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Background: Sarcopenia is critically associated with morbidity and mortality in the progression of Parkinson's disease (PD). However, analyses of clinical severity and brain changes, such as white matter (WM) alterations in PD patients with sarcopenia are limited. Further understanding of the factors associated with sarcopenia may provide a focused screen and potential for early intervention in PD patients. Methods: 52 PD patients and 19 healthy participants accepted dual-energy X-ray absorptiometry to measure the body composition. Using diffusion tensor imaging, the difference of WM integrity was measured between PD patients with sarcopenia (PDSa) and without sarcopenia (PDNSa). Multivariate analysis was performed to explore the relationships between clinical factors, WM integrity, and sarcopenia in PD patients. Results: 21 PD patients (40.4%) had sarcopenia. PDSa had a higher Unified Parkinson's Disease Rating Scale (UPDRS III) score, lower body mass index (BMI) and lower fat weight compared with the PDNSa. Additionally, PDSa patients exhibited lower fractional anisotropy accompanied by higher radial diffusivity and/or higher mean diffusivity in the fronto-striato-thalamic circuits, including bilateral cingulum, left superior longitudinal fasciculus, left genu of corpus callosum, and right anterior thalamic radiation, which participate in the executive function. In addition, decreased muscle mass was associated with worse WM integrity in these regions. Multiple linear regression analysis revealed that WM integrity in the left cingulum, right anterior thalamic radiation, together with gender (male) significantly predicted muscle mass in PD patients. Conclusions: WM alterations in the executive network, such as the fronto-striato-thalamic circuits, may indicate a risk factor for ongoing sarcopenia in PD patients. The effectiveness of using executive function to serve as a prodromal marker of sarcopenia in PD patients should be evaluated in future studies.

With the rapid economic development of industrial rural areas in Southern Jiangsu, the rural landscape and ecological environment of these industrial rural areas are getting damaged. Based on GIS and RS techniques, Landsat Satellite remote sensing images from 1981, 1991, 2001, 2011 and 2018 were collected for Jiangyin, Zhangjiagang, Changshu and Kunshan, to extract landscape pattern indexes and spatial distribution data. Landscape pattern indexes of the patch-class level and landscape level from each year were calculated by FRAGSTATS. After analyzing and comparing landscape pattern variation of five years, progress, characteristics and driving forces of landscape pattern evolution were explored. At the patch-class level, construction land had continuously encroached on green and cultivated land, exhibiting trends of expansion and centralization. At the landscape level, the number of small patches and degree of landscape fragmentation generally increased. The direct cause of landscape pattern evolution in industrial rural areas of Southern Jiangsu was the encroachment and segmentation of green and cultivated land by construction land, and the dominant factors driving the changes in construction land in the industrial rural areas of Southern Jiangsu were the effects of land and population aggregation exerted by the development of township enterprises and rural industries.

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