Rushing to Overpay: The REIT Premium Revisited

We explore the questions of whether and why Real Estate Investment Trusts (REITs) pay more for real estate than non-REIT buyers, consequently breaking the law of one price. We develop a model where REITs optimally pay more for property because (1) they are able, due to capital access advantages and, (2) are occasionally compelled, due to regulatory time constraints on the deployment of capital. We show that the typically large (20 to 60 percent) and statistically significant (p-values less than 0.01) REIT-buyer premiums found in standard empirical hedonic pricing models are biased due to unobserved explanatory variables. Using a repeat-transaction methodology that controls for unobserved independent variables, we find the REIT-buyer premium to be about 5 percent. Furthermore, we show that REITs¿ ability (as measured by access to capital markets) and regulator compulsion (as measured by capital deployment deadlines) are related to the price premium.Real Estate Investment Trusts (REITs), commercial properties, hedonic price analysis, repeat transactions, market efficiency, law of one price, price premium

Morph-specific investment in testes mass in a trimorphic beetle, Proagoderus watanabei

When competition between males for mates is intense, it is common to find that some males will adopt alternative tactics for acquiring fertilizations, often involving the use of ‘sneak’ tactics whereby males avoid precopulatory contests. These alternative tactics are sometimes associated with discrete differences in male morphology, with sneak males investing less in weaponry but more in traits such as testes which may give an advantage in sperm competition. In some cases, it appears that males develop into more than two morphs, with a number of examples of tri- and even tetramorphic arthropod species being described. Here, we analyse the scaling relations of the dung beetle species Proagoderus watanabei, which expresses two distinct weapon traits: paired head horns and a pronotal horn. We find that males of this species are trimorphic, with alpha males expressing long head horns and a pronotal horn, beta males with long head horns but no pronotal horn and gamma males with short head horns only. We also find that alpha males invest relatively less in testes than do beta or gamma males, indicating that beta and gamma males in this species probably experience higher risks of sperm competition than do alphas

Inhibition of γ-secretase induces G2/M arrest and triggers apoptosis in breast cancer cells

γ-Secretase activity is vital for the transmembrane cleavage of Notch receptors and the subsequent migration of their intracellular domains to the nucleus. Notch overexpression has been associated with breast, colon, cervical and prostate cancers. We tested the effect of three different γ-secretase inhibitors (GSIs) in breast cancer cells. One inhibitor (GSI1) was lethal to breast cancer cell lines at concentrations of 2 μM and above but had a minimal effect on the non-malignant breast lines. GSI1 was also cytotoxic for a wide variety of cancer cell lines in the NCI60 cell screen. GSI1 treatment resulted in a marked decrease in γ-secretase activity and downregulation of the Notch signalling pathway with no effects on expression of the γ-secretase components or ligands. Flow cytometric and western blot analyses indicated that GSI1 induces a G2/M arrest leading to apoptosis, through downregulation of Bcl-2, Bax and Bcl-XL. GSI1 also inhibited proteasome activity. Thus, the γ-secretase inhibitor GSI1 has a complex mode of action to inhibit breast cancer cell survival and may represent a novel therapy in breast cancer

The Potential for Student Performance Prediction in Small Cohorts with Minimal Available Attributes

The measurement of student performance during their progress through university study provides academic leadership with critical information on each student’s likelihood of success. Academics have traditionally used their interactions with individual students through class activities and interim assessments to identify those “at risk” of failure/withdrawal. However, modern university environments, offering easy on-line availability of course material, may see reduced lecture/tutorial attendance, making such identification more challenging. Modern data mining and machine learning techniques provide increasingly accurate predictions of student examination assessment marks, although these approaches have focussed upon large student populations and wide ranges of data attributes per student. However, many university modules comprise relatively small student cohorts, with institutional protocols limiting the student attributes available for analysis. It appears that very little research attention has been devoted to this area of analysis and prediction. We describe an experiment conducted on a final-year university module student cohort of 23, where individual student data are limited to lecture/tutorial attendance, virtual learning environment accesses and intermediate assessments. We found potential for predicting individual student interim and final assessment marks in small student cohorts with very limited attributes and that these predictions could be useful to support module leaders in identifying students potentially “at risk.”.Peer reviewe

A combined approach for comparative exoproteome analysis of Corynebacterium pseudotuberculosis

Background: Bacterial exported proteins represent key components of the host-pathogen interplay. Hence, we sought to implement a combined approach for characterizing the entire exoproteome of the pathogenic bacterium Corynebacterium pseudotuberculosis, the etiological agent of caseous lymphadenitis (CLA) in sheep and goats. Results: An optimized protocol of three-phase partitioning (TPP) was used to obtain the C. pseudotuberculosis exoproteins, and a newly introduced method of data-independent MS acquisition (LC-MSE) was employed for protein identification and label-free quantification. Additionally, the recently developed tool SurfG+ was used for in silico prediction of sub-cellular localization of the identified proteins. In total, 93 different extracellular proteins of C. pseudotuberculosis were identified with high confidence by this strategy; 44 proteins were commonly identified in two different strains, isolated from distinct hosts, then composing a core C. pseudotuberculosis exoproteome. Analysis with the SurfG+ tool showed that more than 75% (70/93) of the identified proteins could be predicted as containing signals for active exportation. Moreover, evidence could be found for probable non-classical export of most of the remaining proteins. Conclusions: Comparative analyses of the exoproteomes of two C. pseudotuberculosis strains, in addition to comparison with other experimentally determined corynebacterial exoproteomes, were helpful to gain novel insights into the contribution of the exported proteins in the virulence of this bacterium. The results presented here compose the most comprehensive coverage of the exoproteome of a corynebacterial species so far