853 research outputs found

    Epithelial cell shedding and barrier function: a matter of life and death at the small intestinal villus tip

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    The intestinal epithelium is a critical component of the gut barrier. Composed of a single layer of intestinal epithelial cells (IECs) held together by tight junctions, this delicate structure prevents the transfer of harmful microorganisms, antigens, and toxins from the gut lumen into the circulation. The equilibrium between the rate of apoptosis and shedding of senescent epithelial cells at the villus tip, and the generation of new cells in the crypt, is key to maintaining tissue homeostasis. However, in both localized and systemic inflammation, this balance may be disturbed as a result of pathological IEC shedding. Shedding of IECs from the epithelial monolayer may cause transient gaps or microerosions in the epithelial barrier, resulting in increased intestinal permeability. Although pathological IEC shedding has been observed in mouse models of inflammation and human intestinal conditions such as inflammatory bowel disease, understanding of the underlying mechanisms remains limited. This process may also be an important contributor to systemic and intestinal inflammatory diseases and gut barrier dysfunction in domestic animal species. This review aims to summarize current knowledge about intestinal epithelial cell shedding, its significance in gut barrier dysfunction and host-microbial interactions, and where research in this field is directed

    Appetite suppressants and valvular heart disease - a systematic review

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    Background Although appetite suppressants have been implicated in the development of valvular heart disease, the exact level of risk is still uncertain. Initial studies suggested that as many as 1 in 3 exposed patients were affected, but subsequent research has yielded substantially different figures. Our objective was to systematically assess the risk of valvular heart disease with appetite suppressants. Methods We accepted studies involving obese patients treated with any of the following appetite suppressants: fenfluramine, dexfenfluramine, and phentermine. Three types of studies were reviewed: controlled and uncontrolled observational studies, and randomized controlled trials. Outcomes of interest were echocardiographically detectable aortic regurgitation of mild or greater severity, or mitral regurgitation of moderate or greater severity. Results Of the 1279 patients evaluated in seven uncontrolled cohort studies, 236 (18%) and 60 (5%) were found to have aortic and mitral regurgitation, respectively. Pooled data from six controlled cohort studies yielded, for aortic regurgitation, a relative risk ratio of 2.32 (95% confidence intervals 1.79 to 3.01, p < 0.00001) and an attributable rate of 4.9%, and for mitral regurgitation, a relative risk ratio of 1.55 (95% confidence intervals 1.06 to 2.25, p = 0.02) with an attributable rate of 1.0%. Only one case of valvular heart disease was detected in 57 randomized controlled trials, but this was judged unrelated to drug therapy. Conclusions The risk of valvular heart disease is significantly increased by the appetite suppressants reviewed here. Nevertheless, when considering all the evidence, valvulopathy is much less common than suggested by the initial, less methodologically rigorous studies

    COLD-PCR enhanced melting curve analysis improves diagnostic accuracy for KRAS mutations in colorectal carcinoma

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    <p>Abstract</p> <p>Background</p> <p><it>KRAS </it>mutational analysis is the standard of care prior to initiation of treatments targeting the epidermal growth factor receptor (<it>EGFR</it>) in patients with metastatic colorectal cancer. Sensitive methods are required to reliably detect <it>KRAS </it>mutations in tumor samples due to admixture with non-mutated cells. Many laboratories have implemented sensitive tests for <it>KRAS </it>mutations, but the methods often require expensive instrumentation and reagents, parallel reactions, multiple steps, or opening PCR tubes.</p> <p>Methods</p> <p>We developed a highly sensitive, single-reaction, closed-tube strategy to detect all clinically significant mutations in <it>KRAS </it>codons 12 and 13 using the Roche LightCycler<sup>® </sup>instrument. The assay detects mutations via PCR-melting curve analysis with a Cy5.5-labeled sensor probe that straddles codons 12 and 13. Incorporating a fast COLD-PCR cycling program with a critical denaturation temperature (<it>T<sub>c</sub></it>) of 81°C increased the sensitivity of the assay >10-fold for the majority of <it>KRAS </it>mutations.</p> <p>Results</p> <p>We compared the COLD-PCR enhanced melting curve method to melting curve analysis without COLD-PCR and to traditional Sanger sequencing. In a cohort of 61 formalin-fixed paraffin-embedded colorectal cancer specimens, 29/61 were classified as mutant and 28/61 as wild type across all methods. Importantly, 4/61 (6%) were re-classified from wild type to mutant by the more sensitive COLD-PCR melting curve method. These 4 samples were confirmed to harbor clinically-significant <it>KRAS </it>mutations by COLD-PCR DNA sequencing. Five independent mixing studies using mutation-discordant pairs of cell lines and patient specimens demonstrated that the COLD-PCR enhanced melting curve assay could consistently detect down to 1% mutant DNA in a wild type background.</p> <p>Conclusions</p> <p>We have developed and validated an inexpensive, rapid, and highly sensitive clinical assay for <it>KRAS </it>mutations that is the first report of COLD-PCR combined with probe-based melting curve analysis. This assay significantly improved diagnostic accuracy compared to traditional PCR and direct sequencing.</p

    Rare germline variants in DNA repair genes and the angiogenesis pathway predispose prostate cancer patients to develop metastatic disease

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    Background Prostate cancer (PrCa) demonstrates a heterogeneous clinical presentation ranging from largely indolent to lethal. We sought to identify a signature of rare inherited variants that distinguishes between these two extreme phenotypes. Methods We sequenced germline whole exomes from 139 aggressive (metastatic, age of diagnosis < 60) and 141 non-aggressive (low clinical grade, age of diagnosis ≥60) PrCa cases. We conducted rare variant association analyses at gene and gene set levels using SKAT and Bayesian risk index techniques. GO term enrichment analysis was performed for genes with the highest differential burden of rare disruptive variants. Results Protein truncating variants (PTVs) in specific DNA repair genes were significantly overrepresented among patients with the aggressive phenotype, with BRCA2, ATM and NBN the most frequently mutated genes. Differential burden of rare variants was identified between metastatic and non-aggressive cases for several genes implicated in angiogenesis, conferring both deleterious and protective effects. Conclusions Inherited PTVs in several DNA repair genes distinguish aggressive from non-aggressive PrCa cases. Furthermore, inherited variants in genes with roles in angiogenesis may be potential predictors for risk of metastases. If validated in a larger dataset, these findings have potential for future clinical application

    Forward-time simulation of realistic samples for genome-wide association studies

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    <p>Abstract</p> <p>Background</p> <p>Forward-time simulations have unique advantages in power and flexibility for the simulation of genetic samples of complex human diseases because they can closely mimic the evolution of human populations carrying these diseases. However, a number of methodological and computational constraints have prevented the power of this simulation method from being fully explored in existing forward-time simulation methods.</p> <p>Results</p> <p>Using a general-purpose forward-time population genetics simulation environment, we developed a forward-time simulation method that can be used to simulate realistic samples for genome-wide association studies. We examined the properties of this simulation method by comparing simulated samples with real data and demonstrated its wide applicability using four examples, including a simulation of case-control samples with a disease caused by multiple interacting genetic and environmental factors, a simulation of trio families affected by a disease-predisposing allele that had been subjected to either slow or rapid selective sweep, and a simulation of a structured population resulting from recent population admixture.</p> <p>Conclusions</p> <p>Our algorithm simulates populations that closely resemble the complex structure of the human genome, while allows the introduction of signals of natural selection. Because of its flexibility to generate different types of samples with arbitrary disease or quantitative trait models, this simulation method can simulate realistic samples to evaluate the performance of a wide variety of statistical gene mapping methods for genome-wide association studies.</p

    Reliability of an injury scoring system for horses

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    <p>Abstract</p> <p>Background</p> <p>The risk of injuries is of major concern when keeping horses in groups and there is a need for a system to record external injuries in a standardised and simple way. The objective of this study, therefore, was to develop and validate a system for injury recording in horses and to test its reliability and feasibility under field conditions.</p> <p>Methods</p> <p>Injuries were classified into five categories according to severity. The scoring system was tested for intra- and inter-observer agreement as well as agreement with a 'golden standard' (diagnosis established by a veterinarian). The scoring was done by 43 agricultural students who classified 40 photographs presented to them twice in a random order, 10 days apart. Attribute agreement analysis was performed using Kendall's coefficient of concordance (Kendall's <it>W</it>), Kendall's correlation coefficient (Kendall's τ) and Fleiss' kappa. The system was also tested on a sample of 100 horses kept in groups where injury location was recorded as well.</p> <p>Results</p> <p>Intra-observer agreement showed Kendall's <it>W </it>ranging from 0.94 to 0.99 and 86% of observers had kappa values above 0.66 (substantial agreement). Inter-observer agreement had an overall Kendall's <it>W </it>of 0.91 and the mean kappa value was 0.59 (moderate). Agreement for all observers versus the 'golden standard' had Kendall's τ of 0.88 and the mean kappa value was 0.66 (substantial). The system was easy to use for trained persons under field conditions. Injuries of the more serious categories were not found in the field trial.</p> <p>Conclusion</p> <p>The proposed injury scoring system is easy to learn and use also for people without a veterinary education, it shows high reliability, and it is clinically useful. The injury scoring system could be a valuable tool in future clinical and epidemiological studies.</p

    The role of receptivity in the courtship behavior of Podocnemis erythrocephala in captivity

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    The courtship behavior of Podocnemis erythrocephala (Red-headed Amazon River Turtle) in captivity was studied to examine female receptivity and male response to female rejection. We observed 20 females and 39 males in 150 sessions (3–6 h/day for a total of 450 h). In 36% of the trials, there was no interaction between males and females, and 20% of the trials resulted in copulations. All males introduced into tanks approached females, and eventually there was aggression among the males. In 48% of the experiments, females also searched for or approached males. When males initially approached females, they either accepted the male’s advances (14%), rejected the male passively (38%), or rejected the male aggressively (48%). In 86% of the cases where males were rejected, 4% attempted to approach females again, and in 51% they were ultimately successful

    Ancestral Informative Marker Selection and Population Structure Visualization Using Sparse Laplacian Eigenfunctions

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    Identification of a small panel of population structure informative markers can reduce genotyping cost and is useful in various applications, such as ancestry inference in association mapping, forensics and evolutionary theory in population genetics. Traditional methods to ascertain ancestral informative markers usually require the prior knowledge of individual ancestry and have difficulty for admixed populations. Recently Principal Components Analysis (PCA) has been employed with success to select SNPs which are highly correlated with top significant principal components (PCs) without use of individual ancestral information. The approach is also applicable to admixed populations. Here we propose a novel approach based on our recent result on summarizing population structure by graph Laplacian eigenfunctions, which differs from PCA in that it is geometric and robust to outliers. Our approach also takes advantage of the priori sparseness of informative markers in the genome. Through simulation of a ring population and the real global population sample HGDP of 650K SNPs genotyped in 940 unrelated individuals, we validate the proposed algorithm at selecting most informative markers, a small fraction of which can recover the similar underlying population structure efficiently. Employing a standard Support Vector Machine (SVM) to predict individuals' continental memberships on HGDP dataset of seven continents, we demonstrate that the selected SNPs by our method are more informative but less redundant than those selected by PCA. Our algorithm is a promising tool in genome-wide association studies and population genetics, facilitating the selection of structure informative markers, efficient detection of population substructure and ancestral inference

    Bayesian Computation with Intractable Likelihoods

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    This article surveys computational methods for posterior inference with intractable likelihoods, that is where the likelihood function is unavailable in closed form, or where evaluation of the likelihood is infeasible. We review recent developments in pseudo-marginal methods, approximate Bayesian computation (ABC), the exchange algorithm, thermodynamic integration, and composite likelihood, paying particular attention to advancements in scalability for large datasets. We also mention R and MATLAB source code for implementations of these algorithms, where they are available.Comment: arXiv admin note: text overlap with arXiv:1503.0806
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