Sentiment-based topic suggestion for micro-reviews

Location-based social sites, such as Foursquare or Yelp, are gaining increasing popularity. These sites allow users to check in at venues and leave a short commentary in the form of a micro-review. Micro-reviews are rich in content as they offer a distilled and concise account of user experience. In this paper we consider the problem of predicting the topic of a micro-review by a user who visits a new venue. Such a prediction can help users make informed decisions, and also help venue owners personalize users' experiences. However, topic modeling for micro-reviews is particularly difficult, due to their short and fragmented nature. We address this issue using pooling strategies, which aggregate micro-reviews at the venue or user level, and we propose novel probabilistic models based on Latent Dirichlet Allocation (LDA) for extracting the topics related to a user-venue pair. Our best topic model integrates influences from both venue inherent properties and user preferences, considering at the same the sentiment orientation of the users. Experimental results on real datasets demonstrate the superiority of this model compared to simpler models and previous work; they also show that venue-inherent properties have higher influence on the topics of micro-reviews. © Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.postprin

MIOCENE SCLERACTINIAN CORALS OF GAVDOS ISLAND, SOUTHERN GREECE: IMPLICATIONS FOR TECTONIC CONTROL AND SEA-LEVEL CHANGES

Low-diversity scleractinian patch reefs that have been developed, during Early to Middle Tortonian, in Gavdos island are studied, aiming in a better understanding of the time and space relationships of the reef development and the associated basin fill evolution. Gavdos island consists part of a tectonically active setting constituting the southernmost extension of the Hellenic arc (Eastern Mediterranean). A representative Tortonian section (Bo section), located in the northwest part of the island, which hosts a mass occurrence of hermatypic corals, is studied. Scleractinian samples were collected from the upper 12 m of the section, which is characterized by interchanges of marly limestone and compact marls. The reefs are represented by the coral species Heliastraea oligophylla, Porites maicientensis, Thegioastraea roasendai and Porites collegniana. The microfacies analysis showed that the mediumto-thin-bedded carbonates of the limestone-marl alternations comprise patch reefs (boundstones-framestones, SMF 16, sensu Wilson, 1975, FZ 7-8, sensu Flügel 1982) consisted of screractinian corals. Corals are associated with corallinacean algae. Patch reefs are associated by bioclastic packstones-floatstones, characterized by benthic foraminifera, calcareous algae, spines of echinoids, gastropods and molluscs. Reefs are laterally associated by a bioclastic limestone rich in planktonic forams, associated by detrital material (fragments of quartz, feldspars, quartzites and cherts). The studied reef facies have been dolomitized and cemented in the meteoric realm. In places pseudomorphs after evaporites have been observed, tending to occlude cavities resulted after dissolution. The depositional environment corresponds to a moderate to high-energy inner platform setting, experiencing open-ocean influences. The pattern of coralgal reef development during Miocene, in the tectonically controlled Gavdos island, represents a complex interaction of tectonic activity and global sea-level changes

Renal Sodium-Potassium-Activated Adenosine Triphosphatase and Sodium Reabsorption

A B S T R A C T The role of renal Na+,K+-ATPase in sodium reabsorption was further examined in dogs in which digoxin, a specific inhibitor of the enzyme system, was infused into one renal artery in doses ranginig from 0.4 to 0.9 /Ag/kg/min (low dose) and from 1.0 to 4.0 Ag/kg/ min (high dose). A significant natriuresis occurred with both dose ranges which was accompanied by inhibition of Na+,K+-ATPase of cortex and nmedulla in the infused kidney. Despite over 90% enzyme inhibition in many experiments, at least 80% of the filtered sodium continued to be reabsorbed. The per cent change in enzyme activity correlated with the rate of digoxin administration and the total dose administered but not with changes in sodium excretion. Changes in medullary Na+,K+-ATPase activity, however, bore a direct relationship to alterations in fractional solute free water reabsorption (TcH1o). Inhibition of cortical enzyme activity alone was not associated with natriuresis, suggesting that medullary enzyme activity must be depressed for increased sodium excretion to occur during digoxin infusion. In high-dose experiments, significant inhibition of cortical and medullary enzyme in the contralateral control kidney was also observed, but natriuresis did not occur. In these experiments the rate at which digoxin reached the control kidney rose progressively but never equaled the rates in the directly infused kidney with either dose. Nevertheless, it is clear that under certain circumstances enzyme inhibition of either cortex or medulla need not be accompanied by natriuresis. We conclude that the major role of renal Na+,K+-ATPase is in sodium reabsorption in the medulla (ascending limb of Henle's loop) and that it has a relatively small role in proximal sodium reabsorption. The Dr. Tsaparas is a Hoechst International Fellow in Nephrology

Liver transplantation as last-resort treatment for patients with bile duct injuries following cholecystectomy: A multicenter analysis

Background Liver transplantation (LT) has been used as a last resort in patients with end-stage liver disease due to bile duct injuries (BDI) following cholecystectomy. Our study aimed to identify and evaluate factors that cause or contribute to an extended liver disease that requires LT as ultimate solution, after BDI during cholecystectomy. Methods Data from 8 high-volume LT centers relating to patients who underwent LT after suffering BDI during cholecystectomy were prospectively collected and retrospectively analyzed. Results Thirty-four patients (16 men, 18 women) with a median age of 45 (range 22-69) years were included in this study. Thirty of them (88.2%) underwent LT because of liver failure, most commonly as a result of secondary biliary cirrhosis. The median time interval between BDI and LT was 63 (range 0-336) months. There were 23 cases (67.6%) of postoperative morbidity, 6 cases (17.6%) of post-transplant 30-day mortality, and 10 deaths (29.4%) in total after LT. There was a higher probability that patients with concomitant vascular injury (hazard ratio 10.69, P=0.039) would be referred sooner for LT. Overall survival following LT at 1, 3, 5 and 10 years was 82.4%, 76.5%, 73.5% and 70.6%, respectively. Conclusion LT for selected patients with otherwise unmanageable BDI following cholecystectomy yields acceptable long-term outcomes

A Genomewide Functional Network for the Laboratory Mouse

Establishing a functional network is invaluable to our understanding of gene function, pathways, and systems-level properties of an organism and can be a powerful resource in directing targeted experiments. In this study, we present a functional network for the laboratory mouse based on a Bayesian integration of diverse genetic and functional genomic data. The resulting network includes probabilistic functional linkages among 20,581 protein-coding genes. We show that this network can accurately predict novel functional assignments and network components and present experimental evidence for predictions related to Nanog homeobox (Nanog), a critical gene in mouse embryonic stem cell pluripotency. An analysis of the global topology of the mouse functional network reveals multiple biologically relevant systems-level features of the mouse proteome. Specifically, we identify the clustering coefficient as a critical characteristic of central modulators that affect diverse pathways as well as genes associated with different phenotype traits and diseases. In addition, a cross-species comparison of functional interactomes on a genomic scale revealed distinct functional characteristics of conserved neighborhoods as compared to subnetworks specific to higher organisms. Thus, our global functional network for the laboratory mouse provides the community with a key resource for discovering protein functions and novel pathway components as well as a tool for exploring systems-level topological and evolutionary features of cellular interactomes. To facilitate exploration of this network by the biomedical research community, we illustrate its application in function and disease gene discovery through an interactive, Web-based, publicly available interface at http://mouseNET.princeton.edu

A general co-expression network-based approach to gene expression analysis: comparison and applications

<p>Abstract</p> <p>Background</p> <p>Co-expression network-based approaches have become popular in analyzing microarray data, such as for detecting functional gene modules. However, co-expression networks are often constructed by ad hoc methods, and network-based analyses have not been shown to outperform the conventional cluster analyses, partially due to the lack of an unbiased evaluation metric.</p> <p>Results</p> <p>Here, we develop a general co-expression network-based approach for analyzing both genes and samples in microarray data. Our approach consists of a simple but robust rank-based network construction method, a parameter-free module discovery algorithm and a novel reference network-based metric for module evaluation. We report some interesting topological properties of rank-based co-expression networks that are very different from that of value-based networks in the literature. Using a large set of synthetic and real microarray data, we demonstrate the superior performance of our approach over several popular existing algorithms. Applications of our approach to yeast, Arabidopsis and human cancer microarray data reveal many interesting modules, including a fatal subtype of lymphoma and a gene module regulating yeast telomere integrity, which were missed by the existing methods.</p> <p>Conclusions</p> <p>We demonstrated that our novel approach is very effective in discovering the modular structures in microarray data, both for genes and for samples. As the method is essentially parameter-free, it may be applied to large data sets where the number of clusters is difficult to estimate. The method is also very general and can be applied to other types of data. A MATLAB implementation of our algorithm can be downloaded from <url>http://cs.utsa.edu/~jruan/Software.html</url>.</p