Exoplanets Around Red Giants: Distribution and Habitability

As the search for exoplanets continues, more are being discovered orbiting Red Giant stars. We use current data from the NASA Exoplanet Archive to investigate planet distribution around Red Giant stars and their presence in the host's habitable zone. As well, we update the power law relation between planet mass and stellar radius found in previous studies and provide more detailed investigations on this topic. Ten Red Giant-hosted exoplanets are found to be in the optimistically calculated habitable zone, five of which are in a more conservatively calculated habitable zone. We believe additional exoplanets can be found in habitable zones around Red Giants using the direct imaging and other methods, along with more powerful detection instrumentation

Strong-field general relativity and quasi-periodic oscillations in x-ray binaries

Quasi-periodic oscillations (QPOs) at frequencies near 1000 Hz were recently discovered in several x-ray binaries containing neutron stars. Two sources show no correlation between QPO frequency and source count rate (Berger et al. 1996, Zhang et al. 1996). We suggest that the QPO frequency is determined by the Keplerian orbital frequency near the marginally stable orbit predicted by general relativity in strong gravitational fields (Muchotrzeb-Czerny 1986, Paczynski 1987, Kluzniak et al. 1990). The QPO frequencies observed from 4U 1636-536 imply that the mass of the neutron star is 2.02 +/- 0.12 solar masses. Interpretation of the 4.1 keV absorption line observed from 4U 1636-536 (Waki et al. 1984) as due to Fe XXV ions then implies a neutron star radius of 9.6 +/-0.6 km.Comment: 4 pages, uses aas2pp4.sty, submitted to ApJ

Paracrine Factors of Mesenchymal Stem Cells Recruit Macrophages and Endothelial Lineage Cells and Enhance Wound Healing

Bone marrow derived mesenchymal stem cells (BM-MSCs) have been shown to enhance wound healing; however, the mechanisms involved are barely understood. In this study, we examined paracrine factors released by BM-MSCs and their effects on the cells participating in wound healing compared to those released by dermal fibroblasts. Analyses of BM-MSCs with Real-Time PCR and of BM-MSC-conditioned medium by antibody-based protein array and ELISA indicated that BM-MSCs secreted distinctively different cytokines and chemokines, such as greater amounts of VEGF-α, IGF-1, EGF, keratinocyte growth factor, angiopoietin-1, stromal derived factor-1, macrophage inflammatory protein-1alpha and beta and erythropoietin, compared to dermal fibroblasts. These molecules are known to be important in normal wound healing. BM-MSC-conditioned medium significantly enhanced migration of macrophages, keratinocytes and endothelial cells and proliferation of keratinocytes and endothelial cells compared to fibroblast-conditioned medium. Moreover, in a mouse model of excisional wound healing, where concentrated BM-MSC-conditioned medium was applied, accelerated wound healing occurred compared to administration of pre-conditioned or fibroblast-conditioned medium. Analysis of cell suspensions derived from the wound by FACS showed that wounds treated with BM-MSC-conditioned medium had increased proportions of CD4/80-postive macrophages and Flk-1-, CD34- or c-kit-positive endothelial (progenitor) cells compared to wounds treated with pre-conditioned medium or fibroblast-conditioned medium. Consistent with the above findings, immunohistochemical analysis of wound sections showed that wounds treated with BM-MSC-conditioned medium had increased abundance of macrophages. Our results suggest that factors released by BM-MSCs recruit macrophages and endothelial lineage cells into the wound thus enhancing wound healing

Distributed hydrogen sensing using in-fiber Rayleigh scattering

This letter reports a fully distributed hydrogen sensing technique using Rayleigh backscattering in palladium (Pd) and copper (Cu) coated optical fiber. The local in-fiber strain changes due to Pd hydrogen absorptions are interrogated spatially resolved optical frequency domain reflectrometry measurements of the Rayleigh signals. Electrical power is used to induce heating in the Pd coating, which accelerates both the hydrogen response and the sensor recycling. This technique promises an inexpensive and truly distributed fiber solution for continuous hydrogen leak detection with centimeter spatial resolution at room and low temperatures. © 2012 American Institute of Physics

Integration of Genome and Chromatin Structure with Gene Expression Profiles To Predict c-MYC Recognition Site Binding and Function

The MYC genes encode nuclear sequence specific–binding DNA-binding proteins that are pleiotropic regulators of cellular function, and the c-MYC proto-oncogene is deregulated and/or mutated in most human cancers. Experimental studies of MYC binding to the genome are not fully consistent. While many c-MYC recognition sites can be identified in c-MYC responsive genes, other motif matches—even experimentally confirmed sites—are associated with genes showing no c-MYC response. We have developed a computational model that integrates multiple sources of evidence to predict which genes will bind and be regulated by MYC in vivo. First, a Bayesian network classifier is used to predict those c-MYC recognition sites that are most likely to exhibit high-occupancy binding in chromatin immunoprecipitation studies. This classifier incorporates genomic sequence, experimentally determined genomic chromatin acetylation islands, and predicted methylation status from a computational model estimating the likelihood of genomic DNA methylation. We find that the predictions from this classifier are also applicable to other transcription factors, such as cAMP-response element-binding protein, whose binding sites are sensitive to DNA methylation. Second, the MYC binding probability is combined with the gene expression profile data from nine independent microarray datasets in multiple tissues. Finally, we may consider gene function annotations in Gene Ontology to predict the c-MYC targets. We assess the performance of our prediction results by comparing them with the c-myc targets identified in the biomedical literature. In total, we predict 460 likely c-MYC target genes in the human genome, of which 67 have been reported to be both bound and regulated by MYC, 68 are bound by MYC, and another 80 are MYC-regulated. The approach thus successfully identifies many known c-MYC targets and suggests many novel sites. Our findings suggest that to identify c-MYC genomic targets, integration of different data sources helps to improve the accuracy