Statefinder Parameters for Tachyon Dark Energy Model

In this paper we study the statefinder parameters for the tachyon dark energy model. There are two kinds of stable attractor solutions in this model. The statefinder diagrams characterize the properties of the tachyon dark energy model. Our results show that the evolving trajectories of the attractor solutions lie in the total region and pass through the LCDM fixed point, which is different from other dark energy model.Comment: 5 pages, 5 figures, accepted by MPL

THERMODYNAMIC EQUILIBRIUM DISTRIBUTION OF PARTICLES IN 2-D ELECTRIC FIELD

We study the particles in the colloidal system under a two-dimensional electric field: the way to assemble the particles in the Brownian dynamic simulation and the equilibrium density profile of the system derived by considering the particle-field interaction and the equation of state for hard colloidal particles. In the research, the software COMSOL Multiphysics is used to solve the anisotropic electric field in a lookup table form to work the same as an analytical expression of the field property, which is not available. And triangular interpolation is used to make the lookup table work for every position in the plane. We develop the way to solve the equilibrium density profile given any electric field conditions in the 2D plane and work that on three types of electric field, then simulation is performed to verify our theory. Advisor: Michael A. Bevan Reader: Joelle Frechett

Heterogeneity-aware Clustered Distributed Learning for Multi-source Data Analysis

In diverse fields ranging from finance to omics, it is increasingly common that data is distributed and with multiple individual sources (referred to as ``clients'' in some studies). Integrating raw data, although powerful, is often not feasible, for example, when there are considerations on privacy protection. Distributed learning techniques have been developed to integrate summary statistics as opposed to raw data. In many of the existing distributed learning studies, it is stringently assumed that all the clients have the same model. To accommodate data heterogeneity, some federated learning methods allow for client-specific models. In this article, we consider the scenario that clients form clusters, those in the same cluster have the same model, and different clusters have different models. Further considering the clustering structure can lead to a better understanding of the ``interconnections'' among clients and reduce the number of parameters. To this end, we develop a novel penalization approach. Specifically, group penalization is imposed for regularized estimation and selection of important variables, and fusion penalization is imposed to automatically cluster clients. An effective ADMM algorithm is developed, and the estimation, selection, and clustering consistency properties are established under mild conditions. Simulation and data analysis further demonstrate the practical utility and superiority of the proposed approach

AMER: Automatic Behavior Modeling and Interaction Exploration in Recommender System

User behavior and feature interactions are crucial in deep learning-based recommender systems. There has been a diverse set of behavior modeling and interaction exploration methods in the literature. Nevertheless, the design of task-aware recommender systems still requires feature engineering and architecture engineering from domain experts. In this work, we introduce AMER, namely Automatic behavior Modeling and interaction Exploration in Recommender systems with Neural Architecture Search (NAS). The core contributions of AMER include the three-stage search space and the tailored three-step searching pipeline. In the first step, AMER searches for residual blocks that incorporate commonly used operations in the block-wise search space of stage 1 to model sequential patterns in user behavior. In the second step, it progressively investigates useful low-order and high-order feature interactions in the non-sequential interaction space of stage 2. Finally, an aggregation multi-layer perceptron (MLP) with shortcut connection is selected from flexible dimension settings of stage~3 to combine features extracted from the previous steps. For efficient and effective NAS, AMER employs the one-shot random search in all three steps. Further analysis reveals that AMER's search space could cover most of the representative behavior extraction and interaction investigation methods, which demonstrates the universality of our design. The extensive experimental results over various scenarios reveal that AMER could outperform competitive baselines with elaborate feature engineering and architecture engineering, indicating both effectiveness and robustness of the proposed method

PACAP neuropeptide promotes Hepatocellular Protection via CREB-KLF4 dependent autophagy in mouse liver Ischemia Reperfusion Injury.

Organ ischemia reperfusion injury (IRI), associated with acute hepatocyte death, remains an unresolved problem in clinical orthotopic liver transplantation (OLT). Autophagy, an intracellular self-digesting progress, is responsible for cell reprograming required to regain post-stress homeostasis. Methods: Here, we analyzed the cytoprotective mechanism of pituitary adenylate cyclase-activating polypeptide (PACAP)-promoted hepatocellular autophagy in a clinically relevant mouse model of extended hepatic cold storage (4 °C UW solution for 20 h) followed by syngeneic OLT. Results: In contrast to 41.7% of liver graft failure by day 7 post-transplant in control group, PACAP treatment significantly improved graft survival (91.7% by day 14), and promoted autophagy-associated regeneration programs in OLT. In parallel in vitro studies, PACAP-enhanced autophagy ameliorated cellular damage (LDH/ALT levels), and diminished necrosis in H2O2-stressed primary hepatocytes. Interestingly, PACAP not only induced nuclear cAMP response element-binding protein (CREB), but also triggered reprogramming factor Kruppel-like factor 4 (KLF4) expression in IR-stressed OLT. Indeed, CREB inhibition attenuated hepatic autophagy and recreated hepatocellular injury in otherwise PACAP-protected livers. Furthermore, CREB inhibition suppressed PACAP-induced KLF4 expression, whereas KLF4 blockade abolished PACAP-promoted autophagy and neutralized PACAP-mediated hepatoprotection both in vivo and in vitro. Conclusion: Current study documents the essential neural regulation of PACAP-promoted autophagy in hepatocellular homeostasis in OLT, which provides the emerging therapeutic principle to combat hepatic IRI in OLT

RNA-seq liver transcriptome analysis reveals an activated MHC-I pathway and an inhibited MHC-II pathway at the early stage of vaccine immunization in zebrafish

BACKGROUND: Zebrafish (Danio rerio) is a prominent vertebrate model of human development and pathogenic disease and has recently been utilized to study teleost immune responses to infectious agents threatening the aquaculture industry. In this work, to clarify the host immune mechanisms underlying the protective effects of a putative vaccine and improve its immunogenicity in the future efforts, high-throughput RNA sequencing technology was used to investigate the immunization-related gene expression patterns of zebrafish immunized with Edwardsiella tarda live attenuated vaccine. RESULTS: Average reads of 18.13 million and 14.27 million were obtained from livers of zebrafish immunized with phosphate buffered saline (mock) and E. tarda vaccine (WED), respectively. The reads were annotated with the Ensembl zebrafish database before differential expressed genes sequencing (DESeq) comparative analysis, which identified 4565 significantly differentially expressed genes (2186 up-regulated and 2379 down-regulated in WED; p<0.05). Among those, functional classifications were found in the Gene Ontology database for 3891 and in the Kyoto Encyclopedia of Genes and Genomes database for 3467. Several pathways involved in acute phase response, complement activation, immune/defense response, and antigen processing and presentation were remarkably affected at the early stage of WED immunization. Further qPCR analysis confirmed that the genes encoding the factors involved in major histocompatibility complex (MHC)-I processing pathway were up-regulated, while those involved in MHC-II pathway were down-regulated. CONCLUSION: These data provided insights into the molecular mechanisms underlying zebrafish immune response to WED immunization and might aid future studies to develop a highly immunogenic vaccine against gram-negative bacteria in teleosts

The Novel Sigma Factor-Like Regulator RpoQ Controls Luminescence, Chitinase Activity, and Motility in Vibrio fischeri

Vibrio fischeri, the bacterial symbiont of the Hawaiian bobtail squid, Euprymna scolopes, uses quorum sensing to control genes involved in bioluminescence, host colonization, and other biological processes. Previous work has shown that AinS/R-directed quorum sensing also regulates the expression of rpoQ (VF_A1015), a gene annotated as an RpoS-like sigma factor. In this study, we demonstrate using phylogenetics that RpoQ is related to, but distinct from, the stationary-phase sigma factor RpoS. Overexpression of rpoQ results in elevated chitinase activity but decreased motility and luminescence, three activities associated with symbiosis. The reduction in bacterial luminescence associated with the overexpression of rpoQ occurs both in culture and within the light-emitting organ of the squid host. This suppression of bioluminescence is due to the repression of the luxICDABEG promoter. Our results highlight RpoQ as a novel regulatory component, embedded in the quorum-signaling network that controls several biological processes in V. fischeri