Measurement bias in activation-recovery intervals from unipolar electrograms

The activation-recovery interval (ARI) calculated from unipolar electrograms is regularly used as a convenient surrogate measure of local cardiac action potential durations (APD). This method enables important research bridging between computational studies and in vitro and in vivo human studies. The Wyatt method is well established as a theoretically sound method for calculating ARIs; however, some studies have observed that it is prone to a bias error in measurement when applied to positive T waves. This article demonstrates that recent theoretical and computational studies supporting the use of the Wyatt method are likely to have underestimated the extent of this bias in many practical experimental recording scenarios. This work addresses these situations and explains the measurement bias by adapting existing theoretical expressions of the electrogram to represent practical experimental recording configurations. A new analytic expression for the electrogram's local component is derived, which identifies the source of measurement bias for positive T waves. A computer implementation of the new analytic model confirms our hypothesis that the bias is systematically dependent on the electrode configuration. These results provide an aid to electrogram interpretation in general, and this work's outcomes are used to make recommendations on how to minimize measurement error

Survey of the needs of patients with spinal cord injury: impact and priority for improvement in hand function in tetraplegics\ud

Objective: To investigate the impact of upper extremity deficit in subjects with tetraplegia.\ud \ud Setting: The United Kingdom and The Netherlands.\ud \ud Study design: Survey among the members of the Dutch and UK Spinal Cord Injury (SCI) Associations.\ud \ud Main outcome parameter: Indication of expected improvement in quality of life (QOL) on a 5-point scale in relation to improvement in hand function and seven other SCI-related impairments.\ud \ud Results: In all, 565 subjects with tetraplegia returned the questionnaire (overall response of 42%). Results in the Dutch and the UK group were comparable. A total of 77% of the tetraplegics expected an important or very important improvement in QOL if their hand function improved. This is comparable to their expectations with regard to improvement in bladder and bowel function. All other items were scored lower.\ud \ud Conclusion: This is the first study in which the impact of upper extremity impairment has been assessed in a large sample of tetraplegic subjects and compared to other SCI-related impairments that have a major impact on the life of subjects with SCI. The present study indicates a high impact as well as a high priority for improvement in hand function in tetraplegics.\ud \u

Observation of anomalous decoherence effect in a quantum bath at room temperature

Decoherence of quantum objects is critical to modern quantum sciences and technologies. It is generally believed that stronger noises cause faster decoherence. Strikingly, recent theoretical research discovers the opposite case for spins in quantum baths. Here we report experimental observation of the anomalous decoherence effect for the electron spin-1 of a nitrogen-vacancy centre in high-purity diamond at room temperature. We demonstrate that under dynamical decoupling, the double-transition can have longer coherence time than the single-transition, even though the former couples to the nuclear spin bath as twice strongly as the latter does. The excellent agreement between the experimental and the theoretical results confirms the controllability of the weakly coupled nuclear spins in the bath, which is useful in quantum information processing and quantum metrology.Comment: 22 pages, related paper at http://arxiv.org/abs/1102.557

Regulation of PURA gene transcription by three promoters generating distinctly spliced 5-prime leaders: a novel means of fine control over tissue specificity and viral signals

<p>Abstract</p> <p>Background</p> <p>Purα is an evolutionarily conserved cellular protein participating in processes of DNA replication, transcription, and RNA transport; all involving binding to nucleic acids and altering conformation and physical positioning. The distinct but related roles of Purα suggest a need for expression regulated differently depending on intracellular and external signals.</p> <p>Results</p> <p>Here we report that human <it>PURA </it>(<it>hPURA</it>) transcription is regulated from three distinct and widely-separated transcription start sites (TSS). Each of these TSS is strongly homologous to a similar site in mouse chromosomal DNA. Transcripts from TSS I and II are characterized by the presence of large and overlapping 5'-UTR introns terminated at the same splice receptor site. Transfection of lung carcinoma cells with wild-type or mutated <it>hPURA </it>5' upstream sequences identifies different regulatory elements. TSS III, located within 80 bp of the translational start codon, is upregulated by E2F1, CAAT and NF-Y binding elements. Transcription at TSS II is downregulated through the presence of adjacent consensus binding elements for interferon regulatory factors (IRFs). Chromatin immunoprecipitation reveals that IRF-3 protein binds <it>hPURA </it>promoter sequences at TSS II in vivo. By co-transfecting <it>hPURA </it>reporter plasmids with expression plasmids for IRF proteins we demonstrate that several IRFs, including IRF-3, down-regulate <it>PURA </it>transcription. Infection of NIH 3T3 cells with mouse cytomegalovirus results in a rapid decrease in levels of <it>mPURA </it>mRNA and Purα protein. The viral infection alters the degree of splicing of the 5'-UTR introns of TSS II transcripts.</p> <p>Conclusions</p> <p>Results provide evidence for a novel mechanism of transcriptional control by multiple promoters used differently in various tissues and cells. Viral infection alters not only the use of <it>PURA </it>promoters but also the generation of different non-coding RNAs from 5'-UTRs of the resulting transcripts.</p

The RR Lyrae Distance Scale

We review seven methods of measuring the absolute magnitude M_V of RR Lyrae stars in light of the Hipparcos mission and other recent developments. We focus on identifying possible systematic errors and rank the methods by relative immunity to such errors. For the three most robust methods, statistical parallax, trigonometric parallax, and cluster kinematics, we find M_V (at [Fe/H] = -1.6) of 0.77 +/- 0.13, 0.71 +/- 0.15, 0.67 +/- 0.10. These methods cluster consistently around 0.71 +/- 0.07. We find that Baade-Wesselink and theoretical models both yield a broad range of possible values (0.45-0.70 and 0.45-0.65) due to systematic uncertainties in the temperature scale and input physics. Main-sequence fitting gives a much brighter M_V = 0.45 +/- 0.04 but this may be due to a difference in the metallicity scales of the cluster giants and the calibrating subdwarfs. White-dwarf cooling-sequence fitting gives 0.67 +/- 0.13 and is potentially very robust, but at present is too new to be fully tested for systematics. If the three most robust methods are combined with Walker's mean measurement for 6 LMC clusters, V_{0,LMC} = 18.98 +/- 0.03 at [Fe/H] = -1.9, then mu_{LMC} = 18.33 +/- 0.08.Comment: Invited review article to appear in: `Post-Hipparcos Cosmic Candles', A. Heck & F. Caputo (Eds), Kluwer Academic Publ., Dordrecht, in press. 21 pages including 1 table; uses Kluwer's crckapb.sty LaTeX style file, enclose

Neural Network Parameterizations of Electromagnetic Nucleon Form Factors

The electromagnetic nucleon form-factors data are studied with artificial feed forward neural networks. As a result the unbiased model-independent form-factor parametrizations are evaluated together with uncertainties. The Bayesian approach for the neural networks is adapted for chi2 error-like function and applied to the data analysis. The sequence of the feed forward neural networks with one hidden layer of units is considered. The given neural network represents a particular form-factor parametrization. The so-called evidence (the measure of how much the data favor given statistical model) is computed with the Bayesian framework and it is used to determine the best form factor parametrization.Comment: The revised version is divided into 4 sections. The discussion of the prior assumptions is added. The manuscript contains 4 new figures and 2 new tables (32 pages, 15 figures, 2 tables

Fast automated cell phenotype image classification

BACKGROUND: The genomic revolution has led to rapid growth in sequencing of genes and proteins, and attention is now turning to the function of the encoded proteins. In this respect, microscope imaging of a protein's sub-cellular localisation is proving invaluable, and recent advances in automated fluorescent microscopy allow protein localisations to be imaged in high throughput. Hence there is a need for large scale automated computational techniques to efficiently quantify, distinguish and classify sub-cellular images. While image statistics have proved highly successful in distinguishing localisation, commonly used measures suffer from being relatively slow to compute, and often require cells to be individually selected from experimental images, thus limiting both throughput and the range of potential applications. Here we introduce threshold adjacency statistics, the essence which is to threshold the image and to count the number of above threshold pixels with a given number of above threshold pixels adjacent. These novel measures are shown to distinguish and classify images of distinct sub-cellular localization with high speed and accuracy without image cropping. RESULTS: Threshold adjacency statistics are applied to classification of protein sub-cellular localization images. They are tested on two image sets (available for download), one for which fluorescently tagged proteins are endogenously expressed in 10 sub-cellular locations, and another for which proteins are transfected into 11 locations. For each image set, a support vector machine was trained and tested. Classification accuracies of 94.4% and 86.6% are obtained on the endogenous and transfected sets, respectively. Threshold adjacency statistics are found to provide comparable or higher accuracy than other commonly used statistics while being an order of magnitude faster to calculate. Further, threshold adjacency statistics in combination with Haralick measures give accuracies of 98.2% and 93.2% on the endogenous and transfected sets, respectively. CONCLUSION: Threshold adjacency statistics have the potential to greatly extend the scale and range of applications of image statistics in computational image analysis. They remove the need for cropping of individual cells from images, and are an order of magnitude faster to calculate than other commonly used statistics while providing comparable or better classification accuracy, both essential requirements for application to large-scale approaches

Prediction and Topological Models in Neuroscience

In the last two decades, philosophy of neuroscience has predominantly focused on explanation. Indeed, it has been argued that mechanistic models are the standards of explanatory success in neuroscience over, among other things, topological models. However, explanatory power is only one virtue of a scientific model. Another is its predictive power. Unfortunately, the notion of prediction has received comparatively little attention in the philosophy of neuroscience, in part because predictions seem disconnected from interventions. In contrast, we argue that topological predictions can and do guide interventions in science, both inside and outside of neuroscience. Topological models allow researchers to predict many phenomena, including diseases, treatment outcomes, aging, and cognition, among others. Moreover, we argue that these predictions also offer strategies for useful interventions. Topology-based predictions play this role regardless of whether they do or can receive a mechanistic interpretation. We conclude by making a case for philosophers to focus on prediction in neuroscience in addition to explanation alone