A Comprehensive Analysis of Population Differences in LRRK2 Variant Distribution in Parkinson's Disease

Background:LRRK2 variants have been demonstrated to have distinct distributions in different populations. However, researchers have thus far chosen to focus on relatively few variants, such as R1628P, G2019S, and G2385R. We therefore investigated the relationship between common LRRK2 variants and PD risk in various populations.Methods: Using a set of strict inclusion criteria, six databases were searched, resulting in the selection of 94 articles covering 49,299 cases and 47,319 controls for final pooled analysis and frequency analysis. Subgroup analysis were done for Africans, European/West Asians, Hispanics, East Asians, and mixed populations. Statistical analysis was carried out using the Mantel-Haenszel approach to determine the relationship between common LRRK2 variants and PD risk, with the significance level set at p < 0.05.Results: In the absence of obvious heterogeneities and publication biases among the included studies, we concluded that A419V, R1441C/G/H, R1628P, G2019S, and G2385R were associated with increased PD risk (p: 0.001, 0.0004, < 0.00001, < 0.00001, and < 0.00001, respectively), while R1398H was associated with decreased risk (p: < 0.00001). In East Asian populations, A419V, R1628P, and G2385R increased risk (p: 0.001, < 0.00001, < 0.00001), while R1398H had the opposite effect (p: 0.0005). G2019S increased PD risk in both European/West Asian and mixed populations (p: < 0.00001, < 0.00001), while R1441C/G/H increased risk in European/West Asian populations only (p: 0.0004).Conclusions: We demonstrated that LRRK2 variant distribution is different among various populations, which should inform decisions regarding the development of future genetic screening strategies

A Comprehensive Analysis of the Association Between SNCA Polymorphisms and the Risk of Parkinson's Disease

Background: Various studies have reported associations between synuclein alpha (SNCA) polymorphisms and Parkinson's disease (PD) risk. However, the results are inconsistent. We conducted a comprehensive meta-analysis of the associations between SNCA single-nucleotide polymorphisms (SNPs) and PD risk in overall populations and subpopulations by ethnicity.Methods: Standard meta-analysis was conducted according to our protocol with a cutoff point of p < 0.05. To find the most relevant SNCA SNPs, we used a cutoff point of p < 1 × 10−5 in an analysis based on the allele model. In the subgroup analysis by ethnicity, we divided the overall populations into five ethnic groups. We conducted further analysis on the most relevant SNPs using dominant and recessive models to identify the contributions of heterozygotes and homozygotes regarding each SNP.Results: In our comprehensive meta-analysis, 24,075 cases and 22,877 controls from 36 articles were included. We included 16 variants in the meta-analysis and found 12 statistically significant variants with p < 0.05. After narrowing down the variants using the p < 1 × 10−5 cutoff, in overall populations, seven SNPs increased the risk of PD (rs2736990, rs356220, rs356165, rs181489, rs356219, rs11931074, and rs2737029, with odds ratios [ORs] of 1.22–1.38) and one SNP decreased the risk (rs356186, with an OR of 0.77). In the East Asian group, rs2736990 and rs11931074 increased the risk (with ORs of 1.22–1.34). In the European group, five SNPs increased the risk (rs356219, rs181489, rs2737029, rs356165, and rs11931074, with ORs of 1.26–1.37) while one SNP decreased the risk (rs356186, with an OR of 0.77). The heterozygotes and homozygotes contributed differently depending on the variant.Conclusions: In summary, we found eight SNCA SNPs associated with PD risk, which had obvious differences between ethnicities. Seven SNPs increased the risk of PD and one SNP decreased the risk in the overall populations. In the East Asian group, rs2736990 and rs11931074 increased the risk. In the European group, rs356219, rs181489, rs2737029, rs356165, and rs11931074 increased the risk while rs356186 decreased the risk. Variants with the highest ORs and allele frequencies in our analysis should be given priority when carrying out genetic screening

Atrial Fibrillation Follow-up Investigation to Recover Memory and Learning Trial (AFFIRMING): Rationale and Design of a Multi-center, Double-blind, Randomized Controlled Trial

Background: People with atrial fibrillation (AF) have elevated risk of developing cognitive impairment. At present, there is a dearth of randomized controlled trials investigating cognitive impairment management in patients with AF. The Atrial Fibrillation Follow-up Investigation to Recover Memory and learning (AFFIRMING) study is aimed at evaluating the potential for computerized cognitive training to improve cognitive function in patients with AF. Methods: The study is a multi-center, double-blind, randomized controlled study using a 1:1 parallel design. A total of 200 patients with AF and mild cognitive decline without dementia are planned to be recruited. The intervention group will use the adaptive training software with changes in difficulty, whereas the positive control group will use basic training software with minimal or no variation in difficulty level. At the end of 12 weeks, the participants will be unblinded, and the positive control group will stop training. The intervention group will be rerandomized 1:1 to stop training or continue training. All participants will be followed up until 24 weeks. The primary endpoint is the proportion of the improvement of the global cognitive function at week 12 compared with baseline, using the Basic Cognitive Ability Test (BCAT)

Factors Associated With Dyskinesia in Parkinson's Disease in Mainland China

Background and Objectives: Studies examining the risk factors for dyskinesia in Parkinson's disease (PD) have been inconsistent, and racial differences exist. Since there have been no systematic studies of the characteristics of dyskinesia in the Mainland Chinese population, we sought to elucidate the risk factors for dyskinesia.Methods: A total of 1974 PD patients from Mainland China were systematically investigated by univariable and multivariable analyses. PD patients with and without dyskinesia were stratified into 4 groups according to levodopa equivalent daily dose (LEDD) and analyzed by a Cox proportional hazards model. A longitudinal study of 87 patients with dyskinesia was classified into 3 groups according to the duration from onset of PD to the initiation of levodopa, and comparisons among groups were analyzed by the Mann-Whitney test.Results: Early age of onset, long disease duration, being female, high LEDD, low UPDRS III scores (ON-state) and high Hoehn-Yahr stage (ON-state) were predictors of dyskinesia. Dyskinesia was levodopa dosage-dependent, and the incidence increased remarkably when LEDD exceeded 300 mg/d (p < 0.05). The emergence of dyskinesia had no association with the initiation time of levodopa, and if the latter was more than 4 years, the duration of time on chronic levodopa free of motor complications was significantly shortened.Conclusions: We found risk factors for the prediction of dyskinesia. Our data shows that physicians should be cautious if the LEDD exceeds 300 mg/d. The development of dyskinesia was not correlated with the time of levodopa initiation

Preparation and Strength Formation Mechanism of Calcined Oyster Shell, Red Mud, Slag, and Iron Tailing Composite Cemented Paste Backfill

The use of bulk solid-waste iron tailing (IOT), red mud (RM), and oyster shells to prepare cemented paste backfill (CPB) can effectively solve the ecological problems caused by industrial solid waste storage and improve the utilization rate of such materials. In this study, a new type of CPB was prepared by partially replacing slag with RM, with calcined oyster shell (COS) as the alkaline activator and IOT as aggregate. The central composite design (CCD) method was used to design experiments to predict the effects of the COS dosage, RM substitution rate, solid mass, and aggregate–binder ratio using 28-dUCS, slump, and the cost of CPB. In this way, a regression model was established. The quantum genetic algorithm (QGA) was used to optimize the regression model, and X-ray diffraction (XRD), Fourier transform infrared (FTIR), scanning electron microscope (SEM), and energy dispersive spectroscopy (EDS) microscopic tests are performed on CPB samples of different ages with the optimal mix ratio. The results showed that COS is a highly active alkaline substance that provides an alkaline environment for polymerization reactions. In the alkaline medium, the hematite and goethite in RM and quartz in IOT gradually dissolved and participated in the process of polymerization. The main polymerization products of the CPB samples are calcium–silicate–hydrogel (C–S–H), calcium–aluminosilicate–hydrogel (C–A–S–H), and aluminosilicate crystals such as quartz, albite, and foshagite. These products are intertwined and filled in the internal pores of the CPB, enabling the pore contents to decrease and the interiors of the CPB samples to gradually connect into a whole. In this way, the compressive strength is increased

An Individual Prosthesis Control Method with Human Subjective Choices

An intelligent lower-limb prosthesis can provide walking support and convenience for lower-limb amputees. Trajectory planning of prosthesis joints plays an important role in the intelligent prosthetic control system, which directly determines the performance and helps improve comfort when wearing the prosthesis. Due to the differences in physiology and walking habits, humans have their own walking mode that requires the prosthesis to consider the individual’s demands when planning the prosthesis joint trajectories. The human is an integral part of the control loop, whose subjective feeling is important feedback information, as humans can evaluate many indicators that are difficult to quantify and model. In this study, trajectories were built using the phase variable method by normalizing the gait curve to a unified range. The deviations between the optimal trajectory and current were represented using Fourier series expansion. A gait dataset that contains multi-subject kinematics data is used in the experiments to prove the feasibility and effectiveness of this method. In the experiments, we optimized the subjects’ gait trajectories from an average to an individual gait trajectory. By using the individual trajectory planning algorithm, the average gait trajectory can be effectively optimized into a personalized trajectory, which is beneficial for improving walking comfort and safety and bringing the prosthesis closer to intelligence

25,000 fps Computational Ghost Imaging with Ultrafast Structured Illumination

Computational ghost imaging, as an alternative photoelectric imaging technology, uses a single-pixel detector with no spatial resolution to capture information and reconstruct the image of a scene. Due to its essentially temporal measurement manner, improving the image frame rate is always a major concern in the research of computational ghost imaging technology. By taking advantage of the fast switching time of LED, an LED array was developed to provide a structured illumination light source in our work, which significantly improves the structured illumination rate in the computational ghost imaging system. The design of the LED array driver circuit presented in this work makes full use of the LED switching time and achieves a pattern displaying rate of 12.5 MHz. Continuous images with 32 × 32 pixel resolution are reconstructed at a frame rate of 25,000 fps, which is approximately 500 times faster than what a universally used digital micromirror device can achieve. The LED array presented in this work can potentially be applied to other techniques requiring high-speed structured illumination, such as fringe 3D profiling and array-based LIFI

25,000 fps Computational Ghost Imaging with Ultrafast Structured Illumination

Computational ghost imaging, as an alternative photoelectric imaging technology, uses a single-pixel detector with no spatial resolution to capture information and reconstruct the image of a scene. Due to its essentially temporal measurement manner, improving the image frame rate is always a major concern in the research of computational ghost imaging technology. By taking advantage of the fast switching time of LED, an LED array was developed to provide a structured illumination light source in our work, which significantly improves the structured illumination rate in the computational ghost imaging system. The design of the LED array driver circuit presented in this work makes full use of the LED switching time and achieves a pattern displaying rate of 12.5 MHz. Continuous images with 32 × 32 pixel resolution are reconstructed at a frame rate of 25,000 fps, which is approximately 500 times faster than what a universally used digital micromirror device can achieve. The LED array presented in this work can potentially be applied to other techniques requiring high-speed structured illumination, such as fringe 3D profiling and array-based LIFI