On Tree-Based Neural Sentence Modeling

Neural networks with tree-based sentence encoders have shown better results on many downstream tasks. Most of existing tree-based encoders adopt syntactic parsing trees as the explicit structure prior. To study the effectiveness of different tree structures, we replace the parsing trees with trivial trees (i.e., binary balanced tree, left-branching tree and right-branching tree) in the encoders. Though trivial trees contain no syntactic information, those encoders get competitive or even better results on all of the ten downstream tasks we investigated. This surprising result indicates that explicit syntax guidance may not be the main contributor to the superior performances of tree-based neural sentence modeling. Further analysis show that tree modeling gives better results when crucial words are closer to the final representation. Additional experiments give more clues on how to design an effective tree-based encoder. Our code is open-source and available at https://github.com/ExplorerFreda/TreeEnc.Comment: To Appear at EMNLP 201

Hierarchical community structure in networks

Modular and hierarchical structures are pervasive in real-world complex systems. A great deal of effort has gone into trying to detect and study these structures. Important theoretical advances in the detection of modular, or "community", structures have included identifying fundamental limits of detectability by formally defining community structure using probabilistic generative models. Detecting hierarchical community structure introduces additional challenges alongside those inherited from community detection. Here we present a theoretical study on hierarchical community structure in networks, which has thus far not received the same rigorous attention. We address the following questions: 1)~How should we define a valid hierarchy of communities? 2)~How should we determine if a hierarchical structure exists in a network? and 3)~how can we detect hierarchical structure efficiently? We approach these questions by introducing a definition of hierarchy based on the concept of stochastic externally equitable partitions and their relation to probabilistic models, such as the popular stochastic block model. We enumerate the challenges involved in detecting hierarchies and, by studying the spectral properties of hierarchical structure, present an efficient and principled method for detecting them.Comment: 22 pages, 12 figure

The potential role of kallistatin in the development of Abdominal Aortic Aneurysm

Abdominal aortic aneurysm (AAA) is a vascular condition that causes permanent dilation of the abdominal aorta, which can lead to death due to aortic rupture. The only treatment for AAA is surgical repair, and there is no current drug treatment for AAA. Aortic inflammation, vascular smooth muscle cell apoptosis, angiogenesis, oxidative stress and vascular remodeling are implicated in AAA pathogenesis. Kallistatin is a serine proteinase inhibitor, which has been shown to have a variety of functions, potentially relevant in AAA pathogenesis. Kallistatin has been reported to have inhibitory effects on tumor necrosis factor alpha (TNF-α) signaling induced oxidative stress and apoptosis. Kallistatin also inhibits vascular endothelial growth factor (VEGF) and Wnt canonical signaling, which promote inflammation, angiogenesis, and vascular remodeling in various pre-clinical experimental models. This review explores the potential protective role of kallistatin in AAA pathogenesis

Risk factors and mouse models of abdominal aortic aneurysm rupture

Abdominal aortic aneurysm (AAA) rupture is an important cause of death in older adults. In clinical practice, the most established predictor of AAA rupture is maximum AAA diameter. Aortic diameter is commonly used to assess AAA severity in mouse models studies. AAA rupture occurs when the stress (force per unit area) on the aneurysm wall exceeds wall strength. Previous research suggests that aortic wall structure and strength, biomechanical forces on the aorta and cellular and proteolytic composition of the AAA wall influence the risk of AAA rupture. Mouse models offer an opportunity to study the association of these factors with AAA rupture in a way not currently possible in patients. Such studies could provide data to support the use of novel surrogate markers of AAA rupture in patients. In this review, the currently available mouse models of AAA and their relevance to the study of AAA rupture are discussed. The review highlights the limitations of mouse models and suggests novel approaches that could be incorporated in future experimental AAA studies to generate clinically relevant results

Kallistatin limits abdominal aortic aneurysm by attenuating generation of reactive oxygen species and apoptosis

Inflammation, vascular smooth muscle cell apoptosis and oxidative stress are believed to play important roles in abdominal aortic aneurysm (AAA) pathogenesis. Human kallistatin (KAL; gene SERPINA4) is a serine proteinase inhibitor previously shown to inhibit inflammation, apoptosis and oxidative stress. The aim of this study was to investigate the role of KAL in AAA through studies in experimental mouse models and patients. Serum KAL concentration was negatively associated with the diagnosis and growth of human AAA. Transgenic overexpression of the human KAL gene (KS-Tg) or administration of recombinant human KAL (rhKAL) inhibited AAA in the calcium phosphate (CaPO4) and subcutaneous angiotensin II (AngII) infusion mouse models. Upregulation of KAL in both models resulted in reduction in the severity of aortic elastin degradation, reduced markers of oxidative stress and less vascular smooth muscle apoptosis within the aorta. Administration of rhKAL to vascular smooth muscle cells incubated in the presence of AngII or in human AAA thrombus-conditioned media reduced apoptosis and downregulated markers of oxidative stress. These effects of KAL were associated with upregulation of Sirtuin 1 activity within the aortas of both KS-Tg mice and rodents receiving rhKAL. These results suggest KAL-Sirtuin 1 signalling limits aortic wall remodelling and aneurysm development through reductions in oxidative stress and vascular smooth muscle cell apoptosis. Upregulating KAL may be a novel therapeutic strategy for AAA. © 2021, The Author(s)