Clustering by measuring local direction centrality for data with heterogeneous density and weak connectivity.

Clustering is a powerful machine learning method for discovering similar patterns according to the proximity of elements in feature space. It is widely used in computer science, bioscience, geoscience, and economics. Although the state-of-the-art partition-based and connectivity-based clustering methods have been developed, weak connectivity and heterogeneous density in data impede their effectiveness. In this work, we propose a boundary-seeking Clustering algorithm using the local Direction Centrality (CDC). It adopts a density-independent metric based on the distribution of K-nearest neighbors (KNNs) to distinguish between internal and boundary points. The boundary points generate enclosed cages to bind the connections of internal points, thereby preventing cross-cluster connections and separating weakly-connected clusters. We demonstrate the validity of CDC by detecting complex structured clusters in challenging synthetic datasets, identifying cell types from single-cell RNA sequencing (scRNA-seq) and mass cytometry (CyTOF) data, recognizing speakers on voice corpuses, and testifying on various types of real-world benchmarks.

Effect of quercetin on chondrocyte phenotype and extracellular matrix expression.

Due to the poor repair ability of cartilage tissue, regenerative medicine still faces great challenges in the repair of large articular cartilage defects. Quercetin is widely applied as a traditional Chinese medicine in tissue regeneration including liver, bone and skin tissues. However, the evidence for its effects and internal mechanisms for cartilage regeneration are limited. In the present study, the effects of quercetin on chondrocyte function were systematically evaluated by CCK8 assay, PCR assay, cartilaginous matrix staining assays, immunofluorescence assay, and western blotting. The results showed that quercetin significantly up-regulated the expression of chondrogenesis genes and stimulated the secretion of GAG (glycosaminoglycan) through activating the ERK, P38 and AKT signalling pathways in a dose-dependent manner. Furthermore, in vivo experiments revealed that quercetin-loaded silk protein scaffolds dramatically stimulated the formation of new cartilage-like tissue with higher histological scores in rat femoral cartilage defects. These data suggest that quercetin can effectively stimulate chondrogenesis in vitro and in vivo, demonstrating the potential application of quercetin in the regeneration of cartilage defects.

Clinical and imaging features of intraosseous arteriovenous malformations in jaws: a 15-year experience of single centre.

Intraosseous arteriovenous malformations in jaws (j-AVMs) are rare congenital high-flow vascular anomalies with a high tendency of life-threatening haemorrhage and are regarded as one of the most dangerous haemorrhagic diseases in maxillofacial region. Pre-treatment clinical and imaging evaluations serve as the most important diagnostic modalities. A retrospective study involved 211 patients with j-AVMs from November 2003 to November 2017 was performed. The male-to-female ratio of j-AVMs was approximately 4:3. The mean age of the patients with j-AVMs is 21.86. Bleeding was the main complaint associated with j-AVMs. J-AVMs occurred in the mandible more often than in the maxilla (64.93% and 32.23%, respectively). Most j-AVMs (95.26%) occurred in the posterior teeth region. Classical imaging features of j-AVMs included: an unclear maxillary sinus with a mild ground-glass appearance (maxillary j-AVMs) and a clear oval or irregular lucency that is mostly centred on the root of the first molar (mandibular j-AVMs) on OPGs, enhancement in the cancellous bone on contrast-enhanced CTs. Other atypical features of j-AVMs were also concluded. A comprehensive diagnose system based on clinical and imaging features of j-AVMs could provide valuable reference data for clinical management of j-AVMs and help avoid improper iatrogenic trauma or delayed treatment.

A hierarchical temporal attention-based LSTM encoder-decoder model for individual mobility prediction.

Prediction of individual mobility is crucial in human mobility related applications. Whereas, existing research on individual mobility prediction mainly focuses on next location prediction and short-term dependencies between traveling locations. Long-term location sequence prediction is of great importance for long-time traffic planning and location advertising, and long-term dependencies exist as individual mobility regularity typically occurs daily and weekly. This paper proposes a novel hierarchical temporal attention-based LSTM encoder-decoder model for individual location sequence prediction. The proposed hierarchical attention mechanism captures both long-term and short-term dependencies underlying in individual longitudinal trajectories, and uncovers frequential and periodical mobility patterns in an interpretable manner by incorporating the calendar cycle of individual travel regularities into location prediction. More specifically, the hierarchical attention consists of local temporal attention to identify highly related locations in each day, and global temporal attention to discern important travel regularities over a week. Experiments on individual trajectory datasets with varying degree of traveling uncertainty demonstrate that our method outperforms four baseline methods on three evaluation metrics. In addition, we explore the interpretability of the proposed model in understanding individual daily, and weekly mobility patterns by visualizing the temporal attention weights and frequent traveling patterns associated with locations.

Comprehensive analysis of dysregulated exosomal long non-coding RNA networks associated with arteriovenous malformations.

Arteriovenous malformations (AVMs) are congenital vascular lesions with a high tendency for aggravation and recurrence after treatment, and their genesis remains enigmatic. In this study, we investigated exosomal long non-coding RNA (lncRNA) and mRNA expression and constructed a competitive endogenous RNA regulatory network in AVMs. Ethics approval was provided, and informed written consent was given prior to the inclusion of all participants. Blood samples were obtained from patients with AVMs and healthy controls at Shanghai Ninth People's Hospital, China, from May to November 2018, and total exosomes were isolated and validated. Differentially expressed exosomal lncRNAs and mRNAs were detected by RNA-seq, analysed by bioinformatic methods and validated by qRT-PCR. A competitive endogenous RNA regulatory network was constructed. The characteristics of the captured extracellular vesicles conformed to the features of exosomes. A total of 117 dysregulated exosomal lncRNAs and 1159 dysregulated exosomal mRNAs were identified in AVMs. qRT-PCR demonstrated that the exosomal lncRNAs MIR4435-1HG, LINC00657, LOC101927854 and SEPT5-GP1BB were upregulated in AVM exosomes. The Gene Ontology (GO) terms haemopoiesis and negative regulation of neuron projection development were significantly enriched in relation to dysregulated exosomal cis lncRNAs. A total of 199 GO terms and 80 Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways were enriched for the dysregulated exosomal mRNAs. In the exosomal lncRNA-miRNA-mRNA-related ceRNA regulatory network, the top 3 significant modules involved 31 dysregulated exosomal lncRNAs and 114 dysregulated exosomal mRNAs, which were enriched in the Rap 1, Ras, MAPK signalling pathways and platelet activation KEGG pathway. This study comprehensively identified dysregulated exosomal lncRNAs and mRNAs in AVMs, demonstrated the involvement of dysregulated lncRNA and mRNA patterns in AVMs and constructed an exosomal competitive endogenous RNA regulatory network.

Leptin-Induced Angiogenesis of EA.Hy926 Endothelial Cells via the Akt and Wnt Signaling Pathways In Vitro and In Vivo.

Angiogenesis involves the activation of endothelial cells followed by capillary formation. Leptin, the protein product of the ob gene, can induce the angiogenic potential of endothelial cells. However, the underlying cellular mechanism still remains to be elicited. We firstly evaluated the in vitro effects of leptin on proliferation and angiogenic differentiation of endothelial cell line EA.hy926. Leptin was found to potently induced cell proliferation, expression of angiogenic gene, migration and tube formation. Then we investigated the roles of the Akt and Wnt signaling pathways in the aforementioned processes. It showed that Akt and Wnt signaling pathways could be activated by leptin, while inhibition of the Akt and Wnt signaling pathways by siRNAs effectively blocked the leptin-induced angiogenesis. Finally, we used electrospinning to fabricated leptin-immobilized linear poly(L-lactide-co-caprolactone) (PLCL)-leptin. The in vivo vessel formation of PLCL-leptin was evaluated using subcutaneous implants in Sprague-Dawley rats. The histological and immunofluorescence revealed that cell infiltration with PLCL-leptin was much more significant than that with the control PLCL group. More importantly, the number of laminin+ vessels and CD31+ cells in PLCL-leptin grafts was significantly higher than in control grafts. The study demonstrated that it is via Akt and Wnt signaling pathways that leptin promotes the proliferation and angiogenic differentiation of endothelial cells and the capacity of endogenous tissue regeneration makes the novel leptin-conjugated PLCL promising materials for grafts.

Quercetin alleviates rat osteoarthritis by inhibiting inflammation and apoptosis of chondrocytes, modulating synovial macrophages polarization to M2 macrophages.

Osteoarthritis (OA) is a progressive joint disorder that is primarily characterized by the degeneration and destruction of the articular cartilage. Cartilage matrix degradation, production of proinflammatory mediators, chondrocyte apoptosis and activation of macrophages in the synovial are involved in OA pathogenesis. Current non-surgical therapies for OA mainly aim at relieving pain but can barely alleviate the progression of OA. Quercetin, a naturally occurring flavonoid has shown potent anti-inflammatory effects, however, its effects and underlying mechanisms on OA have seldom been systematically illuminated. In this study, we explored the protective effects of quercetin on repairing OA-induced cartilage injuries and its possible mechanisms. In vitro, quercetin remarkably suppressed the expression of matrix degrading proteases and inflammatory mediators, meantime promoted the production of cartilage anabolic factors in interleukin-1ß-induced (IL-1ß) rat chondrocytes. In addition, quercetin exhibited anti-apoptotic effects by decreasing intracellular reactive oxygen species (ROS), restoring mitochondrial membrane potential (MMP) and inhibiting the Caspase-3 pathway in apoptotic rat chondrocytes. Moreover, quercetin induced M2 polarization of macrophages and upregulated the expression of transforming growth factor ß (TGF-ß) and insulin-like growth factor (IGF), which in turn created a pro-chondrogenic microenvironment for chondrocytes and promoted the synthesis of glycosaminoglycan (GAG) in chondrocytes. In vivo, intra-articular injection of quercetin alleviated the degradation of the cartilage and the apoptosis of chondrocytes in a rat OA model. Moreover, the expression of TGF-ß1 and TGF-ß2 in the synovial fluid and the ratio of M2 macrophages in the synovial membrane were elevated. In summary, our study proves that quercetin exerts chondroprotective effects by inhibiting inflammation and apoptosis of chondrocytes, modulating synovial macrophages polarization to M2 macrophages and creating a pro-chondrogenic environment for chondrocytes to enhance cartilage repair under OA environment. It is suggested that quercetin may serve as a potential drug for OA treatment.

Stimulatory Effects of Boron Containing Bioactive Glass on Osteogenesis and Angiogenesis of Polycaprolactone: In Vitro Study.

Polycaprolactone (PCL) has attracted great attention for bone regeneration attributed to its cost-efficiency, high toughness, and good processability. However, the relatively low elastic modulus, hydrophobic nature, and insufficient bioactivity of pure PCL limited its wider application for bone regeneration. In the present study, the effects of the addition of boron containing bioactive glass (B-BG) materials on the mechanical properties and biological performance of PCL polymer were investigated with different B-BG contents (0, 10, 20, 30, and 40 wt.%), in order to evaluate the potential applications of B-BG/PCL composites for bone regeneration. The results showed that the B-BG/PCL composites possess better tensile strength, human neutral pH value, and fast degradation as compared to pure PCL polymers. Moreover, the incorporation of B-BG could enhance proliferation, osteogenic differentiation, and angiogenic factor expression for rat bone marrow stromal cells (rBMSCs) as compared to pure PCL polymers. Importantly, the B-BG also promoted the angiogenic differentiation for human umbilical vein endothelial cells (HUVECs). These enhanced effects had a concentration dependence of B-BG content, while 30 wt.% B-BG/PCL composites achieved the greatest stimulatory effect. Therefore the 30 wt.% B-BG/PCL composites have potential applications in bone reconstruction fields.

The Effects of Leptin on the Proliferation and Differentiation of Primary Chondrocytes in Vitro and Cartilage Regeneration in Vivo.

Patients with cartilage damage have various discomforts, including pain, clicks, deformities, and dysfunction. Chondrocytes are a crucial component of cartilage restoration; however, their limited proliferative ability and degenerative specificity dramatically reduce their effectiveness. In the present study, the effects of leptin on chondrocyte proliferation, chondrogenic and secretion marker gene expression, and chondrocyte cartilage matrix component secretion were evaluated in vitro. The roles of the mitogen-activated protein kinase (MAPK) and protein kinase B (AKT) signaling pathways in these processes were also investigated. More importantly, a leptin sustained release system was developed using a hydrogel with calcium alginate microspheres and was transplanted into cartilage defects in rabbit femurs to analyze the effect of leptin on promoting cartilage restoration. The results showed that leptin promoted cell proliferation and chondrocyte gene expression in a dose-dependent manner, and a concentration of 100 ng/mL leptin had the greatest effect. The activation of the P38 and AKT signaling pathways might be responsible for these effects. An improved in vivo restoration outcome was observed in the leptin sustained release group compared with the control group. These results suggest that leptin could be used as a suitable drug for cartilage restoration.

Content-Based Discovery for Web Map Service using Support Vector Machine and User Relevance Feedback.

Many discovery methods for geographic information services have been proposed. There are approaches for finding and matching geographic information services, methods for constructing geographic information service classification schemes, and automatic geographic information discovery. Overall, the efficiency of the geographic information discovery keeps improving., There are however, still two problems in Web Map Service (WMS) discovery that must be solved. Mismatches between the graphic contents of a WMS and the semantic descriptions in the metadata make discovery difficult for human users. End-users and computers comprehend WMSs differently creating semantic gaps in human-computer interactions. To address these problems, we propose an improved query process for WMSs based on the graphic contents of WMS layers, combining Support Vector Machine (SVM) and user relevance feedback. Our experiments demonstrate that the proposed method can improve the accuracy and efficiency of WMS discovery.

Developing Subdomain Allocation Algorithms Based on Spatial and Communicational Constraints to Accelerate Dust Storm Simulation.

Dust storm has serious disastrous impacts on environment, human health, and assets. The developments and applications of dust storm models have contributed significantly to better understand and predict the distribution, intensity and structure of dust storms. However, dust storm simulation is a data and computing intensive process. To improve the computing performance, high performance computing has been widely adopted by dividing the entire study area into multiple subdomains and allocating each subdomain on different computing nodes in a parallel fashion. Inappropriate allocation may introduce imbalanced task loads and unnecessary communications among computing nodes. Therefore, allocation is a key factor that may impact the efficiency of parallel process. An allocation algorithm is expected to consider the computing cost and communication cost for each computing node to minimize total execution time and reduce overall communication cost for the entire simulation. This research introduces three algorithms to optimize the allocation by considering the spatial and communicational constraints: 1) an Integer Linear Programming (ILP) based algorithm from combinational optimization perspective; 2) a K-Means and Kernighan-Lin combined heuristic algorithm (K&K) integrating geometric and coordinate-free methods by merging local and global partitioning; 3) an automatic seeded region growing based geometric and local partitioning algorithm (ASRG). The performance and effectiveness of the three algorithms are compared based on different factors. Further, we adopt the K&K algorithm as the demonstrated algorithm for the experiment of dust model simulation with the non-hydrostatic mesoscale model (NMM-dust) and compared the performance with the MPI default sequential allocation. The results demonstrate that K&K method significantly improves the simulation performance with better subdomain allocation. This method can also be adopted for other relevant atmospheric and numerical modeling.

A service brokering and recommendation mechanism for better selecting cloud services.

Cloud computing is becoming the new generation computing infrastructure, and many cloud vendors provide different types of cloud services. How to choose the best cloud services for specific applications is very challenging. Addressing this challenge requires balancing multiple factors, such as business demands, technologies, policies and preferences in addition to the computing requirements. This paper recommends a mechanism for selecting the best public cloud service at the levels of Infrastructure as a Service (IaaS) and Platform as a Service (PaaS). A systematic framework and associated workflow include cloud service filtration, solution generation, evaluation, and selection of public cloud services. Specifically, we propose the following: a hierarchical information model for integrating heterogeneous cloud information from different providers and a corresponding cloud information collecting mechanism; a cloud service classification model for categorizing and filtering cloud services and an application requirement schema for providing rules for creating application-specific configuration solutions; and a preference-aware solution evaluation mode for evaluating and recommending solutions according to the preferences of application providers. To test the proposed framework and methodologies, a cloud service advisory tool prototype was developed after which relevant experiments were conducted. The results show that the proposed system collects/updates/records the cloud information from multiple mainstream public cloud services in real-time, generates feasible cloud configuration solutions according to user specifications and acceptable cost predication, assesses solutions from multiple aspects (e.g., computing capability, potential cost and Service Level Agreement, SLA) and offers rational recommendations based on user preferences and practical cloud provisioning; and visually presents and compares solutions through an interactive web Graphical User Interface (GUI).