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BackgroundPrevious epidemiological studies have reported an association between Sjögren’s syndrome (SS) and Parkinson’s disease (PD); however, the causality and direction of this relationship remain unclear. In this study, we aimed to investigate the causal relationship between genetically determined SS and the risk of PD using bidirectional Mendelian randomization (MR).MethodsSummary statistics for Sjögren’s syndrome used as exposure were obtained from the FinnGen database, comprising 1,290 cases and 213,145 controls. The outcome dataset for PD was derived from the United Kingdom Biobank database, including 6,998 cases and 415,466 controls. Various MR methods, such as inverse variance weighted (IVW), Mendelian randomization Egger regression (MR-Egger), weighted median (WM), simple mode, weighted mode, MR-pleiotropy residual sum and outlier (MR-PRESSO), and robust adjusted profile score (RAPS), were employed to investigate the causal effects of SS on PD. Instrumental variable strength evaluation and sensitivity analyses were conducted to ensure the reliability of the results. In addition, reverse MR analysis was performed to examine the causal effects of PD on SS.ResultsThe WM, IVW, RAPS and MR-PRESSO methods demonstrated a significant association between genetically predicted SS and reduced risk of PD (odds ratio ORWM = 0.9988, ORIVW = 0.9987, ORRAPS = 0.9987, ORMR-PRESSO = 0.9987, respectively, P < 0.05). None of the MR analyses showed evidence of horizontal pleiotropy (P > 0.05) based on the MR-Egger and MR-PRESSO tests, and there was no statistical heterogeneity in the test results of the MR-Egger and IVW methods. The leave-one-out sensitivity analysis confirmed the robustness of the causal relationship between SS and PD. Furthermore, reverse MR analysis did not support any causal effects of PD on SS.ConclusionOur MR study supports a potential causal association between SS and a reduced risk of PD. Further extensive clinical investigations and comprehensive fundamental research are warranted to elucidate the underlying mechanisms linking SS and PD.

IntroductionParkinson’s disease (PD) is the second most common neurodegenerative disease and affects millions of people. Accurate diagnosis and subsequent treatment in the early stages can slow down disease progression. However, making an accurate diagnosis of PD at an early stage is challenging. Previous studies have revealed that even for movement disorder specialists, it was difficult to differentiate patients with PD from healthy individuals until the average modified Hoehn-Yahr staging (mH&Y) reached 1.8. Recent researches have shown that dysarthria provides good indicators for computer-assisted diagnosis of patients with PD. However, few studies have focused on diagnosing patients with PD in the early stages, specifically those with mH&Y ≤ 1.5.MethodWe used a machine learning algorithm to analyze voice features and developed diagnostic models for differentiating between healthy controls (HCs) and patients with PD, and for differentiating between HCs and patients with mild PD (mH&Y ≤ 1.5). The models were independently validated using separate datasets.ResultsOur results demonstrate that, a remarkable diagnostic performance of the model in identifying patients with mild PD (mH&Y ≤ 1.5) and HCs, with area under the ROC curve 0.93 (95% CI: 0.851.00), accuracy 0.85, sensitivity 0.95, and specificity 0.75.ConclusionThe results of our study are helpful for screening PD in the early stages in the community and primary medical institutions where there is a lack of movement disorder specialists and special equipment.

BackgroundCognitive impairment is a prevalent condition that substantially elevates mortality rates among the elderly. The impact of hypertension on mortality in older adults with cognitive impairment is a subject of contention. This study aims to examine the influence of hypertension on both all-cause and CVD-specific mortality in elderly individuals experiencing cognitive impairment within a prospective cohort.MethodsThis study encompassed 2,925 participants (weighted 53,086,905) aged 60 years or older from National Health and Nutrition Examination Survey (NHANES) spanning 2011–2014. Incidence of all-cause and CVD-specific mortality was ascertained through linkage with National Death Index records until 31 December 2019. Survival was performed employing the Kaplan–Meier method. Hazard ratios (HRs) were calculated via Cox proportional hazards regression models.ResultsOver the follow-up period of up to 9.17 years [with a median (IQR) time to death of 6.58 years], equivalent to 18,731.56 (weighted 3.46 × 108) person-years, there were a total of 576 recorded deaths. Participants with CI exhibited a 1.96-fold higher risk of all-cause mortality (95% CI: 1.55–2.49; p

Myotonia congenita (MC) is a rare genetic disease caused by mutations in the skeletal muscle chloride channel gene (CLCN1), encoding the voltage-gated chloride channel ClC-1 in skeletal muscle. Our study reported the clinical and molecular characteristics of six patients with MC and systematically review the literature on Chinese people. We retrospectively analyzed demographics, clinical features, family history, creatine kinase (CK), electromyography (EMG), treatment, and genotype data of our patients and reviewed the clinical data and CLCN1 mutations in literature. The median ages at examination and onset were 26.5 years (range 11–50 years) and 6.5 years (range 1.5–11 years), respectively, in our patients, and 21 years (range 3.5–65 years, n = 45) and 9 years (range 0.5–26 years, n = 50), respectively, in literature. Similar to previous reports, myotonia involved limb, lids, masticatory, and trunk muscles to varying degrees. Warm-up phenomenon (5/6), percussion myotonia (3/5), and grip myotonia (6/6) were common. Menstruation triggered myotonia in females, not observed in Chinese patients before. The proportion of abnormal CK levels (4/5) was higher than data from literature. Electromyography performed in six patients revealed myotonic changes (100%). Five novel CLCN1 mutations, including a splicing mutation (c.853 + 4A>G), a deletion mutation (c.2010_2014del), and three missense mutations (c.2527C>T, c.1727C>T, c.2017 G > C), were identified. The c.892 G > A (p.A298T) mutation was the most frequent mutation in the Chinese population. Our study expanded the clinical and genetic spectrum of patients with MC in the China. The MC phenotype in Chinese people is not different from that found in the West, while the genotype is different.

Abstract Background and objective Zishen Pingchan granule (ZPG), a traditional Chinese herbal recipe for treating Parkinson’s disease (PD), is usually used as an add-on drug with some antiparkinsonian drugs in China. The objectives of this study were to evaluate the efficacy, safety, and tolerability of ZPG combined with pramipexole in the treatment of depression in PD (dPD). Methods A 12-week, multicenter, randomized, double-blind, and placebo-controlled study on ZPG was performed on a total of 200 patients who were treated with pramipexole but still had mild to moderate depressive symptoms. Patients were randomly divided into ZPG (n = 100) or placebo (n = 100). The primary effective result was the mean change from the baseline on the Hamilton Depression Scale 17 items (HAM-D-17) over 12 weeks and the clinical efficacy rate. Secondary endpoints were the mean change from the baseline in the Geriatric Depression Scale (GDS-15), Unified Parkinson's disease rating scale Part III (UPDRS III), Parkinson's quality of life scale (PDQ-8), and Parkinson's disease sleep scale (PDSS-2) over 12 weeks. Results After 12 weeks of treatment, ZPG significantly reduced the mean [95% confidence interval] HAMD score vs. placebo (− 1.43 scores [− 2.50, − 0.36]; p = 0.009). The clinical remission rate and responders of the ZPG group were higher than those of the placebo (46.1% vs. 31.0%; p = 0.041; 34.8% vs. 18.4%; p = 0.014). A significant improvement in the PDSS-2 score was also observed in the ZPG group compared with that in the placebo group (− 3.56 scores [− 5.77, − 1.35]; p = 0.002). A total of 7 patients (7.1%) in the ZPG group had mild adverse events (AEs) vs 9 patients (9%) in the placebo group. No severe AEs were observed in either group. The randomization and controlled clinical study revealed that ZPG was effective, safe, and well-tolerated. Conclusion ZPG combined with pramipexole further reduced the depressive symptoms and improved the sleeping quality of PD patients. Trial registration The protocol was retrospectively registered at the Chinese Clinical Trial Registry, Unique identifier: ChiCTR1800019942, date of registration: December 9, 2018; http://www.chictr.org.cn/showproj.aspx?proj=30432

Abstract The ketogenic diet (KD) is a low‐carbohydrate, high‐fat regime that is protective against neurodegenerative diseases. However, the impact of KD on Parkinson's disease (PD) and its mechanisms remains unclear. 1‐Methyl‐4‐phenyl‐1,2,3,6‐tetrahydropyridine (MPTP)‐induced mouse model of PD was fed with KD for 8 weeks. Motor function and dopaminergic neurons were evaluated. Inflammation in the brain, plasma, and colon tissue were also measured. Fecal samples were assessed by 16S rDNA gene sequencing and untargeted metabolomics. We found that KD protected motor dysfunction, dopaminergic neuron loss, and inflammation in an MPTP mouse model of PD. 16S rDNA sequencing revealed that MPTP administration significantly increased Citrobacter, Desulfovibrio, and Ruminococcus, and decreased Dubosiella, whereas KD treatment reversed the dysbiosis. Meanwhile, KD regulated the MPTP‐induced histamine, N‐acetylputrescine, d‐aspartic acid, and other metabolites. Fecal microbiota transplantation using feces from the KD‐treated mice attenuated the motor function impairment and dopaminergic neuron loss in antibiotic‐pretreated PD mice. Our current study demonstrates that KD played a neuroprotective role in the MPTP mouse model of PD through the diet–gut microbiota–brain axis, which may involve inflammation in the brain and colon. However, future research is warranted to explore the explicit anti‐inflammatory mechanisms of the gut–brain axis in PD models fed with KD.

We report on studying tunnel junctions and an optical cavity structure for developing epitaxially-stacked high-efficiency 905 nm high-power laser diodes. The GaAs tunnel junctions were explored via simulations and experiments to realize a high peak current density of 7.7 × 104 A/cm2 and a low specific resistance of 1.5 × 10−5 Ωcm2 with a high n-doping concentration of 6 × 1019 cm−3. Employing a low-loss epitaxial structure design, single-, double-, and triple-cavity structure laser diodes demonstrated power scaling by epitaxial stacking. Triple-cavity laser diodes have a low optical loss (0.42 cm−1) and generate a peak power of 83 W with a short cavity length of 750 μm at a limited current of 30 A.

We report on the development of a 940-nm diode laser bar based on epitaxially stacked active regions by employing a tunnel junction structure. The tunnel junction and the device parameters were systematically optimized to achieve high output and power conversion efficiency. A record quasi-continuous wave (QCW) peak power of 1.91 kW at 25 °C was demonstrated from a 1-cm wide bar with a 2-mm cavity length at 1 kA drive current (200 μs pulse width and 10 Hz repetition rate). Below the onset of the thermal rollover, the slope efficiency was as high as 2.23 W/A. The maximum power conversion efficiency of 61.1% at 25 °C was measured at 300 A. Reducing the heatsink temperature to 15 °C led to a marginal increase in the peak power to 1.95 kW.

High-power, broad-area, semiconductor lasers are attractive sources for material processing, aerospace, and laser pumping. The design of the active region is crucial to achieve the required high power and electro-optical conversion efficiency, since the temperature significantly affects the performance of the quantum well, including the internal quantum efficiency and mode gain. In this work, the temperature effects on the active region of a 808 nm high-power semiconductor laser were investigated theoretically and experimentally. The simulations were performed with a Quasi-3D model, which involved complete steady-state semiconductor and carrier confinement efficiency combined with a new mathematical method. The critical aluminum content of the quantum barrier was proposed and the relationship between temperature and various loss sources was disclosed in the temperature range of 213 to 333 K, which provides a reliable reference for the design of epitaxial structures of high-power semiconductor lasers in different operating conditions. Subsequently, the optimized epitaxial structure was determined and used to fabricate standard laser bar chips with a cavity length of 2 mm. The experimental electro-optical conversion efficiency of 71% was demonstrated with a slope efficiency of 1.34 W/A and an injection current of 600 A at the heatsink temperature of 223 K. A record high electro-optical conversion efficiency of 73.5% was reached at the injection current of 400 A, while the carrier confinement efficiency was as high as 98%.

Parkinson’s disease (PD) is a common neurodegenerative disease, and the mechanism underlying PD pathogenesis is not completely understood. Increasing evidence indicates that microRNAs (miRNAs) play a critical regulatory role in the pathogenesis of PD. This study aimed to explore the miRNA-mRNA regulatory network for PD. The differentially expressed miRNAs (DEmis) and genes (DEGs) between PD patients and healthy donors were screened from the miRNA dataset GSE16658 and mRNA dataset GSE100054 downloaded from the Gene Expression Omnibus (GEO) database. Target genes of the DEmis were selected when they were predicted by three or four online databases and overlapped with DEGs from GSE100054. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis were then conducted by Database for Annotation, Visualization and Integrated Discovery (DAVID) and Metascape analytic tools. The correlation between the screened genes and PD was evaluated with the online tool Comparative Toxicogenomics Database (CTD), and protein-protein interaction (PPI) networks were built by the STRING platform. We further investigated the expression of genes in the miRNA-mRNA regulatory network in blood samples collected from PD patients and healthy donors via qRT-PCR. We identified 1505 upregulated and 1302 downregulated DEGs, and 77 upregulated and 112 downregulated DEmis were preliminarily screened from the GEO database. Further functional enrichment analysis identified 10 PD-related hub genes, including RAC1, IRS2, LEPR, PPARGC1A, CAMKK2, RAB10, RAB13, RAB27B, RAB11A, and JAK2, which were mainly involved in Rab protein signaling transduction, AMPK signaling pathway, and signaling by Leptin. A miRNA-mRNA regulatory network was then constructed with 10 hub genes, and their interacting miRNAs overlapped with DEmis, including miR-30e-5p, miR-142-3p, miR-101-3p, miR-32-3p, miR-508-5p, miR-642a-5p, miR-19a-3p, and miR-21-5p. Analysis of clinical samples verified significant upregulation of LEPR and downregulation of miR-101-3p and miR-30e-5p in PD patients as compared with healthy donors. Thus, the miRNA-mRNA regulatory network was initially constructed and has the potential to provide novel insights into the pathogenesis and treatment of PD.

Objective. To investigate the utility of AD8 for cognitive impairment in a Chinese physical examination population. Methods. Military cadres who took routine physical examination in Chinese PLA General Hospital from Jan 1, 2013, to Dec 31, 2013, were subjected to AD8 scale. Individual information such as age, gender, and education was also collected. All data were analyzed by SPSS 19.0. Results. 1544 subjects were enrolled in this study with mean age 75.4 ± 10.6 years. The subjects who scored 0 to 8 of AD8 scale were 1015, 269, 120, 60, 30, 14, 19, 8, and 9, respectively. Corresponding proportions were 65.7%, 17.4%, 7.8%, 3.9%, 2.0%, 0.9%, 1.2%, 0.5%, and 0.6%, respectively. The endorsement prevalence of 8 questions was 5.6%, 9.2%, 6.6%, 9.2%, 4.8%, 4.5%, 8.9%, and 24.1%, respectively. The endorsement prevalence of question 8 was significantly higher than others (P

Cerebral microbleeds (CMBs) and white matter hyperintensities (WMH) are the most common manifestations of small vessel disease, and often co-occur in patients with cerebral vascular disease. Hypertension is widely accepted as a risk factor for both CMBs and WMH. However, the effect of hypertension on the association between CMBs and WMH remains unclear. We hypothesized that the relationship between CMBs and WMH is determined by hypertension. One hundred forty-eight patients with acute cerebrovascular disease who were admitted to PLA general hospital in Beijing, China from February 2010 to May 2011 were recruited in this study. CMBs on T2*-weighted angiography (SWAN) were assessed using the Brain Observer Microbleed Rating Scale criteria. The severity of the WMH was separately assessed as either peri-ventricular hyperintensities (PVH) or deep white matter hyperintensities (DWMH). The association among CMBs and the severity of WMH, and hypertension were determined. CMBs were found in 65 (43.9%) patients. The frequency of CMBs was related to the severity of DWMH and PVH. CMBs were more frequently observed in patients with hypertension compared to patients without hypertension (51.3% vs. 20.0%, p = 0.001). Hypertension was an independent risk factor for CMBs (odds ratio 5.239, p = 0.001) and DWMH (odds ratio 2.373, p = 0.040). Furthermore, the relationship between the presence of CMBs and the severity of DWMH was only found in patients with hypertension (r = 0.298, p