The colon as a target for vaccination: quantification of lymphoid tissue in mouse colon prior to vaccination

Currently, most vaccines are given by injection. However, due to the inherent problems associated with injections, other routes of drug delivery are being researched, among them, the oral route. So far, research into oral vaccination has not differentiated between vaccine uptake by the different parts of the gastro-intestinal tract, such as the small and large intestine. It is likely that following oral vaccine administration, the vaccine is mostly taken up by the lymphoid tissue of the small intestine

On pairwise distances and median score of three genomes under DCJ

In comparative genomics, the rearrangement distance between two genomes (equal the minimal number of genome rearrangements required to transform them into a single genome) is often used for measuring their evolutionary remoteness. Generalization of this measure to three genomes is known as the median score (while a resulting genome is called median genome). In contrast to the rearrangement distance between two genomes which can be computed in linear time, computing the median score for three genomes is NP-hard. This inspires a quest for simpler and faster approximations for the median score, the most natural of which appears to be the halved sum of pairwise distances which in fact represents a lower bound for the median score. In this work, we study relationship and interplay of pairwise distances between three genomes and their median score under the model of Double-Cut-and-Join (DCJ) rearrangements. Most remarkably we show that while a rearrangement may change the sum of pairwise distances by at most 2 (and thus change the lower bound by at most 1), even the most "powerful" rearrangements in this respect that increase the lower bound by 1 (by moving one genome farther away from each of the other two genomes), which we call strong, do not necessarily affect the median score. This observation implies that the two measures are not as well-correlated as one's intuition may suggest. We further prove that the median score attains the lower bound exactly on the triples of genomes that can be obtained from a single genome with strong rearrangements. While the sum of pairwise distances with the factor 2/3 represents an upper bound for the median score, its tightness remains unclear. Nonetheless, we show that the difference of the median score and its lower bound is not bounded by a constant.Comment: Proceedings of the 10-th Annual RECOMB Satellite Workshop on Comparative Genomics (RECOMB-CG), 2012. (to appear

A systematic review of ICD complications in randomised controlled trials versus registries: is our 'real-world' data an underestimation?

Implantable cardioverter defibrillator (ICD) implantation carries a significant risk of complications, however published estimates appear inconsistent. We aimed to present a contemporary systematic review using meta-analysis methods of ICD complications in randomised controlled trials (RCTs) and compare it to recent data from the largest international ICD registry, the US National Cardiovascular Data Registry (NCDR). PubMed was searched for any RCTs involving ICD implantation published 1999-2013; 18 were identified for analysis including 6433 patients, mean follow-up 3 months-5.6 years. Exclusion criteria were studies of children, hypertrophic cardiomyopathy, congenital heart disease, resynchronisation therapy and generator changes. Total pooled complication rate from the RCTs (excluding inappropriate shocks) was 9.1%, including displacement 3.1%, pneumothorax 1.1% and haematoma 1.2%. Infection rate was 1.5%.There were no predictors of complications but longer follow-up showed a trend to higher complication rates (p=0.07). In contrast, data from the NCDR ICD, reporting on 356 515 implants (2006-2010) showed a statistically significant threefold lower total major complication rate of 3.08% with lead displacement 1.02%, haematoma 0.86% and pneumothorax 0.44%. The overall ICD complication rate in our meta-analysis is 9.1% over 16 months. The ICD complication reported in the NCDR ICD registry is significantly lower despite a similar population. This may reflect under-reporting of complications in registries. Reporting of ICD complications in RCTs and registries is very variable and there is a need to standardise classification of complications internationally

Brain Differently Changes Its Algorithms in Parallel Processing of Visual Information

Feedback from the visual cortex (Vl) to the Lateral Geniculate Nucleus (LGN) in macaque monkey increase contrast gain of LGN neurons for black and white (B&W) and for color (C) stimuli. LGN parvocellular cells responses to B&W gratings are enhanced by feedback multiplicatively and in contrast independent manner. However, in magnocellular neurons corticofugal pathways enhance cells responses in a contrast~dependent non-linear manner. For C stimuli cortical feedback enhances parvocellular neurons responses in a very strong contrast-dependent manner. Based on these results [13] we propose a model which includes excitatory and inhibitory effects on cells activity (shunting equations) in retina and LGN while taking into account the anatomy of cortical feedback connections. The main mechanisms related to different algorithms of the data processing in the visual brain are differences in feedback properties from Vl to parvocellular (PC) and to magnocellular (MC) neurons. Descending pathways from Vl change differently receptive field (RF) structure of PC and MC cells. For B&W stimuli, in PC cells feedback changes gain similarly in the RF center and in the RF surround, leaving PC RF structure invariant. However, feedback influence MC cells in two ways: directly and through LGN interneurons, which together changes gain and sizes of their RF center differently than gain and size of the RF surround. For C stimuli PC cells operate like MC cells for B&W. The first mechanism extracts from the stimulus an important features in a independent way from other stimulus parameters, whereas the second channel changes its tuning properties as a function of other stimulus attributes like contrast and/or spatial extension. The model suggests novel idea about the possible functional role of PC and MC pathways

JA-trie: Entropy-based packet classification

Any improvement in packet classification performance is crucial to ensure Internet functions continue to track the ever-increasing link capacities. Packet classification is the foundation of many Internet functions: from fundamental packet-forwarding to advanced features such as Quality of Service en-forcement, monitoring and security functions. This work proposes a novel trie-based classification algorithm, named Jump-Ahead Trie (JA-trie), utilizing an entropy-based pre-processing phase and a novel approach to wildcard matching. Through extensive experimental tests, we demonstrate that our proposed algorithm is able to outperform a range of state-of-the-art classification algorithms.This work was jointly supported by the EPSRC INTERNET Project EP/H040536/1, by the National Science Foundation under Grant No. CNS-0855268, and by the MIUR project GreenNet (FIRB 2010).This is the accepted manuscript. The final version is available at http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=6900878

Field theories of paramagnetic Mott insulators

This is a summary of a central argument in recent review articles by the author (cond-mat/0109419, cond-mat/0211005, and cond-mat/0211027). An effective field theory is derived for the low energy spin singlet excitations in a paramagnetic Mott insulator with collinear spin correlations.Comment: 12 pages, 4 figures, Proceedings of the International Conference on Theoretical Physics, Paris, UNESCO, July 200

Quadratic Word Equations with Length Constraints, Counter Systems, and Presburger Arithmetic with Divisibility

Word equations are a crucial element in the theoretical foundation of constraint solving over strings, which have received a lot of attention in recent years. A word equation relates two words over string variables and constants. Its solution amounts to a function mapping variables to constant strings that equate the left and right hand sides of the equation. While the problem of solving word equations is decidable, the decidability of the problem of solving a word equation with a length constraint (i.e., a constraint relating the lengths of words in the word equation) has remained a long-standing open problem. In this paper, we focus on the subclass of quadratic word equations, i.e., in which each variable occurs at most twice. We first show that the length abstractions of solutions to quadratic word equations are in general not Presburger-definable. We then describe a class of counter systems with Presburger transition relations which capture the length abstraction of a quadratic word equation with regular constraints. We provide an encoding of the effect of a simple loop of the counter systems in the theory of existential Presburger Arithmetic with divisibility (PAD). Since PAD is decidable, we get a decision procedure for quadratic words equations with length constraints for which the associated counter system is \emph{flat} (i.e., all nodes belong to at most one cycle). We show a decidability result (in fact, also an NP algorithm with a PAD oracle) for a recently proposed NP-complete fragment of word equations called regular-oriented word equations, together with length constraints. Decidability holds when the constraints are additionally extended with regular constraints with a 1-weak control structure.Comment: 18 page

Information-Theoretic Active Learning for Content-Based Image Retrieval

We propose Information-Theoretic Active Learning (ITAL), a novel batch-mode active learning method for binary classification, and apply it for acquiring meaningful user feedback in the context of content-based image retrieval. Instead of combining different heuristics such as uncertainty, diversity, or density, our method is based on maximizing the mutual information between the predicted relevance of the images and the expected user feedback regarding the selected batch. We propose suitable approximations to this computationally demanding problem and also integrate an explicit model of user behavior that accounts for possible incorrect labels and unnameable instances. Furthermore, our approach does not only take the structure of the data but also the expected model output change caused by the user feedback into account. In contrast to other methods, ITAL turns out to be highly flexible and provides state-of-the-art performance across various datasets, such as MIRFLICKR and ImageNet.Comment: GCPR 2018 paper (14 pages text + 2 pages references + 6 pages appendix

Quantum Bootstrap Aggregation

We set out a strategy for quantizing attribute bootstrap aggregation to enable variance-resilient quantum machine learning. To do so, we utilise the linear decomposability of decision boundary parameters in the Rebentrost et al. Support Vector Machine to guarantee that stochastic measurement of the output quantum state will give rise to an ensemble decision without destroying the superposition over projective feature subsets induced within the chosen SVM implementation. We achieve a linear performance advantage, O(d), in addition to the existing O(log(n)) advantages of quantization as applied to Support Vector Machines. The approach extends to any form of quantum learning giving rise to linear decision boundaries

Quark propagator, instantons and gluon propagator

The Schwinger-Dyson formalism is used to check the consistency of instanton model solutions for the quark propagator with recent models of confining gluon propagators. We find that the models are not consistent. A major discrepancy is the absence of a vector condensate in the instanton model that is present in the solutions with nonperturbative confining gluons.Comment: Latex file, no figure