Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China

Continuous air pollution (CAP) incidents last even longer and generate greater health hazards relative to conventional air pollution episodes. However, few studies have focused on the spatiotemporal distribution characteristics and driving factors of CAP in China. Drawing on the daily reported ground monitoring data on the ambient air quality in 2019 in China, this paper identifies the spatiotemporal distribution characteristics of CAP across 337 Chinese cities above the prefecture level using descriptive statistics and spatial statistical analysis methods, and further examines the spatial heterogeneity effects of both socioeconomic factors and natural factors on CAP with a Multiscale Geographically Weighted Regression (MGWR) model. The results show that the average proportion of CAP days in 2019 reached 11.50% of the whole year across Chinese cities, a figure equaling to about 65 days, while the average frequency, the maximum amount of days and the average amount of days of CAP were 8.02 times, 7.85 days and 4.20 days, respectively. Furthermore, there was a distinct spatiotemporal distribution disparity in CAP in China. Spatially, the areas with high proportions of CAP days were concentrated in the North China Plain and the Southwestern Xinjiang Autonomous Region in terms of the spatial pattern, while the proportion of CAP days showed a monthly W-shaped change in terms of the temporal pattern. In addition, the types of regions containing major pollutants during the CAP period could be divided into four types, including “Composite pollution”, “O3 + NO2 pollution”, “PM10 + PM2.5 pollution” and “O3 + PM2.5 pollution”, while the region type “PM10 + PM2.5 pollution” covered the highest number of cities. The MGWR model, characterized by multiple spatial scale impacts among the driving factors, outperformed the traditional OLS and GWR model, and both socioeconomic factors and natural factors were found to have a spatial non-stationary relationship with CAP in China. Our findings provide new policy insights for understanding the spatiotemporal distribution characteristics of CAP in urban China and can help the Chinese government make prevention and control measures of CAP incidents

Structural and functional hippocampal alterations in Multiple sclerosis and neuromyelitis optica spectrum disorder

Background: Hippocampal involvement may differ between multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD). Objective: To investigate the morphometric, diffusion and functional alterations in hippocampus in MS and NMOSD and the clinical significance. Methods: A total of 752 participants including 236 MS, 236 NMOSD and 280 healthy controls (HC) were included in this retrospective multi-center study. The hippocampus and subfield volumes, fractional anisotropy (FA) and mean diffusivity (MD), amplitude of low frequency fluctuation (ALFF) and degree centrality (DC) were analyzed, and their associations with clinical variables were investigated. Results: The hippocampus showed significantly lower volume, FA and greater MD in MS compared to NMOSD and HC (p 0.7). Conclusions: Hippocampal atrophy and diffusion abnormalities were identified in MS and NMOSD, partly explaining how clinical disability and cognitive impairment are differentially affected

Subtyping relapsing–remitting multiple sclerosis using structural MRI

Background and purpose: Subtyping relapsing–remitting multiple sclerosis (RRMS) patients may help predict disease progression and triage patients for treatment. We aimed to subtype RRMS patients by structural MRI and investigate their clinical significances. Methods: 155 relapse-remitting MS (RRMS) and 210 healthy controls (HC) were retrospectively enrolled with structural 3DT1, diffusion tensor imaging (DTI) and resting-state functional MRI. Z scores of cortical and deep gray matter volumes (CGMV and DGMV) and white matter fractional anisotropy (WM-FA) in RRMS patients were calculated based on means and standard deviations of HC. We defined RRMS as “normal” (− 2 < z scores of both GMV and WM-FA), DGM (z scores of DGMV < − 2), and DGM-plus types (z scores of DGMV and [CGMV or WM-FA] < − 2) according to combinations of z scores compared to HC. Expanded disability status scale (EDSS), cognitive and functional MRI measurements, and conversion rate to secondary progressive MS (SPMS) at 5-year follow-up were compared between subtypes. Results: 77 (49.7%) patients were “normal” type, 37 (23.9%) patients were DGM type and 34 (21.9%) patients were DGM-plus type. 7 (4.5%) patients who were not categorized into the above types were excluded. DGM-plus type had the highest EDSS. Both DGM and DGM-plus types had more severe cognitive impairment than “normal” type. Only DGM-plus type showed decreased functional MRI measures compared to HC. A higher conversion ratio to SPMS in DGM-plus type (55%) was identified compared to “normal” type (14%, p < 0.001) and DGM type (20%, p = 0.005). Conclusion: Three MRI-subtypes of RRMS were identified with distinct clinical and imaging features and different prognosis

Cerebellar connectome alterations and associated genetic signatures in multiple sclerosis and neuromyelitis optica spectrum disorder

BACKGROUND: The cerebellum plays key roles in the pathology of multiple sclerosis (MS) and neuromyelitis optica spectrum disorder (NMOSD), but the way in which these conditions affect how the cerebellum communicates with the rest of the brain (its connectome) and associated genetic correlates remains largely unknown.METHODS: Combining multimodal MRI data from 208 MS patients, 200 NMOSD patients and 228 healthy controls and brain-wide transcriptional data, this study characterized convergent and divergent alterations in within-cerebellar and cerebello-cerebral morphological and functional connectivity in MS and NMOSD, and further explored the association between the connectivity alterations and gene expression profiles.RESULTS: Despite numerous common alterations in the two conditions, diagnosis-specific increases in cerebellar morphological connectivity were found in MS within the cerebellar secondary motor module, and in NMOSD between cerebellar primary motor module and cerebral motor- and sensory-related areas. Both diseases also exhibited decreased functional connectivity between cerebellar motor modules and cerebral association cortices with MS-specific decreases within cerebellar secondary motor module and NMOSD-specific decreases between cerebellar motor modules and cerebral limbic and default-mode regions. Transcriptional data explained &gt; 37.5% variance of the cerebellar functional alterations in MS with the most correlated genes enriched in signaling and ion transport-related processes and preferentially located in excitatory and inhibitory neurons. For NMOSD, similar results were found but with the most correlated genes also preferentially located in astrocytes and microglia. Finally, we showed that cerebellar connectivity can help distinguish the three groups from each other with morphological connectivity as predominant features for differentiating the patients from controls while functional connectivity for discriminating the two diseases.CONCLUSIONS: We demonstrate convergent and divergent cerebellar connectome alterations and associated transcriptomic signatures between MS and NMOSD, providing insight into shared and unique neurobiological mechanisms underlying these two diseases.</p