220 research outputs found

    TCF7L2 gene polymorphisms do not predict susceptibility to diabetes in tropical calcific pancreatitis but may interact with SPINK1 and CTSB mutations in predicting diabetes

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    <p>Abstract</p> <p>Background</p> <p>Tropical calcific pancreatitis (TCP) is a type of chronic pancreatitis unique to developing countries in tropical regions and one of its important features is invariable progression to diabetes, a condition called fibro-calculous pancreatic diabetes (FCPD), but the nature of diabetes in TCP is controversial. We analysed the recently reported type 2 diabetes (T2D) associated polymorphisms in the <it>TCF7L2 </it>gene using a case-control approach, under the hypothesis that <it>TCF7L2 </it>variants should show similar association if diabetes in FCPD is similar to T2D. We also investigated the interaction between the <it>TCF7L2 </it>variants and N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations, since they are strong predictors of risk for TCP.</p> <p>Methods</p> <p>Two polymorphisms rs7903146 and rs12255372 in the <it>TCF7L2 </it>gene were analyzed by direct sequencing in 478 well-characterized TCP patients and 661 healthy controls of Dravidian and Indo-European ethnicities. Their association with TCP with diabetes (FCPD) and without diabetes was tested in both populations independently using chi-square test. Finally, a meta analysis was performed on all the cases and controls for assessing the overall significance irrespective of ethnicity. We dichotomized the whole cohort based on the presence or absence of N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations and further subdivided them into TCP and FCPD patients and compared the distribution of <it>TCF7L2 </it>variants between them.</p> <p>Results</p> <p>The allelic and genotypic frequencies for both <it>TCF7L2 </it>polymorphisms, did not differ significantly between TCP patients and controls belonging to either of the ethnic groups or taken together. No statistically significant association of the SNPs was observed with TCP or FCPD or between carriers and non-carriers of N34S <it>SPINK1 </it>and L26V <it>CTSB </it>mutations. The minor allele frequency for rs7903146 was different between TCP and FCPD patients carrying the N34S <it>SPINK1 </it>variant but did not reach statistical significance (OR = 1.59, 95% CI = 0.93–2.70, P = 0.09), while, <it>TCF7L2</it><it/>variant showed a statistically significant association between TCP and FCPD patients carrying the 26V allele (OR = 1.69, 95% CI = 1.11–2.56, P = 0.013).</p> <p>Conclusion</p> <p>Type 2 diabetes associated <it>TCF7L2 </it>variants are not associated with diabetes in TCP. Since, <it>TCF7L2 </it>is a major susceptibility gene for T2D, it may be hypothesized that the diabetes in TCP patients may not be similar to T2D. Our data also suggests that co-existence of <it>TCF7L2 </it>variants and the <it>SPINK1 </it>and <it>CTSB </it>mutations, that predict susceptibility to exocrine damage, may interact to determine the onset of diabetes in TCP patients.</p

    Flexible Bayesian Modelling for Nonlinear Image Registration

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    We describe a diffeomorphic registration algorithm that allows groups of images to be accurately aligned to a common space, which we intend to incorporate into the SPM software. The idea is to perform inference in a probabilistic graphical model that accounts for variability in both shape and appearance. The resulting framework is general and entirely unsupervised. The model is evaluated at inter-subject registration of 3D human brain scans. Here, the main modeling assumption is that individual anatomies can be generated by deforming a latent 'average' brain. The method is agnostic to imaging modality and can be applied with no prior processing. We evaluate the algorithm using freely available, manually labelled datasets. In this validation we achieve state-of-the-art results, within reasonable runtimes, against previous state-of-the-art widely used, inter-subject registration algorithms. On the unprocessed dataset, the increase in overlap score is over 17%. These results demonstrate the benefits of using informative computational anatomy frameworks for nonlinear registration.Comment: Accepted for MICCAI 202

    Point Mutations in c-Myc Uncouple Neoplastic Transformation from Multiple Other Phenotypes in Rat Fibroblasts

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    Deregulation of c-Myc (Myc) occurs in many cancers. In addition to transforming various cell types, Myc also influences additional transformation-associated cellular phenotypes including proliferation, survival, genomic instability, reactive oxygen species production, and metabolism. Although Myc is wild type in most cancers (wtMyc), it occasionally acquires point mutations in certain lymphomas. Some of these mutations confer a survival advantage despite partially attenuating proliferation and transformation. Here, we have evaluated four naturally-occurring or synthetic point mutations of Myc for their ability to affect these phenotypes, as well as to promote genomic instability, to generate reactive oxygen species and to up-regulate aerobic glycolysis and oxidative phosphorylation. Our findings indicate that many of these phenotypes are genetically and functionally independent of one another and are not necessary for transformation. Specifically, the higher rate of glucose metabolism known to be associated with wtMyc deregulation was found to be independent of transformation. One mutation (Q131R) was greatly impaired for nearly all of the studied Myc phenotypes, yet was able to retain some ability to transform. These findings indicate that, while the Myc phenotypes examined here make additive contributions to transformation, none, with the possible exception of increased reliance on extracellular glutamine for survival, are necessary for achieving this state

    Radiation and breast cancer: a review of current evidence

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    This paper summarizes current knowledge on ionizing radiation-associated breast cancer in the context of established breast cancer risk factors, the radiation dose–response relationship, and modifiers of dose response, taking into account epidemiological studies and animal experiments. Available epidemiological data support a linear dose–response relationship down to doses as low as about 100 mSv. However, the magnitude of risk per unit dose depends strongly on when radiation exposure occurs: exposure before the age of 20 years carries the greatest risk. Other characteristics that may influence the magnitude of dose-specific risk include attained age (that is, age at observation for risk), age at first full-term birth, parity, and possibly a history of benign breast disease, exposure to radiation while pregnant, and genetic factors

    Metabolic Syndrome and Cardiovascular Disease after Hematopoietic Cell Transplantation: Screening and Preventive Practice Recommendations from the CIBMTR and EBMT

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    Metabolic syndrome (MetS) is a constellation of cardiovascular risk factors that increases the risk of cardiovascular disease, diabetes mellitus, and all-cause mortality. Long-term survivors of hematopoietic cell transplantation (HCT) have a substantial risk of developing MetS and cardiovascular disease, with an estimated prevalence of MetS of 31% to 49% among HCT recipients. Although MetS has not yet been proven to impact cardiovascular risk after HCT, an understanding of the incidence and risk factors for MetS in HCT recipients can provide the foundation to evaluate screening guidelines and develop interventions that may mitigate cardiovascular-related mortality. A working group was established through the Center for International Blood and Marrow Transplant Research and the European Group for Blood and Marrow Transplantation with the goal to review literature and recommend practices appropriate to HCT recipients. Here we deliver consensus recommendations to help clinicians provide screening and preventive care for MetS and cardiovascular disease among HCT recipients. All HCT survivors should be advised of the risks of MetS and encouraged to undergo recommended screening based on their predisposition and ongoing risk factors
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