We report the observation of a narrow charmoniumlike state produced in the exclusive decay process B+/--->K+/-pi(+)pi(-)J/psi. This state, which decays into pi(+)pi(-)J/psi, has a mass of 3872.0+/-0.6(stat)+/-0.5(syst) MeV, a value that is very near the M(D0)+M(D(*0)) mass threshold. The results are based on an analysis of 152M B-Bmacr; events collected at the Upsilon(4S) resonance in the Belle detector at the KEKB collider. The signal has a statistical significance that is in excess of 10sigma.

Protein-protein interactions play key roles in protein function and the structural organization of a cell. A thorough description of these interactions should facilitate elucidation of cellular activities, targeted-drug design, and whole cell engineering. A large-scale comprehensive pull-down assay was performed using a His-tagged Escherichia coli ORF clone library. Of 4339 bait proteins tested, partners were found for 2667, including 779 of unknown function. Proteins copurifying with hexahistidine-tagged baits on a Ni 2+

We report the observation of the decay mode B(+/-) --> p(-)pK(+/-)based on an analysis of 29.4 fb(-1) of data collected by the Belle detector at KEKB. This is the first example of a b-->s transition with baryons in the final state. The p(-)p mass spectrum in this decay is inconsistent with phase space and is peaked at low mass. The branching fraction for this decay is measured to be B(B+/--->p(-)pK+/-) = [4.3(+1.1)(-0.9)(stat)+/-0.5(syst)]x 10(-6). We also report upper limits for the decays B(0)-->p(-)pK(S) and B(+/-)-->p(-)p pi(+/-).

Human breast milk is widely recognized as the best source of nutrients for healthy growth and development of infants; it contains a diverse microbiota. Here, we characterized the diversity of the microbiota in the breast milk of East Asian women and assessed whether delivery mode influenced the microbiota in the milk of healthy breast-feeding mothers. We profiled the microbiota in breast milk samples collected from 133 healthy mothers in Taiwan and in six regions of mainland China (Central, East, North, Northeast, South, and Southwest China) by using 16S rRNA pyrosequencing. Lactation stage (months postpartum when the milk sample was collected) and maternal body mass index did not influence the breast milk microbiota. Bacterial composition at the family level differed significantly among samples from the seven geographical regions. The five most predominant bacterial families were Streptococcaceae (mean relative abundance: 24.4%), Pseudomonadaceae (14.0%), Staphylococcaceae (12.2%), Lactobacillaceae (6.2%), and Oxalobacteraceae (4.8%). The microbial profiles were classified into three clusters, driven by Staphylococcaceae (abundance in Cluster 1: 42.1%), Streptococcaceae (Cluster 2: 48.5%), or Pseudomonadaceae (Cluster 3: 26.5%). Microbial network analysis at the genus level revealed that the abundances of the Gram-positive Staphylococcus, Streptococcus, and Rothia were negatively correlated with those of the Gram-negative Acinetobacter, Bacteroides, Halomonas, Herbaspirillum, and Pseudomonas. Milk from mothers who had undergone Caesarian section (C-section group) had a significantly higher abundance of Lactobacillus (P < 0.05) and a higher number of unique unclassified operational taxonomic units (OTUs) (P < 0.001) than that from mothers who had undergone vaginal delivery (vaginal group). These findings revealed that (i) geographic differences in the microbial profiles were found in breast milk from mothers living in Taiwan and mainland China, (ii) the predominant bacterial families Streptococcaceae, Staphylococcaceae, and Pseudomonadaceae were key components for forming three respective clusters, and (iii) a significantly greater number of unique OTUs was found in the breast milk from mothers who had undergone C-section than from those who had delivered vaginally.

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Essential genes are indispensable to the viability of an organism. Identification and analysis of essential genes is key to understanding the systems level organization of living cells. On the other hand, the ability to predict these genes in pathogens is of great importance for directed drug development. Global analysis of protein interaction networks provides an effective way to elucidate the relationships between genes. It has been found that essential genes tend to be highly connected and generally have more interactions than nonessential ones. With recent large-scale identifications of essential genes and protein-protein interactions in Saccharomyces cerevisiae and Escherichia coli, we have systematically investigated the topological properties of essential and nonessential genes in the protein-protein interaction networks. Essential genes tend to play topologically more important roles in protein interaction networks. Many topological features were found to be statistically discriminative between essential and nonessential genes. In addition, we have also examined sequence properties such as open reading frame length, strand, and phyletic retention for their association with the gene essentiality. Employing the topological features in the protein interaction network and the sequence properties, we have built a machine learning classifier capable of predicting essential genes. Computational prediction of essential genes circumvents expensive and difficult experimental screens and will help antimicrobial drug development.

We present a measurement of the standard model CP violation parameter sin2 phi(1) based on a 29.1 fb(-1) data sample collected at the Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric-energy e(+)e(-) collider. One neutral B meson is fully reconstructed as a J/psi K(S), psi(2S)K(S), chi(c1)K(S), eta(c)K(S), J/psi K(L), or J/psi K(*0) decay and the flavor of the accompanying B meson is identified from its decay products. From the asymmetry in the distribution of the time intervals between the two B meson decay points, we determine sin2 phi(1) = 0.99+/-0.14(stat)+/-0.06(syst). We conclude that we have observed CP violation in the neutral B meson system.

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