FutureGRID: A Program for long-term research into GRID systems architecture

Proceedings of the 2003 UK e-Science All Hands Meeting, 31st August - 3rd September, Nottingham UKThis is a project to carry out research into long-term GRID architecture, in the University of Cambridge Computer Laboratory and the Cambridge eScience Center, with support from the Microsoft Research Laboratory, Cambridge. It is part of a larger vision for future systems architectures for public computing platforms, including both scientitic GRID and commodity level computing such as games, peer2peer computing and storage services and so forth, based on work in the laboratories in recent years into massively scaleable distributed systems for storage, computation, content distribution and collaboration[26]

Spectroscopic analysis of finite size effects around a Kondo quantum dot

We consider a simple setup in which a small quantum dot is strongly connected to a finite size box. This box can be either a metallic box or a finite size quantum wire.The formation of the Kondo screening cloud in the box strongly depends on the ratio between the Kondo temperature and the box level spacing. By weakly connecting two metallic reservoirs to the quantum dot, a detailed spectroscopic analysis can be performed. Since the transport channels and the screening channels are almost decoupled, such a setup allows an easier access to the measure of finite-size effects associated with the finite extension of the Kondo cloud.Comment: contribution to Les Houches proceeding, ``Quantum magnetism'' 200

Simpson's Paradox, Lord's Paradox, and Suppression Effects are the same phenomenon – the reversal paradox

This article discusses three statistical paradoxes that pervade epidemiological research: Simpson's paradox, Lord's paradox, and suppression. These paradoxes have important implications for the interpretation of evidence from observational studies. This article uses hypothetical scenarios to illustrate how the three paradoxes are different manifestations of one phenomenon – the reversal paradox – depending on whether the outcome and explanatory variables are categorical, continuous or a combination of both; this renders the issues and remedies for any one to be similar for all three. Although the three statistical paradoxes occur in different types of variables, they share the same characteristic: the association between two variables can be reversed, diminished, or enhanced when another variable is statistically controlled for. Understanding the concepts and theory behind these paradoxes provides insights into some controversial or contradictory research findings. These paradoxes show that prior knowledge and underlying causal theory play an important role in the statistical modelling of epidemiological data, where incorrect use of statistical models might produce consistent, replicable, yet erroneous results

Detection of the pairwise kinematic Sunyaev-Zel'dovich effect with BOSS DR11 and the Atacama Cosmology Telescope

We present a new measurement of the kinematic Sunyaev-Zeldovich effect using data from the Atacama Cosmology Telescope (ACT) and the Baryon Oscillation Spectroscopic Survey (BOSS). Using 600 square degrees of overlapping sky area, we evaluate the mean pairwise baryon momentum associated with the positions of 50,000 bright galaxies in the BOSS DR11 Large Scale Structure catalog. A non-zero signal arises from the large-scale motions of halos containing the sample galaxies. The data fits an analytical signal model well, with the optical depth to microwave photon scattering as a free parameter determining the overall signal amplitude. We estimate the covariance matrix of the mean pairwise momentum as a function of galaxy separation, using microwave sky simulations, jackknife evaluation, and bootstrap estimates. The most conservative simulation-based errors give signal-to-noise estimates between 3.6 and 4.1 for varying galaxy luminosity cuts. We discuss how the other error determinations can lead to higher signal-to-noise values, and consider the impact of several possible systematic errors. Estimates of the optical depth from the average thermal Sunyaev-Zeldovich signal at the sample galaxy positions are broadly consistent with those obtained from the mean pairwise momentum signal.Comment: 15 pages, 8 figures, 2 table

Effects of an exercise programme with people living with HIV: Research in a disadvantaged setting

This study aimed to analyse the physical health effects of a community based 10-week physical activity programme with people living with HIV. It was developed, implemented and evaluated in a disadvantaged community in South Africa. A pre-post research design was chosen. Major recruitment and adherence challenges resulted in a small sample. Among the 23 participants who took part in both baseline and final testing, compliant participants (n = 12) were compared to non-compliant participants (n = 11). Immunological (CD4, viral load), anthropometric (height, weight, skinfolds and waist to hip ratio), muscular strength (h1RM) and cardiopulmonary fitness (time on treadmill) parameters were measured. The compliant and non-compliant groups were not different at baseline. Muscular strength was the parameter most influenced by compliance with the physical activity programme (F = 4.516, p = 0.047). Weight loss and improvement in cardiopulmonary fitness were restricted by the duration of the programme, compliance and influencing factors (e.g. nutrition, medication). The increase in strength is significant and meaningful in the context, as the participants goals were to look healthy and strong to avoid HIV related stigma. The improvements in appearance were a motivational factor, especially since the changes were made visible in a short time. Practical implications for health promotion are described. More research contextualised in disadvantaged settings is needed.DHE

Predicting a small molecule-kinase interaction map: A machine learning approach

<p>Abstract</p> <p>Background</p> <p>We present a machine learning approach to the problem of protein ligand interaction prediction. We focus on a set of binding data obtained from 113 different protein kinases and 20 inhibitors. It was attained through ATP site-dependent binding competition assays and constitutes the first available dataset of this kind. We extract information about the investigated molecules from various data sources to obtain an informative set of features.</p> <p>Results</p> <p>A Support Vector Machine (SVM) as well as a decision tree algorithm (C5/See5) is used to learn models based on the available features which in turn can be used for the classification of new kinase-inhibitor pair test instances. We evaluate our approach using different feature sets and parameter settings for the employed classifiers. Moreover, the paper introduces a new way of evaluating predictions in such a setting, where different amounts of information about the binding partners can be assumed to be available for training. Results on an external test set are also provided.</p> <p>Conclusions</p> <p>In most of the cases, the presented approach clearly outperforms the baseline methods used for comparison. Experimental results indicate that the applied machine learning methods are able to detect a signal in the data and predict binding affinity to some extent. For SVMs, the binding prediction can be improved significantly by using features that describe the active site of a kinase. For C5, besides diversity in the feature set, alignment scores of conserved regions turned out to be very useful.</p

Activation of mTOR coincides with autophagy during ligation-induced atrophy in the rat submandibular gland

Salivary gland atrophy is a common consequence of pathology, including Sjögren's syndrome, irradiation therapy and obstructive sialadenitis. During severe atrophy of the rat submandibular gland caused by excretory duct ligation, the majority of acinar cells disappear through apoptosis, whereas ductal cells proliferate and dedifferentiate; yet, the gland can survive in the atrophic state almost indefinitely, with an ability to fully recover if deligated. The control mechanisms governing these observations are not well understood. We report that ∼10% of acinar cells survive in ligation-induced atrophy. Microarray and quantitative real-time PCR analysis of ligated glands indicated sustained transcription of acinar cell-specific genes, whereas ductal-specific genes were reduced to background levels. After 3 days of ligation, activation of the mammalian target of rapamycin (mTOR) pathway and autophagy occurred as shown by phosphorylation of 4E-BP1 and expression of autophagy-related proteins. These results suggest that activation of mTOR and the autophagosomal pathway are important mechanisms that may help to preserve acinar cells during atrophy of salivary glands after injury

Increased Memory Conversion of Naïve CD8 T Cells Activated during Late Phases of Acute Virus Infection Due to Decreased Cumulative Antigen Exposure

Background: Memory CD8 T cells form an essential part of protective immunity against viral infections. Antigenic load, costimulation, CD4-help, cytokines and chemokines fluctuate during the course of an antiviral immune response thus affecting CD8 T cell activation and memory conversion. Methodology/Principal Findings: In the present study, naïve TCR transgenic LCMV-specific P14 CD8 T cells engaged at a late stage during the acute antiviral LCMV response showed reduced expansion kinetics but greater memory conversion in the spleen. Such late activated cells displayed a memory precursor effector phenotype already at the peak of the systemic antiviral response, suggesting that the environment determined their fate during antigen encounter. In the spleen, the majority of late transferred cells exhibited a central memory phenotype compared to the effector memory displayed by the early transferred cells. Increasing the inflammatory response by exogenous administration of IFNc, PolyI:C or CpG did not affect memory conversion in the late transferred group, suggesting that the diverging antigen load early versus later during acute infection had determined their fate. In agreement, reduction in the LCMV antigenic load after ribavirin treatment enhanced the contribution of early transferred cells to the long lasting memory pool. Conclusions/Significance: Our results show that naïve CD8 cells, exposed to reduced duration or concentration of antigen during viral infection convert into memory more efficiently, an observation that could have significant implications fo