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Introduction: To evaluate the efficacy and safety of sirukumab in giant cell arteritis (GCA). Methods: In this multicentre, randomised, double-blind, placebo-controlled, two-part phase 3 trial (NCT02531633; Part A [52-week double-blind treatment]; Part B [104-week follow-up]), patients with GCA were randomised (3:3:2:2:2) to sirukumab 100 mg every 2 weeks plus 6-month or 3-month prednisone taper, sirukumab 50 mg every 4 weeks plus 6-month prednisone taper, or placebo every 2 weeks plus 6-month or 12-month prednisone taper. The primary endpoint was the proportion of patients in sustained remission at week 52. Secondary endpoints included disease flare and safety. The study was terminated early (October 2017; sponsor decision). Results: Of 161 patients randomised (sirukumab: n = 107; placebo: n = 54), 28 (17.4%) completed week 52 (median treatment duration: 24–30 weeks). In a revised intent-to-treat (ITT) subgroup (completed week 52 or discontinued before study termination [n = 55]); six patients (all receiving sirukumab) achieved the primary endpoint. In the ITT population (n = 161), the proportion of patients with flares (week 2–52) was lower with sirukumab (18.4–30.8%) than placebo (37.0–40.0%). The proportion of patients with flares (week 2–12) was highest with sirukumab 100 mg every 2 weeks plus 3-month prednisone taper (23.1%). In Part A, 94.4% of patients reported ≥ 1 treatment-emergent adverse event (TEAE); 19.3% reported serious TEAEs. The proportions of patients with TEAEs were generally similar across treatment arms. No deaths occurred. Conclusions: Although data were limited due to early termination and shortened treatment duration, sirukumab treatment resulted in numerically lower proportions of patients with flare by week 52 versus placebo, with no unexpected safety findings. Trial Registration: Clinicaltrials.gov: NCT02531633. [ABSTRACT FROM AUTHOR]

Anomaly detection problems (also called change-point detection problems) have been studied in data mining, statistics and computer science over the last several decades (mostly in non-network context) in applications such as medical condition monitoring, weather change detection and speech recognition. In recent days, however, anomaly detection problems have become increasing more relevant in the context of network science since useful insights for many complex systems in biology, finance and social science are often obtained by representing them via networks. Notions of local and non-local curvatures of higher-dimensional geometric shapes and topological spaces play a fundamental role in physics and mathematics in characterizing anomalous behaviours of these higher dimensional entities. However, using curvature measures to detect anomalies in networks is not yet very common. To this end, a main goal in this paper to formulate and analyze curvature analysis methods to provide the foundations of systematic approaches to find critical components and detect anomalies in networks. For this purpose, we use two measures of network curvatures which depend on non-trivial global properties, such as distributions of geodesics and higher-order correlations among nodes, of the given network. Based on these measures, we precisely formulate several computational problems related to anomaly detection in static or dynamic networks, and provide non-trivial computational complexity results for these problems. This paper must not be viewed as delivering the final word on appropriateness and suitability of specific curvature measures. Instead, it is our hope that this paper will stimulate and motivate further theoretical or empirical research concerning the exciting interplay between notions of curvatures from network and non-network domains, a much desired goal in our opinion. [ABSTRACT FROM AUTHOR]

Characterizing shapes of high-dimensional objects via Ricci curvatures plays a critical role in many research areas in mathematics and physics. However, even though several discretizations of Ricci curvatures for discrete combinatorial objects such as networks have been proposed and studied by mathematicians, the computational complexity aspects of these discretizations have escaped the attention of theoretical computer scientists to a large extent. In this paper, we study one such discretization, namely the Ollivier-Ricci curvature, from the perspective of efficient computation by fine-grained reductions and local query-based algorithms. Our main contributions are the following. ▹ We relate our curvature computation problem to minimum weight perfect matching problem on complete bipartite graphs via fine-grained reduction. ▹ We formalize the computational aspects of the curvature computation problems in suitable frameworks so that they can be studied by researchers in local algorithms. ▹ We provide the first known lower and upper bounds on queries for query-based algorithms for the curvature computation problems in our local algorithms framework. En route , we also illustrate a localized version of our fine-grained reduction. We believe that our results bring forth an intriguing set of research questions, motivated both in theory and practice, regarding designing efficient algorithms for curvatures of geometrical objects. • We relate our curvature computation problem to minimum weight perfect matching problem via fine-grained reduction. • We formalize the curvature computation problems so that they can be studied by researchers in local algorithms. • We provide first known query bounds for query-based algorithms for curvature computations in local algorithms framework. • We illustrate a localized version of fine-grained reductions. [ABSTRACT FROM AUTHOR]

With the arrival of modern internet era, large public networks of various types have come to existence to benefit the society as a whole and several research areas such as sociology, economics and geography in particular. However, the societal and research benefits of these networks have also given rise to potentially significant privacy issues in the sense that malicious entities may violate the privacy of the users of such a network by analyzing the network and deliberately using such privacy violations for deleterious purposes. Such considerations have given rise to a new active research area that deals with the quantification of privacy of users in large networks and the corresponding investigation of computational complexity issues of computing such quantified privacy measures. In this paper, we formalize three natural problems related to such a privacy measure for large networks and provide non-trivial theoretical computational complexity results for solving these problems. Our results show the first two problems can be solved efficiently, whereas the third problem is provably hard to solve within a logarithmic approximation factor. Furthermore, we also provide computational complexity results for the case when the privacy requirement of the network is severely restricted, including an efficient logarithmic approximation. [ABSTRACT FROM AUTHOR]

GCA shares many clinical features with PMR and Takayasu arteritis. The current mainstay of therapy for all three conditions is glucocorticoid therapy. Given the chronic, relapsing nature of these conditions and the morbidity associated with glucocorticoid therapy, there is a need for better treatment options to induce and sustain remission with fewer adverse effects. Conventional immunosuppressive treatments have been studied and have a modest effect. There is a keen interest in biologic therapies with studies showing the efficacy of IL-6 antagonists in PMR and GCA. Recently the first two randomized clinical trials in Takayasu arteritis have been completed. A major challenge for all of these conditions is the lack of standardized measures to assess disease activity. Long-term studies are needed to evaluate the impact of biologic therapies showing potential on important clinical outcomes such as vascular damage, cost-effectiveness and quality of life. The optimal duration of treatment also needs to be assessed. [ABSTRACT FROM AUTHOR]

The strong metric dimension of a graph was first introduced by Sebö and Tannier (2004) as an alternative to the (weak) metric dimension of graphs previously introduced independently by Slater (1975) and by Harary and Melter (1976), and has since been investigated in several research papers. However, the exact worst-case computational complexity of computing the strong metric dimension has remained open beyond being NP -complete. In this communication, we show that the problem of computing the strong metric dimension of a graph of n nodes admits a polynomial-time 2 -approximation, admits a O ∗ ( 2 0 . 287 n ) -time exact computation algorithm, admits a O ( 1 . 273 8 k + n k ) -time exact computation algorithm if the strong metric dimension is at most k , does not admit a polynomial time ( 2 − ε ) -approximation algorithm assuming the unique games conjecture is true, does not admit a polynomial time ( 10 5 − 21 − ε ) -approximation algorithm assuming P ≠ NP , does not admit a O ∗ ( 2 o ( n ) ) -time exact computation algorithm assuming the exponential time hypothesis is true, and does not admit a O ∗ ( n o ( k ) ) -time exact computation algorithm if the strong metric dimension is at most k assuming the exponential time hypothesis is true. [ABSTRACT FROM AUTHOR]

In studies of molecular evolution, phylogenetic trees are rooted binary trees, whereas phylogenetic networks are rooted acyclic digraphs. Edges are directed away from the root and leaves are uniquely labeled with taxa in phylogenetic networks. For the purpose of validating evolutionary models, biologists check whether or not a phylogenetic tree (resp. cluster) is contained in a phylogenetic network on the same taxa. These tree and cluster containment problems are known to be NP-complete. A phylogenetic network is reticulation-visible if every reticulation node separates the root of the network from at least a leaf. We answer an open problem by proving that the tree containment problem is solvable in quadratic time for reticulation-visible networks. The key tool used in our answer is a powerful decomposition theorem. It also allows us to design a linear-time algorithm for the cluster containment problem for networks of this type and to prove that every galled network with n leaves has 2 ( n − 1 ) reticulation nodes at most. [ABSTRACT FROM AUTHOR]

Virtual-system coupled adaptive umbrella sampling (VAUS) enhances sampling along a reaction coordinate by using a virtual degree of freedom. However, VAUS and regular adaptive umbrella sampling (AUS) methods are yet computationally expensive. To decrease the computational burden further, improvements of VAUS for all-atom explicit solvent simulation are presented here. The improvements include probability distribution calculation by a Markov approximation; parameterization of biasing forces by iterative polynomial fitting; and force scaling. These when applied to study Ala-pentapeptide dimerization in explicit solvent showed advantage over regular AUS. By using improved VAUS larger biological systems are amenable. [ABSTRACT FROM AUTHOR]

A novel enhanced conformational sampling method, virtual-system-coupled adaptive umbrella sampling (V-AUS), was proposed to compute 300-K free-energy landscape for flexible molecular docking, where a virtual degrees of freedom was introduced to control the sampling. This degree of freedom interacts with the biomolecular system. V-AUS was applied to complex formation of two disordered amyloid-β (Aβ30-35) peptides in a periodic box filled by an explicit solvent. An interpeptide distance was defined as the reaction coordinate, along which sampling was enhanced. A uniform conformational distribution was obtained covering a wide interpeptide distance ranging from the bound to unbound states. The 300-K free-energy landscape was characterized by thermodynamically stable basins of antiparallel and parallel β-sheet complexes and some other complex forms. Helices were frequently observed, when the two peptides contacted loosely or fluctuated freely without interpeptide contacts. We observed that V-AUS converged to uniform distribution more effectively than conventional AUS sampling did. © 2015 Wiley Periodicals, Inc. [ABSTRACT FROM AUTHOR]

Threats on the stability of a financial system may severely affect the functioning of the entire economy, and thus considerable emphasis is placed on the analyzing the cause and effect of such threats. The financial crisis in the current and past decade has shown that one important cause of instability in global markets is the so-called financial contagion, namely the spreadings of instabilities or failures of individual components of the network to other, perhaps healthier, components. This leads to a natural question of whether the regulatory authorities could have predicted and perhaps mitigated the current economic crisis by effective computations of some stability measure of the banking networks. Motivated by such observations, we consider the problem of defining and evaluating stabilities of both homogeneous and heterogeneous banking networks against propagation of synchronous idiosyncratic shocks given to a subset of banks. We formalize the homogeneous banking network model of Nier et al. (J. Econ. Dyn. Control 31:2033-2060, ) and its corresponding heterogeneous version, formalize the synchronous shock propagation procedures outlined in (Nier et al. J. Econ. Dyn. Control 31:2033-2060, ; M. Eboli Mimeo, ), define two appropriate stability measures and investigate the computational complexities of evaluating these measures for various network topologies and parameters of interest. Our results and proofs also shed some light on the properties of topologies and parameters of the network that may lead to higher or lower stabilities. [ABSTRACT FROM AUTHOR]

Ensuring fairness in computational problems has emerged as a key topic during recent years, buoyed by considerations for equitable resource distributions and social justice. It is possible to incorporate fairness in computational problems from several perspectives, such as using optimization, game-theoretic or machine learning frameworks. In this paper we address the problem of incorporation of fairness from a combinatorial optimization perspective. We formulate a combinatorial optimization framework, suitable for analysis by researchers in approximation algorithms and related areas, that incorporates fairness in maximum coverage problems as an interplay between two conflicting objectives. Fairness is imposed in coverage by using coloring constraints that minimizes the discrepancies between number of elements of different colors covered by selected sets; this is in contrast to the usual discrepancy minimization problems studied extensively in the literature where (usually two) colors are not given a priori but need to be selected to minimize the maximum color discrepancy of each individual set. Our main results are a set of randomized and deterministic approximation algorithms that attempts to simultaneously approximate both fairness and coverage in this framework. [ABSTRACT FROM AUTHOR]

In the past few years, multi-objective optimization algorithms have been extensively applied in several fields including engineering design problems. A major reason is the advancement of evolutionary multi-objective optimization (EMO) algorithms that are able to find a set of non-dominated points spread on the respective Pareto-optimal front in a single simulation. Besides just finding a set of Pareto-optimal solutions, one is often interested in capturing knowledge about the variation of variable values over the Pareto-optimal front. Recentinnovizationapproaches for knowledge discovery from Pareto-optimal solutions remain as a major activity in this direction. In this article, a different data-fitting approach for continuous parameterization of the Pareto-optimal front is presented. Cubic B-spline basis functions are used for fitting the data returned by an EMO procedure in a continuous variable space. No prior knowledge about the order in the data is assumed. An automatic procedure for detecting gaps in the Pareto-optimal front is also implemented. The algorithm takes points returned by the EMO as input and returns the control points of the B-spline manifold representing the Pareto-optimal set. Results for several standard and engineering, bi-objective and tri-objective optimization problems demonstrate the usefulness of the proposed procedure. [ABSTRACT FROM PUBLISHER]

In this survey paper, we will present a number of core algorithmic questions concerning several transitive reduction problems on network that have applications in network synthesis and analysis involving cellular processes. Our starting point will be the so-called minimum equivalent digraph problem, a classic computational problem in combinatorial algorithms. We will subsequently consider a few non-trivial extensions or generalizations of this problem motivated by applications in systems biology. We will then discuss the applications of these algorithmic methodologies in the context of three major biological research questions: synthesizing and simplifying signal transduction networks, analyzing disease networks, and measuring redundancy of biological networks. [ABSTRACT FROM AUTHOR]

The elastic network model (ENM) is a widely used method to study native protein dynamics by normal mode analysis (NMA). In ENM we need information about all pairwise distances, and the distance between contacting atoms is restrained to the native value. Therefore ENM requires O(N2) information to realize its dynamics for a protein consisting of N amino acid residues. To see if (or to what extent) such a large amount of specific structural information is required to realize native protein dynamics, here we introduce a novel model based on only O(N) restraints. This model, named the ‘contact number diffusion’ model (CND), includes specific distance restraints for only local (along the amino acid sequence) atom pairs, and semi-specific non-local restraints imposed on each atom, rather than atom pairs. The semi-specific non-local restraints are defined in terms of the non-local contact numbers of atoms. The CND model exhibits the dynamic characteristics comparable to ENM and more correlated with the explicit-solvent molecular dynamics simulation than ENM. Moreover, unrealistic surface fluctuations often observed in ENM were suppressed in CND. On the other hand, in some ligand-bound structures CND showed larger fluctuations of buried protein atoms interacting with the ligand compared to ENM. In addition, fluctuations from CND and ENM show comparable correlations with the experimental B-factor. Although there are some indications of the importance of some specific non-local interactions, the semi-specific non-local interactions are mostly sufficient for reproducing the native protein dynamics. [ABSTRACT FROM AUTHOR]

In this article, a strategy is presented to exploitclassical algorithmsfor multimodal optimization problems, which recursively applies any suitable local optimization method, in the present case Nelder and Mead's simplex search method, in the search domain. The proposed method follows a systematic way to restart the algorithm. The idea of climbing the hills and sliding down to the neighbouring valleys is utilized. The implementation of the algorithm finds local minima as well as maxima. The concept of perturbing the minimum/maximum in several directions and restarting the algorithm for maxima/minima is introduced. The method performs favourably in comparison to other global optimization methods. The results of this algorithm, named RePAMO, are compared with the GA–clearing and ASMAGO techniques in terms of the number of function evaluations. Based on the results, it has been found that the RePAMO outperforms GA clearing and ASMAGO by a significant margin. [ABSTRACT FROM AUTHOR]

Internet advertising is a sophisticated game in which the many advertisers 'play' to optimize their return on investment. There are many 'targets' for the advertisements, and each 'target' has a collection of games with a potentially different set of players involved. In this paper, we study the problem of how advertisers allocate their budget across these 'targets'. In particular, we focus on formulating their best response strategy as an optimization problem. Advertisers have a set of keywords ('targets') and some stochastic information about the future, namely a probability distribution over scenarios of cost vs click combinations. This summarizes the potential states of the world assuming that the strategies of other players are fixed. Then, the best response can be abstracted as stochastic budget optimization problems to figure out how to spread a given budget across these keywords to maximize the expected number of clicks. We present the first known non-trivial poly-logarithmic approximation for these problems as well as the first known hardness results of getting better than logarithmic approximation ratios in the various parameters involved. We also identify several special cases of these problems of practical interest, such as with fixed number of scenarios or with polynomial-sized parameters related to cost, which are solvable either in polynomial time or with improved approximation ratios. Stochastic budget optimization with scenarios has sophisticated technical structure. Our approximation and hardness results come from relating these problems to a special type of (0/1, bipartite) quadratic programs inherent in them. Our research answers some open problems raised by the authors (in Algorithmica, 58(4):1022-1044, ). [ABSTRACT FROM AUTHOR]

Abstract: Given a graph of interactions, a module (also called a community or cluster) is a subset of nodes whose fitness is a function of the statistical significance of the pairwise interactions of nodes in the module. The topic of this paper is a model-based community finding approach, commonly referred to as modularity clustering, that was originally proposed by Newman (Leicht and Newman, 2008 [25]) and has subsequently been extremely popular in practice (e.g., see Agarwal and Kempe, 2008 [1], Guimer‘a et al., 2007 [20], Newman, 2006 [28], Newman and Girvan, 2004 [30], Ravasz et al., 2002 [32]). Various heuristic methods are currently employed for finding the optimal solution. However, as observed in Agarwal and Kempe (2008) [1], the exact computational complexity of this approach is still largely unknown. To this end, we initiate a systematic study of the computational complexity of modularity clustering. Due to the specific quadratic nature of the modularity function, it is necessary to study its value on sparse graphs and dense graphs separately. Our main results include a -inapproximability for dense graphs and a logarithmic approximation for sparse graphs. We make use of several combinatorial properties of modularity to get these results. These are the first non-trivial approximability results beyond the NP-hardness results in Brandes et al. (2007) [10]. [Copyright &y& Elsevier]

Drug target identification is of significant commercial interest to pharmaceutical companies, and there is a vast amount of research done related to the topic of therapeutic target identification. Interdisciplinary research in this area involves both the biological network community and the graph algorithms community. Key steps of a typical therapeutic target identification problem include synthesizing or inferring the complex network of interactions relevant to the disease, connecting this network to the disease-specific behavior, and predicting which components are key mediators of the behavior. All of these steps involve graph theoretical or graph algorithmic aspects. In this perspective, we provide modelling and algorithmic perspectives for therapeutic target identification and highlight a number of algorithmic advances, which have gotten relatively little attention so far, with the hope of strengthening the ties between these two research communities. [ABSTRACT FROM AUTHOR]

Overview. The GiACTA trial is a multicenter, randomized, double-blind, and placebo-controlled study designed to test the ability of tocilizumab (TCZ), an interleukin (IL)-6 receptor antagonist, to maintain disease remission in patients with giant cell arteritis (GCA). Design. Approximately 100 centers will enroll 250 patients with active disease. The trial consists of a 52-week blinded treatment phase followed by 104 weeks of open-label extension. Patients will be randomized into one of four groups. Group A (TCZ 162mg weekly plus a 6-month prednisone-taper); group B (TCZ 162mg every other week plus a 6-month prednisone-taper); group C (placebo plus a 6-month prednisone-taper); and group D (placebo plus a 12-month prednisone taper). We hypothesize that patients assigned to TCZ in addition to a 6-month prednisone course are more likely to achieve the primary efficacy endpoint of sustained remission (SR) at 52 weeks compared with those assigned to a 6-month prednisone course alone, thus potentially minimizing the long-term adverse effects of corticosteroids. Conclusion. GiACTA will test the hypothesis that interference with IL-6 signaling exerts a beneficial effect on patients with GCA. The objective of this paper is to describe the design of the trial and address major issues related to its development. [ABSTRACT FROM AUTHOR]

Abstract: We further investigate and generalize the approximate privacy model recently introduced by Feigenbaum et al. (2010) . We explore the privacy properties of a natural class of communication protocols that we refer to as “dissection protocols”. Informally, in a dissection protocol the communicating parties are restricted to answering questions of the form “Is your input between the values  and  (under a pre-defined order over the possible inputs)?”. We prove that for a large class of functions, called tiling functions, there always exists a dissection protocol that provides a constant average-case privacy approximation ratio for uniform or “almost uniform” probability distributions over inputs. To establish this result we present an interesting connection between the approximate privacy framework and basic concepts in computational geometry. We show that such a good privacy approximation ratio for tiling functions does not, in general, exist in the worst case. We also discuss extensions of the basic setup to more than two parties and to non-tiling functions, and provide calculations of privacy approximation ratios for two functions of interest. [Copyright &y& Elsevier]

In this article, a robust method is presented for handling constraints with the Nelder and Mead simplex search method, which is a direct search algorithm for multidimensional unconstrained optimization. The proposed method is free from the limitations of previous attempts that demand the initial simplex to be feasible or a projection of infeasible points to the nonlinear constraint boundaries. The method is tested on several benchmark problems and the results are compared with various evolutionary algorithms available in the literature. The proposed method is found to be competitive with respect to the existing algorithms in terms of effectiveness and efficiency. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop European League Against Rheumatism/American College of Rheumatology classification criteria for polymyalgia rheumatica (PMR). Candidate criteria were evaluated in a 6-month prospective cohort study of 125 patients with new-onset PMR and 169 non-PMR comparison subjects with conditions mimicking PMR. A scoring algorithm was developed based on morning stiffness >45 minutes (2 points), hip pain/limited range of motion (1 point), absence of rheumatoid factor and/or anti-citrullinated protein antibody (2 points), and absence of peripheral joint pain (1 point). A score ≥4 had 68% sensitivity and 78% specificity for discriminating all comparison subjects from PMR. The specificity was higher (88%) for discriminating shoulder conditions from PMR and lower (65%) for discriminating RA from PMR. Adding ultrasound, a score ≥5 had increased sensitivity to 66% and specificity to 81%. According to these provisional classification criteria, patients ≥50 years old presenting with bilateral shoulder pain, not better explained by an alternative pathology, can be classified as having PMR in the presence of morning stiffness >45 minutes, elevated C-reactive protein and/or erythrocyte sedimentation rate, and new hip pain. These criteria are not meant for diagnostic purposes. [ABSTRACT FROM AUTHOR]

Optimal kinematic design of parallel manipulators is a challenging problem. In this work, an attempt has been made to present a generalized approach of kinematic design for a 6-legged parallel manipulator, by considering only the minimally required design parameters. The same approach has been used to design a 7-legged redundant parallel manipulator. Two ways of introducing redundancy into the parallel manipulator have been demonstrated and comparison between them has been presented. [ABSTRACT FROM AUTHOR]

Objectives. To determine whether ischaemic manifestations of GCA are associated with pre-existing hypertension, atherosclerosis or area-level socio-economic deprivation.Methods. We conducted an observational study of rheumatologist/ophthalmologist-diagnosed GCA in eight UK centres. The main outcome measure was ischaemic manifestations observed during active GCA: visual loss/blurring, aura, diplopia, jaw/tongue/limb claudication, cerebral/myocardial ischaemia or scalp necrosis.Results. Out of 271 patients, 222 had ischaemic manifestations. Adjusted odds ratios (ORs) for the influence of hypertension and atherosclerosis were 1.6 (95% CI 0.8, 3.1) and 1.5 (0.6, 3.5). The most striking finding was an association of ischaemic manifestations with increasing Index of Deprivation 2007 score: OR 4.2 (95% CI 1.3, 13.6) for the most-deprived quartile compared with the least-deprived quartile. Similar effect sizes were seen within each recruitment centre. Deprivation was associated with smoking and negatively associated with previous polymyalgia. However, neither of these variables, nor hypertension or atherosclerosis, appeared responsible for mediating the effect of deprivation on ischaemic complications. Smoking was not associated with ischaemic manifestations. Median symptom duration before treatment was 30 days; after adjusting for symptom duration, the OR for ischaemic complications was 3.2 (95% CI 1.0, 10.8) for the most-deprived quartile compared with the least-deprived quartile.Conclusions. In GCA, area-level socio-economic deprivation was associated with ischaemic manifestations: this was not mediated by traditional cardiovascular risk factors. These findings are novel and require replication. Delay between first symptoms and treatment may play a role. Public awareness campaigns about GCA should aim especially to engage individuals living in more deprived areas to encourage early presentation and prompt treatment. [ABSTRACT FROM PUBLISHER]

It is well known that biological and social interaction networks have a varying degree of redundancy, though a consensus of the precise cause of this is so far lacking. In this paper, we introduce a topological redundancy measure for labeled directed networks that is formal, computationally efficient, and applicable to a variety of directed networks such as cellular signaling, and metabolic and social interaction networks. We demonstrate the computational efficiency of our measure by computing its value and statistical significance on a number of biological and social networks with up to several thousands of nodes and edges. Our results suggest a number of interesting observations: (1) Social networks are more redundant that their biological counterparts, (2) transcriptional networks are less redundant than signaling networks, (3) the topological redundancy of the C. elegans metabolic network is largely due to its inclusion of currency metabolites, and (4) the redundancy of signaling networks is highly (negatively) correlated with the monotonicity of their dynamics. [ABSTRACT FROM AUTHOR]

Abstract: Cellular functions of an organism are maintained by protein–protein interactions. Those proteins that bind multiple partners asynchronously (date hub proteins) are important to make the interaction network coordinated. It is known that many date hub proteins bind different partners at overlapping (OV) interfaces. To understand how OV interfaces of date hub proteins can recognize multiple partners, we analyzed the difference between OV and non-overlapping (Non-OV) regions of interfaces involved in the binding of different partners. By using the structures of 16 date hub proteins with various interaction partners (ranging from 5 to 33), we compared buried surface area, compositions of amino acid residues and secondary structures, and side-chain orientations. It was found that buried interface residues are important for recognizing multiple partners, while exposed interface residues are important for determining specificity to a particular ligand. In addition, our analyses reveal that residue compositions in OV and Non-OV regions are different and that residues in OV region show diverse side-chain torsion angles to accommodate binding to multiple targets. [Copyright &y& Elsevier]

Giant cell arteritis (GCA) or temporal arteritis (TA) with polymyalgia rheumatica (PMR) is among the most common reasons for long-term steroid prescription. GCA is a critically ischaemic disease, the most common form of vasculitis and should be treated as a medical emergency. Visual loss occurs in up to a fifth of patients, which may be preventable by prompt recognition and treatment. The British Society for Rheumatology (BSR) and the British Health Professionals in Rheumatology (BHPR) have recently published guidelines on the management of PMR. The purpose of this concise guidance is to draw attention to the full guidelines to encourage the prompt diagnosis and urgent management of GCA, with emphasis on the prevention of visual loss. They provide a framework for disease assessment, immediate treatment and referral to specialist care for management and monitoring of disease activity, complications and relapse. [ABSTRACT FROM AUTHOR]

The article provides information the guidelines formulated and introduced by the British Society for Rheumatology (BSR) and British Health Professionals in Rheumatology (BHPR) for the prompt diagnosis and management of giant cell arthritis (GCA). The scope of the guideline covers initial and further management of the disease with emphasis on the prevention of vision loss. The full version of the guideline is available at "Rheumatology" online.

Polymyalgia rheumatica (PMR) is among the most common reasons for long-term steroid prescription with great heterogeneity in presentation, response to steroids and disease course. The British Society for Rheumatology and the British Health Professionals in Rheumatology have recently published guidelines on management of PMR. The purpose of this concise guidance is to draw attention to the full guidelines and provide a safe and specific diagnostic process with advice on management and monitoring -- specifically targeted at general practitioners, general physicians and rheumatologists. [ABSTRACT FROM AUTHOR]

The article focuses on the guidelines of British Society for Rheumatology (BSR) and British Health Professional in Rheumatology (BHPR) for managing polymyalgia rheumatic (PMR). It says that the guidelines is aiming for a safe and specific diagnostic process for PMR with the use of continued assessment. Moreover, the conditions which decreases the probability of PMR including inflammatory rheumatic diseases, drug-induced myalgia, and chronic pain syndromes are also presented.

Abstract: Motion planning for hyper-redundant manipulators in a complicated and cluttered workspace is a challenging problem. Many of the path planning algorithms, based on cell decomposition or potential field, fail due to the high dimensionality and complex nature of the C-space. Probabilistic roadmap methods (PRM) which have been proven to be successful in high dimensional C-spaces suffer from the drawback of generating paths which involve a lot of redundant motion. In this paper, we propose a path optimizing method to improve a given path in terms of path length and the safety against the collisions, using a variational approach. The capability of variational calculus to optimize a path is demonstrated on a variety of examples. The approach succeeds in providing a good quality path even in high dimensional C-spaces. [Copyright &y& Elsevier]

Rheumatology has been witnessing dramatic developments. Improvement in our understanding of the pathogenesis of diseases and advancements in therapeutics has forced us to re-look at our approach to the disease. The emphasis is on early recognition, proper assessment and regular follow-up. Musculoskeletal ultrasonography (MSUS) has emerged as a promising tool in fulfilling most of these requirements. It has proved to be of significant utility in a variety of rheumatic diseases and has been in regular use in several European countries. In this review we have discussed in detail its use in various rheumatic diseases, the upcoming developments in the field of MSUS and various issues related to its incorporation into routine care of rheumatic patients. In our opinion MSUS is the future of rheumatology and we shouldn't be left behind just because of our reluctance to understand and appreciate this fascinating technology. [ABSTRACT FROM AUTHOR]

In this paper, we consider the weighted online set -multicover problem. In this problem, we have a universe of elements, a family of subsets of with a positive real cost for every , and a “coverage factor” (positive integer) . A subset of elements are presented online in an arbitrary order. When each element is presented, we are also told the collection of all (at least ) sets and their costs to which belongs and we need to select additional sets from if necessary such that our collection of selected sets contains at least sets that contain the element . The goal is to minimize the total cost of the selected sets. 1 [1] Our algorithm and competitive ratio bounds can be extended to the case when a set can be selected at most a prespecified number of times instead of just once; we do not report these extensions for simplicity and also because they have no relevance to the biological applications that motivated our work. In this paper, we describe a new randomized algorithm for the online multicover problem based on a randomized version of the winnowing approach of [N. Littlestone, Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm, Machine Learning 2 (1988) 285–318]. This algorithm generalizes and improves some earlier results in [N. Alon, B. Awerbuch, Y. Azar, N. Buchbinder, J. Naor, A general approach to online network optimization problems, in: Proceedings of the 15th ACM-SIAM Symposium on Discrete Algorithms, 2004, pp. 570–579; N. Alon, B. Awerbuch, Y. Azar, N. Buchbinder, J. Naor, The online set cover problem, in: Proceedings of the 35th Annual ACM Symposium on the Theory of Computing, 2003, pp. 100–105]. We also discuss lower bounds on competitive ratios for deterministic algorithms for general based on the approaches in [N. Alon, B. Awerbuch, Y. Azar, N. Buchbinder, J. Naor, The online set cover problem, in: Proceedings of the 35th Annual ACM Symposium on the Theory of Computing, 2003, pp. 100–105]. [Copyright &y& Elsevier]

Background: For a proper understanding of protein structure and folding it is important to know if a polypeptide segment adopts a conformation inherent in the sequence or it depends on the context of its flanking secondary structures. Turns of various lengths have been studied and characterized starting from three-residue γ-turn to six-residue π-turn. The Schellman motif occurring at the C-terminal end of α-helices is a classical example of hydrogen bonded π-turn involving residues at (i) and (i+5) positions. Hydrogen bonded and non-hydrogen bonded β- and α- turns have been identified previously; likewise, a systematic characterization of π-turns would provide valuable insight into turn structures. Results: An analysis of protein structures indicates that at least 20% of π-turns occur independent of the Schellman motif. The two categories of π-turns, designated as π-HB and SCH, have been further classified on the basis of backbone conformation and both have AAAa as the major class. They differ in the residue usage at position (i+1), the former having a large preference for Pro that is absent in the latter. As in the case of shorter length β- and α-turns, π-turns have also been identified not only on the basis of the existence of hydrogen bond, but also using the distance between terminal Cα-atoms, and this resulted in a comparable number of non-hydrogen-bonded π-turns (π-NHB). The presence of shorter β- and α-turns within all categories of π-turns, the subtle variations in backbone torsion angles along the turn residues, the location of the turns in the context of tertiary structures have been studied. Conclusion: π-turns have been characterized, first using hydrogen bond and the distance between Cα atoms of the terminal residues, and then using backbone torsion angles. While the Schellman motif has a structural role in helix termination, many of the π-HB turns, being located on surface cavities, have functional role and there is also sequence conservation. [ABSTRACT FROM AUTHOR]

This paper studies a computational problem motivated by the modular response analysis method for reverse engineering of protein and gene networks. This set-cover problem is hard to solve exactly for large networks, but efficient approximation algorithms are given and their complexity is analyzed. [ABSTRACT FROM AUTHOR]

Abstract: This article proposes a dynamic stability index of a flexible manipulator. The method is illustrated by considering the 6-UPS Stewart platform as an example. First, the analysis of dynamics and vibration of a 6-UPS Stewart platform is presented. The dynamic formulation follows the Newton–Euler approach. Leg stiffness, force and torque due to viscous friction at the joints, inertia and gravity effects are considered in the model. Finally, the response of the platform, subjected to base excitations at different frequencies, has been studied and the dynamic stability index developed has been validated. [Copyright &y& Elsevier]

Abstract: Identification of sequence motifs that favor cis peptide bonds in proteins is important for understanding and designing proteins containing turns mediated by cis peptide conformations. From 1H NMR solution studies on short peptides, we show that the Pro-Pro peptide bond in Pro-Pro-Phe almost equally populates the cis and trans isomers, with the cis isomer stabilized by a CH⋯π interaction involving the terminal Pro and Phe. We also show that Phe is over-represented at sequence positions immediately following cis Pro-Pro motifs in known protein structures. Our results demonstrate that the Pro-Pro cis conformer in Pro-Pro-Phe sequence motifs is as important as the trans conformer, both in short peptides as well as in natively folded proteins. [Copyright &y& Elsevier]

Abstract: A useful approach to the mathematical analysis of large-scale biological networks is based upon their decompositions into monotone dynamical systems. This paper deals with two computational problems associated to finding decompositions which are optimal in an appropriate sense. In graph-theoretic language, the problems can be recast in terms of maximal sign-consistent subgraphs. The theoretical results include polynomial-time approximation algorithms as well as constant-ratio inapproximability results. One of the algorithms, which has a worst-case guarantee of 87.9% from optimality, is based on the semidefinite programming relaxation approach of Goemans–Williamson [Goemans, M., Williamson, D., 1995. Improved approximation algorithms for maximum cut and satisfiability problems using semidefinite programming. J. ACM 42 (6), 1115–1145]. The algorithm was implemented and tested on a Drosophila segmentation network and an Epidermal Growth Factor Receptor pathway model, and it was found to perform close to optimally. [Copyright &y& Elsevier]

Abstract: In this paper we investigate the computational complexity of a combinatorial problem that arises in the reverse engineering of protein and gene networks. Our contributions are as follows: [ ] We abstract a combinatorial version of the problem and observe that this is “equivalent” to the set multicover problem when the “coverage” factor k is a function of the number of elements n of the universe. An important special case for our application is the case in which . [ ] We observe that the standard greedy algorithm produces an approximation ratio of even if k is “large” i.e for some constant . [ ] Let denote the maximum number of elements in any given set in our set multicover problem. Then, we show that a non-trivial analysis of a simple randomized polynomial-time approximation algorithm for this problem yields an expected approximation ratio that is an increasing function of . The behavior of is roughly as follows: it is about when is at least about , and for smaller values of it decreases towards 1 as a linear function of with . Our randomized algorithm is a cascade of a deterministic and a randomized rounding step parameterized by a quantity followed by a greedy solution for the remaining problem. We also comment about the impossibility of a significantly faster convergence of towards 1 for any polynomial-time approximation algorithm. [Copyright &y& Elsevier]

Abstract: In this paper we investigate the inverse protein folding (IPF) problem under the Canonical model on 3D and 2D lattices [W.E. Hart, On the computational complexity of sequence design problems, Proceedings of the First Annual International Conference on Computational Molecular Biology 1997, pp. 128–136; E.I. Shakhnovich, A.M. Gutin, Engineering of stable and fast-folding sequences of model proteins, Proc. Natl. Acad. Sci. 90 (1993) 7195–7199]. In this problem, we are given a contact graph of a protein sequence that is embeddable in a 3D (respectively, 2D) lattice and an integer . The goal is to find an induced subgraph of G of at most K vertices with the maximum number of edges. In this paper, we prove the following results: [•] An earlier proof of NP-completeness of the IPF problem on 3D lattices [W.E. Hart, On the computational complexity of sequence design problems, Proceedings of the First Annual International Conference on Computational Molecular Biology 1997, pp. 128–136] is based on the NP-completeness of the IPF problem on the 2D lattices. However, the reduction was not correct and we show that the IPF problem for 2D lattices can be solved in time. But, we show that the IPF problem on 3D lattices is indeed NP-complete by a providing a different reduction from a different NP-complete problem. [•] We design a polynomial-time approximation scheme for the IPF problem on 3D lattices using the shifted slice-and-dice approach in [P. Berman, B. DasGupta, S. Muthukrishnan, Approximation algorithms for MAX-MIN tiling, J. Algorithms 47(2) (2003) 122–134; D. Hochbaum, Approximation Algorithms for NP-hard Problems, PWS Publishing Company, MA, 1997; D.S. Hochbaum, W. Mass, Approximation schemes for covering and packing problems in image processing and VLSI, J. ACM 32(1) (1985) 130–136], thereby improving the previous best polynomial-time approximation algorithm which had a performance ratio of [W.E. Hart, On the computational complexity of sequence design problems, Proceedings of the First Annual International Conference on Computational Molecular Biology 1997, pp. 128–136]. [Copyright &y& Elsevier]

Abstract: In this paper we investigate the problem of searching for a hidden target in a bounded region of the plane using an autonomous robot which is only able to use local sensory information. The problem is naturally formulated in the continuous domain but the solution proposed is based on an aggregation/refinement approach in which the continuous search space is partitioned into a finite collection of regions on which we define a discrete search problem. A solution to the original problem is obtained through a refinement procedure that lifts the discrete path into a continuous one. We show that the discrete optimization is computationally difficult (NP-hard) but there are computationally efficient approximation algorithms for solving it. The resulting solution to the continuous problem is in general not optimal but one can construct bounds to gauge the cost penalty incurred due to (i) the discretization of the problem and (ii) the attempt to approximately solve the NP-hard problem in polynomial time. Numerical simulations show that the algorithms proposed behave significantly better than naive approaches such as a random walk or a greedy algorithm. [Copyright &y& Elsevier]

Abstract: We deal with the problem of efficient learning of feedforward neural networks. First, we consider the objective to maximize the ratio of correctly classified points compared to the size of the training set. We show that it is NP-hard to approximate the ratio within some constant relative error if architectures with varying input dimension, one hidden layer, and two hidden neurons are considered where the activation function in the hidden layer is the sigmoid function, and the situation of epsilon-separation is assumed, or the activation function is the semilinear function. For single hidden layer threshold networks with varying input dimension and hidden neurons, approximation within a relative error depending on is NP-hard even if restricted to situations where the number of examples is limited with respect to . Afterwards, we consider the objective to minimize the failure ratio in the presence of misclassification errors. We show that it is NP-hard to approximate the failure ratio within any positive constant for a multilayered threshold network with varying input dimension and a fixed number of neurons in the hidden layer if the thresholds of the neurons in the first hidden layer are zero. Furthermore, even obtaining weak approximations is almost NP-hard in the same situation. [Copyright &y& Elsevier]

Abstract: In this paper, we investigate the test set problem and its variations that appear in a variety of applications. In general, we are given a universe of objects to be “distinguished” by a family of “tests”, and we want to find the smallest sufficient collection of tests. In the simplest version, a test is a subset of the universe and two objects are distinguished by our collection if one test contains exactly one of them. Variations allow tests to be multi-valued functions or unions of “basic” tests, and different notions of the term distinguished. An important version of this problem that has applications in DNA sequence analysis has the universe consisting of strings over a small alphabet and tests that are detecting presence (or absence) of a substring. For most versions of the problem, including the latter, we establish matching lower and upper bounds on approximation ratio. When tests can be formed as unions of basic tests, we show that the problem is as hard as the graph coloring problem. We conclude by reporting preliminary computational results on the implementations of our algorithmic approaches for the minimum cost probe set problems on a data set used by Borneman et al. [Copyright &y& Elsevier]

This paper deals with the static equilibrium formulation of mechanical systems, including rigid and compliant elements, and the determination of their final equilibrium configuration under known loads. Statically determinate as well as statically indeterminate systems are analysed. Relative coordinates are used as generalised coordinates. The system is modeled using homogeneous transformation matrices and loop closure equations. In the first phase of analysis (assembly), initial correct configuration of the system is obtained, from approximate input provided by the user. For the solution of the equilibrium problem, a potential function is used. Its minimisation, subject to rigid constraints yields the equilibrium configuration. The approach is implemented in a program and tested on a number of planar and spatial mechanical systems. The software program is intended to be used as a design aid for engineers. [Copyright &y& Elsevier]

This paper addresses the problem of singularity-free path-planning for parallel manipulators. Unlike in serial manipulators, where there are only boundary singularities, parallel manipulators also possess singular configurations within the workspace where the manipulators are uncontrollable. Therefore, it is imperative that the generated paths are singularity-free. In this paper, we use a variational approach for planning singularity-free paths for parallel manipulators, based on a Lagrangian incorporating both a kinetic energy term which keeps the path short, and a potential energy term which ensures that the obtained path is singularity-free and the actuator lengths remain within their prescribed limits. The approach is applied to several parallel manipulators to evaluate the performance of this method. [Copyright &y& Elsevier]

The MAX–MIN tiling problem is as follows. We are given A[1,…,n][1,…,n], a two-dimensional array where each entry A[i][j] stores a non-negative number. Define a tile of A to be a subarray A[ℓ,…,r][t,…,b] of A, the weight of a tile to be the sum of all array entries in it, and a tiling of A to be a collection of tiles of A such that each entry A[i][j] is contained in exactly one tile. Given a weight bound W the goal of our MAX–MIN tiling problem is to find a tiling of A such that: (1) each tile is of weight at least W (the MIN condition), and (2) the number of tiles is maximized (the MAX condition). The MAX–MIN tiling problem is known to be NP-hard; here, we present first non-trivial approximations algorithms for solving it. [Copyright &y& Elsevier]

Giant cell arteritis is the most common vasculitis in Caucasians. The aetiology of this disease remains uncertain. This article reviews some of the recent work in epidemiology and pathology in this field, with particular regard to the immunohistochemical findings in temporal artery biopsy specimens. The possible correlation between clinical features and biopsy specimen histology is discussed, and a model of pathogenesis is presented. [Copyright &y& Elsevier]