Background and purpose Faciobrachial dystonic seizures (FBDS) and hyponatremia are the distinct clinical features of autoimmune encephalitis (AE) caused by antibodies against leucine‐rich glioma‐inactivated 1 (LGI1). The present study aims to explore the pathophysiological patterns and neural mechanisms underlying these symptoms. Methods We included 30 patients with anti‐LGI1 AE and 30 controls from a retrospective observational cohort. Whole‐brain metabolic pattern analysis was performed to assess the pathological network of anti‐LGI1 AE, as well as the symptom networks associated with FBDS. Logistic regression was applied to explore independent predictors of FBDS. Finally, we used a multiple regression model to investigate the hyponatremia‐associated brain network and its effect on serum sodium levels. Results The pathological network of anti‐LGI1 AE involved hypermetabolism in the cerebellum, subcortical structures and Rolandic area, as well as hypometabolism in the medial prefrontal cortex. The symptom network of FBDS included hypometabolism in the cerebellum and Rolandic area (pFDR <0.05). Hypometabolism in the cerebellum was an independent predictor of FBDS (p < 0.001). Hyponatremia‐associated network highlighted a negative effect on the caudate nucleus, frontal and temporal white matter. The metabolism of the hypothalamus was negatively associated with (Pearson's R = −0.180, p = 0.342), while not the independent predictor for serum sodium level (path c’ = −7.238, 95% confidence interval = −30.947 to 16.472). Conclusions Our results provide insights into the whole‐brain metabolic patterns of patients with anti‐LGI1 AE, including the symptom network associated with FBDS and the hyponatremia‐associated brain network. The findings help us to understand the neural mechanisms underlying anti‐LGI1 AE and to evaluate the progress of this disease.

With the explosive increase in Mobile apps, more and more threats migrate from traditional PC client to mobile device. Compared with traditional Win+Intel alliance in PC, Android+ARM alliance dominates in Mobile Internet, the apps replace the PC client software as the major target of malicious usage. In this paper, to improve the security status of current mobile apps, we propose a methodology to evaluate mobile apps based on Cloud Computing platform and data mining. We also present a prototype system named MobSafe to identify the mobile app's virulence or benignancy. Compared with traditional method, such as permission pattern based method etc., MobSafe combines the dynamic and static analysis method to comprehensively evaluate a android app. In the implementation, we adopt ASEF and SAAF framework, the two representative dynamic and static analysis method, to evaluate the android apps and estimate the total time needed to evaluate all the apps stored in one mobile app market. Based on the real trace from a commercial mobile app market called AppChina, we can collect the statistics that the number of active android apps, the average number apps installed in one android device and the expanding ratio of mobile apps. As mobile app market serves as the main line of defence against mobile malwares, our evaluation results shown that it is practical to use cloud computing platform and data mining to verify all stored apps routinely to filter out malware apps from mobile app markets. As the future work, MobSafe can extensively use machine learning to conduct automotive forensic analysis of mobile apps based on the generated multifaceted data in this stage.

The function of the root system is crucial for plant survival, such as anchoring plants, absorbing nutrients and water from the soil, and adapting to stress. MYB transcription factors constitute one of the largest transcription factor families in plant genomes with structural and functional diversifications. Members of this superfamily in plant development and cell differentiation, specialized metabolism, and biotic and abiotic stress processes are widely recognized, but their roles in plant roots are still not well characterized. Recent advances in functional studies remind us that MYB genes may have potentially key roles in roots. In this review, the current knowledge about the functions of MYB genes in roots was summarized, including promoting cell differentiation, regulating cell division through cell cycle, response to biotic and abiotic stresses (e.g., drought, salt stress, nutrient stress, light, gravity, and fungi), and mediate phytohormone signals. MYB genes from the same subfamily tend to regulate similar biological processes in roots in redundant but precise ways. Given their increasing known functions and wide expression profiles in roots, MYB genes are proposed as key components of the gene regulatory networks associated with distinct biological processes in roots. Further functional studies of MYB genes will provide an important basis for root regulatory mechanisms, enabling a more inclusive green revolution and sustainable agriculture to face the constant changes in climate and environmental conditions.