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Introduction: Glucosylceramidase beta 1 (GBA1) mutations are a genetic risk factor for Parkinson's disease (PD), though most carriers do not develop the disease. This study aimed to identify exposure factors linked to PD in GBA1 carriers and assess clinical features and the probability of prodromal PD in non-manifesting carriers., Methods: Data from the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China was used, including 59 GBA1 non-manifesting carriers, 62 controls, and 107 GBA1-associated PD, of whom 81 were in the early stage. Exposure factors included pesticide/solvent exposure, smoking, alcohol, and tea consumption. Logistic regression assessed the association between exposure factors and PD. Clinical characteristics were evaluated using multiple scales, relevant markers were collected based on the Movement Disorders Society criteria. A naive Bayesian classifier method determined the probability of prodromal PD in GBA1 non-manifesting carriers and controls., Results: After adjusting for sociodemographic variables, pesticide/solvent exposure was positively associated with PD in GBA1 carriers (OR 8.40; 95 % CI 2.50-28.20), while smoking was inversely associated with PD (OR 0.18; 95 % CI 0.05-0.62). Rapid eye movement sleep behavior disorder, constipation, hyposmia, and cognitive deficits were more severe in early-stage GBA1-associated PD than in carriers and controls. Clinical symptoms and the probability of prodromal PD were similar between carriers and controls., Conclusions: PD in GBA1 carriers is closely linked to exposure factors. Early-stage GBA1-associated PD shows significant prodromal symptoms, which are not evident in carriers. The probability of prodromal PD in carriers is similar to that in controls., Competing Interests: Declaration of competing interest The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article., (Copyright © 2024. Published by Elsevier Ltd.)

Objectives: Parkinson's disease (PD) is a complex neurodegenerative disease with unclear pathogenesis. Some recent studies have shown that there is a close relationship between PD and ferroptosis. We aimed to identify the ferroptosis-related genes (FRGs) and construct competing endogenous RNA (ceRNA) networks to further assess the pathogenesis of PD., Methods: Expression of 97 substantia nigra (SN) samples were obtained and intersected with FRGs. Bioinformatics analysis, including the gene set enrichment analysis (GSEA), consensus cluster analysis, weight gene co-expression network analysis (WGCNA), and machine learning algorithms, were employed to assess the feasible differentially expressed genes (DEGs). Characteristic signature genes were used to create novel diagnostic models and construct competing endogenous RNA (ceRNA) regulatory network for PD, which were further verified by in vitro experiments and single-cell RNA sequencing (scRNA-seq)., Results: A total of 453 DEGs were identified and 11 FRGs were selected. We sorted the entire PD cohort into two subtypes based on the FRGs and obtained 67 hub genes. According to the five machine algorithms, 4 features (S100A2, GNGT1, NEUROD4, FCN2) were screened and used to create a PD diagnostic model. Corresponding miRNAs and lncRNAs were predicted to construct a ceRNA network. The scRNA-seq and experimental results showed that the signature model had a certain diagnostic effect and lncRNA NEAT1 might regulate the progression of ferroptosis in PD via the NEAT1/miR-26b-5p/S100A2 axis., Conclusion: The diagnostic signatures based on the four FRGs had certain diagnostic and individual effects. NEAT1/miR-26b-5p/S100A2 axis is associated with ferroptosis in the pathogenesis of PD. Our findings provide new solutions for treating PD., Competing Interests: The authors declare that there are no competing interests associated with the manuscript., (Copyright: © 2024 Li, Guo. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

This study examines the efficacy and environmental impact of peracetic acid (PAA) activated by thermally modified activated carbon (AC600) for degrading antibiotics in actual groundwater. Laboratory-scale experiments evaluated the system's effects on contaminant degradation, ecological balance, and substance cycling in the hyporheic zone. Our findings demonstrated the effectiveness of the AC600/PAA system in removing sulfamethoxazole (SMX) from groundwater porous media. Additionally, the AC600/PAA system synergistically interacted with the in-situ microbiota of the hyporheic zone, producing more fragmented degradation products without increasing mixed toxicity. Bacterial abundance increased post-reaction, with notable alterations in the bacterial community and enhanced bacterial metabolism. Key genera such as Lysobacter thrived in the treated environment, playing critical roles in microbiota modification and SMX degradation. The pH remained stable before and after the reaction, while dissolved organic carbon content increased. Overall, our results highlight the promising potential of PAA activation by carbonaceous materials as a low-impact, ecologically friendly technology for in-situ remediation of organic pollutants in groundwater, characterized by high compatibility and biosynthesis., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Objective: We established a prospective cohort study to investigate the differences in motor and non-motor symptoms between idiopathic Parkinson's disease (IPD) and Parkinson's disease in carriers of leucine-rich repeat kinase 2 (LRRK2) gene risk variants (LRRK2-PD)., Methods: The study included 1407 individuals with IPD and 649 individuals with LRRK2-PD (comprising 304 with LRRK2-G2385R, 220 with LRRK2-R1628P, and 105 with LRRK2-A419V). Differences in symptoms between LRRK2-PD and IPD were analyzed using LCMM modeling and Cox regression analysis., Results: The LRRK2-G2385R variant showed slower progression in tremor symptoms and excessive daytime sleepiness compared with IPD. In contrast, symptoms associated with LRRK2-R1628P and LRRK2-A419V were more similar to those of IPD. Survival analysis revealed that LRRK2-PD does not affect life expectancy compared with IPD., Interpretation: Our extended longitudinal follow-up of LRRK2-PD in the Chinese population provided valuable insights, further confirming the clinical characteristics of the three LRRK2 variants., (© 2024 The Author(s). Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Aim: To evaluate the efficacy of ultrasound-guided ilioinguinal and iliohypogastric nerve block (IIHB) in children undergoing surgery for inguinal hernias., Material and Methods: PubMed, Embase, Cochrane Library, and Web of Science databases were searched to January 4, 2024. For continuous data, the effect sizes were presented as weighted mean differences (WMDs), and for categorical data, they were reported as relative ratios (RR), each accompanied by 95% confidence intervals (CIs)., Results: IIHB demonstrated a longer duration before the need for the first analgesic compared to transverse abdominis plane (TAP), caudal epidural block (CEB), and pre-incisional wound infiltration (PWI), but a shorter duration than quadratus lumborum block (QLB). The IIHB group had a higher probability of requiring rescue analgesics compared to other blocks or PWI (RR: 1.69, 95% CI: 1.25 to 2.28, p=0.001). Higher FLACC scores were noted at 12 hours for the IIHB group (WMD:0.50, 95% CI: 0.13 to 0.86, p=0.008). IIHB required more intraoperative fentanyl compared to controls (RR: 2.14, 95% CI:1.17 to 3.92, p=0.014)., Conclusion: While IIHB may have some benefits, it does not appear to be more effective overall in managing postoperative pain in pediatric inguinal hernia surgery patients compared to other blocks or PWI.

This study aimed to investigate the effects of different voltage and aeration conditions on catering wastewater treatment and membrane fouling in a novel annular electric field membrane bioreactor (AEMBR). The results indicated that the synergistic effect of annular electric field and aeration promoted the degradation of wastewater and the alleviation of membrane fouling. The treatment effect was optimal under a micro electric field of 0.5 V, with removal rates for COD, NH 4 + -N, TP, and oil ranging from 96.85% to 99.36%, 80.43%-83.01%, 95.46%-97.79%, and 98.83%-99.15%, respectively. Additionally, the fluorescence intensity of macromolecular proteins and small molecular acids decreased. Simultaneously, the average growth rate of transmembrane pressure (TMP) reduced by approximately 0.4 kPa/d. The species abundance and diversity of activated sludge increased, promoting the growth of dominant bacteria, all while maintaining low energy consumption. The aeration intensity had relatively little impact on system operation, and the force of the annular electric field was greater than the force of aeration. This study verified the optimal benefits under micro electric field conditions and provided a basis for the optimization of future process design to achieve a more efficient and economical wastewater treatment system., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Broad learning system (BLS) with semi-supervised learning relieves label dependence and expands application. Despite some efforts and progress, the semi-supervised BLS still needs improvement, especially in handling imbalanced data or concept drift scenarios for self-training-based methods. To this extent, this article proposes a robust semi-supervised BLS guided by ensemble-based self-training (ESTSS-BLS). Distinctive to self-training that assigns the pseudo-label via a single classifier and confidence, the advocated ensemble-based self-training determines the pseudo-label according to the turnout of multiple BLSs. In addition, label purity is proposed to ensure the correctness and credibility of the auxiliary training data, which is a comprehensive evaluation of the voting. During iterative learning, a small portion of labeled data first trains multiple BLSs in parallel. Then, the system recursively updates its data, structure, and meta-parameters using label purity and a data-driven dynamic nodes mechanism that dynamically guides the network's structural adjustments to solve the concept drift problem caused by a large amount of auxiliary training data. The experimental results demonstrate that ESTSS-BLS exhibits exceptional performance compared to existing methods, with the lowest-time consumption and the highest accuracy, precision, recall, F1 score, and AUC. Exhilaratingly, it achieves an accuracy of 87.84% with only 0.1% labeled data on MNIST, and with just 2% labeled data, it matches the performance of supervised learning using all training data on NORB. In addition, ESTSS-BLS also performs stably on medical or biological data, verifying its high adaptability.

Unmanned aerial vehicles (UAVs) have been widely used in urban target-tracking tasks, where long-term tracking of evasive targets is of great significance for public safety. However, the tracked targets are easily lost due to the evasive behavior of the targets and the unstructured characteristics of the urban environment. To address this issue, this article proposes a hybrid target-tracking approach based on target intention inference and deep reinforcement learning (DRL). First, a target intention inference model based on convolution neural networks (CNNs) is built to infer target intentions by fusing urban environment information and observed target trajectory. Then, the prediction of the target trajectory can be inspired by the inferred target intentions, which can further provide effective guidance to the target search process. In order to fully explore the policy space, the target search policy is developed under a DRL framework, where the search policy is modeled as a deep neural network (DNN) and trained by interacting with the task environment. The simulation results show that the inference of the target intentions can effectively guide the UAV to search for the target and significantly improve the target-tracking performance. Meanwhile, the generalization results indicate that the proposed DRL-based search policy has high robustness to the uncertainty of the target behavior.

Background: Parkinson's disease (PD) is a neurodegenerative disease caused by a combination of aging, environmental, and genetic factors. Previous research has implicated both causative and susceptibility genes in PD development. Nogo-A, a neurite outgrowth inhibitor, has been shown to impact axon growth through ligand-receptor interactions negatively, thereby involved in the deterioration of dopaminergic neurons. However, rare genetic studies have identified the relationship between neurite outgrowth inhibitor (Nogo)-associated genes and PD from a signaling pathway perspective., Methods: We enrolled 3959 PD patients and 2931 healthy controls, categorized into two cohorts based on their family history and age at onset: sporadic early Parkinson's disease & familial Parkinson's disease (sEOPD & FPD) cohort and sporadic late Parkinson's disease (sLOPD) cohort. We selected 17 Nogo-associated genes and stratified them into three groups via their function, respectively, ligand, receptors, and signaling pathway groups. Additionally, we conducted the burden analysis in rare variants, the logistic regression analysis in common variants, and the genotype-phenotype association analysis. Last, bioinformatics analysis and functional experiments were conducted to identify the role of the MTOR gene in PD., Results: Our findings demonstrated that the missense variants in the MTOR gene might increase PD risk, while the deleterious variants in the receptor subtype of Nogo-associated genes might mitigate PD risk. However, common variants of Nogo-associated genes showed no association with PD development in two cohorts. Furthermore, genotype-phenotype association analysis suggested that PD patients with MTOR gene variants exhibited relatively milder motor symptoms but were more susceptible developing dyskinesia. Additionally, bioinformatics analysis results showed MTOR gene was significantly decreased in PD, indicating a potential negative role of the mTOR in PD pathogenesis. Experimental data further demonstrated that MHY1485, a mTOR agonist, could rescue MPP + -induced axon inhibition, further implicating the involvement of mTOR protein in PD by regulating cell growth and axon growth., Conclusions: Our preliminary investigation highlights the association of Nogo-associated genes with PD onset in the Chinese mainland population and hints at the potential role of the MTOR gene in PD. Further research is warranted to elucidate the mechanistic pathways underlying these associations and their therapeutic implications., (© 2024 The Author(s). CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Parkinson's disease (PD) is the second most common neurodegenerative disease. The development of PD is closely linked to genetic and environmental factors, with GBA1 variants being the most common genetic risk. Mutations in the GBA1 gene lead to reduced activity of the coded enzyme, glucocerebrosidase, which mediates the development of PD by affecting lipid metabolism (especially sphingolipids), lysosomal autophagy, endoplasmic reticulum, as well as mitochondrial and other cellular functions. Clinically, PD with GBA1 mutations (GBA1-PD) is characterized by particular features regarding the progression of symptom severity. On the therapeutic side, the discovery of the relationship between GBA1 variants and PD offers an opportunity for targeted therapeutic interventions. In this review, we explore the genotypic and phenotypic correlations, etiologic mechanisms, biomarkers, and therapeutic approaches of GBA1-PD and summarize the current state of research and its challenges., (© 2024. The Author(s).)

There is an obvious clinical-pathological overlap between essential tremor and some known tremor-associated short tandem repeat expansion disorders. The aim is to analyse whether these short tandem repeat genes, including ATXN1 , ATXN2 , ATXN3 , CACNA1A , ATXN7 , ATXN8OS , ATXN10 , PPP2R2B , TBP , BEAN1 , NOP56 , DAB1 , ATN1 , SADM12 and FMR1 , are associated with familial essential tremor patients. Genetic analysis of repeat sizes in tremor-associated short tandem repeat expansions was performed in a large cohort of 515 familial essential tremor probands and 300 controls. The demographic and clinical features among carriers of pathogenic expansions, intermediate repeats and non-carriers were compared. A total of 18 out of 515 (18/515, 3.7%) patients were found to have repeats expansions, including 12 cases (12/515, 2.5%) with intermediate repeat expansions (one ATXN1 , eight TBP , two FMR1 , one ATN1 ), and six cases (6/515, 1.2%) with pathogenic expansions (one ATXN1 , one ATXN2 , one ATXN8OS , one PPP2R2B , one FMR1 , one SAMD12 ). There were no statistically significant differences in intermediate repeats compared to healthy controls. Furthermore, there were no significant differences in demographics and clinical features among individuals with pathogenic expansions, intermediate repeat expansions carriers and non-carriers. Our study indicates that the intermediate repeat expansion in tremor-associated short tandem repeat expansions does not pose an increased risk for essential tremor, and rare pathogenic expansion carriers have been found in the familial essential tremor cohort. The diagnosis of essential tremor based solely on clinical symptoms remains a challenge in distinguishing it from known short tandem repeat expansions diseases with overlapping clinical-pathological features., Competing Interests: The authors report no competing interests., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Guarantors of Brain.)

The broad learning system (BLS) has recently been applied in numerous fields. However, it is mainly a supervised learning system and thus not suitable for specific practical applications with a mixture of labeled and unlabeled data. Despite a manifold regularization-based semi-supervised BLS, its performance still requires improvement, because its assumption is not always applicable. Therefore, this article proposes an incremental-self-training-guided semi-supervised BLS (ISTSS-BLS). Distinctive to traditional self-training, where all unlabeled data are labeled simultaneously, incremental self-training (IST) obtains unlabeled data incrementally from an established sorted list based on the distance between the data and their cluster center. During iterative learning, a small portion of labeled data is first used to train BLS. The system recursively self-updates its structure and meta-parameters using: 1) the double-restricted mechanism and 2) the dynamic neuron-incremental mechanism. The double-restricted mechanism is beneficial to preventing the introduction of incorrect pseudo-labeled samples, and the dynamic neuron-incremental mechanism guides the self-updating of the network structure effectively based on the training accuracy of the labeled data. These strategies guarantee a parsimonious model during the update. Besides, a novel metric, the accuracy-time ratio (A/T), is proposed to evaluate the model's performance comprehensively regarding time and accuracy. In experimental verifications, ISTSS-BLS performs outstandingly on 11 datasets. Specifically, the IST is compared with the traditional one on three scales data, saving up to 52.02% learning time. In addition, ISTSS-BLS is compared with different state-of-the-art alternatives, and all results indicate that it possesses significant advantages in performance.

The traditional diagnostic process for autism spectrum disorder (ASD) is subjective, where early and accurate diagnosis significantly affects treatment outcomes and life quality. Thus, improving ASD diagnostic methods is critical. This paper proposes ASD-SWNet, a new shared-weight feature extraction and classification network. It resolves the issue found in previous studies of inefficiently integrating unsupervised and supervised learning, thereby enhancing diagnostic precision. The approach utilizes functional magnetic resonance imaging to improve diagnostic accuracy, featuring an autoencoder (AE) with Gaussian noise for robust feature extraction and a tailored convolutional neural network (CNN) for classification. The shared-weight mechanism utilizes features learned by the AE to initialize the convolutional layer weights of the CNN, thereby integrating AE and CNN for joint training. A novel data augmentation strategy for time-series medical data is also introduced, tackling the problem of small sample sizes. Tested on the ABIDE-I dataset through nested ten-fold cross-validation, the method achieved an accuracy of 76.52% and an AUC of 0.81. This approach surpasses existing methods, showing significant enhancements in diagnostic accuracy and robustness. The contribution of this paper lies not only in proposing new methods for ASD diagnosis but also in offering new approaches for other neurological brain diseases., (© 2024. The Author(s).)

To clarify the genetic role of phospholipase A2 (PLA2) genes in Parkinson's disease (PD), we performed a genetic association study in large Chinese population cohorts using next-generation sequencing. In this study, we analyzed both rare and common variants of 38 phospholipase A2 genes in two large cohorts. We detected 1558 and 1115 rare variants in these two cohorts, respectively. In both cohorts, we observed suggestive associations between specific subgroups and the risk of PD. At the single-gene level, several genes (PLA2G2D, PLA2G12A, PLA2G12B, PLA2G4F, PNPLA1, PNPLA3, PNPLA7, PLA2G7, PLA2G15, PLAAT5, and ABHD12) are suggestively associated with PD. Meanwhile, 364 and 2261 common variants were identified in two cohorts, respectively. Our study has expanded the genetic spectrum of the PLA2 family genes and suggested potential pathogenetic roles of PLA2 superfamily in PD., Competing Interests: Declaration of Competing Interest The authors declare no conflicts of interest., (Copyright © 2024. Published by Elsevier B.V.)

Due to its marvelous performance and remarkable scalability, a broad learning system (BLS) has aroused a wide range of attention. However, its incremental learning suffers from low accuracy and long training time, especially when dealing with unstable data streams, making it difficult to apply in real-world scenarios. To overcome these issues and enrich its relevant research, a robust incremental BLS (RI-BLS) is proposed. In this method, the proposed weight update strategy introduces two memory matrices to store the learned information, thus the computational procedure of ridge regression is decomposed, resulting in precomputed ridge regression. During incremental learning, RI-BLS updates two memory matrices and renews weights via precomputed ridge regression efficiently. In addition, this update strategy is theoretically analyzed in error, time complexity, and space complexity compared with existing incremental BLSs. Different from Greville's method used in the original incremental BLS, its results are closer to the solution of one-shot calculation. Compared with the existing incremental BLSs, the proposed method exhibits more stable time complexity and superior space complexity. The experiments prove that RI-BLS outperforms other incremental BLSs when handling both stable and unstable data streams. Furthermore, experiments demonstrate that the proposed weight update strategy applies to other random neural networks as well.

Background: Parkinson's disease (PD) and Essential tremor (ET) are the two most common tremor diseases with recognized genetic pathogenesis. The overlapping clinical features suggest they may share genetic predispositions. Our previous study systematically investigated the association between rare coding variants in ET-associated genes and early-onset PD (EOPD), and found the suggestive association between teneurin transmembrane protein 4 ( TENM4 ) and EOPD. In the current research, we explored the potential genetic interplay between ET-associated genetic loci/genes and sporadic late-onset PD (LOPD)., Methods: We performed whole-genome sequencing in the 1962 sporadic LOPD cases and 1279 controls from mainland China. We first used logistic regression analysis to test the top 16 SNPs identified by the ET genome-wide association study for the association between ET and LOPD. Then we applied the optimized sequence kernel association testing to explore the rare variant burden of 33 ET-associated genes in this cohort., Results: We did not observe a significant association between the included SNPs with LOPD. We also did not discover a significant burden of rare deleterious variants of ET-associated genes in association with LOPD risk., Conclusion: Our results do not support the role of ET-associated genetic loci and variants in LOPD., Highlights: 1962 cases and 1279 controls were recruited to study the potential genetic interplay between ET-associated genetic loci/variants and sporadic LOPD.No significant association between the ET-associated SNPs and LOPD were observed.No significant burden of rare deleterious variants of ET-associated gene in LOPD risk were found., Competing Interests: The authors have no competing interests to declare., (Copyright: © 2024 The Author(s).)

Background: An intronic GAA repeat expansion in FGF14 was recently identified as a cause of GAA-FGF14 ataxia. We aimed to characterise the frequency and phenotypic profile of GAA-FGF14 ataxia in a large Chinese ataxia cohort., Methods: A total of 1216 patients that included 399 typical late-onset cerebellar ataxia (LOCA), 290 early-onset cerebellar ataxia (EOCA), and 527 multiple system atrophy with predominant cerebellar ataxia (MSA-c) were enrolled. Long-range and repeat-primed PCR were performed to screen for GAA expansions in FGF14. Targeted long-read and whole-genome sequencing were performed to determine repeat size and sequence configuration. A multi-modal study including clinical assessment, MRI, and neurofilament light chain was conducted for disease assessment., Findings: 17 GAA-FGF14 positive patients with a (GAA) ≥250 expansion (12 patients with a GAA-pure expansion, five patients with a (GAA) ≥250 -[(GAA) n (GCA) m ] z expansion) and two possible patients with biallelic (GAA) 202/222 alleles were identified. The clinical phenotypes of the 19 positive and possible positive cases covered LOCA phenotype, EOCA phenotype and MSA-c phenotype. Five of six patients with EOCA phenotype were found to have another genetic disorder. The NfL levels of patients with EOCA and MSA-c phenotypes were significantly higher than patients with LOCA phenotype and age-matched controls (p < 0.001). NfL levels of pre-ataxic GAA-FGF14 positive individuals were lower than pre-ataxic SCA3 (p < 0.001) and similar to controls., Interpretation: The frequency of GAA-FGF14 expansion in a large Chinese LOCA cohort was low (1.3%). Biallelic (GAA) 202/222 alleles and co-occurrence with other acquired or hereditary diseases may contribute to phenotypic variation and different progression., Funding: This study was funded by the National Key R&D Program of China (2021YFA0805200 to H.J.), the National Natural Science Foundation of China (81974176 and 82171254 to H.J.; 82371272 to Z.C.; 82301628 to L.W.; 82301438 to Z.L.; 82201411 to L.H.), the Innovation Research Group Project of Natural Science Foundation of Hunan Province (2020JJ1008 to H.J.), the Key Research and Development Program of Hunan Province (2020SK2064 to H.J.), the Innovative Research and Development Program of Development and Reform Commission of Hunan Province to H.J., the Natural Science Foundation of Hunan Province (2024JJ3050 to H.J.; 2022JJ20094 and 2021JJ40974 to Z.C.; 2022JJ40783 to L.H.; 2022JJ40703 to Z.L.), the Project Program of National Clinical Research Center for Geriatric Disorders (Xiangya Hospital, 2020LNJJ12 to H.J.), the Central South University Research Programme of Advanced Interdisciplinary Study (2023QYJC010 to H.J.) and the Science and Technology Innovation Program of Hunan Province (2022RC1027 to Z.C.). D.P. holds a Fellowship award from the Canadian Institutes of Health Research (CIHR)., Competing Interests: Declaration of interests S.Z. has received consultancy honoraria from Neurogene, Aeglea BioTherapeutics, Applied Therapeutics, and is an unpaid officer of the TGP foundation, all unrelated to the present manuscript. The other authors report no conflicts of interest., (Copyright © 2024 The Author(s). Published by Elsevier B.V. All rights reserved.)

Calcium-independent phospholipase A 2 β (iPLA 2 β), a member of the phospholipase A2 (PLA2s) superfamily, is encoded by the PLA2G6 gene. Mutations in the PLA2G6 gene have been identified as the primary cause of infantile neuroaxonal dystrophy (INAD) and, less commonly, as a contributor to Parkinson's disease (PD). Recent studies have revealed that iPLA 2 β deficiency leads to neuroinflammation, iron accumulation, mitochondrial dysfunction, lipid dysregulation, and other pathological changes, forming a complex pathogenic network. These discoveries shed light on potential mechanisms underlying PLA2G6-associated neurodegeneration (PLAN) and offer valuable insights for therapeutic development. This review provides a comprehensive analysis of the fundamental characteristics of iPLA 2 β, its association with neurodegeneration, the pathogenic mechanisms involved in PLAN, and potential targets for therapeutic intervention. It offers an overview of the latest advancements in this field, aiming to contribute to ongoing research endeavors and facilitate the development of effective therapies for PLAN., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The outbreak of harmful algae blooms caused by water eutrophication seriously jeopardizes the aquatic ecological environment and human health. Therefore, algae control technology has attracted widespread attention between environmental scholars. Allelochemical sustained-release technology which releases the active ingredient to the target medium at a certain rate within the effective time, so that the system maintains a certain concentration, thus prolonging its influence on the target organism. Allelochemical sustained-release technology has become the focus of research due to the characteristics of high efficiency, safety, low-cost, environment friendly and no secondary pollution. This paper reviews the characteristics of allelochemical substances and the status quo of plant extraction, explains the detailed classification of allelochemical sustained-release microspheres (ASRMs) and the application of algae inhibition, summarizes the preparation method of ASRMs, elaborates on the mechanism of algae inhibition of sustained-release technology from the perspective of photosynthesis, cellular enzyme activity, algae cell structure, gene expression, and target site action. Focuses on the summary of the factors influencing the effect of algae inhibition of ASRMs, including particle size of sustained-release microspheres, selection of carrier materials, and the growth stage of algae. The future direction and prospect of algae inhibition by allelochemical sustained-release technology were prospected to provide the scientific basis for water ecological restoration., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Background: Genetic variants of dopaminergic transcription factor-encoding genes are suggested to be Parkinson's disease (PD) risk factors; however, no comprehensive analyses of these genes in patients with PD have been undertaken. Therefore, we aimed to genetically analyze 16 dopaminergic transcription factor genes in Chinese patients with PD., Methods: Whole-exome sequencing (WES) was performed using a Chinese cohort comprising 1917 unrelated patients with familial or sporadic early-onset PD and 1652 controls. Additionally, whole-genome sequencing (WGS) was performed using another Chinese cohort comprising 1962 unrelated patients with sporadic late-onset PD and 1279 controls., Results: We detected 308 rare and 208 rare protein-altering variants in the WES and WGS cohorts, respectively. Gene-based association analyses of rare variants suggested that MSX1 is enriched in sporadic late-onset PD. However, the significance did not pass the Bonferroni correction. Meanwhile, 72 and 1730 common variants were found in the WES and WGS cohorts, respectively. Unfortunately, single-variant logistic association analyses did not identify significant associations between common variants and PD., Conclusions: Variants of 16 typical dopaminergic transcription factors might not be major genetic risk factors for PD in Chinese patients. However, we highlight the complexity of PD and the need for extensive research elucidating its etiology., (Copyright © 2024 The Chinese Medical Association, produced by Wolters Kluwer, Inc. under the CC-BY-NC-ND license.)

Background and Purpose: The role of GGC repeat expansions within NOTCH2NLC in Parkinson's disease (PD) and the substantia nigra (SN) dopaminergic neuron remains unclear. Here, we profile the NOTCH2NLC GGC repeat expansions in a large cohort of patients with PD. We also investigate the role of GGC repeat expansions within NOTCH2NLC in the dopaminergic neurodegeneration of SN., Methods: A total of 2,522 patients diagnosed with PD and 1,085 health controls were analyzed for the repeat expansions of NOTCH2NLC by repeat-primed PCR and GC-rich PCR assay. Furthermore, the effects of GGC repeat expansions in NOTCH2NLC on dopaminergic neurons were investigated by using recombinant adeno-associated virus (AAV)-mediated overexpression of NOTCH2NLC with 98 GGC repeats in the SN of mice by stereotactic injection., Results: Four PD pedigrees (4/333, 1.2%) and three sporadic PD patients (3/2189, 0.14%) were identified with pathogenic GGC repeat expansions (larger than 60 GGC repeats) in the NOTCH2NLC gene, while eight PD patients and one healthy control were identified with intermediate GGC repeat expansions ranging from 41 to 60 repeats. No significant difference was observed in the distribution of intermediate NOTCH2NLC GGC repeat expansions between PD cases and controls (Fisher's exact test p-value = 0.29). Skin biopsy showed P62-positive intranuclear NOTCH2NLC-polyGlycine (polyG) inclusions in the skin nerve fibers of patient. Expanded GGC repeats in NOTCH2NLC produced widespread intranuclear and perinuclear polyG inclusions, which led to a severe loss of dopaminergic neurons in the SN. Consistently, polyG inclusions were presented in the SN of EIIa-NOTCH2NLC-(GGC)98 transgenic mice and also led to dopaminergic neuron loss in the SN., Conclusions: Overall, our findings provide strong evidence that GGC repeat expansions within NOTCH2NLC contribute to the pathogenesis of PD and cause degeneration of nigral dopaminergic neurons., (© 2023 The Authors. European Journal of Neurology published by John Wiley & Sons Ltd on behalf of European Academy of Neurology.)

Introduction: Whether the integration of eye-tracking, gait, and corresponding dual-task analysis can distinguish cognitive impairment (CI) patients from controls remains unclear., Methods: One thousand four hundred eighty-one participants, including 724 CI and 757 controls, were enrolled in this study. Eye movement and gait, combined with dual-task patterns, were measured. The LightGBM machine learning models were constructed., Results: A total of 105 gait and eye-tracking features were extracted. Forty-six parameters, including 32 gait and 14 eye-tracking features, showed significant differences between two groups (P < 0.05). Of these, the Gait&#95;3Back-TurnTime and Dual-task cost-TurnTime patterns were significantly correlated with plasma phosphorylated tau 181 (p-tau181) level. A model based on dual-task gait, dual-task smooth pursuit, prosaccade, and anti-saccade achieved the best area under the receiver operating characteristics curve (AUC) of 0.987 for CI detection, while combined with p-tau181, the model discriminated mild cognitive impairment from controls with an AUC of 0.824., Discussion: Combining dual-task gait and dual-task eye-tracking analysis is feasible for the detection of CI., Highlights: This is the first study to report the efficiency of integrated parameters of dual-task gait and eye-tracking for cognitive impairment (CI) detection in a large cohort. We identified 46 gait and eye-tracking features associated with CI, and two were correlated to plasma phosphorylated tau 181. We constructed the model based on dual-task gait, smooth pursuit, prosaccade, and anti-saccade, achieving the best area under the curve of 0.987 for CI detection., (© 2023 The Authors. Alzheimer's & Dementia published by Wiley Periodicals LLC on behalf of Alzheimer's Association.)

Introduction: Recently, chloride channel CLIC-like 1 (CLCC1) was reported to be a novel ALS-related gene. We aimed to screen CLCC1 variants in our ALS cohort and further explore the genotype-phenotype correlation of CLCC1-related ALS., Methods: We screened rare damaging variants in CLCC1 from our cohorts of 1005 ALS patients and 1224 healthy controls with whole-exome sequencing in Central South China. Fisher's exact test was conducted for association analysis at the entire gene level and single variant level., Results: In total, four heterozygous missense variants in CLCC1 were identified from four unrelated sporadic ALS patients and predicted to be putative pathogenic by in silico tools and protein model prediction, accounting for 0.40% of all patients (4/1005). The four variants were c.A275C (p.Q92P), c.G1139A (p.R380K), c.C1244T (p.T415M), and c.G1328A (p.R443Q), respectively, which had not been reported in ALS patients previously. Three of four variants were located in exon 10. Patients harboring CLCC1 variants seemed to share a group of similar clinical features, including earlier age at onset, rapid progression, spinal onset, and vulnerable cognitive status. Statistically, we did not find CLCC1 to be associated with the risk of ALS at the entire gene level or single variant level., Conclusion: Our findings further expanded the genetic and clinical spectrum of CLCC1-related ALS and provided more genetic evidence for anion channel involvement in the pathogenesis of ALS, but further investigations are needed to verify our findings., (© 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

This article explores deep reinforcement learning (DRL) for the flocking control of unmanned aerial vehicle (UAV) swarms. The flocking control policy is trained using a centralized-learning-decentralized-execution (CTDE) paradigm, where a centralized critic network augmented with additional information about the entire UAV swarm is utilized to improve learning efficiency. Instead of learning inter-UAV collision avoidance capabilities, a repulsion function is encoded as an inner-UAV "instinct." In addition, the UAVs can obtain the states of other UAVs through onboard sensors in communication-denied environments, and the impact of varying visual fields on flocking control is analyzed. Through extensive simulations, it is shown that the proposed policy with the repulsion function and limited visual field has a success rate of 93.8% in training environments, 85.6% in environments with a high number of UAVs, 91.2% in environments with a high number of obstacles, and 82.2% in environments with dynamic obstacles. Furthermore, the results indicate that the proposed learning-based methods are more suitable than traditional methods in cluttered environments.

Objective: To estimate the sequence of several common biomarker changes in Parkinson's disease (PD) using a novel data-driven method., Methods: We included 374 PD patients and 169 healthy controls (HC) from the Parkinson's Progression Markers Initiative (PPMI). Biomarkers, including the left putamen striatal binding ratio (SBR), right putamen SBR, left caudate SBR, right caudate SBR, cerebrospinal fluid (CSF) α-synuclein, and serum neurofilament light chain (NfL), were selected in our study. The discriminative event-based model (DEBM) was utilized to model the sequence of biomarker changes and establish the disease progression timeline. The estimated disease stages for each subject were obtained through cross-validation. The associations between the estimated disease stages and the clinical symptoms of PD were explored using Spearman's correlation., Results: The left putamen is the earliest biomarker to become abnormal among the selected biomarkers, followed by the right putamen, CSF α-synuclein, right caudate, left caudate, and serum NfL. The estimated disease stages are significantly different between PD and HC and yield a high accuracy for distinguishing PD from HC, with an area under the curve (AUC) of 0.98 (95% confidence interval 0.97-0.99), a sensitivity of 0.95, and a specificity of 0.92. Moreover, the estimated disease stages correlate with motor experiences of daily living, motor symptoms, autonomic dysfunction, and anxiety in PD patients., Conclusion: We determined the sequence of several common biomarker changes in PD using DEBM, providing data-driven evidence of the disease progression of PD., Competing Interests: Declaration of competing interest The authors disclose no actual or potential conflicts of interest., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

Autoimmunity plays a key role in the pathogenesis of Alzheimer's disease (AD). However, whether autoantibodies in peripheral blood can be used as biomarkers for AD has been elusive. Serum samples were obtained from 1,686 participants, including 767 with AD, 146 with mild cognitive impairment (MCI), 255 with other neurodegenerative diseases, and 518 healthy controls. Specific autoantibodies were measured using a custom-made immunoassay. Multivariate support vector machine models were employed to investigate the correlation between serum autoantibody levels and disease states. As a result, seven candidate AD-specific autoantibodies were identified, including MAPT, DNAJC8, KDM4D, SERF1A, CDKN1A, AGER, and ASXL1. A classification model with high accuracy (area under the curve (AUC) = 0.94) was established. Importantly, these autoantibodies could distinguish AD from other neurodegenerative diseases and out-performed amyloid and tau protein concentrations in cerebrospinal fluid in predicting cognitive decline (P < 0.001). This study indicated that AD onset and progression are possibly accompanied by an unappreciated serum autoantibody response. Therefore, future studies could optimize its application as a convenient biomarker for the early detection of AD., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Inc. All rights reserved.)

The role of microbiota-gut-brain axis in modulating longevity remains undetermined. Here, we performed a multiomics analysis of gut metagenomics, gut metabolomics, and brain functional near-infrared spectroscopy (fNIRS) in a cohort of 164 participants, including 83 nonagenarians (NAs) and 81 non-nonagenarians (NNAs) matched with their spouses and offspring. We found that 438 metabolites were significantly different between the two groups; among them, neuroactive compounds and anti-inflammatory substances were enriched in NAs. In addition, increased levels of neuroactive metabolites in NAs were significantly associated with NA-enriched species that had three corresponding biosynthetic potentials: Enterocloster asparagiformis , Hungatella hathewayi and Oxalobacter formigenes . Further analysis showed that the altered gut microbes and metabolites were linked to the enhanced brain connectivity in NAs, including the left dorsolateral prefrontal cortex (DLPFC)-left premotor cortex (PMC), left DLPFC-right primary motor area (M1), and right inferior frontal gyrus (IFG)-right M1. Finally, we found that neuroactive metabolites, altered microbe and enhanced brain connectivity contributed to the cognitive preservation in NAs. Our findings provide a comprehensive understanding of the microbiota-gut-brain axis in a long-lived population and insights into the establishment of a microbiome and metabolite homeostasis that can benefit human longevity and cognition by enhancing functional brain connectivity.

Parkinson's disease (PD) is one of the most prevalent neurodegenerative diseases. The typical symptomatology of PD includes motor symptoms; however, a range of nonmotor symptoms, such as intestinal issues, usually occur before the motor symptoms. Various microorganisms inhabiting the gastrointestinal tract can profoundly influence the physiopathology of the central nervous system through neurological, endocrine, and immune system pathways involved in the microbiota-gut-brain axis. In addition, extensive evidence suggests that the gut microbiota is strongly associated with PD. This review summarizes the latest findings on microbial changes in PD and their clinical relevance, describes the underlying mechanisms through which intestinal bacteria may mediate PD, and discusses the correlations between gut microbes and anti-PD drugs. In addition, this review outlines the status of research on microbial therapies for PD and the future directions of PD-gut microbiota research., (© 2023. The Author(s).)

Autism Spectrum Disorder (ASD) is a neurodevelopmental condition whose current psychiatric diagnostic process is subjective and behavior-based. In contrast, functional magnetic resonance imaging (fMRI) can objectively measure brain activity and is useful for identifying brain disorders. However, the ASD diagnostic models employed to date have not reached satisfactory levels of accuracy. This study proposes the use of MAACNN, a method that utilizes multi-view convolutional neural networks (CNNs) in conjunction with attention mechanisms for identifying ASD in multi-scale fMRI. The proposed algorithm effectively combines unsupervised and supervised learning. In the initial stage, we employ stacked denoising autoencoders, an unsupervised learning method for feature extraction, which provides different nodes to adapt to multi-scale data. In the subsequent stage, we perform supervised learning by employing multi-view CNNs for classification and obtain the final results. Finally, multi-scale data fusion is achieved by using the attention fusion mechanism. The ABIDE dataset is used to evaluate the model we proposed., and the experimental results show that MAACNN achieves superior performance with 75.12% accuracy and 0.79 AUC on ABIDE-I, and 72.88% accuracy and 0.76 AUC on ABIDE-II. The proposed method significantly contributes to the clinical diagnosis of ASD., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2023 Wang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Cerebrotendinous xanthomatosis (CTX), an autosomal recessive disorder characterized by high levels of cholestanol in the blood and accumulation of cholestanol in multiple tissues, especially the brain, often presents in parkinsonism. However, it remains unknown whether cholestanol plays a role in the pathogenesis of sporadic Parkinson's disease (PD). Here, we show that the levels of serum cholestanol in patients with sporadic PD are higher than those in control participants. Cholestanol activates the protease asparagine endopeptidase (AEP) and induces the fragmentation of α-synuclein (α-syn) and facilitates its aggregation. Furthermore, cholestanol promotes the spreading of α-syn pathology in a mouse model induced by intrastriatal injection of α-syn fibrils. KO of AEP or administration of an AEP inhibitor ameliorates α-syn pathology, degeneration of the nigrostriatal dopaminergic pathway, and PD-like motor symptoms. These results not only indicate that cholestanol contributes to the aggregation and spreading of α-syn by activating AEP but also reveal an opportunity for treating PD with AEP inhibitors.

Misfolding and aggregation of α-Synuclein (α-Syn), which are hallmark pathological features of neurodegenerative diseases such as Parkinson's disease (PD) and dementia with Lewy Bodies, continue to be significant areas of research. Among the diverse forms of α-Syn - monomer, oligomer, and fibril, the oligomer is considered the most toxic. However, the mechanisms governing α-Syn oligomerization are not yet fully understood. In this study, we utilized genome-wide CRISPR/Cas9 loss-of-function screening in human HEK293 cells to identify negative regulators of α-Syn oligomerization. We found that tetraspanin 3 (TSPAN3), a presumptive four-pass transmembrane protein, but not its homolog TSPAN7, significantly modulates α-Syn oligomer levels. TSPAN3 was observed to interact with α-Syn oligomers, regulate the amount of α-Syn oligomers on the cell membrane, and promote their degradation via the clathrin-AP2 mediated endo-lysosome pathway. Our findings highlight TSPAN3 as a potential regulator of α-Syn oligomers, presenting a promising target for future PD prevention and treatment strategies., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Objective: To investigate the risk factors for REM sleep behavior disorder (RBD) in a case-control study., Methods: Participants with probable RBD (pRBD) were defined using the RBD Questionnaire-Hong Kong (RBDQ-HK). Controls were collected by matching age and sex. Demographic information, lifestyle, comorbidity, prodromal symptoms of Parkinson's disease (PD), and blood biomarkers were assessed. The associations between these factors and pRBD were investigated by logistic regression. Partial correlation analysis was used to assess the association between the severity of RBD and depression., Results: A total of 278 pRBD participants (age = 58.31 ± 15.82 years) and 556 controls (age = 58.16 ± 15.84 years) were enrolled in this study. Patients with pRBD were more likely to be current alcohol drinkers (OR 1.50, 95% CI 1.0-2.32). Participants with pRBD had a higher Hamilton Depression Rating Scale (HAMD-17) score (OR 1.17, 95% CI 1.11-1.22) than controls and were more likely to report arthritis (OR 1.53, 95% CI 1.08-2.16), constipation (OR 1.93, 95% CI 1.31-2.86), hyposmia (OR 1.71, 95% CI 1.10-2.67), and depression (OR 3.15, 95% CI 2.17-4.58). Higher levels of total cholesterol (OR 1.15, 95% CI 0.99-1.33) and low-density lipoprotein (OR 1.21, 95% CI 0.99-1.47) had borderline associations with pRBD. Additionally, the severity of pRBD was positively related to depression (r = 0.31, P < 0.01)., Conclusions: We determined several risk factors for pRBD in this case-control study. Future studies are needed to understand the mechanism underlying the association between these factors and pRBD., Competing Interests: Declaration of competing interest The authors disclose no actual or potential conflicts of interest., (Copyright © 2023 Elsevier B.V. All rights reserved.)

Background: Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder. An increasing number of researchers have found extra motor features in ALS, which are also called ALS-plus syndromes. Besides, a great majority of ALS patients also have cognitive impairment. However, clinical surveys of the frequency and genetic background of ALS-plus syndromes are rare, especially in China., Methods: We investigated a large cohort of 1015 patients with ALS, classifying them into six groups according to different extramotor symptoms and documenting their clinical manifestations. Meanwhile, based on their cognitive function, we divided these patients into two groups and compared demographic characteristics. Genetic screening for rare damage variants (RDVs) was also performed on 847 patients., Results: As a result, 16.75% of patients were identified with ALS-plus syndrome, and 49.5% of patients suffered cognitive impairment. ALS-plus group had lower ALSFRS-R scores, longer diagnostic delay time, and longer survival times, compared to ALS pure group. RDVs occurred less frequently in ALS-plus patients than in ALS-pure patients (P = 0.042) but showed no difference between ALS-cognitive impairment patients and ALS-cognitive normal patients. Besides, ALS-cognitive impairment group tends to harbour more ALS-plus symptoms than ALS-cognitive normal group (P = 0.001)., Conclusion: In summary, ALS-plus patients in China are not rare and show multiple differences from ALS-pure patients in clinical and genetic features. Besides, ALS-cognitive impairment group tends to harbour more ALS-plus syndrome than ALS-cognitive normal group. Our observations correspond with the theory that ALS involves several diseases with different mechanisms and provide clinical validation., (© 2023. Fondazione Società Italiana di Neurologia.)

Motion planning is important to the automatic operation of the manipulator. It is difficult for traditional motion planning algorithms to achieve efficient online motion planning in a rapidly changing environment and high-dimensional planning space. The neural motion planning (NMP) algorithm based on reinforcement learning provides a new way to solve the above-mentioned task. Aiming to overcome the difficulty of training the neural network in high-accuracy planning tasks, this article proposes to combine the artificial potential field (APF) method and reinforcement learning. The neural motion planner can avoid obstacles in a wide range; meanwhile, the APF method is exploited to adjust the partial position. Considering that the action space of the manipulator is high-dimensional and continuous, the soft-actor-critic (SAC) algorithm is adopted to train the neural motion planner. By training and testing with different accuracy values in a simulation engine, it is verified that, in the high-accuracy planning tasks, the success rate of the proposed hybrid method is better than using the two algorithms alone. Finally, the feasibility of directly transferring the learned neural network to the real manipulator is verified by a dynamic obstacle-avoidance task.

GBA1 variants are important risk factors for Parkinson's disease (PD). Most studies assessing GBA1-related PD risk have been performed in European-derived populations. Although the coding region of the GBA1 gene in the Chinese population has been analyzed, the sample sizes were not adequate. In this study, we aimed to investigate GBA1 variants in a large Chinese cohort of patients with PD and healthy control and explore the associated clinical characteristics. GBA1 variants in 4034 patients and 2931 control participants were investigated using whole-exome and whole-genome sequencing. The clinical features of patients were evaluated using several scales. Regression analysis, chi-square, and Fisher exact tests were used to analyze GBA1 variants and the clinical symptoms of different groups. We identified 104 variants, including 8 novel variants, expanding the spectrum of GBA1 variants. The frequency of GBA1 variants in patients with PD was 7.46%, higher than that in the control (1.81%) (P < 0.001, odds ratio [OR] = 4.38, 95% confidence interval [CI]: 3.26-5.89). Among patients, 176 (4.36%) had severe variants, 34 (0.84%) carried mild variants, three (0.07%) had risk variants, and 88 (2.18%) carried unknown variants. Our study, for the first time, found that p.G241R (P = 0.007, OR = 15.3, 95% CI: 1.25-261.1) and p.S310G (P = 0.005, OR = 4.86, 95% CI: 1.52-28.04) variants increased the risk of PD. Patients with GBA1 variants exhibited an earlier onset age and higher risk of probable rapid-eye-movement sleep behavior disorder, olfactory dysfunction, depression, and autonomic dysfunction than patients without GBA1 variants., (© 2023. Springer Nature Limited.)

Aims: To study the brain metabolic signature in Chinese amyotrophic lateral sclerosis (ALS) patients and compare the difference in brain metabolic patterns between ALS with and without genetic variants., Methods: We included 146 patients with ALS and 128 healthy controls (HCs). All patients with ALS underwent genetic testing to screen for ALS related genetic variants and were then divided into genetic (n = 22) and nongenetic ALS (n = 93) subgroups. All participants underwent brain 18 F-FDG-PET scans. Group comparisons were performed using the two-sample t-test model of SPM12., Results: We identified a large of hypometabolic clusters in ALS patients as compared with HCs, especially in the bilateral basal ganglia, midbrain, and cerebellum. Moreover, hypometabolism in the bilateral temporal lobe, precentral gyrus and hypermetabolism in the left anterior cingulate, occipital lobe, and bilateral frontal lobe were also found in ALS patients as compared with HCs. Compared with nongenetic ALS patients, genetic ALS patients showed hypometabolism in the right postcentral gyrus, precuneus, and middle occipital gyrus. The incidence of sensory disturbance in patients with genetic ALS was higher than that in patients with nongenetic ALS (5 of 22 [22.72%] vs. 7 of 93 [7.52%], p = 0.036)., Conclusions: Our investigation provided unprecedented evidence of relative hypometabolism in the midbrain and cerebellum in ALS patients. Genetic ALS patients showed a specific signature of brain metabolism and a higher incidence of sensory disturbance, indicating that genetic factors may be an underlying cause affecting the brain metabolism and increasing the risk of sensory disturbance in ALS., (© 2023 The Authors. CNS Neuroscience & Therapeutics published by John Wiley & Sons Ltd.)

Objectives: Hereditary spastic paraplegia (HSP) is a genetically heterogeneous disease caused by over 70 genes, with a significant number of patients still genetically unsolved. In this study, we recruited a suspected HSP family characterized by spasticity, developmental delay, ataxia and hypomyelination, and intended to reveal its molecular etiology by whole exome sequencing (WES) and long-read sequencing (LRS) analyses., Methods: WES was performed on 13 individuals of the family to identify the causative mutations, including analyses of SNVs (single-nucleotide variants) and CNVs (copy number variants). Accurate circular consensus (CCS) long-read sequencing (LRS) was used to verify the findings of CNV analysis from WES., Results: SNVs analysis identified a missense variant c.195G>T (p.E65D) of MORF4L2 at Xq22.2 co-segregating in this family from WES data. Further CNVs analysis revealed a microdeletion, which was adjacent to the MORF4L2 gene, also co-segregating in this family. LRS verified this microdeletion and confirmed the deletion range (chrX: 103,690,507-103,715,018, hg38) with high resolution at nucleotide level accuracy., Interpretations: In this study, we identified an Xq22.2 microdeletion (about 24.5 kb), which contains distal enhancers of the PLP1 gene, as a likely cause of SPG2 in this family. The lack of distal enhancers may result in transcriptional repression of PLP1 in oligodendrocytes, potentially affecting its role in the maintenance of myelin, and causing SPG2 phenotype. This study has highlighted the importance of noncoding genomic alterations in the genetic etiology of SPG2., (© 2023 The Authors. Annals of Clinical and Translational Neurology published by Wiley Periodicals LLC on behalf of American Neurological Association.)

Focal epilepsy accounts for 60% of all forms of epilepsy, but the pathogenic mechanism is not well understood. In this study, three novel mutations in NPRL3 (nitrogen permease regulator-like 3), c.937&#95;945del, c.1514dupC and 6,706-bp genomic DNA (gDNA) deletion, were identified in three families with focal epilepsy by linkage analysis, whole exome sequencing (WES) and Sanger sequencing. NPRL3 protein is a component of the GATOR1 complex, a major inhibitor of mTOR signaling. These mutations led to truncation of the NPRL3 protein and hampered the binding between NPRL3 and DEPDC5, which is another component of the GATOR1 complex. Consequently, the mutant proteins enhanced mTOR signaling in cultured cells, possibly due to impaired inhibition of mTORC1 by GATOR1. Knockdown of nprl3 in Drosophila resulted in epilepsy-like behavior and abnormal synaptic development. Taken together, these findings expand the genotypic spectrum of NPRL3-associated focal epilepsy and provide further insight into how NPRL3 mutations lead to epilepsy., (© 2023. Science China Press.)

Background: Progressive supranuclear palsy (PSP) is a clinically heterogenous atypical parkinsonian syndrome. Therefore, early recognition and correct diagnosis of PSP is challenging but essential. This study aims to characterize the clinical manifestations, magnetic resonance imaging (MRI), and longitudinal MRI changes of PSP in China., Method: Clinical and MRI presentations were compared among 150 cases with PSP. Then the longitudinal MRI changes among 20 patients with PSP were further explored. Additionally, a series of midbrain-based MRI parameters was compared between PSP-P and PD., Results: Throughout the course of the disease, there were differences in the symptoms of the fall and hand tremor between the PSP-RS and PSP-P. There were significant differences in the six midbrain-based MRI parameters between the PSP-RS and the PSP-P, including hummingbird sign, midbrain diameter, midbrain to pons ratio (MTPR), midbrain area, midbrain area to pons area ratio (Ma/Pa), and midbrain tegmental length (MBTegm). Longitudinal MRI studies revealed that the annual rel.ΔMTPR and rel.Δ (Ma/Pa) for PSP were 5.55 and 6.52%, respectively; additionally, PSP-RS presented a higher decline rate than PSP-P. Moreover, MTPR ≤0.56, midbrain diameter ≤ 0.92, midbrain area ≤ 1.00, and third ventricle width ≤ 0.75 could identify PSP-P from PD., Conclusion: PSP-P differs from PSP-RS regarding clinical manifestations, MRI, and longitudinal MRI changes. MRI parameters could be potential imaging markers to identify PSP-P from PD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wen, Yang, Jiao, Zhang, Lin, Zhu, Xu, Zhou, Weng, Liao, Zhou, Wang, Guo, Yan, Jiang, Tang and Shen.)

Membrane bioreactor (MBR), as a biological unit for wastewater treatment, has been proven to have the advantages of simple structure and high pollutant removal rate. However, membrane fouling limits its wide application, and it is crucial to adopt effective membrane fouling control methods. As a new type of membrane fouling control technology, electrically-enhanced MBR (EMBR) has attracted more interest recently. It uses the driving force of electric field to make pollutants flocculate or move away from the membrane surface to achieve the purpose of inhibiting membrane fouling. This paper expounds the configuration of EMBR in recent years, including the location of membrane components, the way of electric field application and the selection of electrode and membrane materials, and provides the latest development information in various aspects. The enhanced effect of electric field on the removal of comprehensive and refractory pollutants is outlined in detail. And from the perspective of sludge properties (EPS, SMP, sludge particle size, zeta potential and microbial activity), the influence of electric field on sludge characteristics and the relationship between the changes of sludge properties in EMBR and membrane fouling are discussed. Moreover, the electrochemical mechanisms of electric field alleviating membrane fouling are elucidated from electrophoresis, electrostatic repulsion, electroflocculation, electroosmosis, and electrochemical oxidation, and the regeneration and stability of EMBR are assessed. The existing challenges and future research directions are also proposed. This review could provide theoretical guidance and further studies for subsequent topic, and promoting the wide engineering applications of EMBR., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

The new term essential tremor (ET) plus was proposed in the 2018 tremor consensus criteria. The National Survey of Essential Tremor Plus in China, a large multicenter registry study, aimed to evaluate the clinical features of pure ET and ET plus and explore possible factors related to ET plus. All patients with ET underwent neurological examination and neuropsychological assessment at 17 clinical sites. The diagnosis was made according to the 2018 consensus criteria. Clinicodemographic characteristics were analyzed. A total of 1160 patients were included, including 546 patients with pure ET and 614 patients with ET plus. The proportion of females was significantly higher in the ET plus than that in the pure ET (P = 0.001). The age at onset (AAO) of pure ET showed a bimodal distribution, with peaks in the 2nd and 5th decades. However, the AAO of the ET plus group demonstrated a skewed distribution, with a single peak in the 6th decade. Female sex (OR=1.645, P<0.001), older age (OR=1.023, P<0.001), lower educational level (OR=0.934, P<0.001), head tremor (OR=1.457, P<0.001), and higher the Tremor Research Group Essential Tremor Rating Assessment Scale (TETRAS)-II scores (OR=1.134, P<0.001) were significantly associated with ET plus. Old age and female sex may contribute to ET plus development. Pure ET showed a bimodal distribution for AAO, whereas ET plus showed a unimodal distribution. It remains unclear whether pure ET and ET plus are merely different stages of a single disease or represent distinct disease entities.

Objective: There is controversial evidence that FMR1 premutation or "gray zone" (GZ) allele (small CGG expansion, 45-54 repeats) was associated with Parkinson's disease (PD). We aimed to explore further the association between FMR1 CGG repeat expansions and PD in a large sample of Chinese origin., Methods: We included a cohort of 2,362 PD patients and 1,072 controls from the Parkinson's Disease and Movement Disorders Multicenter Database and Collaborative Network in China (PD-MDCNC) in this study and conducted repeat-primed polymerase chain reaction (RP-PCR) for the size of FMR1 CGG repeat expansions., Results: Two PD patients were detected with FMR1 premutation (61 and 56 repeats), and the other eleven PD patients were detected with the GZ allele of FMR1 CGG repeat expansions. Those thirteen PD patients responded well to levodopa and were diagnosed with clinically established PD. Specifically, one female PD patient with GZ allele was also found with premature ovarian failure. However, compared to healthy controls, we found no significant enrichment of GZ allele carriers in PD patients or other subgroups of PD cases, including the subgroups of female, male, early-onset, and late-onset PD patients. Furthermore, we did not find any correlation between the FMR1 gene CGG repeat sizes and age at onset of PD., Conclusion: It suggested that FMR1 premutation was related to PD, but the GZ allele of FMR1 CGG repeat expansions was not significantly enriched in PD cases of Chinese origin. Further larger multiple ethnic studies are needed to determine further the role of the FMR1 GZ allele in PD., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Chen, Zhao, Zhou, Xue, Xiao, Pan, Zhou, Xiang, Li, Zhu, Zhou, Yang, Xu, Sun, Yan, Tan, Li, Guo, Duan, Tang, Yu and Liu.)

In modern precision medicine, it is an important research topic to predict cancer drug response. Due to incomplete chemical structures and complex gene features, however, it is an ongoing work to design efficient data-driven methods for predicting drug response. Moreover, since the clinical data cannot be easily obtained all at once, the data-driven methods may require relearning when new data are available, resulting in increased time consumption and cost. To address these issues, an incremental broad Transformer network (iBT-Net) is proposed for cancer drug response prediction. Different from the gene expression features learning from cancer cell lines, structural features are further extracted from drugs by Transformer. Broad learning system is then designed to integrate the learned gene features and structural features of drugs to predict the response. With the capability of incremental learning, the proposed method can further use new data to improve its prediction performance without retraining totally. Experiments and comparison studies demonstrate the effectiveness and superiority of iBT-Net under different experimental configurations and continuous data learning., (© The Author(s) 2023. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Background: The pathogenic missense mutations of the gelsolin ( GSN ) gene lead to familial amyloidosis of the Finnish type (FAF); however, our previous study identified GSN frameshift mutations existed in patients with Alzheimer's disease (AD). The GSN genotype-phenotype heterogeneity and the role of GSN frameshift mutations in patients with AD are unclear., Method: In total, 1192 patients with AD and 1403 controls were screened through whole genome sequencing, and 884 patients with AD were enrolled for validation. Effects of GSN mutations were evaluated in vitro. GSN, Aβ42, Aβ40 and Aβ42/40 were detected in both plasma and cerebrospinal fluid (CSF)., Results: Six patients with AD with GSN P3fs and K346fs mutations (0.50%, 6/1192) were identified, who were diagnosed with AD but not FAF. In addition, 13 patients with AD with GSN frameshift mutations were found in the validation cohort (1.47%, 13/884). Further in vitro experiments showed that both K346fs and P3fs mutations led to the GSN loss of function in inhibiting Aβ-induced toxicity. Moreover, a higher level of plasma (p=0.001) and CSF (p=0.005) GSN was observed in AD cases than controls, and a positive correlation was found between the CSF GSN and CSF Aβ42 (r=0.289, p=0.009). Besides, the GSN level was initially increasing and then decreasing with the disease course and cognitive decline., Conclusions: GSN frameshift mutations may be associated with AD. An increase in plasma GSN is probably a compensatory reaction in AD, which is a potential biomarker for early AD., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2023. Re-use permitted under CC BY-NC. No commercial re-use. See rights and permissions. Published by BMJ.)

Background: Severe reduced synaptic density was observed in spinocerebellar ataxia (SCA) in postmortem neuropathology, but in vivo assessment of synaptic loss remains challenging. OBJECTIVE SPINOCEREBELLAR ATAXIA TYPE 3: The objective of this study was to assess in vivo synaptic loss and its clinical correlates in spinocerebellar ataxia type 3 (SCA3) patients by synaptic vesicle glycoprotein 2A (SV2A)-positron emission tomography (PET) imaging., Methods: We recruited 74 SCA3 individuals including preataxic and ataxic stages and divided into two cohorts. All participants received SV2A-PET imaging using 18 F-SynVesT-1 for synaptic density assessment. Specifically, cohort 1 received standard PET procedure and quantified neurofilament light chain (NfL), and cohort 2 received simplified PET procedure for exploratory purpose. Bivariate correlation was performed between synaptic loss and clinical as well as genetic assessments., Results: In cohort 1, significant reductions of synaptic density were observed in cerebellum and brainstem in SCA3 ataxia stage compared to preataxic stage and controls. Vermis was found significantly involved in preataxic stage compared to controls. Receiver operating characteristic (ROC) curves highlighted SV2A of vermis, pons, and medulla differentiating preataxic stage from ataxic stage, and SV2A combined with NfL improved the performance. Synaptic density was significantly negatively correlated with disease severity in cerebellum and brainstem (International Co-operative Ataxia Rating Scale: ρ ranging from -0.467 to -0.667, P ≤ 0.002; Scale of Assessment and Rating of Ataxia: ρ ranging from -0.465 to -0.586, P ≤ 0.002). SV2A reduction tendency of cerebellum and brainstem identified in cohort 1 was observed in cohort 2 with simplified PET procedure., Conclusions: We first identified in vivo synaptic loss was related to disease severity of SCA3, suggesting SV2A PET could be a promising clinical biomarker for disease progression of SCA3. © 2023 International Parkinson and Movement Disorder Society., (© 2023 International Parkinson and Movement Disorder Society.)

Non-coding variants in the human genome significantly influence human traits and complex diseases via their regulation and modification effects. Hence, an increasing number of computational methods are developed to predict the effects of variants in human non-coding sequences. However, it is difficult for inexperienced users to select appropriate computational methods from dozens of available methods. To solve this issue, we assessed 12 performance metrics of 24 methods on four independent non-coding variant benchmark datasets: (1) rare germline variants from clinical relevant sequence variants (ClinVar), (2) rare somatic variants from Catalogue Of Somatic Mutations In Cancer (COSMIC), (3) common regulatory variants from curated expression quantitative trait locus (eQTL) data, and (4) disease-associated common variants from curated genome-wide association studies (GWAS). All 24 tested methods performed differently under various conditions, indicating varying strengths and weaknesses under different scenarios. Importantly, the performance of existing methods was acceptable for rare germline variants from ClinVar with the area under the receiver operating characteristic curve (AUROC) of 0.4481-0.8033 and poor for rare somatic variants from COSMIC (AUROC = 0.4984-0.7131), common regulatory variants from curated eQTL data (AUROC = 0.4837-0.6472), and disease-associated common variants from curated GWAS (AUROC = 0.4766-0.5188). We also compared the prediction performance of 24 methods for non-coding de novo mutations in autism spectrum disorder, and found that the combined annotation-dependent depletion (CADD) and context-dependent tolerance score (CDTS) methods showed better performance. Summarily, we assessed the performance of 24 computational methods under diverse scenarios, providing preliminary advice for proper tool selection and guiding the development of new techniques in interpreting non-coding variants., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Objective: Parkinson's disease (PD) and dystonia are two closely related movement disorders with overlaps in clinical phenotype. Variants in several dystonia-related genes were demonstrated to be associated with PD; however, genetic evidence for the involvement of dystonia-related genes in PD has not been fully studied. Here, we comprehensively investigated the association between rare variants in dystonia-related genes and PD in a large Chinese cohort., Methods: We comprehensively analyzed the rare variants of 47 known dystonia-related genes by mining the whole-exome sequencing (WES) and whole-genome sequencing (WGS) data from 3,959 PD patients and 2,931 healthy controls. We initially identified potentially pathogenic variants of dystonia-related genes in patients with PD based on different inheritance models. Sequence kernel association tests were conducted in the next step to detect the association between the burden of rare variants and the risk for PD., Results: We found that five patients with PD carried potentially pathogenic biallelic variants in recessive dystonia-related genes including COL6A3 and TH . Additionally, we identified 180 deleterious variants in dominant dystonia-related genes based on computational pathogenicity predictions and four of which were considered as potentially pathogenic variants (p.W591X and p.G820S in ANO3 , p.R678H in ADCY5 , and p.R458Q in SLC2A1 ). A gene-based burden analysis revealed the increased burden of variant subgroups of TH, SQSTM1, THAP1 , and ADCY5 in sporadic early-onset PD, whereas COL6A3 was associated with sporadic late-onset PD. However, none of them reached statistical significance after the Bonferroni correction., Conclusion: Our findings indicated that rare variants in several dystonia-related genes are suggestively associated with PD, and taken together, the role of COL6A3 and TH genes in PD is highlighted., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Wang, Zhao, Pan, Zeng, Zhou, Xiang, Zhou, Xu, Sun, Tan, Yan, Li, Guo, Tang, Yu and Liu.)