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Background With the aging trend intensifying in China, the number of super-aged population (≥80 years old) is also increasing. This demographic faces a notable decline in balance and reaction capabilities, resulting in an elevated risk of falls than that of other age groups of the elderly. Falls leading to long-term bedridden risk of falls often pose a serious disease burden to families and society. Exploring the potential risk factors for falls in the super-aged people may provide reference for the fall prevention in this population. Objective To identify long-term bedridden risk of falls in super-aged population and develop a risk predictive model. Methods A prospective cohort study was conducted to collect relevant information based on the China Health and Retirement Longitudinal Study questionnaire among the super-aged people who regularly participate in annual physical examination in five districts and counties of Shanghai and Hangzhou from March to November 2015, and to follow up and observe long-term bedridden caused by falls (endpoint events) and death (competing events), a competing risk model was constructed to analyze the influencing factors of long-term bedridden caused by falls. Independent risk factors identified by the competing risk model were used to construct a risk predictive model and nomogram of long-term bedridden risk of falls in super-aged population, and receiver operating characteristic (ROC) curve was plotted to evaluate the accuracy of the model. Results A total of 986 super-aged individuals were included in this study, including 431 (43.7%) males and 555 (56.3%) females, with an average age of (89.8±5.2) years. After 8 years of follow-up, 96 people were lost to follow-up, with a loss rate of 9.7%; endpoint events occurred in 165 people with an incidence rate of 16.7%; 134 people had competing events, with an incidence rate of 13.6%. Competing risk model analysis showed an increase in muscle strength (HR=1.071, 95%CI=1.049-1.091), age>85 years (HR=1.954, 95%CI=1.255-3.042), rural household location (HR=1.946, 95%CI=1.385-2.731), poor sleep quality (HR=5.756, 95%CI=3.904-8.491), cataract (HR=1.832, 95%CI=1.201-2.794), diabetes (HR=1.549, 95%CI=1.121-2.143), cognitive impairment (HR=1.717, 95%CI=1.258-2.344) were independent risk factors for long-term bedridden caused by falls in elderly population under the influence of competing events, and the difference was statistically significant (P

Introduction: Intracranial aneurysm (IA) is a common vascular enlargement that occurs in the wall of cerebral vessels and frequently leads to fatal subarachnoid hemorrhage. PDZ and LIM domain protein 1 (PDLIM1) is a cytoskeletal protein that functions as a platform for multiple protein complex formation. However, whether PDLIM is involved in the pathogenesis of IA remains poorly understood. Methods: Loss-of-function and gain-of-function strategies were employed to determine the in vitro roles of PDLIM1 in vascular endothelial cells (VECs). A rat model of IA was generated to study the role of PDLIM1 in vivo. Gene expression profiling, Western blotting, and dual luciferase reporter assays were performed to uncover the underlying cellular mechanism. Clinical IA samples were used to determine the expression of PDLIM1 and its downstream signaling molecules. Results: PDLIM1 expression was reduced in the endothelial cells of IA and was regulated by Yes-associated protein 1 (YAP1). Genetic silencing of PDLIM1 inhibited the viability, migratory ability, and tube formation ability of VECs. Opposite results were obtained by ectopic expression of PDLIM1. Additionally, PDLIM1 overexpression mitigated IA in vivo. Mechanistic investigations revealed that PDLIM1 promoted the transcriptional activity of β-catenin and induced the expression of v-myc myelocytomatosis viral oncogene homolog (MYC) and cyclin D1 (CCND1). In clinical settings, reduced expression of PDLIM1 and β-catenin downstream target genes was observed in human IA samples. Conclusion: Our study indicates that YAP1-dependent expression of PDLIM1 can inhibit IA development by modulating the activity of the Wnt/β-catenin signaling pathway and that PDLIM1 deficiency in VECs may represent a potential marker of aggressive disease. [ABSTRACT FROM AUTHOR]

China has built a nationwide transportation network, but there needs to be a smooth connection and transfer between different modes. Five networks are constructed to explore the characteristics of a multimodal comprehensive transportation network (CNet) in Jiangsu Province based on the optimized modeling method and multisource data. Statistical and robustness characteristics are analyzed for CNet and other single-mode networks including the highway, railway, navigation channel and airway networks (HNet, RNet, NNet and ANet, respectively). The research results show following: (ⅰ) In Jiangsu, CNet, HNet, RNet and NNet are not scale-free networks and do not have small-world properties. However, ANet is the opposite. (ⅱ) The five networks in Jiangsu are robust to the random attack and their robustness changes during the attack. However, their robustness is different under different calculated attacks. For all attack strategies, CNet is the most robust. (ⅲ) In Jiangsu, the three optimized methods enhance the robustness significantly. The network failure is delayed by 12.34, 2.79 and 2.44%, respectively. The average connectivity degree is improved by 265.69, 52.95 and 32.54%, respectively. The more hubs there are with powerful transfer capacity, the stronger the network robustness. The results reveal the key points of the construction of a multimodal comprehensive transportation system and can guide the design and optimization of it. [ABSTRACT FROM AUTHOR]