Tag-Aware Recommender Systems: A State-of-the-art Survey

In the past decade, Social Tagging Systems have attracted increasing attention from both physical and computer science communities. Besides the underlying structure and dynamics of tagging systems, many efforts have been addressed to unify tagging information to reveal user behaviors and preferences, extract the latent semantic relations among items, make recommendations, and so on. Specifically, this article summarizes recent progress about tag-aware recommender systems, emphasizing on the contributions from three mainstream perspectives and approaches: network-based methods, tensor-based methods, and the topic-based methods. Finally, we outline some other tag-related works and future challenges of tag-aware recommendation algorithms.Comment: 19 pages, 3 figure

A new primary dental care service compared with standard care for child and family to reduce the re-occurrence of childhood dental caries (Dental RECUR): study protocol for a randomised controlled trial

Background: In England and Scotland, dental extraction is the single highest cause of planned admission to the hospital for children under 11 years. Traditional dental services have had limited success in reducing this disease burden. Interventions based on motivational interviewing have been shown to impact positively dental health behaviours and could facilitate the prevention of re-occurrence of dental caries in this high-risk population. The objective of the study is to evaluate whether a new, dental nurse-led service, delivered using a brief negotiated interview based on motivational interviewing, is a more cost-effective service than treatment as usual, in reducing the re-occurrence of dental decay in young children with previous dental extractions. Methods/Design: This 2-year, two-arm, multicentre, randomised controlled trial will include 224 child participants, initially aged 5 to 7 years, who are scheduled to have one or more primary teeth extracted for dental caries under general anaesthesia (GA), relative analgesia (RA: inhalation sedation) or local anaesthesia (LA). The trial will be conducted in University Dental Hospitals, Secondary Care Centres or other providers of dental extraction services across the United Kingdom. The intervention will include a brief negotiated interview (based on the principles of motivational interviewing) delivered between enrolment and 6 weeks post-extraction, followed by directed prevention in primary dental care. Participants will be followed up for 2 years. The main outcome measure will be the dental caries experienced by 2 years post-enrolment at the level of dentine involvement on any tooth in either dentition, which had been caries-free at the baseline assessment. Discussion: The participants are a hard-to-reach group in which secondary prevention is a challenge. Lack of engagement with dental care makes the children and their families scheduled for extraction particularly difficult to recruit to an RCT. Variations in service delivery between sites have also added to the challenges in implementing the Dental RECUR protocol during the recruitment phase. Trial registration: ISRCTN24958829 (date of registration: 27 September 2013), Current protocol version: 5.0

Analysis of Xq27-28 linkage in the international consortium for prostate cancer genetics (ICPCG) families.

BACKGROUND: Genetic variants are likely to contribute to a portion of prostate cancer risk. Full elucidation of the genetic etiology of prostate cancer is difficult because of incomplete penetrance and genetic and phenotypic heterogeneity. Current evidence suggests that genetic linkage to prostate cancer has been found on several chromosomes including the X; however, identification of causative genes has been elusive. METHODS: Parametric and non-parametric linkage analyses were performed using 26 microsatellite markers in each of 11 groups of multiple-case prostate cancer families from the International Consortium for Prostate Cancer Genetics (ICPCG). Meta-analyses of the resultant family-specific linkage statistics across the entire 1,323 families and in several predefined subsets were then performed. RESULTS: Meta-analyses of linkage statistics resulted in a maximum parametric heterogeneity lod score (HLOD) of 1.28, and an allele-sharing lod score (LOD) of 2.0 in favor of linkage to Xq27-q28 at 138 cM. In subset analyses, families with average age at onset less than 65 years exhibited a maximum HLOD of 1.8 (at 138 cM) versus a maximum regional HLOD of only 0.32 in families with average age at onset of 65 years or older. Surprisingly, the subset of families with only 2-3 affected men and some evidence of male-to-male transmission of prostate cancer gave the strongest evidence of linkage to the region (HLOD = 3.24, 134 cM). For this subset, the HLOD was slightly increased (HLOD = 3.47 at 134 cM) when families used in the original published report of linkage to Xq27-28 were excluded. CONCLUSIONS: Although there was not strong support for linkage to the Xq27-28 region in the complete set of families, the subset of families with earlier age at onset exhibited more evidence of linkage than families with later onset of disease. A subset of families with 2-3 affected individuals and with some evidence of male to male disease transmission showed stronger linkage signals. Our results suggest that the genetic basis for prostate cancer in our families is much more complex than a single susceptibility locus on the X chromosome, and that future explorations of the Xq27-28 region should focus on the subset of families identified here with the strongest evidence of linkage to this region.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Pathogenetics of alveolar capillary dysplasia with misalignment of pulmonary veins.

Alveolar capillary dysplasia with misalignment of pulmonary veins (ACDMPV) is a lethal lung developmental disorder caused by heterozygous point mutations or genomic deletion copy-number variants (CNVs) of FOXF1 or its upstream enhancer involving fetal lung-expressed long noncoding RNA genes LINC01081 and LINC01082. Using custom-designed array comparative genomic hybridization, Sanger sequencing, whole exome sequencing (WES), and bioinformatic analyses, we studied 22 new unrelated families (20 postnatal and two prenatal) with clinically diagnosed ACDMPV. We describe novel deletion CNVs at the FOXF1 locus in 13 unrelated ACDMPV patients. Together with the previously reported cases, all 31 genomic deletions in 16q24.1, pathogenic for ACDMPV, for which parental origin was determined, arose de novo with 30 of them occurring on the maternally inherited chromosome 16, strongly implicating genomic imprinting of the FOXF1 locus in human lungs. Surprisingly, we have also identified four ACDMPV families with the pathogenic variants in the FOXF1 locus that arose on paternal chromosome 16. Interestingly, a combination of the severe cardiac defects, including hypoplastic left heart, and single umbilical artery were observed only in children with deletion CNVs involving FOXF1 and its upstream enhancer. Our data demonstrate that genomic imprinting at 16q24.1 plays an important role in variable ACDMPV manifestation likely through long-range regulation of FOXF1 expression, and may be also responsible for key phenotypic features of maternal uniparental disomy 16. Moreover, in one family, WES revealed a de novo missense variant in ESRP1, potentially implicating FGF signaling in the etiology of ACDMPV

Chemical Elemental Distribution and Soil DNA Fingerprints Provide the Critical Evidence in Murder Case Investigation

Background: The scientific contribution to the solution of crime cases, or throughout the consequent forensic trials, is a crucial aspect of the justice system. The possibility to extract meaningful information from trace amounts of samples, and to match and validate evidences with robust and unambiguous statistical tests, are the key points of such process. The present report is the authorized disclosure of an investigation, carried out by Attorney General appointment, on a murder case in northern Italy, which yielded the critical supporting evidence for the judicial trial. Methodology/Principal Findings: The proportional distribution of 54 chemical elements and the bacterial community DNA fingerprints were used as signature markers to prove the similarity of two soil samples. The first soil was collected on the crime scene, along a corn field, while the second was found in trace amounts on the carpet of a car impounded from the main suspect in a distant location. The matching similarity of the two soils was proven by crossing the results of two independent techniques: a) elemental analysis via inductively coupled plasma mass spectrometry (ICP-MS) and optical emission spectrometry (ICP-OES) approaches, and b) amplified ribosomal DNA restriction analysis by gel electrophoresis (ARDRA). Conclusions: Besides introducing the novel application of these methods to forensic disciplines, the highly accurate level of resolution observed, opens new possibilities also in the fields of soil typing and tracking, historical analyses, geochemical surveys and global land mapping

Soil and Cultivar Type Shape the Bacterial Community in the Potato Rhizosphere

The rhizospheres of five different potato cultivars (including a genetically modified cultivar) obtained from a loamy sand soil and two from a sandy peat soil, next to corresponding bulk soils, were studied with respect to their community structures and potential function. For the former analyses, we performed bacterial 16S ribosomal RNA gene-based PCR denaturing gradient gel electrophoresis (PCR-DGGE) on the basis of soil DNA; for the latter, we extracted microbial communities and subjected these to analyses in phenotype arrays (PM1, PM2, and PM4, Biolog), with a focus on the use of different carbon, sulfur and phosphorus sources. In addition, we performed bacterial PCR-DGGE on selected wells to assess the structures of these substrate-responsive communities. Effects of soil type, the rhizosphere, and cultivar on the microbial community structures were clearly observed. Soil type was the most determinative parameter shaping the functional communities, whereas the rhizosphere and cultivar type also exerted an influence. However, no genetically modified plant effect was observed. The effects were imminent based on general community analysis and also single-compound analysis. Utilization of some of the carbon and sulfur sources was specific per cultivar, and different microbial communities were found as defined by cultivar. Thus, both soil and cultivar type shaped the potato root-associated bacterial communities that were responsive to some of the substrates in phenotype arrays

Indigenous Populations of Three Closely Related Lysobacter spp. in Agricultural Soils Using Real-Time PCR

Previous research had shown that three closely related species of Lysobacter, i.e., Lysobacter antibioticus, Lysobacter capsici, and Lysobacter gummosus, were present in different Rhizoctonia-suppressive soils. However, the population dynamics of these three Lysobacter spp. in different habitats remains unknown. Therefore, a specific primer–probe combination was designed for the combined quantification of these three Lysobacter spp. using TaqMan. Strains of the three target species were efficiently detected with TaqMan, whereas related non-target strains of Lysobacter enzymogenes and Xanthomonas campestris were not or only weakly amplified. Indigenous Lysobacter populations were analyzed in soils of 10 organic farms in the Netherlands during three subsequent years with TaqMan. These soils differed in soil characteristics and crop rotation. Additionally, Lysobacter populations in rhizosphere and bulk soil of different crops on one of these farms were studied. In acid sandy soils low Lysobacter populations were present, whereas pH neutral clay soils contained high populations (respectively, <4.0–5.87 and 6.22–6.95 log gene copy numbers g−1 soil). Clay content, pH and C/N ratio, but not organic matter content in soil, correlated with higher Lysobacter populations. Unexpectedly, different crops did not significantly influence population size of the three Lysobacter spp. and their populations were barely higher in rhizosphere than in bulk soil

Influenza A Gradual and Epochal Evolution: Insights from Simple Models

The recurrence of influenza A epidemics has originally been explained by a “continuous antigenic drift” scenario. Recently, it has been shown that if genetic drift is gradual, the evolution of influenza A main antigen, the haemagglutinin, is punctuated. As a consequence, it has been suggested that influenza A dynamics at the population level should be approximated by a serial model. Here, simple models are used to test whether a serial model requires gradual antigenic drift within groups of strains with the same antigenic properties (antigenic clusters). We compare the effect of status based and history based frameworks and the influence of reduced susceptibility and infectivity assumptions on the transient dynamics of antigenic clusters. Our results reveal that the replacement of a resident antigenic cluster by a mutant cluster, as observed in data, is reproduced only by the status based model integrating the reduced infectivity assumption. This combination of assumptions is useful to overcome the otherwise extremely high model dimensionality of models incorporating many strains, but relies on a biological hypothesis not obviously satisfied. Our findings finally suggest the dynamical importance of gradual antigenic drift even in the presence of punctuated immune escape. A more regular renewal of susceptible pool than the one implemented in a serial model should be part of a minimal theory for influenza at the population level

An Activation Force-based Affinity Measure for Analyzing Complex Networks

Affinity measure is a key factor that determines the quality of the analysis of a complex network. Here, we introduce a type of statistics, activation forces, to weight the links of a complex network and thereby develop a desired affinity measure. We show that the approach is superior in facilitating the analysis through experiments on a large-scale word network and a protein-protein interaction (PPI) network consisting of ∼5,000 human proteins. The experiment on the word network verifies that the measured word affinities are highly consistent with human knowledge. Further, the experiment on the PPI network verifies the measure and presents a general method for the identification of functionally similar proteins based on PPIs. Most strikingly, we find an affinity network that compactly connects the cancer-associated proteins to each other, which may reveal novel information for cancer study; this includes likely protein interactions and key proteins in cancer-related signal transduction pathways

Identification and Analysis of Co-Occurrence Networks with NetCutter

BACKGROUND: Co-occurrence analysis is a technique often applied in text mining, comparative genomics, and promoter analysis. The methodologies and statistical models used to evaluate the significance of association between co-occurring entities are quite diverse, however. METHODOLOGY/PRINCIPAL FINDINGS: We present a general framework for co-occurrence analysis based on a bipartite graph representation of the data, a novel co-occurrence statistic, and software performing co-occurrence analysis as well as generation and analysis of co-occurrence networks. We show that the overall stringency of co-occurrence analysis depends critically on the choice of the null-model used to evaluate the significance of co-occurrence and find that random sampling from a complete permutation set of the bipartite graph permits co-occurrence analysis with optimal stringency. We show that the Poisson-binomial distribution is the most natural co-occurrence probability distribution when vertex degrees of the bipartite graph are variable, which is usually the case. Calculation of Poisson-binomial P-values is difficult, however. Therefore, we propose a fast bi-binomial approximation for calculation of P-values and show that this statistic is superior to other measures of association such as the Jaccard coefficient and the uncertainty coefficient. Furthermore, co-occurrence analysis of more than two entities can be performed using the same statistical model, which leads to increased signal-to-noise ratios, robustness towards noise, and the identification of implicit relationships between co-occurring entities. Using NetCutter, we identify a novel protein biosynthesis related set of genes that are frequently coordinately deregulated in human cancer related gene expression studies. NetCutter is available at http://bio.ifom-ieo-campus.it/NetCutter/). CONCLUSION: Our approach can be applied to any set of categorical data where co-occurrence analysis might reveal functional relationships such as clinical parameters associated with cancer subtypes or SNPs associated with disease phenotypes. The stringency of our approach is expected to offer an advantage in a variety of applications