Uncovering the overlapping community structure of complex networks in nature and society

Many complex systems in nature and society can be described in terms of networks capturing the intricate web of connections among the units they are made of. A key question is how to interpret the global organization of such networks as the coexistence of their structural subunits (communities) associated with more highly interconnected parts. Identifying these a priori unknown building blocks (such as functionally related proteins, industrial sectors and groups of people) is crucial to the understanding of the structural and functional properties of networks. The existing deterministic methods used for large networks find separated communities, whereas most of the actual networks are made of highly overlapping cohesive groups of nodes. Here we introduce an approach to analysing the main statistical features of the interwoven sets of overlapping communities that makes a step towards uncovering the modular structure of complex systems. After defining a set of new characteristic quantities for the statistics of communities, we apply an efficient technique for exploring overlapping communities on a large scale. We find that overlaps are significant, and the distributions we introduce reveal universal features of networks. Our studies of collaboration, word-association and protein interaction graphs show that the web of communities has non-trivial correlations and specific scaling properties.Comment: The free academic research software, CFinder, used for the publication is available at the website of the publication: http://angel.elte.hu/clusterin

Amelioration of Proteolipid Protein 139–151-Induced Encephalomyelitis in SJL Mice by Modified Amino Acid Copolymers and Their Mechanisms

Copolymer 1 [Cop1, glatiramer acetate, Copaxone, poly(Y,E,A,K)n] is widely used in the treatment of relapsing/remitting multiple sclerosis in which it reduces the frequency of relapses by ≈30%. In the present study, copolymers with modified amino acid compositions (based on the binding motif of myelin basic protein 85–99 to HLA-DR2) have been developed with the aim of suppressing multiple sclerosis more effectively. The enhanced efficacy of these copolymers in experimental autoimmune encephalomyelitis (EAE) induced in SJL/J mice with proteolipid protein 139–151 was demonstrated by using three protocols: (i) simultaneous administration of autoantigen and copolymer (termed prevention), (ii) pretreatment with copolymers (vaccination), or (iii) administration of copolymers after disease onset (treatment). Strikingly, in the treatment protocol administration of soluble VWAK and FYAK after onset of disease led to stasis of its progression and suppression of histopathological evidence of EAE. The mechanisms by which these effects are achieved have been examined in several types of assays: binding of copolymers to I-As in competition with proteolipid protein 139–151 (blocking), cytokine production by T cells (T helper 2 polarization), and transfer of protection by CD3+ splenocytes or, notably, by copolymer-specific T cell lines (induction of regulatory T cells). The generation of these copolymerspecific regulatory T cells that secrete IL-4 and IL-10 and are independent of the immunizing autoantigen is very prominent among the multiple mechanisms that account for the observed suppressive effect of copolymers in EAE

Spectra of "Real-World" Graphs: Beyond the Semi-Circle Law

Many natural and social systems develop complex networks, that are usually modelled as random graphs. The eigenvalue spectrum of these graphs provides information about their structural properties. While the semi-circle law is known to describe the spectral density of uncorrelated random graphs, much less is known about the eigenvalues of real-world graphs, describing such complex systems as the Internet, metabolic pathways, networks of power stations, scientific collaborations or movie actors, which are inherently correlated and usually very sparse. An important limitation in addressing the spectra of these systems is that the numerical determination of the spectra for systems with more than a few thousand nodes is prohibitively time and memory consuming. Making use of recent advances in algorithms for spectral characterization, here we develop new methods to determine the eigenvalues of networks comparable in size to real systems, obtaining several surprising results on the spectra of adjacency matrices corresponding to models of real-world graphs. We find that when the number of links grows as the number of nodes, the spectral density of uncorrelated random graphs does not converge to the semi-circle law. Furthermore, the spectral densities of real-world graphs have specific features depending on the details of the corresponding models. In particular, scale-free graphs develop a triangle-like spectral density with a power law tail, while small-world graphs have a complex spectral density function consisting of several sharp peaks. These and further results indicate that the spectra of correlated graphs represent a practical tool for graph classification and can provide useful insight into the relevant structural properties of real networks.Comment: 14 pages, 9 figures (corrected typos, added references) accepted for Phys. Rev.

Freezing by Heating in a Driven Mesoscopic System

We investigate a simple model corresponding to particles driven in opposite directions and interacting via a repulsive potential. The particles move off-lattice on a periodic strip and are subject to random forces as well. We show that this model - which can be considered as a continuum version of some driven diffusive systems - exhibits a paradoxial, new kind of transition called here ``freezing by heating''. One interesting feature of this transition is that a crystallized state with a higher total energy is obtained from a fluid state by increasing the amount of fluctuations.Comment: For related work see http://www.theo2.physik.uni-stuttgart.de/helbing.html and http://angel.elte.hu/~vicsek

Substantial variation across geographic regions in the obesity prevalence among 6–8 years old Hungarian children (COSI Hungary 2016)

Abstract Background There have been previous representative nutritional status surveys conducted in Hungary, but this is the first one that examines overweight and obesity prevalence according to the level of urbanization and in different geographic regions among 6–8-year-old children. We also assessed whether these variations were different by sex. Methods This survey was part of the fourth data collection round of World Health Organization (WHO) Childhood Obesity Surveillance Initiative which took place during the academic year 2016/2017. The representative sample was determined by two-stage cluster sampling. A total of 5332 children (48.4% boys; age 7.54 ± 0.64 years) were measured from all seven geographic regions including urban (at least 500 inhabitants per square kilometer; n = 1598), semi-urban (100 to 500 inhabitants per square kilometer; n = 1932) and rural (less than 100 inhabitants per square kilometer; n = 1802) areas. Results Using the WHO reference, prevalence of overweight and obesity within the whole sample were 14.2, and 12.7%, respectively. According to the International Obesity Task Force (IOTF) reference, rates were 12.6 and 8.6%. Northern Hungary and Southern Transdanubia were the regions with the highest obesity prevalence of 11.0 and 12.0%, while Central Hungary was the one with the lowest obesity rate (6.1%). The prevalence of overweight and obesity tended to be higher in rural areas (13.0 and 9.8%) than in urban areas (11.9 and 7.0%). Concerning differences in sex, girls had higher obesity risk in rural areas (OR = 2.0) but boys did not. Odds ratios were 2.0–3.4 in different regions for obesity compared to Central Hungary, but only among boys. Conclusions Overweight and obesity are emerging problems in Hungary. Remarkable differences were observed in the prevalence of obesity by geographic regions. These variations can only be partly explained by geographic characteristics. Trial registration Study protocol was approved by the Scientific and Research Ethics Committee of the Medical Research Council (61158–2/2016/EKU)

The phase 3 DUO trial: duvelisib vs ofatumumab in relapsed and refractory CLL/SLL

Duvelisib (also known as IPI-145) is an oral, dual inhibitor of phosphatidylinositol 3-kinase δ and γ (PI3K-δ,γ) being developed for treatment of hematologic malignancies. PI3K-δ,γ signaling can promote B-cell proliferation and survival in clonal B-cell malignancies, such as chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL). In a phase 1 study, duvelisib showed clinically meaningful activity and acceptable safety in CLL/SLL patients. We report here the results of DUO, a global phase 3 randomized study of duvelisib vs ofatumumab monotherapy for patients with relapsed or refractory (RR) CLL/SLL. Patients were randomized 1:1 to oral duvelisib 25 mg twice daily (n = 160) or ofatumumab IV (n = 159). The study met the primary study end point by significantly improving progression-free survival per independent review committee assessment compared with ofatumumab for all patients (median, 13.3 months vs 9.9 months; hazard ratio [HR] = 0.52; P < .0001), including those with high-risk chromosome 17p13.1 deletions [del(17p)] and/or TP53 mutations (HR = 0.40; P = .0002). The overall response rate was significantly higher with duvelisib (74% vs 45%; P < .0001) regardless of del(17p) status. The most common adverse events were diarrhea, neutropenia, pyrexia, nausea, anemia, and cough on the duvelisib arm, and neutropenia and infusion reactions on the ofatumumab arm. The DUO trial data support duvelisib as a potentially effective treatment option for patients with RR CLL/SLL. This trial was registered at www.clinicaltrials.gov as #NCT02004522

In middle-aged and old obese patients, training intervention reduces leptin level: A meta-analysis

BACKGROUND: Leptin is one of the major adipokines in obesity that indicates the severity of fat accumulation. It is also an important etiological factor of consequent cardiometabolic and autoimmune disorders. Aging has been demonstrated to aggravate obesity and to induce leptin resistance and hyperleptinemia. Hyperleptinemia, on the other hand, may promote the development of age-related abnormalities. While major weight loss has been demonstrated to ameliorate hyperleptinemia, obese people show a poor tendency to achieve lasting success in this field. The question arises whether training intervention per se is able to reduce the level of this adipokine. OBJECTIVES: We aimed to review the literature on the effects of training intervention on peripheral leptin level in obesity during aging, in order to evaluate the independent efficacy of this method. In the studies that were included in our analysis, changes of adiponectin levels (when present) were also evaluated. DATA SOURCES: 3481 records were identified through searching of PubMed, Embase and Cochrane Library Database. Altogether 19 articles were suitable for analyses. STUDY ELIGIBILITY CRITERIA: Empirical research papers were eligible provided that they reported data of middle-aged or older (above 45 years of age) overweight or obese (body mass index above 25) individuals and included physical training intervention or at least fitness status of groups together with corresponding blood leptin values. STATISTICAL METHODS: We used random effect models in each of the meta-analyses calculating with the DerSimonian and Laird weighting methods. I-squared indicator and Q test were performed to assess heterogeneity. To assess publication bias Egger's test was applied. In case of significant publication bias, the Duval and Tweedie's trim and fill algorithm was used. RESULTS: Training intervention leads to a decrease in leptin level of middle-aged or older, overweight or obese male and female groups, even without major weight loss, indicated by unchanged serum adiponectin levels. Resistance training appears to be more efficient in reducing blood leptin level than aerobic training alone. CONCLUSIONS: Physical training, especially resistance training successfully reduces hyperleptinemia even without diet or major weight loss