Hierarchical information clustering by means of topologically embedded graphs

We introduce a graph-theoretic approach to extract clusters and hierarchies in complex data-sets in an unsupervised and deterministic manner, without the use of any prior information. This is achieved by building topologically embedded networks containing the subset of most significant links and analyzing the network structure. For a planar embedding, this method provides both the intra-cluster hierarchy, which describes the way clusters are composed, and the inter-cluster hierarchy which describes how clusters gather together. We discuss performance, robustness and reliability of this method by first investigating several artificial data-sets, finding that it can outperform significantly other established approaches. Then we show that our method can successfully differentiate meaningful clusters and hierarchies in a variety of real data-sets. In particular, we find that the application to gene expression patterns of lymphoma samples uncovers biologically significant groups of genes which play key-roles in diagnosis, prognosis and treatment of some of the most relevant human lymphoid malignancies

Revisiting the BB-physics anomalies in RR-parity violating MSSM

In recent years, several deviations from the Standard Model predictions in semileptonic decays of $B$-meson might suggest the existence of new physics which would break the lepton-flavour universality. In this work, we have explored the possibility of using muon sneutrinos and right-handed sbottoms to solve these $B$-physics anomalies simultaneously in $R$-parity violating minimal supersymmetric standard model. We find that the photonic penguin induced by exchanging sneutrino can provide sizable lepton flavour universal contribution due to the existence of logarithmic enhancement for the first time. This prompts us to use the two-parameter scenario $(C^{\rm V}_9, \, C^{\rm U}_9)$ to explain $b \to s \ell^+ \ell^-$ anomaly. Finally, the numerical analyses show that the muon sneutrinos and right-handed sbottoms can explain $b \to s \ell^+ \ell^-$ and $R(D^{(\ast)})$ anomalies simultaneously, and satisfy the constraints of other related processes, such as $B \to K^{(\ast)} \nu \bar\nu$ decays, $B_s-\bar B_s$ mixing, $Z$ decays, as well as $D^0 \to \mu^+ \mu^-$, $\tau \to \mu \rho^0$, $B \to \tau \nu$, $D_s \to \tau \nu$, $\tau \to K \nu$, $\tau \to \mu \gamma$, and $\tau \to \mu\mu\mu$ decays.Comment: 10 pages, 8 figures, matches to the version published in EPJ

Nested hierarchies in planar graphs

We construct a partial order relation which acts on the set of 3-cliques of a maximal planar graph G and defines a unique hierarchy. We demonstrate that G is the union of a set of special subgraphs, named `bubbles', that are themselves maximal planar graphs. The graph G is retrieved by connecting these bubbles in a tree structure where neighboring bubbles are joined together by a 3-clique. Bubbles naturally provide the subdivision of G into communities and the tree structure defines the hierarchical relations between these communities

Chlorido{N-[(diethyl­amino)­dimethyl­sil­yl]anilido-κN}(N,N,N′,N′-tetra­methyl­ethane-1,2-diamine-κ2 N,N′)cobalt(II)

In the title cobalt(II) compound, [Co(C12H21N2Si)Cl(C6H16N2)], the ethane-1,2-diamine donor mol­ecule coordin­ates the metal atom in an N,N′-chelating mode, with Co—N distances of 2.136 (2) and 2.140 (3) Å. An anilide ligand connects to the CoII atom with a σ–bond, the Co—Nanilide distance being 1.931 (2) Å. The four-coordinate CoII atom demonstrates a slightly distorted tetra­hedral geometry

Multi-marker approach using procalcitonin, presepsin, galectin-3, and soluble suppression of tumorigenicity 2 for the prediction of mortality in sepsis

Background: Biomarker could be objective and reliable tools to predict mortality in sepsis. We explored the prognostic utilities of emerging biomarkers in septic patients and questioned whether adding biomarkers to the clinical variables would improve the prediction of mortality in sepsis. Methods: This retrospective study included 157 septic patients (112 patients with sepsis; 45 patients with septic shock). Procalcitonin (PCT), presepsin, galectin-3, and soluble suppression of tumorigenicity 2 (sST2) concentrations were analyzed in relation to the 30-day all-cause mortality. Their value added on top of Sequential (Sepsis-related) Organ Failure Assessment (SOFA) score, high-sensitivity C-reactive protein, and white blood cells was also analyzed. Results: PCT could not predict 30-day mortality. Univariate hazard ratio [HR with 95% confidence interval (CI)] of the other dichotomized variables was: 1.33 (0.55–3.194) for presepsin; 7.87 (2.29–26.96) for galectin-3; 1.55 (0.71–3.38) for sST2; and 2.18 (1.01–4.75) for SOFA score. The risk of 30-day mortality increased stepwise as the number of biomarkers above optimal cutoff values increased, and the highest risk was observed when all four biomarkers and SOFA score increased (HR = 14.5). Multi-marker approach predicted 30-day mortality better than SOFA score [area under the curves (95% CI), 0.769 (0.695–0.833) vs. 0.615 (0.535–0.692)]. In reclassification analyses, adding biomarkers to clinical variables improved the prediction of mortality. Conclusion: This study demonstrated a possible prognostic utility of PCT, presepsin, galectin-3, and sST2 in sepsis. Multi-marker approach could be beneficial for an optimized management of patients with sepsis