Human herpesvirus 6 congenital infection results primarily from chromosomally integrated virus which is passed through the germ-line. Infants with chromosomally integrated human herpesvirus 6 had high viral loads in all specimens, produced human herpesvirus 6 antibody, and mRNA. The clinical relevance needs study as 1 of 116 newborns may have chromosomally integrated human herpesvirus 6 blood specimens.

Light-induced excited spin-state trapping (LIESST) in iron(II) spin-crossover compounds, that is, the light-induced population of the high-spin (S=2) state below the thermal transition temperature, was discovered thirty years ago. For irradiation into metal-ligand charge transfer (MLCT) bands of the low-spin (S=0) species the acknowledged sequence takes the system from the initially excited (1) MLCT to the high-spin state via the (3) MLCT state within ca. 150 fs, thereby bypassing low-lying ligand-field (LF) states. Nevertheless, these play a role, as borne out by the observation of LIESST and reverse-LIESST on irradiation directly into the LF bands for systems with only high-energy MLCT states. Herein we elucidate the ultrafast reverse-LIESST pathway by identifying the lowest energy S=1 LF state as an intermediate state with a lifetime of 39 ps for the light-induced high-spin to low-spin conversion on irradiation into the spin-allowed LF transition of the high-spin species in the NIR.

International audienceThe (Gromov) hyperbolicity is a topological property of a graph, which has been recently applied in several different contexts, such as the design of routing schemes, network security, computational biology, the analysis of graph algorithms, and the classification of complex networks. Computing the hyperbolicity of a graph can be very time consuming: indeed, the best available algorithm has running-time O(n^{3.69}), which is clearly prohibitive for big graphs. In this paper, we provide a new and more efficient algorithm: although its worst-case complexity is O(n^4), in practice it is much faster, allowing, for the first time, the computation of the hyperbolicity of graphs with up to 200,000 nodes. We experimentally show that our new algorithm drastically outperforms the best previously available algorithms, by analyzing a big dataset of real-world networks. Finally, we apply the new algorithm to compute the hyperbolicity of random graphs generated with the Erdös-Renyi model, the Chung-Lu model, and the Configuration Model

Centrality indices are widely used analytic measures for the importance of nodes in a network. Closeness centrality is very popular among these measures. For a single node v, it takes the sum of the distances of v to all other nodes into account. The currently best algorithms in practical applications for computing the closeness for all nodes exactly in unweighted graphs are based on breadth-first search (BFS) from every node. Thus, even for sparse graphs, these algorithms require quadratic running time in the worst case, which is prohibitive for large networks.In many relevant applications, however, it is unnecessary to compute closeness values for all nodes. Instead, one requires only the k nodes with the highest closeness values in descending order. Thus, we present a new algorithm for computing this top-k ranking in unweighted graphs. Following the rationale of previous work, our algorithm significantly reduces the number of traversed edges. It does so by computing upper bounds on the closeness and stopping the current BFS search when k nodes already have higher closeness than the bounds computed for the other nodes.In our experiments with real-world and synthetic instances of various types, one of these new bounds is good for small-world graphs with low diameter (such as social networks), while the other one excels for graphs with high diameter (such as road networks). Combining them yields an algorithm that is faster than the state of the art for top-k computations for all test instances, by a wide margin for high-diameter * E. B.'s and H. M.

Search results clustering (SRC) is a challenging algorithmic problem that requires grouping together the results returned by one or more search engines in topically coherent clusters, and labeling the clusters with meaningful phrases describing the topics of the results included in them.In this paper we propose to solve SRC via an innovative approach that consists of modeling the problem as the labeled clustering of the nodes of a newly introduced graph of topics. The topics are Wikipedia-pages identified by means of recently proposed topic annotators [9,11,16,20] applied to the search results, and the edges denote the relatedness among these topics computed by taking into account the linkage of the Wikipedia-graph.We tackle this problem by designing a novel algorithm that exploits the spectral properties and the labels of that graph of topics. We show the superiority of our approach with respect to academic state-of-the-art work [6] and wellknown commercial systems (Clusty and Lingo3G) by performing an extensive set of experiments on standard datasets and user studies via Amazon Mechanical Turk. We test several standard measures for evaluating the performance of all systems and show a relative improvement of up to 20%.

Congenital HHV-6 infection results from germline passage of chromosomally-integrated HHV-6 (CI-HHV-6) and from transplacental passage of maternal HHV-6 infection (TP-HHV-6). We aimed to determine if CI-HHV-6 could replicate and cause TP-HHV-6 infection. HHV-6 DNA, variant type, and viral loads were determined on samples (cord blood, peripheral blood, saliva, urine, hair) from 6 infants with TP-HHV-6 and on their parents’ hair. No fathers, but all mothers of TP-HHV-6 infants had CI-HHV-6, and the mother's CI-HHV-6 variant was the same variant causing the TP-HHV-6 congenital infection. This suggests the possibility that CI-HHV-6 replicates, and may cause most, possibly all, congenital HHV-6 infections.

We conducted focal observations of territorial guanacos, a highly polygynous and social mammal, to compare time budgets between sexes and test the hypothesis that the differences in reproductive interests are associated with differential group size effects on male and female time allocation patterns. In addition, we used group instantaneous sampling to test the hypothesis that grouping improves detection capacity through increased collective vigilance. We fit GLM to assess how group size and group composition (i.e., presence or absence of calves) affected individual time allocation of males and females, and collective vigilance. As expected from differences in reproductive interests, males in family groups devoted more time to scan the surroundings and less to feeding activities compared to females. Both sexes benefited from grouping by reducing the time invested in vigilance and increased foraging effort, according to predation risk theory, but the factors affecting time allocation differed between males and females. Group size effects were significant when females were at less than five body‐lengths from their nearest neighbour, suggesting that grouping benefits arise when females are close to each other. Female time budgets were also affected by season, topography and vegetation structure. In contrast to our expectation, males reduced the time invested in vigilance as the number of females in the group increased, supporting the predation risk theory rather the intrasexual competition hypothesis. The presence of calves was associated with an increase in male individual vigilance; and vegetation type also affected the intensity of the group size effect over male time allocation. In closed habitats, collective vigilance increased with the number of adults but decreased with the number of calves present. Although male and female guanacos differed in their time allocation patterns, our results support the hypothesis that both sexes perceive significant antipredator benefits of group living.

Background-Human herpesvirus 6 (HHV-6) causes ubiquitous infection in early childhood with lifelong latency or persistence. Reactivation of HHV-6 has been associated with multiple diseases including encephalitis. Chromosomal integration of HHV-6 also occurs. Previous studies have suggested that the detection of HHV-6 DNA in plasma is an accurate marker of active viral replication.