Nankai University

About: Nankai University is a education organization based out in Tianjin, China. It is known for research contribution in the topics: Catalysis & Adsorption. The organization has 42964 authors who have published 51866 publications receiving 1127896 citations. The organization is also known as: Nánkāi Dàxué.

Sequential Click Prediction for Sponsored Search with Recurrent Neural Networks

Abstract: Click prediction is one of the fundamental problems in sponsored search. Most of existing studies took advantage of machine learning approaches to predict ad click for each event of ad view independently. However, as observed in the real-world sponsored search system, user's behaviors on ads yield high dependency on how the user behaved along with the past time, especially in terms of what queries she submitted, what ads she clicked or ignored, and how long she spent on the landing pages of clicked ads, etc. Inspired by these observations, we introduce a novel framework based on Recurrent Neural Networks (RNN). Compared to traditional methods, this framework directly models the dependency on user's sequential behaviors into the click prediction process through the recurrent structure in RNN. Large scale evaluations on the click-through logs from a commercial search engine demonstrate that our approach can significantly improve the click prediction accuracy, compared to sequence-independent approaches.

Novel mesoporous graphite carbon nitride/BiOI heterojunction for enhancing photocatalytic performance under visible-light irradiation.

Abstract: A novel organic–inorganic three-dimensional (3D) mesoporous graphite carbon nitride/BiOI (MCN/BiOI) heterojunction photocatalyst with excellent visible-light-driven photocatalytic performance was synthesized by a facile solvothermal method and used for degradation of bisphenol A (BPA) in water. After hybridization with MCN, a heterojunction was formed and the photogenerated carriers could be effectively separated by the internal electric field built at the heterojunction interface. The photocatalytic and photoelectrochemical performance of BiOI were improved and much higher than pure BiOI and MCN. The best photocatalytic performance was achieved with MCN proportion of 10%, and the kobs was approximately 1.6 times of pure BiOI and 3.4 times of MCN under simulated solar light irradiation, respectively. The photocurrent intensity generated by 10%-MCN/BiOI electrode was about 1.5 and 2.0 times of those induced by BiOI and MCN under visible-light irradiation, respectively. The superoxide radical species were p...

Improved In Vitro and In Vivo Biocompatibility of Graphene Oxide through Surface Modification: Poly(Acrylic Acid)-Functionalization is Superior to PEGylation

Abstract: The unique physicochemical properties of two-dimensional (2D) graphene oxide (GO) could greatly benefit the biomedical field; however, recent research demonstrated that GO could induce in vitro and in vivo toxicity. We determined the mechanism of GO induced toxicity, and our in vitro experiments revealed that pristine GO could impair cell membrane integrity and functions including regulation of membrane- and cytoskeleton-associated genes, membrane permeability, fluidity and ion channels. Furthermore, GO induced platelet depletion, pro-inflammatory response and pathological changes of lung and liver in mice. To improve the biocompatibility of pristine GO, we prepared a series of GO derivatives including aminated GO (GO-NH2), poly(acrylamide)-functionalized GO (GO-PAM), poly(acrylic acid)-functionalized GO (GO-PAA) and poly(ethylene glycol)-functionalized GO (GO-PEG), and compared their toxicity with pristine GO in vitro and in vivo. Among these GO derivatives, GO-PEG and GO-PAA induced less toxicity than pristine GO, and GO-PAA was the most biocompatible one in vitro and in vivo. The differences in biocompatibility were due to the differential compositions of protein corona, especially immunoglobulin G (IgG), formed on their surfaces that determine their cell membrane interaction and cellular uptake, the extent of platelet depletion in blood, thrombus formation under short-term exposure and the pro-inflammatory effects under long-term exposure. Overall, our combined data delineated the key molecular mechanisms underlying the in vivo and in vitro biological behaviors and toxicity of pristine GO, and identified a safer GO derivative that could be used for future applications.

Long Noncoding RNA HULC Modulates Abnormal Lipid Metabolism in Hepatoma Cells through an miR-9–Mediated RXRA Signaling Pathway

Abstract: HULC is a long noncoding RNA overexpressed in hepatocellular carcinoma (HCC), but its functional contributions in this setting have not been determined. In this study, we explored the hypothesis that HULC contributes to malignant development by supporting abnormal lipid metabolism in hepatoma cells. HULC modulated the deregulation of lipid metabolism in HCC by activating the acyl-CoA synthetase subunit ACSL1. Immunohistochemical analysis of tissue microarrays revealed that approximately 77% (180/233) of HCC tissues were positive for ACSL1. Moreover, HULC mRNA levels correlated positively with ACSL1 levels in 60 HCC cases according to real-time PCR analysis. Mechanistic investigations showed that HULC upregulated the transcriptional factor PPARA, which activated the ACSL1 promoter in hepatoma cells. HULC also suppressed miR-9 targeting of PPARA mRNA by eliciting methylation of CpG islands in the miR-9 promoter. We documented the ability of HULC to promote lipogenesis, thereby stimulating accumulation of intracellular triglycerides and cholesterol in vitro and in vivo. Strikingly, ACSL1 overexpression that generates cholesterol was sufficient to enhance the proliferation of hepatoma cells. Further, cholesterol addition was sufficient to upregulate HULC expression through a positive feedback loop involving the retinoid receptor RXRA, which activated the HULC promoter. Overall, we concluded that HULC functions as an oncogene in hepatoma cells, acting mechanistically by deregulating lipid metabolism through a signaling pathway involving miR-9, PPARA, and ACSL1 that is reinforced by a feed-forward pathway involving cholesterol and RXRA to drive HULC signaling.