This study aims to investigate how the frequency settings of deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) influence the motor symptoms of Parkinson’s disease (PD). Stimulation with frequencies less than 100 Hz (mostly 60 or 80 Hz) is considered low-frequency stimulation (LFS) and with frequencies greater than 100 Hz (mostly 130 or 150 Hz) is considered high-frequency stimulation (HFS). We conducted a comprehensive literature review and meta-analysis with a random-effect model. Ten studies with 132 patients were included in our analysis. The pooled results showed no significant difference in the total Unified Parkinson Disease Rating Scale part III (UPDRS-III) scores (mean effect, −1.50; p = 0.19) or the rigidity subscore between HFS and LFS. Compared to LFS, HFS induced greater reduction in the tremor subscore within the medication-off condition (mean effect, 1.01; p = 0.002), while no significance was shown within the medication-on condition (mean effect, 0.01; p = 0.92). LFS induced greater reduction in akinesia subscore (mean effect, −1.68, p = 0.003), the time to complete the stand-walk-sit (SWS) test (mean effect, −4.84; p < 0.00001), and the number of freezing of gait (FOG) (mean effect, −1.71; p = 0.03). These results suggest that two types of frequency settings may have different effects, that is, HFS induces better responses for tremor and LFS induces greater response for akinesia, gait, and FOG, respectively, which are worthwhile to be confirmed in future study, and will ultimately inform the clinical practice in the management of PD using STN-DBS.
Background Parkinson disease (PD) is a common movement disorder. Patients with PD have multiple gait impairments that result in an increased risk of falls and diminished quality of life. Therefore, gait measurement is important for the management of PD. Objective We previously developed a smartphone-based dual-task gait assessment that was validated in healthy adults. The aim of this study was to test the validity of this gait assessment in people with PD, and to examine the association between app-derived gait metrics and the clinical and functional characteristics of PD. Methods Fifty-two participants with clinically diagnosed PD completed assessments of walking, Movement Disorder Society Unified Parkinson Disease Rating Scale III (UPDRS III), Montreal Cognitive Assessment (MoCA), Hamilton Anxiety (HAM-A), and Hamilton Depression (HAM-D) rating scale tests. Participants followed multimedia instructions provided by the app to complete two 20-meter trials each of walking normally (single task) and walking while performing a serial subtraction dual task (dual task). Gait data were simultaneously collected with the app and gold-standard wearable motion sensors. Stride times and stride time variability were derived from the acceleration and angular velocity signal acquired from the internal motion sensor of the phone and from the wearable sensor system. Results High correlations were observed between the stride time and stride time variability derived from the app and from the gold-standard system (r=0.98-0.99, P<.001), revealing excellent validity of the app-based gait assessment in PD. Compared with those from the single-task condition, the stride time (F1,103=14.1, P<.001) and stride time variability (F1,103=6.8, P=.008) in the dual-task condition were significantly greater. Participants who walked with greater stride time variability exhibited a greater UPDRS III total score (single task: β=.39, P<.001; dual task: β=.37, P=.01), HAM-A (single-task: β=.49, P=.007; dual-task: β=.48, P=.009), and HAM-D (single task: β=.44, P=.01; dual task: β=.49, P=.009). Moreover, those with greater dual-task stride time variability (β=.48, P=.001) or dual-task cost of stride time variability (β=.44, P=.004) exhibited lower MoCA scores. Conclusions A smartphone-based gait assessment can be used to provide meaningful metrics of single- and dual-task gait that are associated with disease severity and functional outcomes in individuals with PD.
This study aims to investigate how the frequency settings of deep brain stimulation (DBS) targeting the subthalamic nucleus (STN) influence the motor symptoms of Parkinson's disease (PD). Stimulation with frequencies less than 100 Hz (mostly 60 or 80 Hz) is considered low-frequency stimulation (LFS) and with frequencies greater than 100 Hz (mostly 130 or 150 Hz) is considered high-frequency stimulation (HFS). We conducted a comprehensive literature review and meta-analysis with a random-effect model. Ten studies with 132 patients were included in our analysis. The pooled results showed no significant difference in the total Unified Parkinson Disease Rating Scale part III (UPDRS-III) scores (mean effect, −1.50; p = 0.19) or the rigidity subscore between HFS and LFS. Compared to LFS, HFS induced greater reduction in the tremor subscore within the medication-off condition (mean effect, 1.01; p = 0.002), while no significance was shown within the medication-on condition (mean effect, 0.01; p = 0.92). LFS induced greater reduction in akinesia subscore (mean effect, −1.68, p = 0.003), the time to complete the stand-walk-sit (SWS) test (mean effect, −4.84; p < 0.00001), and the number of freezing of gait (FOG) (mean effect, −1.71; p = 0.03). These results suggest that two types of frequency settings may have different effects, that is, HFS induces better responses for tremor and LFS induces greater response for akinesia, gait, and FOG, respectively, which are worthwhile to be confirmed in future study, and will ultimately inform the clinical practice in the management of PD using STN-DBS.
The hippocampus is a structurally and functionally complex brain area that plays important and diverse roles in higher brain functions, such as learning and memory, and mounting evidence indicates that different hippocampal subregions play distinctive roles. The hippocampus is also one of the first regions in the brain to suffer damage in Alzheimer's disease (AD). Synaptic dysfunction in the hippocampus, rather than neuronal loss per se, is paralleled by behavioural and functional deficits in AD. The membrane-associated guanylate kinase (MAGUK) family of proteins, including SAP102, PSD-95, PSD-93 and SAP97, have long been recognized as essential components of the postsynaptic density (PSD) at excitatory synapses. Hippocampal spines are the predominant synaptic transmission sites of excitatory glutamatergic synapses. During postnatal brain development, individual MAGUK members show distinct expression patterns. Although SAP102 has been confirmed as the dominant scaffold protein in neonatal synapses, its expression profiles in adult and ageing rodent hippocampi are discrepant. Furthermore, in AD brains, significantly reduced SAP102 protein levels have been found, suggesting that SAP102 may be related to AD progression; however, the precise mechanism underlying this result remains unclear. Herein, we observed distinct SAP102 expression profiles in the hippocampal CA1, CA3 and DG subregions of rats and APPswe/PS1dE9 (APP/PS1) mice at various ages using immunofluorescence. In Wistar rats, SAP102 was not only highly expressed in the hippocampal subregions of neonatal rats but also maintained relatively high expression levels in adult hippocampi and displayed no obvious decreases in the CA1 and DG subregions of aged rats. Surprisingly, we observed abnormally high SAP102 expression levels in the CA1 stratum moleculare and CA3 stratum polymorphum subregions of 2-month-old APP/PS1 mice, but low SAP102 levels in the DG and CA3 subregions of 7-month-old APP/PS1 mice, reflecting the subregion-specific reactivity and vulnerability of AD mouse models in different disease stages. Our findings provide fundamental data to support the functional differences of SAP102 in different hippocampal subregions during postnatal periods and may serve as the basis for additional functional studies on SAP102 in normal physiological conditions and different stages of AD.
BackgroundThe pathophysiology of depression in Parkinson’s disease (PD) is not fully understood. Studies based upon functional MRI (fMRI) showed the alterations in the blood-oxygen-level-dependent (BOLD) fluctuations in multiple brain regions pertaining to depression in PD. However, large variance was observed across previous studies. Therefore, we conducted a meta-analysis to quantitatively evaluate the results in previous publications and completed an independent regions-of-interests (ROIs)-based analysis using our own data to validate the results of the meta-analysis.MethodsWe searched PubMed, Embase, and Web of Science to identify fMRI studies in PD patients with depression. Using signed differential mapping (SDM) method, we performed a voxel-based meta-analysis. Then, a validation study by using multiscale entropy (MSE) in 28 PD patients with depression and 25 PD patients without depression was conducted. The fMRI scan was completed in anti-depression-medication-off state. The ROIs of the MSE analysis were the regions identified by the meta-analysis.ResultsA total of 126 PD patients with depression and 153 PD patients without depression were included in meta-analysis. It was observed that the resting-state activities within the posterior cingulate gyrus, supplementary motor area (SMA), and cerebellum were altered in depressed patients. Then, in the validation study, these regions were used as ROIs. PD patients with depression had significantly lower MSE of the BOLD fluctuations in these regions (posterior cingulate gyrus: F = 0.856, p = 0.049; SMA: F = 0.914, p = 0.039; cerebellum: F = 0.227, p = 0.043).ConclusionOur study revealed that the altered BOLD activity in cingulate, SMA, and cerebellum of the brain were pertaining to depression in PD.
Background/Objectives: Distinguishing between Parkinson's disease (PD) and multiple system atrophy (MSA) is challenging in the clinic because patients with these two conditions present with similar symptoms in motor dysfunction. Here, we aimed to determine whether tremor characteristics can serve as novel markers for distinguishing the two conditions. Methods: Ninety-one subjects with clinically diagnosed PD and 93 subjects with MSA were included. Tremor of the limbs was measured in different conditions (such as resting, postural, and weight-holding) using electromyography (EMG) surface electrodes and accelerometers. The dominant frequency, tremor occurrence rate, and harmonic occurrence rate (HOR) of the tremor were then calculated. Results: Our results demonstrated that the tremor dominant frequency in the upper limbs of the MSA group was significantly higher than that in the PD group across all resting ( F = 5.717, p = 0.023), postural ( F = 13.409, p < 0.001), and weight-holding conditions ( F = 9.491, p < 0.001) and that it was not dependent on the patient's age or disease course. The tremor occurrence rate (75.6 vs. 14.9%, χ 2 = 68.487, p < 0.001) and HOR (75.0 vs. 4.5%, χ 2 = 46.619, p < 0.001) in the resting condition were significantly lower in the MSA group than in the PD group. The sensitivity of the harmonic for PD diagnosis was 75.0% and the specificity was relatively high, in some cases up to 95.5%. The PPV and NPV were 95.2 and 75.9%, respectively. Conclusion: Our study confirmed that several tremor characteristics, including the dominant tremor frequency and the occurrence rate in different conditions, help detect PD and MSA. The presence of harmonics may serve as a novel marker to help distinguish PD from MSA with high sensitivity and specificity.
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