or those receiving DT alone [SMD=–0.42, 95%CI (–0.84, 0.00), P>0.05]. Assessed by BDI-Ⅱ as the primary outcome, patients who received DT alone showed worse outcome in depression than those who received STN-DBS plus DT [SMD=0.29, 95%CI (0.05, 0.54), P<0.05]; compared with STN-DBS plus DT and DT alone, GPi-DBS plus DT was associated with better improvement in depression [SMD=–0.26, 95%CI (–0.46, –0.06), P<0.05; SMD=–0.55, 95%CI (–0.88, –0.23), P<0.05]. The ranking results of surface under the cumulative ranking curves showed that DBS plus DT had a better superiority in depression symptoms, and GPi-DBS was better than STN-DBS. Conclusion Compared with DT, STN-DBS plus DT is more likely to improve the depressive symptoms of PD patients, and GPi-DBS may be better than STN-DBS.
Objective To understand the frailty status and main influencing factors of elderly Parkinson’s disease (PD) patients. Methods The elderly PD patients who attended the Department of Neurology of Changshu Hospital of Traditional Chinese Medicine between November 2023 and March 2024 were selected. The patients’ frailty conditions were investigated using general information questionnaire, Chinese version of Tilburg Frailty Indicator, Hoehn-Yahr Rating Scale, Mini-Nutritional Assessment Short Form, Movement Disorder Society-Unified PD Rating Scale Part Ⅲ, PD Sleep Scale-2, and Mini-Mental State Examination. Multiple linear regression analysis was used to further determine the influencing factors of the frailty status in elderly PD patients. Results A total of 170 PD patients were included. Among them, 117 cases (68.82%) had frailty, while 53 cases (31.18%) had not frailty. The average score for frailty was (6.48±3.34) points, the average score for nutritional status was (11.89±1.65) points, the average score for motor function was (27.40±13.73) points, the average score for sleep quality was (16.05±7.76) points, and the average score for cognitive status is (26.25±4.51) points. The Pearson correlation analysis results showed that PD patient frailty was positively correlated with motor function and sleep quality (P<0.01), and negatively correlated with nutritional status and cognitive status (P<0.01). The results of multiple linear regression analysis showed that age, education, place of residence, course of disease, Hoehn-Yahr Rating, nutritional status, motor function, cognitive status and sleep quality were the influencing factors of frailty in PD patients (P<0.05). Conclusions Elderly PD patients are prone to frailty. Healthcare professionals should pay attention to early screening for frailty in this population and provide timely and effective interventions to prevent or delay the onset of frailty in patients.
For speech detection in Parkinson’s patients, we proposed a method based on time-frequency domain gradient statistics to analyze speech disorders of Parkinson’s patients. In this method, speech signal was first converted to time-frequency domain (time-frequency representation). In the process, the speech signal was divided into frames. Through calculation, each frame was Fourier transformed to obtain the energy spectrum, which was mapped to the image space for visualization. Secondly, deviations values of each energy data on time axis and frequency axis was counted. According to deviations values, the gradient statistical features were used to show the abrupt changes of energy value in different time-domains and frequency-domains. Finally, KNN classifier was applied to classify the extracted gradient statistical features. In this paper, experiments on different speech datasets of Parkinson’s patients showed that the gradient statistical features extracted in this paper had stronger clustering in classification. Compared with the classification results based on traditional features and deep learning features, the gradient statistical features extracted in this paper were better in classification accuracy, specificity and sensitivity. The experimental results show that the gradient statistical features proposed in this paper are feasible in speech classification diagnosis of Parkinson’s patients.
ObjectiveThis study aims to analyze the trends in Parkinson’s disease incidence rates among the elderly population in China from 1990 to 2021 and to forecast incidence growth over the next 20 years, providing. MethodsJoinpoint regression and age-period-cohort models were employed to analyze temporal trends in Parkinson’s disease incidence, and the Nordpred model was used to predict case numbers and incidence rates among the elderly in China from 2022 to 2044. ResultsFindings indicated a significant increase in Parkinson’s disease incidence among China’s elderly population from 1990 to 2021, with crude and age-standardized incidence rates rising from 95.37 per 100 000 and 111.05 per 100 000 to 170.52 per 100 000 and 183.91 per 100 000, respectively. Predictions suggested that by 2044, the number of cases will rise to approximately 878 264, with the age-standardized incidence rate reaching 223.4 per 100 000, and men showing significantly higher incidence rates than women. The rapid increase in both cases and incidence rates indicated that Parkinson’s disease will continue to impose a heavy disease burden on China’s elderly population. ConclusionThe burden of Parkinson’s disease in China’s elderly population has grown significantly and is expected to worsen. To address the rising incidence rates effectively, it is recommended to enhance early screening and health education for high-risk groups, improve diagnostic and treatment protocols, and prioritize resource allocation to Parkinson’s disease prevention and care services to reduce future public health burdens.
The dysfunction of subthalamic nucleus is the main cause of Parkinson’s disease. Local field potentials in human subthalamic nucleus contain rich physiological information. The present study aimed to quantify the oscillatory and dynamic characteristics of local field potentials of subthalamic nucleus, and their modulation by the medication therapy for Parkinson’s disease. The subthalamic nucleus local field potentials were recorded from patients with Parkinson’s disease at the states of on and off medication. The oscillatory features were characterised with the power spectral analysis. Furthermore, the dynamic features were characterised with time-frequency analysis and the coefficient of variation measure of the time-variant power at each frequency. There was a dominant peak at low beta band with medication off. The medication significantly suppressed the low beta component and increased the theta component. The amplitude fluctuation of neural oscillations was measured by the coefficient of variation. The coefficient of variation in 4-7 Hz and 60-66 Hz was increased by medication. These effects proved that medication had significant modulation to subthalamic nucleus neural oscillatory synchronization and dynamic features. The subthalamic nucleus neural activities tend towards stable state under medication. The findings would provide quantitative biomarkers for studying the mechanisms of Parkinson’s disease and clinical treatments of medication or deep brain stimulation.
Evidence has been retrieved through MEDLINE and Cochrane Libray about the treatment for patients with advanced Parkinson’s disease who suffered from on-off, dyskinesia and depression after chronic use of L-dopa. All of the evidence has been evaluated. Methods of evidence-based treatment were drawn up according to the evidence, clinciams’ experiences and patients’ preferences. All symptoms of the patient have been improved obviously.