A comparative study of Type II-P and II-L supernova rise times as exemplified by the case of LSQ13cuw

We report on our findings based on the analysis of observations of the Type II-L supernova LSQ13cuw within the framework of currently accepted physical predictions of core-collapse supernova explosions. LSQ13cuw was discovered within a day of explosion, hitherto unprecedented for Type II-L supernovae. This motivated a comparative study of Type II-P and II-L supernovae with relatively well-constrained explosion epochs and rise times to maximum (optical) light. From our sample of twenty such events, we find evidence of a positive correlation between the duration of the rise and the peak brightness. On average, SNe II-L tend to have brighter peak magnitudes and longer rise times than SNe II-P. However, this difference is clearest only at the extreme ends of the rise time versus peak brightness relation. Using two different analytical models, we performed a parameter study to investigate the physical parameters that control the rise time behaviour. In general, the models qualitatively reproduce aspects of the observed trends. We find that the brightness of the optical peak increases for larger progenitor radii and explosion energies, and decreases for larger masses. The dependence of the rise time on mass and explosion energy is smaller than the dependence on the progenitor radius. We find no evidence that the progenitors of SNe II-L have significantly smaller radii than those of SNe II-P.

Identification and bioactivity evaluation of a novel bradykinin inhibitory peptide from the skin secretion of Chinese large odorous frog, Odorrana livida

A novel peptide was isolated from the skin secretion of Chinese large odorous frog, Odorrana livida, and was named as Rana-BI. The cDNA sequencing was obtained by 'shotgun' cloning. The amino acid sequence of the mature peptide was identified as Gly-Leu-Leu-Ser-Gly-Lys-Ser-Val-Lys-Gly-Ser-Ile-OH by automated Edman degradation, and the molecular weight of the peptide was confirmed to be 1144.68 Da by MALDI-TOF and liquid chromatography/MS. Subsequently, the bioactivity of synthetic peptide was evaluated by smooth muscle assay using isolated rat bladder preparation. It was demonstrated that Rana-BI inhibited the contraction of rat bladder induced by bradykinin. Comparing with other peptides by searching from database, the primary structure of Rana-BI showed high similarity with that of an antimicrobial peptide of Rana family (12/12 residues). These data revealed a novel biological function of this peptide

Introducing the CTA concept

The Cherenkov Telescope Array (CTA) is a new observatory for very high-energy (VHE) gamma rays. CTA has ambitions science goals, for which it is necessary to achieve full-sky coverage, to improve the sensitivity by about an order of magnitude, to span about four decades of energy, from a few tens of GeV to above 100 TeV with enhanced angular and energy resolutions over existing VHE gamma-ray observatories. An international collaboration has formed with more than 1000 members from 27 countries in Europe, Asia, Africa and North and South America. In 2010 the CTA Consortium completed a Design Study and started a three-year Preparatory Phase which leads to production readiness of CTA in 2014. In this paper we introduce the science goals and the concept of CTA, and provide an overview of the project. © 2013 Elsevier B.V. All rights reserved.

Urinary thrombomodulin levels were significantly higher following occupational exposure to chemicals, in the presence of dipstick protein, but not in the presence of dipstick blood

Currently, there are no biomarkers which can identify patients with an increased risk of developing urothelial cancer as a result of occupational chemical exposure. The aim of this study was to evaluate the relationships between final diagnosis and 22 biomarkers measured in urine, serum and plasma collected from 156 hematuric patients. Fourteen of the 80 patients (17.5%) with urothelial cancer and 13/76 (17.1%) of the controls were deemed to have a history of chemical exposure. We applied Fisher's exact tests to explore associations between chemical exposure and final diagnosis, and tumor stage and grade, where applicable; ANOVA and t-test to compare age across patients with and without chemical exposure; and Zelen's exact test to evaluate relationships across final diagnosis, chemical exposure and smoking. Following pre-selection of biomarkers using Lasso, we identified biomarkers with differential levels across patients with and without chemical exposure using Welch's t-test. Using a one-sided t-test and considering multiple testing using FDR, we observed that TM levels in urine were significantly higher in samples from patients with a history of chemical exposure regardless of their diagnosis as control or urothelial cancer (one-sided t-test, p_UC = 0.014 and p_CTL = 0.043); in the presence of dipstick protein and when urinary pH levels ≤ 6 (p = 0.003), but not in the presence of dipstick blood (p = 0.115). Urothelial cancer patients with a history of chemical exposure were significantly younger (64.1 years) than those without chemical exposure (70.2 years) (one-sided t-test p-value = 0.012); and their tumors were higher grade (Fisher's exact test; p = 0.008). There was a strong association between a history of chemical exposure and smoking in urothelial cancer patients (Zelen's exact test; p = 0.025). Elevated urinary thrombomodulin levels could have the potential to identify chemical exposure in hematuric patients at high risk of developing urothelial cancer.

Network signatures based on gene pair expression ratios improve classification and the analysis of muscle-invasive urothelial cancer

Urothelial cancer (UC) is highly recurrent and can progress from non-invasive (NMIUC) to a more aggressive muscle-invasive (MIUC) subtype that invades the muscle tissue layer of the bladder. We present a proof of principle study that network-based features of gene pairs can be used to improve classifier performance and the functional analysis of urothelial cancer gene expression data. In the first step of our procedure each individual sample of a UC gene expression dataset is inflated by gene pair expression ratios that are defined based on a given network structure. In the second step an elastic net feature selection procedure for network-based signatures is applied to discriminate between NMIUC and MIUC samples. We performed a repeated random subsampling cross validation in three independent datasets. The network signatures were characterized by a functional enrichment analysis and studied for the enrichment of known cancer genes. We observed that the network-based gene signatures from meta collections of proteinprotein interaction (PPI) databases such as CPDB and the PPI databases HPRD and BioGrid improved the classification performance compared to single gene based signatures. The network based signatures that were derived from PPI databases showed a prominent enrichment of cancer genes (e.g., TP53, TRIM27 and HNRNPA2Bl). We provide a novel integrative approach for large-scale gene expression analysis for the identification and development of novel diagnostical targets in bladder cancer. Further, our method allowed to link cancer gene associations to network-based expression signatures that are not observed in gene-based expression signatures.