Algorithms for dynamic and distributed networks : shortest paths, betweenness centrality and related problems

In this thesis we study the problem of computing Betweenness Centrality in dynamic and distributed networks. Betweenness Centrality (BC) is a well-known measure for the relative importance of a node in a social network. It is widely used in applications such as understanding lethality in biological networks, identifying key actors in terrorist networks, supply chain management processes and more. The necessity of computing BC in large networks, especially when they quickly change their topology over time, motivates the study of dynamic algorithms that can perform faster than static ones. Moreover, the current techniques for computing BC requires a deeper understanding of a classic problem in computer science: computing all pairs all shortest paths (APASP) in a graph. One of the main contributions of this thesis is a collection of dynamic algorithms for computing APASP and BC scores which are provably faster than static algorithms for several classes of graphs. We use n = |V| and m = |E| to indicate respectively the number of nodes and edges in a directed positively weighted graph G = (V,E). Our bounds depend on the parameter [nu]* that is defined as the maximum number of edges that lie on shortest paths through any single vertex. The main results in the first part of this thesis are listed below. - A decrease-only algorithm for computing BC and APASP running in time O([nu]* n) that is provably faster than recomputing from scratch in sparse graphs. - An increase-only algorithm for computing BC and APASP that runs in O([nu]*² log n) per update for a sequence of at least [Omega](m*/[nu]*) updates. Here m* is the number of edges in G that lie on shortest paths. This algorithm uses O(m* [nu]*) space. - An increase-only algorithm for computing BC and APASP that runs in O([nu]*² log n) but improves the computational space to O(m*n). - A fully dynamic algorithm for computing BC and APASP that runs in O([nu]*² log³ n) amortized time per update for a sequence of at least [Omega](n) updates. - A refinement of our fully dynamic algorithm that improves the amortized running time to O([nu]*² log² n), saving a logarithmic factor. In the second part of this thesis, we study the case when the input graph is a distributed network of machines and the BC score of each machine, considering its location within the network topology, needs to be computed. In this scenario, each node in the input graph is a self-contained machine with limited knowledge of the network and communication power. Each machine only knows the (virtual) location of the neighbors machines (adjacent nodes in the input graph). The messages, exchanged in each round between machines, cannot exceed a bounded size of at most O(log n) bits. In this distributed model, called CONGEST, we present algorithms for computing BC in near-optimal time for unweighted networks, and some classes of weighted networks. Specifically, our main results are: - A distributed BC algorithm for unweighted undirected graphs completing in at most min(2n+O(D[underscore u]); 4n) rounds, where D[underscore u] is the diameter of the undirected network. - A distributed BC algorithm for unweighted directed graphs completing in at most min(2n + O(D); 4n) rounds, where D is the diameter of the directed network. - A distributed APSP algorithm for unweighted directed graphs completing in at most min(n + O(D); 2n) rounds. - A distributed BC algorithm for weighted directed acyclic graphs (dag) completing in at most 2n + O(L) rounds, where L is the longest length of a path in the dag. - A distributed APSP algorithm for weighted dags completing in at most n + O(L) rounds.Computer Science

On exosome functional role in cancer. miR-494 complex regulation in melanoma cells and corresponding exosomes

No abstract availabl

SCD5 restored expression favors differentiation and epithelial-mesenchymal reversion in advanced melanoma

Our previous data supported a role for the Stearoyl-CoA desaturase (SCD5) in protection against malignancy, whereby it appears to functionally modify tumor stroma impairing tumor spread. SCD5 is significantly expressed in primary melanoma, but becomes barely detectable at tumor advanced stages. Looking for the regulatory mechanisms underlying SCD5 reduced expression during melanoma progression, we demonstrated a significantly lower stability of SCD5 protein as well as the direct targeting of SCD5 mRNA by the oncogenic miR-221 & 222 in metastatic cell lines. Moreover, our results indicated the existence of a negative feedback loop between SCD5 and miR-221 & 222, in good agreement with their opposite functions. Also, we showed how SCD5 re-expression and the direct supplementation of its main product oleic acid (OA) can drive advanced melanoma cell lines toward differentiation and reversion of the epithelial-mesenchymal (EMT)-like process, eventually inducing a less malignant phenotype. Indeed, SCD5 re-established the sensitivity to all-trans retinoic acid in A375M metastatic melanoma, associated with increased levels of Tyrosinase, melanin production and reduced proliferation. As evidenced by the correct modulation of some key transcription factors, SCD5 managed by favoring a partial mesenchymal-to-epithelial (MET) transition in in vitro studies. Interestingly, a more complete MET, including E-cadherin re-expression correctly localized at cell membranes, was obtained in in vivo xenograft models, thus indicating the requirement of direct contacts between tumor cells and the surrounding microenvironment as well as the presence of some essential factors for SCD5 complete function

Fibrinolysis protease receptors promote activation of astrocytes to express pro-inflammatory cytokines.

BACKGROUND:Astrocytes contribute to the crosstalk that generates chronic neuro-inflammation in neurological diseases; however, compared with microglia, astrocytes respond to a more limited continuum of innate immune system stimulants. Recent studies suggest that the fibrinolysis system may regulate inflammation. The goal of this study was to test whether fibrinolysis system components activate astrocytes and if so, elucidate the responsible biochemical pathway. METHODS:Primary cultures of astrocytes and microglia were prepared from neonatal mouse brains. The ability of purified fibrinolysis system proteins to elicit a pro-inflammatory response was determined by measuring expression of the mRNAs encoding tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), and chemokine (C-C motif) ligand 2 (CCL2). IκBα phosphorylation also was measured. Plasminogen activation in association with cells was detected by chromogenic substrate hydrolysis. The activity of specific receptors was tested using neutralizing antibodies and reagents. RESULTS:Astrocytes expressed pro-inflammatory cytokines when treated with plasminogen but not when treated with agonists for Toll-like Receptor-4 (TLR4), TLR2, or TLR9. Microglia also expressed pro-inflammatory cytokines in response to plasminogen; however, in these cells, the response was observed only when tissue-type plasminogen activator (tPA) was added to activate plasminogen. In astrocytes, endogenously produced urokinase-type plasminogen activator (uPA) converted plasminogen into plasmin in the absence of tPA. Plasminogen activation was dependent on the plasminogen receptor, α-enolase, and the uPA receptor, uPAR. Although uPAR is capable of directly activating cell-signaling, the receptor responsible for cytokine expression and IκBα phosphorylation response to plasmin was Protease-activated Receptor-1 (PAR-1). The pathway, by which plasminogen induced astrocyte activation, was blocked by inhibiting any one of the three receptors implicated in this pathway with reagents such as εACA, α-enolase-specific antibody, uPAR-specific antibody, the uPA amino terminal fragment, or a pharmacologic PAR-1 inhibitor. CONCLUSIONS:Plasminogen may activate astrocytes for pro-inflammatory cytokine expression through the concerted action of at least three distinct fibrinolysis protease receptors. The pathway is dependent on uPA to activate plasminogen, which is expressed endogenously by astrocytes in culture but also may be provided by other cells in the astrocytic cell microenvironment in the CNS

Thyroid ultrasonography reporting: consensus of Italian Thyroid Association (AIT), Italian Society of Endocrinology (SIE), Italian Society of Ultrasonography in Medicine and Biology (SIUMB) and Ultrasound Chapter of Italian Society of Medical Radiology (SIRM)

Thyroid ultrasonography (US) is the gold standard for thyroid imaging and its widespread use is due to an optimal spatial resolution for superficial anatomic structures, a low cost and the lack of health risks. Thyroid US is a pivotal tool for the diagnosis and follow-up of autoimmune thyroid diseases, for assessing nodule size and echostructure and defining the risk of malignancy in thyroid nodules. The main limitation of US is the poor reproducibility, due to the variable experience of the operators and the different performance and settings of the equipments. Aim of this consensus statement is to standardize the report of thyroid US through the definition of common minimum requirements and a correct terminology. US patterns of autoimmune thyroid diseases are defined. US signs of malignancy in thyroid nodules are classified and scored in each nodule. We also propose a simplified nodule risk stratification, based on the predictive value of each US sign, classified and scored according to the strength of association with malignancy, but also to the estimated reproducibility among different operators