Neutrino Masses via the Zee Mechanism in 5D split fermions model

We study the Zee model in the framework of the split fermion model in $M_4\times S_1/Z_2$ spacetime. Neutrino masses are generated through 1-loop diagrams without the right-handed neutrinos introduced. By assuming an order one anarchical complex 5D Yukawa couplings, all the effective 4D Yukawa couplings are determined by the wave function overlap between the split fermions and the bulk scalars in the fifth dimension. The predictability of the Yukawa couplings is in sharp contrast to the original Zee model in 4D where the Yukawa couplings are unknown free parameters. This setup exhibits a geometrical alternative to the lepton flavor symmetry. By giving four explicit sets of the split fermion locations, we demonstrate that it is possible to simultaneously fit the lepton masses and neutrino oscillation data by just a handful free parameters without much fine tuning. Moreover, we are able to make definite predictions for the mixing angle $\theta_{13}$, the absolute neutrino masses, and the lepton flavor violation processes for each configuration.Comment: 16 pages, 2 figure

A Chemical and Enzymatic Approach to Study Site-Specific Sumoylation.

A variety of cellular pathways are regulated by protein modifications with ubiquitin-family proteins. SUMO, the Small Ubiquitin-like MOdifier, is covalently attached to lysine on target proteins via a cascade reaction catalyzed by E1, E2, and E3 enzymes. A major barrier to understanding the diverse regulatory roles of SUMO has been a lack of suitable methods to identify protein sumoylation sites. Here we developed a mass-spectrometry (MS) based approach combining chemical and enzymatic modifications to identify sumoylation sites. We applied this method to analyze the auto-sumoylation of the E1 enzyme in vitro and compared it to the GG-remnant method using Smt3-I96R as a substrate. We further examined the effect of smt3-I96R mutation in vivo and performed a proteome-wide analysis of protein sumoylation sites in Saccharomyces cerevisiae. To validate these findings, we confirmed several sumoylation sites of Aos1 and Uba2 in vivo. Together, these results demonstrate that our chemical and enzymatic method for identifying protein sumoylation sites provides a useful tool and that a combination of methods allows a detailed analysis of protein sumoylation sites

Very large G protein-coupled receptor 1 regulates myelin-associated glycoprotein via Gαs/Gαq-mediated protein kinases A/C.

VLGR1 (very large G protein-coupled receptor 1), also known as MASS1 (monogenic audiogenic seizure susceptible 1), is an orphan G protein-coupled receptor that contains a large extracellular N terminus with 35 calcium-binding domains. A truncating mutation in the Mass1 gene causes autosomal recessive, sound-induced seizures in the Frings mouse. However, the function of MASS1 and the mechanism underlying Frings mouse epilepsy are not known. Here, we found that MASS1 protein is enriched in the myelinated regions of the superior and inferior colliculi, critical areas for the initiation and propagation of audiogenic seizures. Using a panel of myelin antibodies, we discovered that myelin-associated glycoprotein (MAG) expression is dramatically decreased in Frings mice. MASS1 inhibits the ubiquitylation of MAG, thus enhancing the stability of this protein, and the calcium-binding domains of MASS1 are essential for this regulation. Furthermore, MASS1 interacts with Gαs/Gαq and activates PKA and PKC in response to extracellular calcium. Suppression of signaling by MASS1 RNAi or a specific inhibitor abrogates MAG up-regulation. We postulate that MASS1 senses extracellular calcium and activates cytosolic PKA/PKC pathways to regulate myelination by means of MAG protein stability in myelin-forming cells of the auditory pathway. Further work is required to determine whether MAG dysregulation is a cause or consequence of audiogenic epilepsy and whether there are other pathways regulated by MASS1

When Crowdsourcing Meets Mobile Sensing: A Social Network Perspective

Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces crowdsourcing methods for mobile sensing. Inspired by social network, one can establish trust among participatory agents to leverage the wisdom of crowds for mobile sensing. A prototype of social network inspired mobile multimedia and sensing application is presented for illustrative purpose. Numerical experiments on real-world datasets show improved performance of mobile sensing via crowdsourcing. Challenges for mobile sensing with respect to Internet layers are discussed.Comment: To appear in Oct. IEEE Communications Magazine, feature topic on "Social Networks Meet Next Generation Mobile Multimedia Internet

MicroRNA-23a promotes myelination in the central nervous system.

Demyelinating disorders including leukodystrophies are devastating conditions that are still in need of better understanding, and both oligodendrocyte differentiation and myelin synthesis pathways are potential avenues for developing treatment. Overexpression of lamin B1 leads to leukodystrophy characterized by demyelination of the central nervous system, and microRNA-23 (miR-23) was found to suppress lamin B1 and enhance oligodendrocyte differentiation in vitro. Here, we demonstrated that miR-23a-overexpressing mice have increased myelin thickness, providing in vivo evidence that miR-23a enhances both oligodendrocyte differentiation and myelin synthesis. Using this mouse model, we explored possible miR-23a targets and revealed that the phosphatase and tensin homologue/phosphatidylinositol trisphosphate kinase/Akt/mammalian target of rapamycin pathway is modulated by miR-23a. Additionally, a long noncoding RNA, 2700046G09Rik, was identified as a miR-23a target and modulates phosphatase and tensin homologue itself in a miR-23a-dependent manner. The data presented here imply a unique role for miR-23a in the coordination of proteins and noncoding RNAs in generating and maintaining healthy myelin