327-MHz GMRT observations of one candidate and three Galactic Supernova Remnants

Results from the 327-MHz Giant Meterwave Radio Telescope (GMRT) observations of four fields - three fields containing Galactic supernova remnants (SNRs) (G001.4-0.1, G003.8+0.3, and G356.3-1.5) and one field containing a candidate SNR (G004.2+0.0), are reported in this paper. These fields were selected from the 843-MHz survey conducted by Gray (1994b) using the Molonglo Synthesis Telescope (MOST). All the three SNRs are detected in the GMRT images. Significant amount of thermal emission is seen at the location of the candidate SNR, and the GMRT image shows a discrete source of emission which is consistent with it being a flat spectrum thermal source. An incomplete arc of emission with a compact central source detected in one of the fields, is coincident with the extended OH(1720 MHz) emission reported earlier. Possible implications of this morphology and correlation with the OH(1720 MHz) emission are also discussed.Comment: 7 pages, 6 Postscript figures, accepted for publication in MNRA

A Sparse Reconstruction Algorithm for Multi-Frequency Radio Images

In radio interferometry, every pair of antennas in an array defines one sampling point in the Fourier domain of the sky image. By combining information from different wavelengths, sample coverage - and therefore reconstruction quality - can be increased. However, the images at different wavelengths can be dramatically dissimilar; this fact must be taken into account when reconstructing multi-frequency images. In this paper, we present a novel reconstruction algorithm based on the assumption that the spectrum is continuous. In contrast to prior work, we allow for sparse deviations from this assumption: this allows, for example, for accurate reconstruction of line spectra superimposed on a continuum. Using simulated measurements on synthetic multi-frequency images, we show that the proposed approach provides significant improvements over a comparable method based solely on a continuity assumption

Tumor Necrosis Factor-α Regulates Distinct Molecular Pathways and Gene Networks in Cultured Skeletal Muscle Cells

Skeletal muscle wasting is a debilitating consequence of large number of disease states and conditions. Tumor necrosis factor-α (TNF-α) is one of the most important muscle-wasting cytokine, elevated levels of which cause significant muscular abnormalities. However, the underpinning molecular mechanisms by which TNF-α causes skeletal muscle wasting are less well-understood.We have used microarray, quantitative real-time PCR (QRT-PCR), Western blot, and bioinformatics tools to study the effects of TNF-α on various molecular pathways and gene networks in C2C12 cells (a mouse myoblastic cell line). Microarray analyses of C2C12 myotubes treated with TNF-α (10 ng/ml) for 18h showed differential expression of a number of genes involved in distinct molecular pathways. The genes involved in nuclear factor-kappa B (NF-kappaB) signaling, 26s proteasome pathway, Notch1 signaling, and chemokine networks are the most important ones affected by TNF-α. The expression of some of the genes in microarray dataset showed good correlation in independent QRT-PCR and Western blot assays. Analysis of TNF-treated myotubes showed that TNF-α augments the activity of both canonical and alternative NF-κB signaling pathways in myotubes. Bioinformatics analyses of microarray dataset revealed that TNF-α affects the activity of several important pathways including those involved in oxidative stress, hepatic fibrosis, mitochondrial dysfunction, cholesterol biosynthesis, and TGF-β signaling. Furthermore, TNF-α was found to affect the gene networks related to drug metabolism, cell cycle, cancer, neurological disease, organismal injury, and abnormalities in myotubes.TNF-α regulates the expression of multiple genes involved in various toxic pathways which may be responsible for TNF-induced muscle loss in catabolic conditions. Our study suggests that TNF-α activates both canonical and alternative NF-κB signaling pathways in a time-dependent manner in skeletal muscle cells. The study provides novel insight into the mechanisms of action of TNF-α in skeletal muscle cells