S₃ flavor symmetry at the LHC

Discrete symmetries employed to explain neutrino mixing and mass hierarchies are often associated with an enlarged scalar sector which might lead to exotic Higgs decay modes. We explore such a possibility in a scenario with S3 flavor symmetry which requires three scalar SU(2) doublets. The spectrum is fixed by minimizing the scalar potential, and we observe that the symmetry of the model leads to tantalizing Higgs decay models potentially observable at the CERN Large Hadron Collider (LHC)

Proceedings of the 2nd Workshop on Flavor Symmetries and Consequences in Accelerators and Cosmology (FLASY12)

These are the proceedings of the 2nd Workshop on Flavor Symmetries and Consequences in Accelerators and Cosmology, held 30 June 2012 - 4 July 2012, Dortmund, Germany.Comment: Order 400 pages, several figures including the group picture v2: corrected author list and contributio

Detection of variable VHE gamma-ray emission from the extra-galactic gamma-ray binary LMC P3

Context. Recently, the high-energy (HE, 0.1-100 GeV) $\gamma$-ray emission from the object LMC P3 in the Large Magellanic Cloud (LMC) has been discovered to be modulated with a 10.3-day period, making it the first extra-galactic $\gamma$-ray binary. Aims. This work aims at the detection of very-high-energy (VHE, >100 GeV) $\gamma$-ray emission and the search for modulation of the VHE signal with the orbital period of the binary system. Methods. LMC P3 has been observed with the High Energy Stereoscopic System (H.E.S.S.); the acceptance-corrected exposure time is 100 h. The data set has been folded with the known orbital period of the system in order to test for variability of the emission. Energy spectra are obtained for the orbit-averaged data set, and for the orbital phase bin around the VHE maximum. Results. VHE $\gamma$-ray emission is detected with a statistical significance of 6.4 $\sigma$. The data clearly show variability which is phase-locked to the orbital period of the system. Periodicity cannot be deduced from the H.E.S.S. data set alone. The orbit-averaged luminosity in the $1-10$ TeV energy range is $(1.4 \pm 0.2) \times 10^{35}$ erg/s. A luminosity of $(5 \pm 1) \times 10^{35}$ erg/s is reached during 20% of the orbit. HE and VHE $\gamma$-ray emissions are anti-correlated. LMC P3 is the most luminous $\gamma$-ray binary known so far.Comment: 5 pages, 3 figures, 1 table, accepted for publication in A&

Characterizing the gamma-ray long-term variability of PKS 2155-304 with H.E.S.S. and Fermi-LAT

Studying the temporal variability of BL Lac objects at the highest energies provides unique insights into the extreme physical processes occurring in relativistic jets and in the vicinity of super-massive black holes. To this end, the long-term variability of the BL Lac object PKS 2155-304 is analyzed in the high (HE, 100 MeV 200 GeV) gamma-ray domain. Over the course of ~9 yr of H.E.S.S observations the VHE light curve in the quiescent state is consistent with a log-normal behavior. The VHE variability in this state is well described by flicker noise (power-spectral-density index {\ss}_VHE = 1.10 +0.10 -0.13) on time scales larger than one day. An analysis of 5.5 yr of HE Fermi LAT data gives consistent results ({\ss}_HE = 1.20 +0.21 -0.23, on time scales larger than 10 days) compatible with the VHE findings. The HE and VHE power spectral densities show a scale invariance across the probed time ranges. A direct linear correlation between the VHE and HE fluxes could neither be excluded nor firmly established. These long-term-variability properties are discussed and compared to the red noise behavior ({\ss} ~ 2) seen on shorter time scales during VHE-flaring states. The difference in power spectral noise behavior at VHE energies during quiescent and flaring states provides evidence that these states are influenced by different physical processes, while the compatibility of the HE and VHE long-term results is suggestive of a common physical link as it might be introduced by an underlying jet-disk connection.Comment: 11 pages, 16 figure

Adult enteric nervous system in health is maintained by a dynamic balance between neuronal apoptosis and neurogenesis

According to current dogma, there is little or no ongoing neurogenesis in the fully developed adult enteric nervous system. This lack of neurogenesis leaves unanswered the question of how enteric neuronal populations are maintained in adult guts, given previous reports of ongoing neuronal death. Here, we confirm that despite ongoing neuronal cell loss because of apoptosis in the myenteric ganglia of the adult small intestine, total myenteric neuronal numbers remain constant. This observed neuronal homeostasis is maintained by new neurons formed in vivo from dividing precursor cells that are located within myenteric ganglia and express both Nestin and p75NTR, but not the pan-glial marker Sox10. Mutation of the phosphatase and tensin homolog gene in this pool of adult precursors leads to an increase in enteric neuronal number, resulting in ganglioneuromatosis, modeling the corresponding disorder in humans. Taken together, our results show significant turnover and neurogenesis of adult enteric neurons and provide a paradigm for understanding the enteric nervous system in health and disease

Visualizing the 3D Architecture of Multiple Erythrocytes Infected with Plasmodium at Nanoscale by Focused Ion Beam-Scanning Electron Microscopy

Different methods for three-dimensional visualization of biological structures have been developed and extensively applied by different research groups. In the field of electron microscopy, a new technique that has emerged is the use of a focused ion beam and scanning electron microscopy for 3D reconstruction at nanoscale resolution. The higher extent of volume that can be reconstructed with this instrument represent one of the main benefits of this technique, which can provide statistically relevant 3D morphometrical data. As the life cycle of Plasmodium species is a process that involves several structurally complex developmental stages that are responsible for a series of modifications in the erythrocyte surface and cytoplasm, a high number of features within the parasites and the host cells has to be sampled for the correct interpretation of their 3D organization. Here, we used FIB-SEM to visualize the 3D architecture of multiple erythrocytes infected with Plasmodium chabaudi and analyzed their morphometrical parameters in a 3D space. We analyzed and quantified alterations on the host cells, such as the variety of shapes and sizes of their membrane profiles and parasite internal structures such as a polymorphic organization of hemoglobin-filled tubules. The results show the complex 3D organization of Plasmodium and infected erythrocyte, and demonstrate the contribution of FIB-SEM for the obtainment of statistical data for an accurate interpretation of complex biological structures

Integrating protein-protein interactions and text mining for protein function prediction

<p>Abstract</p> <p>Background</p> <p>Functional annotation of proteins remains a challenging task. Currently the scientific literature serves as the main source for yet uncurated functional annotations, but curation work is slow and expensive. Automatic techniques that support this work are still lacking reliability. We developed a method to identify conserved protein interaction graphs and to predict missing protein functions from orthologs in these graphs. To enhance the precision of the results, we furthermore implemented a procedure that validates all predictions based on findings reported in the literature.</p> <p>Results</p> <p>Using this procedure, more than 80% of the GO annotations for proteins with highly conserved orthologs that are available in UniProtKb/Swiss-Prot could be verified automatically. For a subset of proteins we predicted new GO annotations that were not available in UniProtKb/Swiss-Prot. All predictions were correct (100% precision) according to the verifications from a trained curator.</p> <p>Conclusion</p> <p>Our method of integrating CCSs and literature mining is thus a highly reliable approach to predict GO annotations for weakly characterized proteins with orthologs.</p

Lipase-catalyzed Reactions at Interfaces of Two-phase Systems and Microemulsions

This work describes the influence of two polar lipids, Sn-1/3 and Sn-2 monopalmitin, on the activity of lipase in biphasic systems and in microemulsions. In previous communications, we have shown that Sn-2 monoglycerides can replace Sn-1,3 regiospecific lipases at the oil–water interface, causing a drastically reduced rate of lipolysis. We here demonstrate that even if the lipase is expelled from the interface, it can catalyze esterification of the Sn-2 monoglyceride with fatty acids in both macroscopic oil–water systems and in microemulsions, leading to formation of di- and triglycerides

Building Disease-Specific Drug-Protein Connectivity Maps from Molecular Interaction Networks and PubMed Abstracts

The recently proposed concept of molecular connectivity maps enables researchers to integrate experimental measurements of genes, proteins, metabolites, and drug compounds under similar biological conditions. The study of these maps provides opportunities for future toxicogenomics and drug discovery applications. We developed a computational framework to build disease-specific drug-protein connectivity maps. We integrated gene/protein and drug connectivity information based on protein interaction networks and literature mining, without requiring gene expression profile information derived from drug perturbation experiments on disease samples. We described the development and application of this computational framework using Alzheimer's Disease (AD) as a primary example in three steps. First, molecular interaction networks were incorporated to reduce bias and improve relevance of AD seed proteins. Second, PubMed abstracts were used to retrieve enriched drug terms that are indirectly associated with AD through molecular mechanistic studies. Third and lastly, a comprehensive AD connectivity map was created by relating enriched drugs and related proteins in literature. We showed that this molecular connectivity map development approach outperformed both curated drug target databases and conventional information retrieval systems. Our initial explorations of the AD connectivity map yielded a new hypothesis that diltiazem and quinidine may be investigated as candidate drugs for AD treatment. Molecular connectivity maps derived computationally can help study molecular signature differences between different classes of drugs in specific disease contexts. To achieve overall good data coverage and quality, a series of statistical methods have been developed to overcome high levels of data noise in biological networks and literature mining results. Further development of computational molecular connectivity maps to cover major disease areas will likely set up a new model for drug development, in which therapeutic/toxicological profiles of candidate drugs can be checked computationally before costly clinical trials begin