About the numerical robustness of biomedical benchmark cases: Interlaboratory FDA's idealized medical device

Summary

The need for reliable approaches in numerical simulations stands out as a critical issue for the development and optimization of cardiovascular biomedical devices. This led the United States Food and Drug Administration to undertake a program of validation of computational fluid dynamics methods for transitional and turbulent flows. In the current investigation, large-eddy simulation is used to simulate the flow in the first benchmark medical device and results are confronted to the existing laboratory experiments. This idealized medical device has the particularity to feature transition to turbulence after a sudden expansion. The effects of numerical parameters and low-level inlet perturbations are investigated. Results indicate a considerable impact of numerical aspects on the prediction of the location of the transition to turbulence. The study also demonstrates that injecting small perturbations at the inflow greatly improves the streamwise velocity estimation in the transition region and substantially contributes to the robustness of the flow statistical data. This article is protected by copyright. All rights reserved.

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How many biological replicates are needed in an RNA-seq experiment and which differential expression tool should you use? [ARTICLE]

RNA-seq is now the technology of choice for genome-wide differential gene expression experiments, but it is not clear how many biological replicates are needed to ensure valid biological interpretation of the results or which statistical tools are best for analyzing the data. An RNA-seq experiment with 48 biological replicates in each of two conditions was performed to answer these questions and provide guidelines for experimental design. With three biological replicates, eight of the 11 tools evaluated found only 20%–40% of the significantly differentially expressed (SDE) genes identified with the full set of 42 clean replicates. This rises to >85% for the subset of SDE genes changing in expression by more than fourfold. To achieve >85% for all SDE genes regardless of fold change requires more than 20 biological replicates. The same eight tools successfully control their false discovery rate at 5% for all numbers of replicates, while the remaining three tools fail to control their FDR adequately, particularly for low numbers of replicates. For future RNA-seq experiments, these results suggest that more than six biological replicates should be used, rising to more than 12 when it is important to identify SDE genes for all fold changes. If less than 12 replicates are used, a superior combination of true positive and false positive performances makes edgeR the leading tool. For higher replicate numbers, minimizing false positives is more important and DESeq marginally outperforms the other tools.

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Carbon Dioxide Expanded Ethanol Extraction: Solubility and Extraction Kinetics of α-Pinene and cis-Verbenol

Analytical Chemistry

DOI: 10.1021/acs.analchem.5b04534

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Identification of Analytical Factors Affecting Complex Proteomics Profiles Acquired in a Factorial Design Study with Analysis of Variance: Simultaneous Component Analysis

Analytical Chemistry

DOI: 10.1021/acs.analchem.5b03483

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Dynamics of Molecular Orientation Observed Using Angle Resolved Photoemission Spectroscopy during Deposition of Pentacene on Graphite

Analytical Chemistry

DOI: 10.1021/acs.analchem.6b00986

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Faster Convergence of Diffusion Anisotropy Detection by Three-Step Relation of Single-Particle Trajectory

Analytical Chemistry

DOI: 10.1021/acs.analchem.6b00390

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Cardiac tamponade as a symptom of the blast crisis of chronic myeloid leukemia

Publication date: Available online 28 March 2016
Source:The Kaohsiung Journal of Medical Sciences
Author(s): Chiung-Tang Huang, Shih-Hao Yu, Yi-Hsien Chen, Sheng-Fung Lin




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