Estrogen receptor-Beta activated apoptosis in benign hyperplasia and cancer of the prostate is androgen independent and TNF-alpha mediated

Prostate cancer (PCa) and benign prostatic hyperplasia (BPH) are androgen-dependent diseases commonly treated by inhibiting androgen action. However, androgen ablation or castration fail to target androgen-independent cells implicated in disease etiology and recurrence. Mechanistically different to castration, this study shows beneficial proapoptotic actions of estrogen receptor–β (ERβ) in BPH and PCa. ERβ agonist induces apoptosis in prostatic stromal, luminal and castrate-resistant basal epithelial cells of estrogen-deficient aromatase knock-out mice. This occurs via extrinsic (caspase-8) pathways, without reducing serum hormones, and perturbs the regenerative capacity of the epithelium. TNFα knock-out mice fail to respond to ERβ agonist, demonstrating the requirement for TNFα signaling. In human tissues, ERβ agonist induces apoptosis in stroma and epithelium of xenografted BPH specimens, including in the CD133+ enriched putative stem/progenitor cells isolated from BPH-1 cells in vitro. In PCa, ERβ causes apoptosis in Gleason Grade 7 xenografted tissues and androgen-independent cells lines (PC3 and DU145) via caspase-8. These data provide evidence of the beneficial effects of ERβ agonist on epithelium and stroma of BPH, as well as androgen-independent tumor cells implicated in recurrent disease. Our data are indicative of the therapeutic potential of ERβ agonist for treatment of PCa and/or BPH with or without androgen withdrawal.

A comparison of alternative bankruptcy prediction models

Early models of bankruptcy prediction employed financial ratios drawn from pre-bankruptcy financial statements and performed well both in-sample and out-of-sample. Since then there has been an ongoing effort in the literature to develop models with even greater predictive performance. A significant innovation in the literature was the introduction into bankruptcy prediction models of capital market data such as excess stock returns and stock return volatility, along with the application of the Black–Scholes–Merton option-pricing model. In this note, we test five key bankruptcy models from the literature using an upto- date data set and find that they each contain unique information regarding the probability of bankruptcy but that their performance varies over time. We build a new model comprising key variables from each of the five models and add a new variable that proxies for the degree of diversification within the firm. The degree of diversification is shown to be negatively associated with the risk of bankruptcy. This more general model outperforms the existing models in a variety of in-sample and out-of-sample tests.

Do Australian public and nonprofit nurses cope with administrative stressors?

The nursing profession in Australia and other OECD countries such as the USA and the UK, have focused on ways to recruit and retain nurses (e.g., Bartram, Joiner, & Stanton, 2004). Research has shown that the most common factors impacting negatively on retention include sources of nursing stress such as workload and work environment. While the literature has shown that nursing staff encounter these stressors, studies do not examine the effects of stress caused by an increasing degree of administrative demand placed on nurses, caused by the new public management (NPM) reform in public and nonprofit (PNP) health care organizations. At best, some studies have alluded to some aspects of administrative related stressors (vis-a-vis nursing related stressors such as death, sickness, etc), but they have not been examined in any detail. Similarly, extant research has not examined how nurses cope with these administrative stressors. These will be the main aims of the present study.

Computational approaches for modelling intrinsic noise and delays in genetic regulatory networks

This chapter focuses on the interactions and roles between delays and intrinsic noise effects within cellular pathways and regulatory networks. We address these aspects by focusing on genetic regulatory networks that share a common network motif, namely the negative feedback loop, leading to oscillatory gene expression and protein levels. In this context, we discuss computational simulation algorithms for addressing the interplay of delays and noise within the signaling pathways based on biological data. We address implementational issues associated with efficiency and robustness. In a molecular biology setting we present two case studies of temporal models for the Hes1 gene (Monk, 2003; Hirata et al., 2002), known to act as a molecular clock, and the Her1/Her7 regulatory system controlling the periodic somite segmentation in vertebrate embryos (Giudicelli and Lewis, 2004; Horikawa et al., 2006).

Assessing students in senior science: an analysis of questions in contextualised chemistry exams

This study explores the development of a coding system for analysing test questions in two context-based chemistry exams. We describe our unique analytical procedures before contrasting the data from both tests. Our findings indicate that when a new curriculum is developed such as a context-based curriculum, teachers are required to combine the previously separate domains of context and concept to develop contextualised assessment. We argue that constructing contextualised assessment items requires teachers to view concepts and context as interconnected rather than as separate entities that may polarise scientific endeavour. Implications for practice, curriculum and assessment-development in context-based courses are proposed.