Narrative Persuasion 2.0: Transportation in Participatory Websites

This research applies narrative persuasion theory to participatory websites. Specifically, the study examines the joint effect of online review structure (narrative/nonnarrative) and source attributes (expert/nonexpert) on attitude strength (attitude certainty and intensity). Results demonstrate that source attributes moderate the relationship between transportation and attitude intensity but not attitude certainty. These findings advance transportation theory by illuminating that readers glean source attributes on participatory websites, and these attributes modify transportation effects. The findings offer implications for participatory websites and design features that may facilitate or hinder readers in their quest to make decisions based on the reviews they read

The Adoption of Collaborative Robots toward Ubiquitous Diffusion: A Research Agenda

This paper proposes a framework to study the adoption of collaborative robots (co-robots or cobots) as an innovation and their diffusion into the larger population. Collaborative robots are only starting to appear in our society, yet challenges such as fear and distrust may impede their further adoption. This paper discusses the foundational work necessary to understand collaborative robot adoption and the core elements to achieve ubiquitous diffusion, with a focus on human users and the communication processes

Predicting adverse side effects of drugs

<p>Abstract</p> <p>Background</p> <p>Studies of toxicity and unintended side effects can lead to improved drug safety and efficacy. One promising form of study comes from molecular systems biology in the form of "systems pharmacology". Systems pharmacology combines data from clinical observation and molecular biology. This approach is new, however, and there are few examples of how it can practically predict adverse reactions (ADRs) from an experimental drug with acceptable accuracy.</p> <p>Results</p> <p>We have developed a new and practical computational framework to accurately predict ADRs of trial drugs. We combine clinical observation data with drug target data, protein-protein interaction (PPI) networks, and gene ontology (GO) annotations. We use cardiotoxicity, one of the major causes for drug withdrawals, as a case study to demonstrate the power of the framework. Our results show that an <it>in silico </it>model built on this framework can achieve a satisfactory cardiotoxicity ADR prediction performance (median AUC = 0.771, Accuracy = 0.675, Sensitivity = 0.632, and Specificity = 0.789). Our results also demonstrate the significance of incorporating prior knowledge, including gene networks and gene annotations, to improve future ADR assessments.</p> <p>Conclusions</p> <p>Biomolecular network and gene annotation information can significantly improve the predictive accuracy of ADR of drugs under development. The use of PPI networks can increase prediction specificity and the use of GO annotations can increase prediction sensitivity. Using cardiotoxicity as an example, we are able to further identify cardiotoxicity-related proteins among drug target expanding PPI networks. The systems pharmacology approach that we developed in this study can be generally applicable to all future developmental drug ADR assessments and predictions.</p

Maximizing Sharability and Persuasiveness on Web 2.0

Online marketing efforts usually focus on the persuasiveness or sharability of a message. However, research has not established where these two concepts overlap. The current study explores this overlap. Web 2.0 platforms facilitate the delivery of different content and statistics to convey the persuasiveness and the sharability. An original experiment varied message quality (high argument strength, direct message, and emotional message) and web cues (i.e., ratio of views, likes, and shares) to signal self-presentation (favorable and unfavorable). Prospective participants will view mock webpages for internet news and donation collection, followed by measures of the content persuasiveness and sharability

Classification of Stellar Spectra with LLE

We investigate the use of dimensionality reduction techniques for the classification of stellar spectra selected from the SDSS. Using local linear embedding (LLE), a technique that preserves the local (and possibly non-linear) structure within high dimensional data sets, we show that the majority of stellar spectra can be represented as a one dimensional sequence within a three dimensional space. The position along this sequence is highly correlated with spectral temperature. Deviations from this "stellar locus" are indicative of spectra with strong emission lines (including misclassified galaxies) or broad absorption lines (e.g. Carbon stars). Based on this analysis, we propose a hierarchical classification scheme using LLE that progressively identifies and classifies stellar spectra in a manner that requires no feature extraction and that can reproduce the classic MK classifications to an accuracy of one type.Comment: 15 pages, 13 figures; accepted for publication in The Astronomical Journa

Hepatic differentiation of human pluripotent stem cells in miniaturized format suitable for high-throughput screen

AbstractThe establishment of protocols to differentiate human pluripotent stem cells (hPSCs) including embryonic (ESC) and induced pluripotent (iPSC) stem cells into functional hepatocyte-like cells (HLCs) creates new opportunities to study liver metabolism, genetic diseases and infection of hepatotropic viruses (hepatitis B and C viruses) in the context of specific genetic background. While supporting efficient differentiation to HLCs, the published protocols are limited in terms of differentiation into fully mature hepatocytes and in a smaller-well format. This limitation handicaps the application of these cells to high-throughput assays. Here we describe a protocol allowing efficient and consistent hepatic differentiation of hPSCs in 384-well plates into functional hepatocyte-like cells, which remain differentiated for more than 3weeks. This protocol affords the unique opportunity to miniaturize the hPSC-based differentiation technology and facilitates screening for molecules in modulating liver differentiation, metabolism, genetic network, and response to infection or other external stimuli

Induction of sterilizing immunity against West Nile Virus (WNV), by immunization with WNV-like particles produced in insect cells

No specific vaccine for West Nile virus (WNV) is currently available for human use. In the present study, we describe the generation of WNV-like particles (WNV-LPs) in insect cells by use of recombinant baculoviruses expressing the WNV structural proteins prME or CprME. BALB/c mice immunized with purified WNV-LPs developed WNV-specific antibodies that had potent neutralizing activities. Mice immunized with prME-like particles (prME-LPs) showed no morbidity or mortality after challenge with WNV. Immunization with prMELPs can induce sterilizing immunity without producing any evidence of viremia or viral RNA in the spleen or brain. These results suggest that WNV-LPs hold promise as a vaccine candidate for WNV infection