Suchergebnisse

Cover -- Copyright Page -- Title Page -- Dedication -- Contents -- Acknowledgments -- Introduction -- Motivation -- An Interdisciplinary View on Fake News -- Fake News in Social Media Age -- Characteristics of Social Media -- Problem Definition -- What News Content Tells -- How Social Context Helps -- Challenging Problems of Fake News Detection -- What News Content Tells -- Textual Features -- Linguistic Features -- Low-Rank Textual Features -- Neural Textual Features -- Visual Features -- Visual Statistical Features -- Visual Content Features -- Neural Visual Features -- Style Features -- Deception Styles -- Clickbaity Styles -- News Quality Styles -- Knowledge-Based Methods -- Manual Fact-Checking -- Automatic Fact-Checking -- How Social Context Helps -- User-Based Detection -- User Feature Modeling -- User Behavior Modeling -- Post-Based Detection -- Stance-Aggregated Modeling -- Emotion-Enhanced Modeling -- Credibility-Propagated Modeling -- Network-Based Detection -- Representative Network Types -- Friendship Networking Modeling -- Diffusion Network Temporal Modeling -- Interaction Network Modeling -- Propagation Network Deep-Geometric Modeling -- Hierarchical Propagation Network Modeling -- Challenging Problems of Fake News Detection -- Fake News Early Detection -- A User-Response Generation Approach -- An Event-Invariant Adversarial Approach -- A Propagation-Path Modeling Approach -- Weakly Supervised Fake News Detection -- A Tensor Decomposition Semi-Supervised Approach -- A Tensor Decomposition Unsupervised Approach -- A Probabilistic Generative Unsupervised Approach -- Explainable Fake News Detection -- A Web Evidence-Aware Approach -- A Social Context-Aware Approach -- Data Repository -- Tools -- Relevant Activities -- Bibliography -- Authors' Biographies.

Xi Chen,1 Shizhu Bai,1 Bei Li,2 Huan Liu,1 Guofeng Wu,1 Sha Liu,3 Yimin Zhao1 1State Key Laboratory of Military Stomatology and National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Oral Diseases, Department of Prosthodontics, 2State Key Laboratory of Military Stomatology and National Clinical Research Center for Oral Diseases, Shaanxi Key Laboratory of Oral Diseases, Center for Tissue Engineering, School of Stomatology, 3Department of Plastic and Reconstructive Surgery, Xijing Hospital, The Fourth Military Medical University, Shaanxi, People's Republic of China Introduction: Periodontitis is a chronic infectious disease and is the major cause of tooth loss and other oral health issues around the world. Periodontal tissue regeneration has therefore always been the ultimate goal of dentists and researchers. Existing fabrication methods mainly focused on a top–down tissue engineering strategy in which several drawbacks remain, including low throughput and limited diffusion properties resulting from a large sample size. Gelatin methacrylate (GelMA) is a kind of photocrosslinkable and biocompatible hydrogel, with the capacities of enabling cell encapsulation and regeneration of functional tissues. Here, we developed a novel method to fabricate GelMA/nanohydroxylapatite (nHA) microgel arrays using a photocrosslinkable strategy. The viability, proliferation, and osteogenic differentiation and in vivo osteogenesis of human periodontal ligament stem cells (hPDLSCs) encapsulated in microgels were evaluated. The results suggested that such microgels provide great potential for periodontal tissue repair and regeneration. Methods: Microgel arrays were fabricated by blending different weight ratios of GelMA and nHA. hPDLSCs were encapsulated in GelMA/nHA microgels of various ratios for a systematic evaluation of cell viability, proliferation, and osteogenic differentiation. In vivo osteogenesis in nude mice was also studied. Results: The GelMA/nHA microgels exhibited appropriate microarchitecture, mechanical strength, and surface roughness, thus enabling cell adhesion and proliferation. Additionally, the GelMA/nHA microgels (10%/2% w/v) enhanced the osteogenic differentiation of hPDLSCs by elevating the expression levels of osteogenic biomarker genes, such as ALP, BSP, OCN, and RUNX2. In vivo ectopic transplantation results showed that GelMA/nHA microgels (10%/2% w/v) increased mineralized tissue formation with abundant vascularization, compared with the 1%, 3%, and the pure GelMA group. Conclusion: The GelMA/nHA microgels (10%/2% w/v) facilitated hPDLSCs viability, proliferation, and osteogenic differentiation in vitro and further promoted new bone formation in vivo, suggesting that the GelMA/nHA microgels (10%/2% w/v) provide great potential for periodontal tissue regeneration. Keywords: periodontal ligament stem cells, gelatin methacrylate, nanohydroxyapatite, microgel array, differentiation, periodontal tissue regeneration