Causal associations between modifiable risk factors and isolated REM sleep behavior disorder: a mendelian randomization study.

Objectives: This Mendelian randomization (MR) study identified modifiable risk factors for isolated rapid eye movement sleep behavior disorder (iRBD). Methods: Genome-wide association study (GWAS) datasets for 29 modifiable risk factors for iRBD in discovery and replication stages were used. GWAS data for iRBD cases were obtained from the International RBD Study Group. The inverse variance weighted (IVW) method was primarily employed to explore causality, with supplementary analyses used to verify the robustness of IVW findings. Co-localization analysis further substantiated causal associations identified via MR. Genetic correlations between mental illness and iRBD were identified using trait covariance, linkage disequilibrium score regression, and co-localization analyses. Results: Our study revealed causal associations between sun exposure-related factors and iRBD. Utilizing sun protection (odds ratio [OR] = 0.31 [0.14, 0.69], p = 0.004), ease of sunburn (OR = 0.70 [0.57, 0.87], p = 0.001), childhood sunburn occasions (OR = 0.58 [0.39, 0.87], p = 0.008), and phototoxic dermatitis (OR = 0.78 [0.66, 0.92], p = 0.003) decreased iRBD risk. Conversely, a deep skin color increased risk (OR = 1.42 [1.04, 1.93], p = 0.026). Smoking, alcohol consumption, low education levels, and mental illness were not risk factors for iRBD. Anxiety disorders and iRBD were genetically correlated. Conclusion: Our study does not corroborate previous findings that identified smoking, alcohol use, low education, and mental illness as risk factors for iRBD. Moreover, we found that excessive sun exposure elevates iRBD risk. These findings offer new insights for screening high-risk populations and devising preventive measures.

Utility of serum neurofilament light chain and glial fibrillary acidic protein as diagnostic biomarkers of freezing of gait in Parkinson's disease.

Freezing of gait (FOG) is one of the most distressing features of Parkinson's disease (PD), increasing the risks of fractures and seriously affecting patients' quality of life. We aimed to examine the potential diagnostic roles of serum neurofilament light chain (NFL) and glial fibrillary acidic protein (GFAP) in PD patients with FOG (PD-FOG). We included 99 patients, comprising 54 PD patients without FOG (PD-NoFOG), 45 PD-FOG and 37 healthy controls (HCs). Our results indicated serum markers were significantly higher in PD-FOG and postural instability and gait difficulty (PIGD) motor subtype patients than in PD-NoFOG and non-PIGD subtype patients (P < 0.05), respectively. Patients with high concentrations of the markers NFL and GFAP had higher PIGD scores and greater FOG severity than those with low concentrations. Moreover, serum levels of both NFL and GFAP were significantly positively associated with age, FOG severity, PD-FOG status, and negatively associated with Mini-Mental State Examination (MMSE) scores. Logistic regression analysis identified serum levels of NFL and GFAP as independent risk factors for PD-FOG. Mediation analysis revealed that MMSE scores fully mediated the relationship between serum GFAP levels and FOG-Q scores, accounting for 33.33% of the total effects (indirect effect = 0.01, 95% CI 0.01-0.02). NFL levels differentiated PD-FOG from PD-NoFOG with reliable diagnostic accuracy (AUC 0.75, 95% CI 0.66-0.84), and the combination of NFL, GFAP, duration and MMSE scores demonstrated high accuracy (AUC 0.84, 95% CI 0.76-0.91). Our findings support the notion that NFL and GFAP may be potential biomarkers for the diagnosis of PD-FOG.

Association between serum neurofilament light chain levels and sleep disorders in patients with Parkinson's disease.

OBJECTIVES: This study aimed to investigate the levels of serum neurofilament light chain (NFL) and glial fibrillary acidic protein (GFAP) in patients with Parkinson's disease (PD) and PD patients with sleep disorders (PD-SD), as well as the relationship between these proteins and sleep disorders in PD patients. METHODS: A total of 96 PD patients and 38 healthy controls (HC) were included in this study, of which 70 PD patients experienced sleep disorders. Both motor symptoms and sleep conditions were assessed in all PD patients. The ultrasensitive single molecule array (SIMOA) technique was used to quantify NFL and GFAP in the serum. All data were statistically analyzed using SPSS 23.0. RESULTS: Serum NFL and GFAP levels were significantly higher in PD patients than in HC. Similarly, PD-SD patients exhibited higher levels of these two proteins than PD patients without sleep disorders (PD-NSD). In addition, both serum GFAP and NFL were significantly associated with sleep-related scales in PD patients. After covariate-adjusted binary logistic regression analysis, NFL remained statistically significant in PD patients with or without sleep disorders, unlike GFAP. CONCLUSIONS: Our findings substantiate that serum NFL and GFAP levels are elevated in PD and PD-SD, suggesting neurological axon damage in PD patients, which may be more severe in PD-SD than in PD-NSD. These findings may affect disease diagnosis and provide the foothold for future studies on the underlying mechanisms.

Spatial-Temporal Evolution and Improvement Measures of Embodied Carbon Emissions in Interprovincial Trade for Coal Energy Supply Bases: Case Study of Anhui, China.

On account of the long-term dependence on energy trade and the phenomenon of embodied carbon emissions in interprovincial trade (ECEs-IPT), energy supply bases (ESBs) in the economic integration regions (EIRs) are under unprecedented dual pressure of achieving carbon emissions (CEs) reduction targets and ensuring security and stability of the energy supply. This problem has attracted more and more attention and research by experts and scholars. This paper took Anhui, the coal ESB of the Yangtze River Economic Belt (YREB), as an example and took the key stage of rapid development of regional economic integration (REI) and accelerated the realization of CEs reduction targets in YREB from 2007 to 2017 as the study period. From the perspectives of regions and industry sectors, we calculated the transfer amount of ECEs-IPT in Anhui among the YREB, analyzed the spatial-temporal evolution pattern of ECEs-IPT, and revealed the industrial characteristics of ECEs-IPT. Then, we classified the industry sectors and proposed the direction of industrial improvement measures. The results showed that, during the decade, the amount of provinces undertaking the net ECEs-IPT outflow from Anhui increased significantly and spatially expanded from only Jiangxi Province to almost all of the YREB. In addition, 39.77% of the net ECEs-IPT outflow of Anhui was concentrated in petroleum processing, coking, and nuclear fuel processing (RefPetraol), metal smelting and rolling processing (MetalSmelt), and electricity and heat production and supply (ElectpowerProd) that trade with Shanghai, Jiangsu, Zhejiang, and Jiangxi. The analytical model and results will provide a useful reference for the global similar coal ESBs, especially the coal ESBs within the EIRs, to formulate improvement measures for regions or even the world to ensure stability of the energy supply and achieve regional CEs reduction targets.

Green Economy Development Progress in the Republic of Buryatia (Russia).

Under current conditions, the green economy concept has received a comprehensive response in achieving the sustainable development of regions. However, measuring green economic development progress is dynamic, quantitatively characterized by indicators reflecting various aspects. The difficulty lies in a comprehensive environmental sustainability assessment in a context that includes the territory's environmental, social, and economic factors. The study aimed to assess the progress of the Republic of Buryatia's (Russia) "green" economic development. The proposed methodology for constructing a composite index is based on five dimensions' aggregation-resource efficiency, environmental efficiency, environmental quality of life, natural assets, and institutional factors. The composite index helped generalize the complex processes of the region's environmental-socio-economic development. Its main feature is the reflection of the environmental specificity of the territory. We built a mid-term forecast of the composite and sub-indices, determined their future trend, and assessed the opportunities and conditions for the fastest transition of the Republic of Buryatia to a green economy. The developed composite index is a key tool for regulating green economic development progress, determining prospects, and region management. This paper attempts to fill the gap in a comprehensive assessment of the Republic of Buryatia's current situation using a composite index.

Risk Assessment of China Rapeseed Supply Chain and Policy Suggestions.

Rapeseed, as the most important oil crop in the world, not only affects national food security but also affects energy security and environmental security. It is very important to conduct a risk assessment of China's rapeseed supply chain and put forward suggestions to construct a safe, effective, and accessible supply chain. In order to accurately evaluate the safety of the rapeseed supply chain from 2010 to 2020, we applied fuzzy multiconnection theory and analytic hierarchy process model (AHP). A comprehensive risk assessment model for the rapeseed supply chain with two primary indicators and 10 secondary indicators was constructed. By establishing the rapeseed risk evaluation model, we quantitatively analyzed the risk of China's rapeseed supply chain. The domestic risk of production is still high, and the international risk under the high import dependence is alarming. We put forward risk prevention and countermeasures for China's rapeseed supply chain. The results show that China has a large demand for rapeseed products, but the increase in China production is limited and the import from other countries is unstable. The proposed suggestions are designed to optimize and enhance the stability of the rapeseed product's supply chain. It is recommended to continue to consolidate and deepen the cooperation with traditional trading partners such as Germany, Spain, the United States, and Brazil; expand other import sources to build a more diversified and efficient rapeseed product import network and extend the supply chain of rapeseed products. This research can be a basis for making decisions for promoting the sustainable and efficient development of the rapeseed supply chain.

Socio-Economic Factor Impact on the Republic of Buryatia (Russia) Green Economic Development Transition.

Sustainable green development and environment preservation problems are relevant for unique territories with special economic activity modes, such as the Baikal natural territory. Within Russia, the Republic of Buryatia serves as the model territory for the Lake Baikal ecosystem preservation. Determining the socio-economic development impact on the region's natural environment and resolving contradictions in transition to the green economic development requires the systematization of economic, social, and environmental processes of quantitative information based on the construction of composite indicators. We construct a composite indicator to assess the socio-economic factor's impact on the Republic of Buryatia's current economic state and to compare the current environmental subsystem state and the socio-economic parameters of Buryatia to the average Russian level. We use multiple regression models to determine relationships between various environmental-socio-economic parameters and identify the factors that most impact the environmental states (situations). The measures taken to preserve the unique ecosystem of Lake Baikal have an actual effect. This study shows, that according to the accepted scale, the environmental situation in the region can be characterized as a step towards the green economy transition. The proposed sustainable green development criteria and tools assessment system of the Republic may serve as the basis for forming information and analytical support for an effective economic policy.

Spatio-temporal evolution of urban thermal environment and its driving factors: Case study of Nanjing, China.

In recent years, with rapid urbanization, the underlying urban surface has changed dramatically. Various urban eco-environmental problems have emerged globally, among which the urban heat island effect has become one of the most obvious urban eco-environmental problems. In this study, Nanjing, China, was chosen as the study area. Based on Landsat 8 remote sensing image data collected in Nanjing from 2014 to 2018, land surface temperatures were retrieved, the spatiotemporal variation track and characteristics of the thermal environment pattern were systematically depicted, and the driving factors of these variations were revealed. The results show that over the past five years, the spatial pattern of the heat field in Nanjing changed from a scattered distribution in the periphery of the city to a centralized distribution in the centre of the city, and the heat island intensity increased annually. Changes in administrative divisions, changes in the layout of the transportation trunk lines, transfer of industrial centres, and ecological construction projects are important driving factors for the evolution of the land surface thermal environment patterns of these regions. These research results will provide scientific and technological support for similar cities with typical heat island effects elsewhere in the world to formulate urban development plan, and to improve the urban ecological environment.

Multiregional Input-Output Analysis of Spatial-Temporal Evolution Driving Force for Carbon Emissions Embodied in Interprovincial Trade and Optimization Policies: Case Study of Northeast Industrial District in China.

In the counties with rapid economy and carbon emissions (CEs) growth, CEs embodied in interprovincial trade (CEs-PT) significantly impacts the CEs amount and structure and represents a key issue to consider in CEs reduction policies formulation. This study applied EEBT and two-stage SDA model to analyze the characteristics and driving force of spatial-temporal evolution for net CEs-PT outflow in the Northeast Industrial District of China (NID). We found that, during 1997-2007, the net CEs-PT flowed out from NID to 16 south and east provinces, then to 23 provinces all over China, and its amount has increased 216.798Mt (by 211.67% per year). The main driving forces are technology and demand (further decomposed into structure and scale matrix); the contribution are 71.6418 Mt and 145.1562 Mt. Then, we constructed coupling relationship model and took the top three industries with the greatest net CEs-PT outflow (farming, forestry, animal husbandry and fisheries, electricity and heat production and supply, petroleum processing, coking, and nuclear fuel processing) as examples, adjusted the interprovincial trade constructions, scales, and objects, to reduce the CEs-PT with lower costs, greater effect, and more equitability. The achievement could provide reference for formulating CEs reduction policies for similar areas in the world characterized by rapid growth of economy and CEs.