In vivo Targeting of DNA Vaccines to Dendritic Cells via the Mannose Receptor Induces Long-Lasting Immunity against Melanoma

Herein, we report effective, C-type lectin mannose receptor (MR)-selective, in vivo dendritic cell (DC)-targeting lipid nanoparticles (LNPs) of a novel lipid-containing mannose-mimicking di-shikimoyl- and guanidine head group and two n-hexadecyl hydrophobic tails (DSG). Subcutaneous administration of LNPs of the DSG/p-CMV-GFP complex showed a significant expression of green fluorescence protein in the CD11c⁺ DCs of the neighboring lymph nodes compared to the control LNPs of the BBG/p-CMV-GFP complex. Mannose receptor-facilitated in vivo DC-targeted vaccination (s.c.) with the electrostatic complex of LNPs of DSG/pCMV-MART1 stimulated long-lasting (270 days post B16F10 tumor challenge) antimelanoma immunity under prophylactic conditions. Remarkably, under therapeutic settings, vaccination (s.c.) with LNPs of the DSG/pCMV-MART1 complex significantly delayed melanoma growth and improved the survival of mice with melanoma. These findings demonstrate that this nonviral delivery system offers a resilient and potential approach to deliver DNA vaccines encoding tumor antigens to DCs in vivo with high efficacy.     

Content-Based Recommendations for Sustainable Wardrobes Using Linked Open Data

Mobile Networks and Applications - Textile production industry is one of the biggest industries available and it is known by its negative effects to the environment. Greenhouse gas emissions can...     

User-Tailored Planning of Mixed Initiative Information-Seeking Dialogues

Intelligent dialogue systems usually concentrate on user support at the level of the domain of discourse, following a plan-based approach. Whereas this is appropriate for collaborative planning tasks, the situation in interactive information retrieval systems is quite different: there is no inherent plan-goal hierarchy, and users are known to often opportunistically change their goals and strategies during and through interaction. We need to allow for mixed-initiative retrieval dialogues, where the system evaluates the user's individual dialogue behavior and performs situation-dependent interpretation of user goals, to determine when to take the initiative and to change the control of the dialogue, e.g., to propose (new) problem-solving strategies to the user. In this article, we present the dialogue planning component of a concept- oriented, logic-based retrieval system (MIRACLE). Users are guided through the global stages of the retrieval interaction but may depart, at any time, from this guidance and change the direction of the dialogue. When users submit ambiguous queries or enter unexpected dialogue control acts, abductive reasoning is used to generate interpretations of these user inputs in light of the dialogue history and other internal knowledge sources. Based on these interpretations, the system initiates a short dialogue offering the user suitable options and strategies for proceeding with the retrieval dialogue. Depending on the user's choice and constraints resulting from the history, the system adapts its strategy accordingly.     

Safety effects of traffic signing for left turn flashing yellow arrow signals

In 2010, the left turn flashing yellow arrow (FYA) signal displays were installed at signalized intersections on state routes in the Peoria, Illinois, area. Supplemental traffic signs with text “Left Turn Yield on Flashing Yellow Arrow” were mounted on the mast arm adjacent to the left turn signal at over half of the FYA installations. The purpose of this paper is to present the results of the effectiveness evaluation of the FYA supplemental sign on safety. Analyses are presented on the effects of the FYA supplemental sign for all drivers and a subset of drivers age 65 and older. A crash-based comparison of 164 FYA approaches including 90 approaches with the sign and 74 approaches without the sign showed greater crash reductions when the supplemental FYA sign was present. The results also showed that crashes involving drivers age 65 and older did not experience the same magnitudes of crash reductions as compared to all drivers. The findings of this research indicate that supplemental FYA signs may help in improving safety for left-turning vehicles during the permissive interval. Thus, it is recommended that supplemental signs be used when initially implementing the FYA, and that effort to educate the driving public on new traffic control be made to further improve safety at signalized intersections.     

Retraction Note to: A joint model for analyzing topic and sentiment dynamics from large-scale online news

World Wide Web - The Editors-in-Chief have retracted “A joint model for analyzing topic and sentiment dynamics from large-scale online news” [1] because the article shows significant...     

Bioconversion of soysterols to androstenedione by Mycobacterium fortuitum subsp. fortuitum NCIM 5239, a mutant derived from total sterol degrader strain

BACKGROUND: The bioconversion of soysterols to androstenedione (AD) by microbial cleavage of C‐17 side chain is of practical interest since AD serves as the starting compound for the production of the majority of pharmaceutically active steroids. A total soysterols degrader strain was subjected to combined mitomycin C and UV treatments and a mutant designated Mycobacterium fortuitum subsp. fortuitum NCIM 5239 was isolated that accumulated AD as major bioconversion product. RESULTS: The maximum bioconversion of soysterols to AD (71.3 mol %) was obtained at 30 °C, pH 5, 15% inoculum grown for 48 h, glycerol (12.68 g L^?1) and urea (1.06 g L^?1) as carbon and nitrogen sources, respectively, at C:N ratio of 10, the use of 10% polypropylene glycol‐400 (PPG‐400) as soysterols carrier solvent and 3 mg mL^?1 concentration of soysterols after 240 h incubation period in shake flask culture. In a laboratory scale fermentor, a maximum of 64.8 mol % bioconversion of soysterols to AD was recorded after 99 h. CONCLUSION: The mutant Mycobacterium fortuitum subsp. fortuitum NCIM 5239 possesses high potential for industrial production of AD from soysterols. Copyright © 2010 Society of Chemical Industry     

A joint model for analyzing topic and sentiment dynamics from large-scale online news

Many of today’s online news websites and aggregator apps have enabled users to publish their opinions without respect to time and place. Existing works on topic-based sentiment analysis of product reviews cannot be applied to online news directly because of the following two reasons: (1) The dynamic nature of news streams require the topic and sentiment analysis model also to be dynamically updated. (2) The user interactions among news comments can easily lead to inaccurate topic extraction and sentiment classification. In this paper, we propose a novel probabilistic generative model (DTSA) to extract topics and the specified sentiments from news streams and analyze their evolution over time simultaneously. In DTSA, three different timescale models are studied to account for the historical dependencies of sentiment-topic word distributions at current epoch, continuous, skip and multiple timescale models. Additionally, we further consider the links among news comments to avoid the error caused by user interactions. In order to mine more interpretable topics, a Conditional Random Fields (CRF) model is adopted to label a set of meaningful phrases for augmenting the bag-of-word features. Finally, we derive distributed online inference procedures to update the model with newly arrived data and show the effectiveness of our proposed model on real-world data sets.     

Model-Based Business Process Mining

As companies use enterprise resource planning (ERP) systems to support their business processes, they need to verify that the systems are configured appropriately and used in the most efficient way. This article describes the approach taken and results from a business process mining project at a midsized company in Norway. A newly released tool for analyzing ERP system logs is used to construct the underlying business flows and to provide new insights that can be used by the company to improve the procurement process.