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      Circulating miR-19b and miR-181b are potential biomarkers for diabetic cardiomyopathy

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          Abstract

          Diabetic cardiomyopathy is characterized by metabolic changes in the myocardium that promote a slow and silent dysfunction of muscle fibers, leading to myocardium remodelling and heart failure, independently of the presence of coronary artery diseases or hypertension. At present, no imaging methods allow an early diagnosis of this disease. Circulating miRNAs in plasma have been proposed as biomarkers in the prognosis of several cardiac diseases. This study aimed to determine whether circulating miRNAs could be potential biomarkers of diabetic cardiomyopathy. Mice that were fed with a high fat diet for 16 months, showed metabolic syndrome manifestations, cardiac hypertrophy (without hypertension) and a progressive cardiac function decline. At 16 months, when maximal degree of cardiac dysfunction was observed, 15 miRNAs from a miRNA microarray screening in myocardium were selected. Then, selected miRNAs expression in myocardium (at 4 and 16 months) and plasma (at 4, 12 and 16 months) were measured by RT-qPCR. Circulating miR-19b-3p and miR-181b-5p levels were associated with myocardium levels during the development of diabetic cardiomyopathy (in terms of cardiac dysfunction), suggesting that these miRNAs could be suitable biomarkers of this disease in asymptomatic diabetic patients.

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          Normalization of real-time quantitative reverse transcription-PCR data: a model-based variance estimation approach to identify genes suited for normalization, applied to bladder and colon cancer data sets.

          Accurate normalization is an absolute prerequisite for correct measurement of gene expression. For quantitative real-time reverse transcription-PCR (RT-PCR), the most commonly used normalization strategy involves standardization to a single constitutively expressed control gene. However, in recent years, it has become clear that no single gene is constitutively expressed in all cell types and under all experimental conditions, implying that the expression stability of the intended control gene has to be verified before each experiment. We outline a novel, innovative, and robust strategy to identify stably expressed genes among a set of candidate normalization genes. The strategy is rooted in a mathematical model of gene expression that enables estimation not only of the overall variation of the candidate normalization genes but also of the variation between sample subgroups of the sample set. Notably, the strategy provides a direct measure for the estimated expression variation, enabling the user to evaluate the systematic error introduced when using the gene. In a side-by-side comparison with a previously published strategy, our model-based approach performed in a more robust manner and showed less sensitivity toward coregulation of the candidate normalization genes. We used the model-based strategy to identify genes suited to normalize quantitative RT-PCR data from colon cancer and bladder cancer. These genes are UBC, GAPD, and TPT1 for the colon and HSPCB, TEGT, and ATP5B for the bladder. The presented strategy can be applied to evaluate the suitability of any normalization gene candidate in any kind of experimental design and should allow more reliable normalization of RT-PCR data.
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            How to calculate sample size in animal studies?

            Calculation of sample size is one of the important component of design of any research including animal studies. If a researcher select less number of animals it may lead to missing of any significant difference even if it exist in population and if more number of animals selected then it may lead to unnecessary wastage of resources and may lead to ethical issues. In this article, on the basis of review of literature done by us we suggested few methods of sample size calculations for animal studies.
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              New type of cardiomyopathy associated with diabetic glomerulosclerosis.

                Author and article information

                Contributors
                scalligaris@udd.cl
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                18 October 2017
                18 October 2017
                2017
                : 7
                : 13514
                Affiliations
                [1 ]Centro de Medicina Regenerativa, Facultad de Medicina, Clínica Alemana Universidad del Desarrollo, Av. Las Condes 12.438, Lo Barnechea, Santiago Chile
                [2 ]GRID grid.441837.d, Instituto de Ciencias Biomédicas, Facultad de Ciencias de la Salud, Universidad Autónoma de Chile, Pedro de Valdivia 425, ; Providencia, Santiago Chile
                [3 ]Departamento de Cardiología, Clínica Alemana de Santiago - Universidad del Desarrollo, Vitacura 5951, Vitacura, Santiago Chile
                Article
                13875
                10.1038/s41598-017-13875-2
                5647433
                29044172
                1cc8bd7a-cc9b-411f-a75f-4c707f5d7140
                © The Author(s) 2017

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 31 March 2017
                : 3 October 2017
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