25 research outputs found

    Hidden Markov Model Analysis of Maternal Behavior Patterns in Inbred and Reciprocal Hybrid Mice

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    Individual variation in maternal care in mammals shows a significant heritable component, with the maternal behavior of daughters resembling that of their mothers. In laboratory mice, genetically distinct inbred strains show stable differences in maternal care during the first postnatal week. Moreover, cross fostering and reciprocal breeding studies demonstrate that differences in maternal care between inbred strains persist in the absence of genetic differences, demonstrating a non-genetic or epigenetic contribution to maternal behavior. In this study we applied a mathematical tool, called hidden Markov model (HMM), to analyze the behavior of female mice in the presence of their young. The frequency of several maternal behaviors in mice has been previously described, including nursing/grooming pups and tending to the nest. However, the ordering, clustering, and transitions between these behaviors have not been systematically described and thus a global description of maternal behavior is lacking. Here we used HMM to describe maternal behavior patterns in two genetically distinct mouse strains, C57BL/6 and BALB/c, and their genetically identical reciprocal hybrid female offspring. HMM analysis is a powerful tool to identify patterns of events that cluster in time and to determine transitions between these clusters, or hidden states. For the HMM analysis we defined seven states: arched-backed nursing, blanket nursing, licking/grooming pups, grooming, activity, eating, and sleeping. By quantifying the frequency, duration, composition, and transition probabilities of these states we were able to describe the pattern of maternal behavior in mouse and identify aspects of these patterns that are under genetic and nongenetic inheritance. Differences in these patterns observed in the experimental groups (inbred and hybrid females) were detected only after the application of HMM analysis whereas classical statistical methods and analyses were not able to highlight them

    Impact of antimicrobial drug restrictions on doctors' behaviors

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    Background/aim: Broad-spectrum antibiotics have become available for use only with the approval of infectious disease specialists (IDSs) since 2003 in Turkey. This study aimed to analyze the tendencies of doctors who are not disease specialists (non-IDSs) towards the restriction of antibiotics.Materials and methods: A questionnaire form was prepared, which included a total of 22 questions about the impact of antibiotic restriction (AR) policy, the role of IDSs in the restriction, and the perception of this change in antibiotic consumption. The questionnaire was completed by each participating physician.Results: A total of 1906 specialists from 20 cities in Turkey participated in the study. Of those who participated, 1271 (67.5%) had 5 years of occupational experience in their branch expressed that they followed the antibiotic guidelines more strictly than the JSs (P < 0.05) and 755 of physicians (88%) and 720 of surgeons (84.6%) thought that the AR policy was necessary and useful (P < 0.05).Conclusion: This study indicated that the AR policy was supported by most of the specialists. Physicians supported this restriction policy more so than surgeons did

    Visualization and Analysis of 3D Microscopic Images

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    In a wide range of biological studies, it is highly desirable to visualize and analyze three-dimensional (3D) microscopic images. In this primer, we first introduce several major methods for visualizing typical 3D images and related multi-scale, multi-time-point, multi-color data sets. Then, we discuss three key categories of image analysis tasks, namely segmentation, registration, and annotation. We demonstrate how to pipeline these visualization and analysis modules using examples of profiling the single-cell gene-expression of C. elegans and constructing a map of stereotyped neurite tracts in a fruit fly brain

    Current findings for recurring mutations in acute myeloid leukemia

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    The development of acute myeloid leukemia (AML) is a multistep process that requires at least two genetic abnormalities for the development of the disease. The identification of genetic mutations in AML has greatly advanced our understanding of leukemogenesis. Recently, the use of novel technologies, such as massively parallel DNA sequencing or high-resolution single-nucleotide polymorphism arrays, has allowed the identification of several novel recurrent gene mutations in AML. The aim of this review is to summarize the current findings for the identification of these gene mutations (Dnmt, TET2, IDH1/2, NPM1, ASXL1, etc.), most of which are frequently found in cytogenetically normal AML. The cooperative interactions of these molecular aberrations and their interactions with class I/II mutations are presented. The prognostic and predictive significances of these aberrations are also reviewed
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