The Parameterized Complexity of Centrality Improvement in Networks

The centrality of a vertex v in a network intuitively captures how important v is for communication in the network. The task of improving the centrality of a vertex has many applications, as a higher centrality often implies a larger impact on the network or less transportation or administration cost. In this work we study the parameterized complexity of the NP-complete problems Closeness Improvement and Betweenness Improvement in which we ask to improve a given vertex' closeness or betweenness centrality by a given amount through adding a given number of edges to the network. Herein, the closeness of a vertex v sums the multiplicative inverses of distances of other vertices to v and the betweenness sums for each pair of vertices the fraction of shortest paths going through v. Unfortunately, for the natural parameter "number of edges to add" we obtain hardness results, even in rather restricted cases. On the positive side, we also give an island of tractability for the parameter measuring the vertex deletion distance to cluster graphs

Outlier Edge Detection Using Random Graph Generation Models and Applications

Outliers are samples that are generated by different mechanisms from other normal data samples. Graphs, in particular social network graphs, may contain nodes and edges that are made by scammers, malicious programs or mistakenly by normal users. Detecting outlier nodes and edges is important for data mining and graph analytics. However, previous research in the field has merely focused on detecting outlier nodes. In this article, we study the properties of edges and propose outlier edge detection algorithms using two random graph generation models. We found that the edge-ego-network, which can be defined as the induced graph that contains two end nodes of an edge, their neighboring nodes and the edges that link these nodes, contains critical information to detect outlier edges. We evaluated the proposed algorithms by injecting outlier edges into some real-world graph data. Experiment results show that the proposed algorithms can effectively detect outlier edges. In particular, the algorithm based on the Preferential Attachment Random Graph Generation model consistently gives good performance regardless of the test graph data. Further more, the proposed algorithms are not limited in the area of outlier edge detection. We demonstrate three different applications that benefit from the proposed algorithms: 1) a preprocessing tool that improves the performance of graph clustering algorithms; 2) an outlier node detection algorithm; and 3) a novel noisy data clustering algorithm. These applications show the great potential of the proposed outlier edge detection techniques.Comment: 14 pages, 5 figures, journal pape

Primary vs. Secondary Antibody Deficiency: Clinical Features and Infection Outcomes of Immunoglobulin Replacement

<div><p>Secondary antibody deficiency can occur as a result of haematological malignancies or certain medications, but not much is known about the clinical and immunological features of this group of patients as a whole. Here we describe a cohort of 167 patients with primary or secondary antibody deficiencies on immunoglobulin (Ig)-replacement treatment. The demographics, causes of immunodeficiency, diagnostic delay, clinical and laboratory features, and infection frequency were analysed retrospectively. Chemotherapy for B cell lymphoma and the use of Rituximab, corticosteroids or immunosuppressive medications were the most common causes of secondary antibody deficiency in this cohort. There was no difference in diagnostic delay or bronchiectasis between primary and secondary antibody deficiency patients, and both groups experienced disorders associated with immune dysregulation. Secondary antibody deficiency patients had similar baseline levels of serum IgG, but higher IgM and IgA, and a higher frequency of switched memory B cells than primary antibody deficiency patients. Serious and non-serious infections before and after Ig-replacement were also compared in both groups. Although secondary antibody deficiency patients had more serious infections before initiation of Ig-replacement, treatment resulted in a significant reduction of serious and non-serious infections in both primary and secondary antibody deficiency patients. Patients with secondary antibody deficiency experience similar delays in diagnosis as primary antibody deficiency patients and can also benefit from immunoglobulin-replacement treatment.</p></div

Beyond the culture effect on credibility perception on microblogs

We investigated the credibility perception of tweet readers from the USA and by readers from eight Arabic countries; our aim was to understand if credibility was affected by country and/or by culture. Results from a crowd-sourcing experiment, showed a wide variety of factors affected credibility perception, including a tweet author&#039;s gender, profile image, username style, location, and social network overlap with the reader. We found that culture determines readers&#039; credibility perception, but country has no effect. We discuss the implications of our findings for user interface design and social media systems

Climate change promotes parasitism in a coral symbiosis.

Coastal oceans are increasingly eutrophic, warm and acidic through the addition of anthropogenic nitrogen and carbon, respectively. Among the most sensitive taxa to these changes are scleractinian corals, which engineer the most biodiverse ecosystems on Earth. Corals' sensitivity is a consequence of their evolutionary investment in symbiosis with the dinoflagellate alga, Symbiodinium. Together, the coral holobiont has dominated oligotrophic tropical marine habitats. However, warming destabilizes this association and reduces coral fitness. It has been theorized that, when reefs become warm and eutrophic, mutualistic Symbiodinium sequester more resources for their own growth, thus parasitizing their hosts of nutrition. Here, we tested the hypothesis that sub-bleaching temperature and excess nitrogen promotes symbiont parasitism by measuring respiration (costs) and the assimilation and translocation of both carbon (energy) and nitrogen (growth; both benefits) within Orbicella faveolata hosting one of two Symbiodinium phylotypes using a dual stable isotope tracer incubation at ambient (26 °C) and sub-bleaching (31 °C) temperatures under elevated nitrate. Warming to 31 °C reduced holobiont net primary productivity (NPP) by 60% due to increased respiration which decreased host %carbon by 15% with no apparent cost to the symbiont. Concurrently, Symbiodinium carbon and nitrogen assimilation increased by 14 and 32%, respectively while increasing their mitotic index by 15%, whereas hosts did not gain a proportional increase in translocated photosynthates. We conclude that the disparity in benefits and costs to both partners is evidence of symbiont parasitism in the coral symbiosis and has major implications for the resilience of coral reefs under threat of global change

Theories for influencer identification in complex networks

In social and biological systems, the structural heterogeneity of interaction networks gives rise to the emergence of a small set of influential nodes, or influencers, in a series of dynamical processes. Although much smaller than the entire network, these influencers were observed to be able to shape the collective dynamics of large populations in different contexts. As such, the successful identification of influencers should have profound implications in various real-world spreading dynamics such as viral marketing, epidemic outbreaks and cascading failure. In this chapter, we first summarize the centrality-based approach in finding single influencers in complex networks, and then discuss the more complicated problem of locating multiple influencers from a collective point of view. Progress rooted in collective influence theory, belief-propagation and computer science will be presented. Finally, we present some applications of influencer identification in diverse real-world systems, including online social platforms, scientific publication, brain networks and socioeconomic systems.Comment: 24 pages, 6 figure

Psychological interventions in asthma

Asthma is a multifactorial chronic respiratory disease characterised by recurrent episodes of airway obstruction. The current management of asthma focuses principally on pharmacological treatments, which have a strong evidence base underlying their use. However, in clinical practice, poor symptom control remains a common problem for patients with asthma. Living with asthma has been linked with psychological co-morbidity including anxiety, depression, panic attacks and behavioural factors such as poor adherence and suboptimal self-management. Psychological disorders have a higher-than-expected prevalence in patients with difficult-to-control asthma. As psychological considerations play an important role in the management of people with asthma, it is not surprising that many psychological therapies have been applied in the management of asthma. There are case reports which support their use as an adjunct to pharmacological therapy in selected individuals, and in some clinical trials, benefit is demonstrated, but the evidence is not consistent. When findings are quantitatively synthesised in meta-analyses, no firm conclusions are able to be drawn and no guidelines recommend psychological interventions. These inconsistencies in findings may in part be due to poor study design, the combining of results of studies using different interventions and the diversity of ways patient benefit is assessed. Despite this weak evidence base, the rationale for psychological therapies is plausible, and this therapeutic modality is appealing to both patients and their clinicians as an adjunct to conventional pharmacological treatments. What are urgently required are rigorous evaluations of psychological therapies in asthma, on a par to the quality of pharmaceutical trials. From this evidence base, we can then determine which interventions are beneficial for our patients with asthma management and more specifically which psychological therapy is best suited for each patient

FAK acts as a suppressor of RTK-MAP kinase signalling in Drosophila melanogaster epithelia and human cancer cells

Receptor Tyrosine Kinases (RTKs) and Focal Adhesion Kinase (FAK) regulate multiple signalling pathways, including mitogen-activated protein (MAP) kinase pathway. FAK interacts with several RTKs but little is known about how FAK regulates their downstream signalling. Here we investigated how FAK regulates signalling resulting from the overexpression of the RTKs RET and EGFR. FAK suppressed RTKs signalling in Drosophila melanogaster epithelia by impairing MAPK pathway. This regulation was also observed in MDA-MB-231 human breast cancer cells, suggesting it is a conserved phenomenon in humans. Mechanistically, FAK reduced receptor recycling into the plasma membrane, which resulted in lower MAPK activation. Conversely, increasing the membrane pool of the receptor increased MAPK pathway signalling. FAK is widely considered as a therapeutic target in cancer biology; however, it also has tumour suppressor properties in some contexts. Therefore, the FAK-mediated negative regulation of RTK/MAPK signalling described here may have potential implications in the designing of therapy strategies for RTK-driven tumours

Prevalence, prenatal screening and neonatal features in children with Down syndrome: a registry-based national study

BACKGROUND: Down syndrome (DS) is one of the most common chromosomal abnormalities among newborns. In recent years advances in perinatal and neonatal care have improved chance of survival for the children with DS. The objective of this Registry-Based study was to get more accurate data of DS prevalence with evaluation of antenatal screening, neonatal and maternal features among total births in Croatia from 2009 to 2012. ----- METHODS: We used retrospectively collected data for DS newborns from the medical birth database and perinatal mortality database for the period of 2009-2012. Differences between DS and the referent population for each year in quantitative measures were assessed with the independent t-test. Other differences in nominal and categorical values were analyzed with the chi-square test. ----- RESULTS: The total prevalence for DS in the period of 2009-2012 was 7.01 per 10,000 births, while the live-birth prevalence was 6.49 per 10,000 births. The significant differences (p < 0.05) between the DS and reference populations for each year were noticed for birth weight and length, gestational age, mother age, Apgar score of ≥6 after 5 min and breastfeeding. Among newborns with DS, there were 64 (53.33 %) males and 56 (46.67 %) females versus 88,587 (51.76 %) males and 82,553 (48.23 %) females in the reference population. In the DS group compared to the reference population the mean birth weight was 2845 grams versus 3467 grams in males and 2834 grams versus 3329 grams in females, respectively, with a mean birth length of 47 cm versus 50 cm for both genders. The mean gestational age of the DS births was 37 weeks and the mean age of the mothers was 32.6 years, versus 39 weeks and 29.1 years, respectively, in the reference population. Only 68.3 % of children with DS were breastfed from birth, compared with 94.72 % of children in the reference population. ----- CONCLUSIONS: The significant differences for neonatal and maternal features between DS and the referent population were found similar to other studies. The total prevalence of DS in Croatia in the period of 2009-2012 was lower than the previously estimated prevalence based on EUROCAT data. The establishment of a new national registry of congenital malformations covering 99 % of all births in Croatia is necessary to improve the health and prosperity of children, adolescents and adults with DS in Croatia