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Low Reproducibility (low + reproducibility)
Selected AbstractsBiotype stability of Candida albicans isolates after culture storage determined by randomly amplified polymorphic DNA and phenotypical methodsMYCOSES, Issue 6 2010Katia Leston Bacelo Summary Typing methods to evaluate isolates in relation to their phenotypical and molecular characteristics are essential in epidemiological studies. In this study, Candida albicans biotypes were determined before and after storage in order to verify their stability. Twenty C. albicans isolates were typed by Randomly Amplified Polymorphic DNA (RAPD), production of phospholipase and proteinase exoenzymes (enzymotyping) and morphotyping before and after 180 days of storage in Sabouraud dextrose agar (SDA) and sterilised distilled water. Before the storage, 19 RAPD patterns, two enzymotypes and eight morphotypes were identified. The fragment patterns obtained by RAPD, on the one hand, were not significantly altered after storage. On the other hand, the majority of the isolates changed their enzymotype and morphotype after storage. RAPD typing provided the better discriminatory index (DI) among isolates (DI = 0.995) and maintained the profile identified, thereby confirming its utility in epidemiological surveys. Based on the low reproducibility observed after storage in SDA and distilled water by morphotyping (DI = 0.853) and enzymotyping (DI = 0.521), the use of these techniques is not recommended on stored isolates. [source] Does the skull carry a phylogenetic signal?BIOLOGICAL JOURNAL OF THE LINNEAN SOCIETY, Issue 4 2008Evolution, modularity in the guenons Form and genes often tell different stories about the evolution of animals, with molecular data generally considered to be more objective than morphological data. However, form provides the basis for the description of organisms, and the study of fossils crucially depends on morphology. Complex organisms tend to evolve as ,mosaics', in which parts may be modified at varying rates and in response to different selective pressures. Thus, individual anatomical regions may contain different phylogenetic signals. In the present study, we used computerized methods to ,dissect' the skulls of a primate clade, the guenons, into functional and developmental modules (FDM). The potential of different modules as proxies for phylogenetic divergence in modern lineages was investigated. We found that the chondrocranium was the only FDM in which shape consistently had a strong and significant phylogenetic signal. This region might be less susceptible to epigenetic factors and thus more informative about phylogeny. The examination of the topology of trees from the chondrocranium suggested that the main differences evolved at the time of the radiation of terrestrial and arboreal guenons. However, phylogenetic reconstructions were found to be strongly affected by sampling error, with more localized anatomical regions (i.e. smaller/less complex FDMs) generally producing less reproducible tree topologies. This finding, if confirmed in other groups, implies that the utility of specific FDMs for phylogenetic inference could, in many cases, be hampered by the low reproducibility of results. The study also suggested that uncertainties due to sampling error may be larger than those from character sampling. This might have implications for phylogenetic analyses, which typically provide estimates of support of tree nodes based on characters but do not generally take into account the effect of sampling error on the tree topology. Nonetheless, studies of the potential of different FDMs as proxies for phylogenetic divergence in modern lineages, such as the present study, provide a framework that may help in modelling the morphological evolution of present and fossil species. © 2008 The Linnean Society of London, Biological Journal of the Linnean Society, 2008, 93, 813,834. [source] Improving the reproducibility of diagnosing micrometastases and isolated tumor cells,CANCER, Issue 2 2005Gábor Cserni M.D., Ph.D. Abstract BACKGROUND The latest edition of the tumor-lymph node-metastasis (TNM) classification of malignant tumors distinguishes between isolated tumor cells (pN0) and micrometastases (pN1mi). The reproducibility of these categories has not been assessed previously. METHODS Digital images from 50 cases with low-volume lymph node involvement from axillary sentinel lymph nodes were circulated twice for evaluation (Evaluation Rounds 1 and 2) among the members of the European Working Group for Breast Screening Pathology, and the members were asked to categorize lesions as micrometastasis, isolated tumor cells, or something else and to classify each case into a pathologic lymph node (pN) category of the pathologic TNM system. Methods for improving the low reproducibility of the categorizations were discussed between the two evaluation rounds. , Statistics were used for the assessment of interobserver variability. RESULTS The , value for the consistency of categorizing low-volume lymph node load into micrometastasis, isolated tumor cells, or neither of those changed from 0.39 to 0.49 between Evaluation Rounds 1 and 2, but it was slightly lower for the pN categories (0.35 and 0.44, respectively). Interpretation of the definitions of isolated tumor cells (especially with respect to their localization within the lymph node), lack of guidance on how to measure them if they were multiple, and lack of any definitions for multiple simultaneous foci of lymph node involvement were listed among the causes of discordant diagnoses. CONCLUSIONS The results of the current study indicated that the definitions available have minor contradictions and do not permit a reproducible distinction between micrometastases and isolated tumor cells. Refinement of these definitions, therefore, is required. One refinement that may improve reproducibility is suggested in this report. Cancer 2005. © 2004 American Cancer Society. [source] Considering Dependencies Amongst Genes Helps to Adjust the Significance Rank of DEGsCHINESE JOURNAL OF CHEMISTRY, Issue 7 2010Qi Liu Abstract Lists of differentially expressed genes (DEGs) detected often show low reproducibility even in technique replicate experiments. The reproducibility is even lower for those real cancer data with large biological variations and limited number of samples. Since existing methods for identifying differentially expressed genes treat each gene separately, they cannot circumvent the problem of low reproducibility. Considering correlation structures of genes may help to mitigate the effect of errors on individual gene estimates and thus get more reliable lists of DEGs. We borrowed information from large amount of existing microarray data to define the expression dependencies amongst genes. We use this prior knowledge of dependencies amongst genes to adjust the significance rank of DEGs. We applied our method and four popular ranking algorithms including mean fold change (FC), SAM, t-statistic and Wilcoxon rank sum-test on two cancer microarray datasets. Our method achieved higher reproducibility than other methods across a range of sample sizes. Furthermore, our method obtained higher accuracy than other methods, especially when the sample size is small. The results demonstrate that considering the dependencies amongst genes helps to adjust the significance rank of genes and find those truly differentially expressed genes. [source] | ||||||||||