Decays of the Meson BcB_c to a PP-Wave Charmonium State χc\chi_c or hch_c

The semileptonic decays, $B_{c}{\longrightarrow}{\chi_c}(h_c)+{\ell}+{{\nu}}_{\ell}$, and the two-body nonleptonic decays, $B_{c}{\longrightarrow}{\chi_c}(h_c)+h$, (here $\chi_c$ and $h_c$ denote $(c\bar c[^3P_J])$ and $(c\bar c[^1P_1])$ respectively, and $h$ indicates a meson) were computed. All of the form factors appearing in the relevant weak-current matrix elements with $B_c$ as its initial state and a $P$-wave charmonium state as its final state for the decays were precisely formulated in terms of two independent overlapping-integrations of the wave-functions of $B_c$ and the $P$-wave charmonium and with proper kinematics factors being `accompanied'. We found that the decays are quite sizable, so they may be accessible in Run-II at Tevatron and in the foreseen future at LHC, particularly, when BTeV and LHCB, the special detectors for B-physics, are borne in mind. In addition, we also pointed out that the decays $B_c\to h_c+...$ may potentially be used as a fresh window to look for the $h_c$ charmonium state, and the cascade decays, $B_c\to \chi_c[^3P_{1,2}]+l+\nu_l$ ($B_c\to \chi_c[^3P_{1,2}]+h$) with one of the radiative decays $\chi_c[^3P_{1,2}] \to J/\psi+\gamma$ being followed accordingly, may affect the observations of $B_c$ meson through the decays $B_{c}\to {J/\psi}+{l}+\nu_{l}$ ($B_c\to J/\psi+h$) substantially.Comment: 24 pages, 3 figures, the replacement for improving the presentation and adding reference

Network Biology of Tumor Stem-like Cells Identified a Regulatory Role of CBX5 in Lung Cancer

Mounting evidence links cancers possessing stem-like properties with worse prognosis. Network biology with signal processing mechanics was explored here using expression profiles of a panel of tumor stem-like cells (TSLCs). The profiles were compared to their parental tumor cells (PTCs) and the human embryonic stem cells (hESCs), for the identification of gene chromobox homolog 5, CBX5, as a potential target for lung cancer. CBX5 was found to regulate the stem-like properties of lung TSLCs and was predictive of lung cancer prognosis. The investigation was facilitated by finding target genes based on modeling epistatic signaling mechanics via a predictive and scalable network-based survival model. Topologically-weighted measurements of CBX5 were synchronized with those of BIRC5, DNMT1, E2F1, ESR1, MLH1, MSH2, RB1, SMAD1 and TAF5. We validated our findings in another Taiwanese lung cancer cohort, as well as in knockdown experiments using sh-CBX5 RNAi both in vitro and in vivo.National Science Council (China) (NSC grant 100-2325-B-010-010-MY3/98-2314-B-010-024-MY2/97-3111-B075-001-MY3/ 96-2314-075-056-MY3)National Yang-Ming University (Ministry of Education, Aim for the Top University Plan: 96ADD122, 96ADD125, 96ADT191, 97ACD113, 97ACT302, 98ACT302, 98ACD107, 98ACT192 and Brain Research Center-3T-MRI project)))Taipei Veterans General Hospital (98-C1-099/E1-003/ER3-001)Taipei Veterans General Hospital (Joint Projects of VGHUST (98-G6-6/ 98-P1-01/99-P6-39)Chi Mei Medical Center (CMYM9801)Yen-Tjing-Ling Medical Foundation (96/97/98)Taipei City Hospital (96-002-62-092)Technology Development Program for Academia (TDPA; 98-EC-17-A-19-S2-0107)Taiwan. Department of Industrial Technology, Ministry of Economic AffairsNational Science Council (China) (NSC 101-2325-B-010 -009)Taiwan. Department of Health. Cancer Research Center of Excellence (DOH101-TD-C-111-007

Sox2, a stemness gene, regulates tumor-initiating and drug-resistant properties in CD133-positive glioblastoma stem cells

AbstractBackgroundGlioblastoma multiforme (GBM) is the most lethal type of adult brain cancer and performs outrageous growth and resistance regardless of adjuvant chemotherapies, eventually contributing to tumor recurrence and poor outcomes. Considering the common heterogeneity of cancer cells, the imbalanced regulatory mechanism could be switched on/off and contribute to drug resistance. Moreover, the subpopulation of GBM cells was recently discovered to share similar phenotypes with neural stem cells. These cancer stem cells (CSCs) promote the potency of tumor initiation. As a result, targeting of glioma stem cells has become the dominant way of improving the therapeutic outcome against GBM and extending the life span of patients. Among the biomarkers of CSCs, CD-133 (prominin-1) has been known to effectively isolate CSCs from cancer population, including GBM; however, the underlying mechanism of how stemness genes manipulate CSC-associated phenotypes, such as tumor initiation and relapse, is still unclear.MethodsTumorigenicity, drug resistance and embryonic stem cell markers were examined in primary CD133-positive (CD133+) GBM cells and CD133+ subpopulation. Stemness signature of CD133+ GBM cells was identified using microarray analysis. Stem cell potency, tumorigenicity and drug resistance were also tested in differential expression of SOX2 in GBM cells.ResultsIn this study, high tumorigenic and drug resistance was noticed in primary CD-133+ GBM cells; meanwhile, plenty of embryonic stem cell markers were also elevated in the CD-133+ subpopulation. Using microarray analysis, we identified SOX2 as the most enriched gene among the stemness signature in CD133+ GBM cells. Overexpression of SOX2 consistently enhanced the stem cell potency in the GBM cell lines, whereas knockdown of SOX2 dramatically withdrew CD133 expression in CD133+ GBM cells. Additionally, we silenced SOX2 expression using RNAi system, which abrogated the ability of tumor initiation as well as drug resistance of CD133+ GBM cells, suggesting that SOX2 plays a crucial role in regulating tumorigenicity in CD133+ GBM cells.ConclusionSOX2 plays a crucial role in regulating tumorigenicity in CD133+ GBM cells. Our results not only revealed the genetic plasticity contributing to drug resistance and stemness but also demonstrated the dominant role of SOX2 in maintenance of GBM CSCs, which may provide a novel therapeutic target to overcome the conundrum of poor survival of brain cancers

Testbeds for Transition Metal Dichalcogenide Photonics: Efficacy of Light Emission Enhancement in Monomer vs. Dimer Nanoscale Antennae

Monolayer transition metal dichalcogenides are uniquely-qualified materials for photonics because they combine well defined tunable direct band gaps and selfpassivated surfaces without dangling bonds. However, the atomic thickness of these 2D materials results in low photo absorption limiting the achievable photo luminescence intensity. Such emission can, in principle, be enhanced via nanoscale antennae resulting in; a. an increased absorption cross-section enhancing pump efficiency, b. an acceleration of the internal emission rate via the Purcell factor mainly by reducing the antennas optical mode volume beyond the diffraction limit, and c. improved impedance matching of the emitter dipole to the freespace wavelength. Plasmonic dimer antennae show orders of magnitude hot-spot field enhancements when an emitter is positioned exactly at the midgap. However, a 2D material cannot be grown, or easily transferred, to reside in mid-gap of the metallic dimer cavity. In addition, a spacer layer between the cavity and the emissive material is required to avoid non-radiative recombination channels. Using both computational and experimental methods, in this work we show that the emission enhancement from a 2D emitter- monomer antenna cavity system rivals that of dimers at much reduced lithographic effort. We rationalize this finding by showing that the emission enhancement in dimer antennae does not specifically originate from the gap of the dimer cavity, but is an average effect originating from the effective cavity crosssection taken below each optical cavity where the emitting 2D film is located. In particular, we test an array of different dimer and monomer antenna geometries and observe a representative 3x higher emission for both monomer and dimer cavities as compared to intrinsic emission of Chemical Vapor Deposition synthesized WS2 flakes.Comment: 31 pages, 5 figure

Enhanced Differentiation of Three-Gene-Reprogrammed Induced Pluripotent Stem Cells into Adipocytes via Adenoviral-Mediated PGC-1α Overexpression

Induced pluripotent stem cells formed by the introduction of only three factors, Oct4/Sox2/Klf4 (3-gene iPSCs), may provide a safer option for stem cell-based therapy than iPSCs conventionally introduced with four-gene iPSCs. Peroxisome proliferator-activated receptor gamma coactivator-1α (PGC-1α) plays an important role during brown fat development. However, the potential roles of PGC-1α in regulating mitochondrial biogenesis and the differentiation of iPSCs are still unclear. Here, we investigated the effects of adenovirus-mediated PGC-1α overexpression in 3-gene iPSCs. PGC-1α overexpression resulted in increased mitochondrial mass, reactive oxygen species production, and oxygen consumption. Microarray-based bioinformatics showed that the gene expression pattern of PGC-1α-overexpressing 3-gene iPSCs resembled the expression pattern observed in adipocytes. Furthermore, PGC-1α overexpression enhanced adipogenic differentiation and the expression of several brown fat markers, including uncoupling protein-1, cytochrome C, and nuclear respiratory factor-1, whereas it inhibited the expression of the white fat marker uncoupling protein-2. Furthermore, PGC-1α overexpression significantly suppressed osteogenic differentiation. These data demonstrate that PGC-1α directs the differentiation of 3-gene iPSCs into adipocyte-like cells with features of brown fat cells. This may provide a therapeutic strategy for the treatment of mitochondrial disorders and obesity

A Novel High-Content Flow Cytometric Method for Assessing the Viability and Damage of Rat Retinal Ganglion Cells

PURPOSE: The aim of the study was to develop a high-content flow cytometric method for assessing the viability and damage of small, medium, and large retinal ganglion cells (RGCs) in N-methyl-D-aspartic acid (NMDA)-injury model. METHODS/RESULTS: Retinal toxicity was induced in rats by intravitreal injection of NMDA and RGCs were retrogradely labeled with Fluoro-Gold (FG). Seven days post-NMDA injection, flatmount and flow cytometric methods were used to evaluate RGCs. In addition, the RGC area diameter (D((a))) obtained from retinal flatmount imaging were plotted versus apparent volume diameter (D((v))) obtained from flow cytometry for the same cumulative cell number (sequentially from small to large RGCs) percentile (Q) to establish their relationship for accurately determining RGC sizes. Good correlation (r = 0.9718) was found between D((a)) and apparent D((v)). Both flatmount and flow cytometric analyses of RGCs showed that 40 mM NMDA significantly reduced the numbers of small and medium RGCs but not large RGCs. Additionally, flow cytometry showed that the geometric means of FG and thy-1 intensities in three types of RGCs decreased to 90.96±2.24% (P<0.05) and 91.78±1.89% (P>0.05) for small, 69.62±2.11% (P<0.01) and 69.07±2.98% (P<0.01) for medium, and 69.68±6.48% (P<0.05) and 69.91±6.23% (P<0.05) for large as compared with the normal RGCs. CONCLUSION: The established flow cytometric method provides high-content analysis for differential evaluation of RGC number and status and should be useful for the evaluation of various models of optic nerve injury and the effects of potential neuroprotective agents

A computational study on outliers in world music

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country

The Princeton Protein Orthology Database (P-POD): A Comparative Genomics Analysis Tool for Biologists

Many biological databases that provide comparative genomics information and tools are now available on the internet. While certainly quite useful, to our knowledge none of the existing databases combine results from multiple comparative genomics methods with manually curated information from the literature. Here we describe the Princeton Protein Orthology Database (P-POD, http://ortholog.princeton.edu), a user-friendly database system that allows users to find and visualize the phylogenetic relationships among predicted orthologs (based on the OrthoMCL method) to a query gene from any of eight eukaryotic organisms, and to see the orthologs in a wider evolutionary context (based on the Jaccard clustering method). In addition to the phylogenetic information, the database contains experimental results manually collected from the literature that can be compared to the computational analyses, as well as links to relevant human disease and gene information via the OMIM, model organism, and sequence databases. Our aim is for the P-POD resource to be extremely useful to typical experimental biologists wanting to learn more about the evolutionary context of their favorite genes. P-POD is based on the commonly used Generic Model Organism Database (GMOD) schema and can be downloaded in its entirety for installation on one's own system. Thus, bioinformaticians and software developers may also find P-POD useful because they can use the P-POD database infrastructure when developing their own comparative genomics resources and database tools

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871