A Survey on Location-Driven Influence Maximization

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, is an evergreen hot research topic. Its research outcomes significantly impact real-world applications such as business marketing. The booming location-based network platforms of the last decade appeal to the researchers embedding the location information into traditional IM research. In this survey, we provide a comprehensive review of the existing location-driven IM studies from the perspective of the following key aspects: (1) a review of the application scenarios of these works, (2) the diffusion models to evaluate the influence propagation, and (3) a comprehensive study of the approaches to deal with the location-driven IM problems together with a particular focus on the accelerating techniques. In the end, we draw prospects into the research directions in future IM research

Suppression of Tumor Energy Supply by Liposomal Nanoparticle-Mediated Inhibition of Aerobic Glycolysis

Aerobic glycolysis enables cancer cells to rapidly take up nutrients (e.g., nucleotides, amino acids, and lipids) and incorporate them into the biomass needed to produce a new cell. In contrast to existing chemotherapy/radiotherapy strategies, inhibiting aerobic glycolysis to limit the adenosine 5′-triphosphate (ATP) yield is a highly efficient approach for suppressing tumor cell proliferation. However, most, if not all, current inhibitors of aerobic glycolysis cause significant adverse effects because of their nonspecific delivery and distribution to nondiseased organs, low bioavailability, and a narrow therapeutic window. New strategies to enhance the biosafety and efficacy of these inhibitors are needed for moving them into clinical applications. To address this need, we developed a liposomal nanocarrier functionalized with a well-validated tumor-targeting peptide to specifically deliver the aerobic glycolysis inhibitor 3-bromopyruvate (3-BP) into the tumor tissue. The nanoparticles effectively targeted tumors after systemic administration into tumor-bearing mice and suppressed tumor growth by locally releasing 3-BP to inhibit the ATP production of the tumor cells. No overt side effects were observed in the major organs. This report demonstrates the potential utility of the nanoparticle-enabled delivery of an aerobic glycolysis inhibitor as an anticancer therapeutic agent

GENOMIC VARIANTS AND VARIOUS TF BINDING ENRICHMENT RESULT IN ENHANCER HETEROGENEITY IN GASTRIC ADENOCARCINOMA

Ph.DDOCTOR OF PHILOSOPHY (SOM

Reconnecting the Estranged Relationships: Optimizing the Influence Propagation in Evolving Networks

Influence Maximization (IM), which aims to select a set of users from a social network to maximize the expected number of influenced users, has recently received significant attention for mass communication and commercial marketing. Existing research efforts dedicated to the IM problem depend on a strong assumption: the selected seed users are willing to spread the information after receiving benefits from a company or organization. In reality, however, some seed users may be reluctant to spread the information, or need to be paid higher to be motivated. Furthermore, the existing IM works pay little attention to capture user's influence propagation in the future period as well. In this paper, we target a new research problem, named Reconnecting Top-l Relationships (RTlR) query, which aims to find l number of previous existing relationships but being stranged later, such that reconnecting these relationships will maximize the expected benefit of influenced users by the given group in a future period. We prove that the RTlR problem is NP-hard. An efficient greedy algorithm is proposed to answer the RTlR queries with the influence estimation technique and the well-chosen link prediction method to predict the near future network structure. We also design a pruning method to reduce unnecessary probing from candidate edges. Further, a carefully designed order-based algorithm is proposed to accelerate the RTlR queries. Finally, we conduct extensive experiments on real-world datasets to demonstrate the effectiveness and efficiency of our proposed methods

Author Correction: CRISPRi enables isoform-specific loss-of-function screens and identification of gastric cancer-specific isoform dependencies (Genome Biology, (2021), 22, 1, (47), 10.1186/s13059-021-02266-6)

10.1186/s13059-021-02314-1Genome Biology2218

CRISPRi enables isoform-specific loss-of-function screens and identification of gastric cancer-specific isoform dependencies

10.1186/s13059-021-02266-6Genome Biology2214

AQP5 enriches for stem cells and cancer origins in the distal stomach

LGR5 marks resident adult epithelial stem cells at the gland base in the mouse pyloric stomach(1), but the identity of the equivalent human stem cell population remains unknown owing to a lack of surface markers that facilitate its prospective isolation and validation. In mouse models of intestinal cancer, LGR5(+) intestinal stem cells are major sources of cancer following hyperactivation of the WNT pathway(2). However, the contribution of pyloric LGR5(+) stem cells to gastric cancer following dysregulation of the WNT pathway-a frequent event in gastric cancer in humans(3)-is unknown. Here we use comparative profiling of LGR5(+) stem cell populations along the mouse gastrointestinal tract to identify, and then functionally validate, the membrane protein AQP5 as a marker that enriches for mouse and human adult pyloric stem cells. We show that stem cells within the AQP5(+) compartment are a source of WNT-driven, invasive gastric cancer in vivo, using newly generated Aqp5-creERT2 mouse models. Additionally, tumour-resident AQP5(+) cells can selectively initiate organoid growth in vitro, which indicates that this population contains potential cancer stem cells. In humans, AQP5 is frequently expressed in primary intestinal and diffuse subtypes of gastric cancer (and in metastases of these subtypes), and often displays altered cellular localization compared with healthy tissue. These newly identified markers and mouse models will be an invaluable resource for deciphering the early formation of gastric cancer, and for isolating and characterizing human-stomach stem cells as a prerequisite for harnessing the regenerative-medicine potential of these cells in the clinic. AQP5 is identified as a marker for pyloric stem cells in humans and mice, and stem cells in the AQP5(+) compartment are shown to be a source of invasive gastric cancer in mouse models