An alternative polyadenylation signal in TCF7L2 generates isoforms that inhibit T cell factor/lymphoid-enhancer factor (TCF/LEF)-dependent target genes.

Journal ArticleResearch Support, Non-U.S. Gov't© The Author(s) 2011. This article is published with open access at Springerlink.comAIMS/HYPOTHESIS: Intronic single nucleotide polymorphisms within the transcription factor 7-like 2 (TCF7L2) gene are associated with risk of type 2 diabetes. It is widely hypothesised that the predisposing variation is involved in cis-regulation of TCF7L2 activity. The aim of this study was to seek evidence for the existence of novel TCF7L2 isoforms encoded within the type 2 diabetes-associated genomic region. METHODS: We searched expressed sequence tag (EST) databases for novel TCF7L2 transcripts and sought to validate the function and integrity of any isoforms found using a combination of RT-PCR, western blotting and reporter gene techniques. RESULTS: Analysis of EST databases suggested the presence of an alternative polyadenylation site located in intron 4 of TCF7L2. We used 3' rapid amplification of cDNA ends and real-time PCR to validate the integrity of this polyadenylation signal and show its wide use across human tissues. Western blotting results are consistent with the use of this polyadenylation signal to generate novel protein isoforms. The alternative polyadenylation signal results in the production of isoforms that retain the β-catenin binding domain but do not possess the high-mobility group box DNA-binding domain. Promoter-reporter gene assays suggest that these isoforms inhibit TCF7L2-dependent target genes by sequestering β-catenin. CONCLUSIONS/INTERPRETATION: We have identified a novel polyadenylation signal within TCF7L2 that can result in the production of isoforms that act to repress TCF/LEF-dependent target genes. These findings may provide new insights into the association of TCF7L2 with susceptibility to type 2 diabetes.Wellcome TrustMRCEuropean Community’s Seventh Framework Programm

Degenerate perturbation theory in thermoacoustics: High-order sensitivities and exceptional points

In this study, we connect concepts that have been recently developed in thermoacoustics, specifically, (i) high-order spectral perturbation theory, (ii) symmetry induced degenerate thermoacoustic modes, (iii) intrinsic thermoacoustic modes, and (iv) exceptional points. Their connection helps gain physical insight into the behaviour of the thermoacoustic spectrum when parameters of the system are varied. First, we extend high-order adjoint-based perturbation theory of thermoacoustic modes to the degenerate case. We provide explicit formulae for the calculation of the eigenvalue corrections to any order. These formulae are valid for self-adjoint, non-self-adjoint or even non-normal systems; therefore, they can be applied to a large range of problems, including fluid dynamics. Second, by analysing the expansion coefficients of the eigenvalue corrections as a function of a parameter of interest, we accurately estimate the radius of convergence of the power series. Third, we connect the existence of a finite radius of convergence to the existence of singularities in parameter space. We identify these singularities as exceptional points, which correspond to defective thermoacoustic eigenvalues, with infinite sensitivity to infinitesimal changes in the parameters. At an exceptional point, two eigenvalues and their associated eigenvectors coalesce. Close to an exceptional point, strong veering of the eigenvalue trajectories is observed. As demonstrated in recent work, exceptional points naturally arise in thermoacoustic systems due to the interaction between modes of acoustic and intrinsic origin. The role of exceptional points in thermoacoustic systems sheds new light on the physics and sensitivity of thermoacoustic stability, which can be leveraged for passive control by small design modifications

Exceptional points in the thermoacoustic spectrum

Exceptional points are found in the spectrum of a prototypical thermoacoustic system as the parameters of the flame transfer function are varied. At these points, two eigenvalues and the associated eigenfunctions coalesce. The system's sensitivity to changes in the parameters becomes infinite. Two eigenvalue branches collide at the exceptional point as the interaction index is increased. One branch originates from a purely acoustic mode, whereas the other branch originates from an intrinsic thermoacoustic mode. The existence of exceptional points in thermoacoustic systems has implications for physical understanding, computing, modeling and control

Animal welfare concepts and strategy for poultry production: a review

Well being of animals had been historically a public concern, since the beginning of human kind history. As world's population grows there is a need for food including meat. In the last decades there has been a great improvement in poultry production based on the careful control of several aspects, among which nutrition and management (environment, health and rearing systems). Nowadays, the search for good welfare conditions is a global tendency in animal production; however issues surrounding farm animal welfare or well-being, such as definitions, measurements, interpretation, and perception, continue to be controversial. It is known that the result of a broiler not adequately housed is a direct loss in production which leads towards a thought that health, welfare and productivity are intimately connected. In the other hand hints are found in the observation of behavioral responses as well as vocalization, which may provide more precise assessment to welfare. This has been possible due to the use of information technology applied to the field of ethology as well as the multidisciplinary view of the problem. This text provides a review on broiler's welfare issues since its definition to several way of trying to assess it adequately.13714

Increased expression of miR-187 in human islets from individuals with type 2 diabetes is associated with reduced glucose-stimulated insulin secretion

Journal ArticleThis article is published with open access at Springerlink.com Electronic supplementary material. The online version of this article (doi:10.1007/s00125-013-3089-4) contains peer-reviewed but unedited supplementary material, which is available to authorised usersAims/hypothesis: Type 2 diabetes is characterised by progressive beta cell dysfunction, with changes in gene expression playing a crucial role in its development. MicroRNAs (miRNAs) are post-transcriptional regulators of gene expression and therefore alterations in miRNA levels may be involved in the deterioration of beta cell function. Methods: Global TaqMan arrays and individual TaqMan assays were used to measure islet miRNA expression in discovery (n = 20) and replication (n = 20) cohorts from individuals with and without type 2 diabetes. The role of specific dysregulated miRNAs in regulating insulin secretion, content and apoptosis was subsequently investigated in primary rat islets and INS-1 cells. Identification of miRNA targets was assessed using luciferase assays and by measuring mRNA levels. Results: In the discovery and replication cohorts miR-187 expression was found to be significantly increased in islets from individuals with type 2 diabetes compared with matched controls. An inverse correlation between miR-187 levels and glucose-stimulated insulin secretion (GSIS) was observed in islets from normoglycaemic donors. This correlation paralleled findings in primary rat islets and INS-1 cells where overexpression of miR-187 markedly decreased GSIS without affecting insulin content or apoptotic index. Finally, the gene encoding homeodomain-interacting protein kinase-3 (HIPK3), a known regulator of insulin secretion, was identified as a direct target of miR-187 and displayed reduced expression in islets from individuals with type 2 diabetes. Conclusions/interpretation: Our findings suggest a role for miR-187 in the blunting of insulin secretion, potentially involving regulation of HIPK3, which occurs during the pathogenesis of type 2 diabetes. © 2013 The Author(s).This work was supported by the Wellcome Trust (project grant number 089845/Z/09/Z). GAR is the recipient of Royal Society Wolfson Research and Wellcome Trust Senior Investigator (WT098424AIA) Awards, and thanks the Medical Research Council (MRC) for Programme Grant MR/J0003042/1. GdSX and GAR were supported by a project grant from Diabetes UK (BDA 13/0004672) and HDR by MRC grant G1001644

Optimally combining dynamical decoupling and quantum error correction

We show how dynamical decoupling (DD) and quantum error correction (QEC) can be optimally combined in the setting of fault tolerant quantum computing. To this end we identify the optimal generator set of DD sequences designed to protect quantum information encoded into stabilizer subspace or subsystem codes. This generator set, comprising the stabilizers and logical operators of the code, minimizes a natural cost function associated with the length of DD sequences. We prove that with the optimal generator set the restrictive local-bath assumption used in earlier work on hybrid DD-QEC schemes, can be significantly relaxed, thus bringing hybrid DD-QEC schemes, and their potentially considerable advantages, closer to realization.Comment: 6 pages, 1 figur

Beyond Quantum Noise Spectroscopy: modelling and mitigating noise with quantum feature engineering

The ability to use quantum technology to achieve useful tasks, be they scientific or industry related, boils down to precise quantum control. In general it is difficult to assess a proposed solution due to the difficulties in characterising the quantum system or device. These arise because of the impossibility to characterise certain components in situ, and are exacerbated by noise induced by the environment and active controls. Here we present a general purpose characterisation and control solution making use of a novel deep learning framework composed of quantum features. We provide the framework, sample data sets, trained models, and their performance metrics. In addition, we demonstrate how the trained model can be used to extract conventional indicators, such as noise power spectra