Antimalarial drugs based on artemisinin: DFT calculations on the principal reactions

Theoretical calculations have been carried out on the interactions of several endoperoxides which are potential antimalarials, including the clinically useful artemisinin, with two possible sources of iron in the parasite, namely the hexa-aquo ferrous ion [Fe(H2O)(6)](2+) and haeme. DFT calculations show that the reactions of all endoperoxides considered, with both sources of iron, initially generate a Fe-O bond followed by cleavage of the O-O bond to oxygen radical species. Subsequently, they can be transformed into carbon-centred radicals of greater stability. However, with [Fe(H2O)(6)](2+) as the iron source, the oxygen-centred radical species are more likely to react further akin to Fenton's reagent, whereby iron salts encourage hydrogen peroxide to act as an oxidizing agent, and that solvent plays a major role. In contrast, when reacting with haeme, the oxygen-centred radicals interconvert to more stable carbon-centred radicals, which can then alkylate haeme. Subsequent cleavage of the Fe-O bond leads to stable and inactive antimalarial products. These results indicate that the reactivity of the endoperoxides as antimalarials is greater with iron hexahydrates for radical-mediated damage as opposed to haeme, which leads to unreactive species. Since only nanomolar quantities of hydrated metal ions could catalyse the reactions leading to damage to the parasites, this could be an alternative or competitive reaction responsible for the antimalarial activity. (c) 2005 Elsevier B.V. All rights reserved.

On the principal eigenvalue of a Robin problem with a large parameter

We study the asymptotic behaviour of the principal eigenvalue of a Robin (or generalised Neumann) problem with a large parameter in the boundary condition for the Laplacian in a piecewise smooth domain. We show that the leading asymptotic term depends only on the singularities of the boundary of the domain, and give either explicit expressions or two-sided estimates for this term in a variety of situations.

Principal-agent issues in asset acquisition: UK institutions and their investment agents

This paper explores principal‐agent issues in the stock selection processes of institutional property investors. Drawing upon an interview survey of fund managers and acquisition professionals, it focuses on the relationships between principals and external agents as they engage in property transactions. The research investigated the extent to which the presence of outcome‐based remuneration structures could lead to biased advice, overbidding and/or poor asset selection. It is concluded that institutional property buyers are aware of incentives for opportunistic behaviour by external agents, often have sufficient expertise to robustly evaluate agents’ advice and that these incentives are counter‐balanced by a number of important controls on potential opportunistic behaviour. There are strong counter‐incentives in the need for the agents to establish personal relationships and trust between themselves and institutional buyers, to generate repeat and related business and to preserve or generate a good reputation in the market.

Effective elements of cognitive behaviour therapy for psychosis: results of a novel type of subgroup analysis based on principal stratification

Background. Meta-analyses show that cognitive behaviour therapy for psychosis (CBT-P) improves distressing positive symptoms. However, it is a complex intervention involving a range of techniques. No previous study has assessed the delivery of the different elements of treatment and their effect on outcome. Our aim was to assess the differential effect of type of treatment delivered on the effectiveness of CBT-P, using novel statistical methodology. Method. The Psychological Prevention of Relapse in Psychosis (PRP) trial was a multi-centre randomized controlled trial (RCT) that compared CBT-P with treatment as usual (TAU). Therapy was manualized, and detailed evaluations of therapy delivery and client engagement were made. Follow-up assessments were made at 12 and 24 months. In a planned analysis, we applied principal stratification (involving structural equation modelling with finite mixtures) to estimate intention-to-treat (ITT) effects for subgroups of participants, defined by qualitative and quantitative differences in receipt of therapy, while maintaining the constraints of randomization. Results. Consistent delivery of full therapy, including specific cognitive and behavioural techniques, was associated with clinically and statistically significant increases in months in remission, and decreases in psychotic and affective symptoms. Delivery of partial therapy involving engagement and assessment was not effective. Conclusions. Our analyses suggest that CBT-P is of significant benefit on multiple outcomes to patients able to engage in the full range of therapy procedures. The novel statistical methods illustrated in this report have general application to the evaluation of heterogeneity in the effects of treatment.

Feedback regulation by Atf3 in the endothelin-1-responsive transcriptome of cardiomyocytes: Egr1 is a principal Atf3 target

Endothelin-1 promotes cardiomyocyte hypertrophy by inducing changes in gene expression. Immediate early genes including activating transcription factor 3 (Atf3), Egr1 and Ptgs2 are rapidly and transiently upregulated by endothelin-1 in cardiomyocytes. Atf3 regulates expression of downstream genes and is implicated in negative feedback regulation of other immediate early genes. To identify Atf3-regulated genes, we knocked down Atf3 expression in cardiomyocytes exposed to endothelin-1 and used microarrays to interrogate the transcriptomic effects. Of upregulated mRNAs, expression of 23 (including Egr1, Ptgs2) was enhanced and expression of 25 was inhibited by Atf3 knockdown. Using quantitative PCR, we determined that knockdown of Atf3 had little effect on upregulation of Egr1 mRNA over 30 min, but abolished the subsequent decline, causing sustained Egr1 mRNA expression and enhanced protein expression. This resulted from direct binding of Atf3 to the Egr1 promoter. Mathematical modelling established that Atf3 can suffice to suppress Egr1 expression. Given the widespread co-regulation of Atf3 with Egr1, we suggest that the Atf3-Egr1 negative feedback loop is of general significance. Loss of Atf3 caused abnormal cardiomyocyte growth, presumably resulting from dysregulation of target genes. Our data therefore identify Atf3 as a nexus in cardiomyocyte hypertrophy required to facilitate the full and proper growth response.

Constrained principal component analysis reveals functionally connected load-dependent networks involved in multiple stages of working memory

Constrained principal component analysis (CPCA) with a finite impulse response (FIR) basis set was used to reveal functionally connected networks and their temporal progression over a multistage verbal working memory trial in which memory load was varied. Four components were extracted, and all showed statistically significant sensitivity to the memory load manipulation. Additionally, two of the four components sustained this peak activity, both for approximately 3 s (Components 1 and 4). The functional networks that showed sustained activity were characterized by increased activations in the dorsal anterior cingulate cortex, right dorsolateral prefrontal cortex, and left supramarginal gyrus, and decreased activations in the primary auditory cortex and "default network" regions. The functional networks that did not show sustained activity were instead dominated by increased activation in occipital cortex, dorsal anterior cingulate cortex, sensori-motor cortical regions, and superior parietal cortex. The response shapes suggest that although all four components appear to be invoked at encoding, the two sustained-peak components are likely to be additionally involved in the delay period. Our investigation provides a unique view of the contributions made by a network of brain regions over the course of a multiple-stage working memory trial.

Analysis of diffusion tensor magnetic resonance imaging data using principal component analysis

An analysis method for diffusion tensor (DT) magnetic resonance imaging data is described, which, contrary to the standard method (multivariate fitting), does not require a specific functional model for diffusion-weighted (DW) signals. The method uses principal component analysis (PCA) under the assumption of a single fibre per pixel. PCA and the standard method were compared using simulations and human brain data. The two methods were equivalent in determining fibre orientation. PCA-derived fractional anisotropy and DT relative anisotropy had similar signal-to-noise ratio (SNR) and dependence on fibre shape. PCA-derived mean diffusivity had similar SNR to the respective DT scalar, and it depended on fibre anisotropy. Appropriate scaling of the PCA measures resulted in very good agreement between PCA and DT maps. In conclusion, the assumption of a specific functional model for DW signals is not necessary for characterization of anisotropic diffusion in a single fibre.