19 resultados para Subtraction
Resumo:
Superluminous supernovae (SLSNe) of Type Ic have a tendency to occur in faint host galaxies which are likely to have low mass and low metallicity. PTF12dam is one of the closest and best-studied superluminous explosions that has a broad and slowly fading light curve similar to SN 2007bi. Here we present new photometry and spectroscopy for PTF12dam from 200-500 d (rest frame) after peak and a detailed analysis of the host galaxy (SDSS J142446.21+461348.6 at z = 0.107). Using deep templates and image subtraction we show that the light curve can be fit with a magnetar model if escape of high-energy gamma rays is taken into account. The full bolometric light curve from -53 to +399 d (with respect to peak) cannot be fit satisfactorily with the pair-instability models. An alternative model of interaction with a dense circumstellar material (CSM) produces a good fit to the data although this requires a very large mass (˜13 M⊙) of hydrogen-free CSM. The host galaxy is a compact dwarf (physical size ˜1.9 kpc) and with Mg = -19.33 ± 0.10, it is the brightest nearby SLSN Ic host discovered so far. The host is a low-mass system (2.8 × 108 M⊙) with a star formation rate (5.0 M⊙ yr-1), which implies a very high specific star formation rate (17.9 Gyr-1). The remarkably strong nebular emission provide detections of the [O III] λ4363 and [O II] λλ7320, 7330auroral lines and an accurate oxygen abundance of 12 + log (O/H) = 8.05 ± 0.09. We show here that they are at the extreme end of the metallicity distribution of dwarf galaxies and propose that low metallicity is a requirement to produce these rare and peculiar SNe.
Resumo:
The reciprocal interaction between cancer cells and the tissue-specific stroma is critical for primary and metastatic tumor growth progression. Prostate cancer cells colonize preferentially bone (osteotropism), where they alter the physiological balance between osteoblast-mediated bone formation and osteoclast-mediated bone resorption, and elicit prevalently an osteoblastic response (osteoinduction). The molecular cues provided by osteoblasts for the survival and growth of bone metastatic prostate cancer cells are largely unknown. We exploited the sufficient divergence between human and mouse RNA sequences together with redefinition of highly species-specific gene arrays by computer-aided and experimental exclusion of cross-hybridizing oligonucleotide probes. This strategy allowed the dissection of the stroma (mouse) from the cancer cell (human) transcriptome in bone metastasis xenograft models of human osteoinductive prostate cancer cells (VCaP and C4-2B). As a result, we generated the osteoblastic bone metastasis-associated stroma transcriptome (OB-BMST). Subtraction of genes shared by inflammation, wound healing and desmoplastic responses, and by the tissue type-independent stroma responses to a variety of non-osteotropic and osteotropic primary cancers generated a curated gene signature ("Core" OB-BMST) putatively representing the bone marrow/bone-specific stroma response to prostate cancer-induced, osteoblastic bone metastasis. The expression pattern of three representative Core OB-BMST genes (PTN, EPHA3 and FSCN1) seems to confirm the bone specificity of this response. A robust induction of genes involved in osteogenesis and angiogenesis dominates both the OB-BMST and Core OB-BMST. This translates in an amplification of hematopoietic and, remarkably, prostate epithelial stem cell niche components that may function as a self-reinforcing bone metastatic niche providing a growth support specific for osteoinductive prostate cancer cells. The induction of this combinatorial stem cell niche is a novel mechanism that may also explain cancer cell osteotropism and local interference with hematopoiesis (myelophthisis). Accordingly, these stem cell niche components may represent innovative therapeutic targets and/or serum biomarkers in osteoblastic bone metastasis.
Resumo:
Abstract The dehydrogenation of cyclohexanol to cyclohexanone is very important in the manufacture of nylon. Copper-based catalysts are the most popular catalysts for this reaction, and on these catalysts the reaction mechanism and active site are in debate. In order to elucidate the mechanism and active site of the cyclohexanol dehydrogenation on copper-based catalysts, density functional theory with dispersion corrections were performed on up to six facets of copper in two different oxidation states: monovalent copper and metallic copper. By calculating the surface energies of these facets, Cu(111) and Cu2O(111) were found to be the most stable facets for metallic copper and for monovalent copper, respectively. On these two facets, all the possible elementary steps in the dehydrogenation pathway of cyclohexanol were calculated, including the adsorption, dehydrogenation, hydrogen coupling and desorption. Two different reaction pathways for dehydrogenation were considered on both surfaces. It was revealed that the dehydrogenation mechanisms are different on these two surfaces: on Cu(111) the hydrogen belonging to the hydroxyl is removed first, then the hydrogen belonging to the carbon is subtracted, while on Cu2O(111) the hydrogen belonging to the carbon is removed followed by the subtraction of the hydrogen in the hydroxyl group. Furthermore, by comparing the energy profiles of these two surfaces, Cu2O(111) was found to be more active for cyclohexanol dehydrogenation than Cu(111). In addition, we found that the coordinatively unsaturated copper sites on Cu2O(111) are the reaction sites for all the steps. Therefore, the coordinatively unsaturated copper site on Cu2O(111) is likely to be the active site for cyclohexanol dehydrogenation on the copper-based catalysts.
Resumo:
To define specific pathways important in the multistep transformation process of normal plasma cells (PCs) to monoclonal gammopathy of uncertain significance (MGUS) and multiple myeloma (MM), we have applied microarray analysis to PCs from 5 healthy donors (N), 7 patients with MGUS, and 24 patients with newly diagnosed MM. Unsupervised hierarchical clustering using 125 genes with a large variation across all samples defined 2 groups: N and MGUS/MM. Supervised analysis identified 263 genes differentially expressed between N and MGUS and 380 genes differentially expressed between N and MM, 197 of which were also differentially regulated between N and MGUS. Only 74 genes were differentially expressed between MGUS and MM samples, indicating that the differences between MGUS and MM are smaller than those between N and MM or N and MGUS. Differentially expressed genes included oncogenes/tumor-suppressor genes (LAF4, RB1, and disabled homolog 2), cell-signaling genes (RAS family members, B-cell signaling and NF-kappaB genes), DNA-binding and transcription-factor genes (XBP1, zinc finger proteins, forkhead box, and ring finger proteins), and developmental genes (WNT and SHH pathways). Understanding the molecular pathogenesis of MM by gene expression profiling has demonstrated sequential genetic changes from N to malignant PCs and highlighted important pathways involved in the transformation of MGUS to MM.