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A fundamental tenet of scientific research is that published results are open to independent validation and refutation. Minimum data standards aid data providers, users, and publishers by providing a specification of what is required to unambiguously interpret experimental findings. Here, we present the Minimum Information about a Flow Cytometry Experiment (MIFlowCyt) standard, stating the minimum information required to report flow cytometry (FCM) experiments. We brought together a crossdisciplinary international collaborative group of bioinformaticians, computational statisticians, software developers, instrument manufacturers, and clinical and basic research scientists to develop the standard. The standard was subsequently vetted by the International Society for Advancement of Cytometry (ISAC) Data Standards Task Force, Standards Committee, membership, and Council. The MIFlowCyt standard includes recommendations about descriptions of the specimens and reagents included in the FCM experiment, the configuration of the instrument used to perform the assays, and the data processing approaches used to interpret the primary output data. MIFlowCyt has been adopted as a standard by ISAC, representing the FCM scientific community including scientists as well as software and hardware manufacturers. Adoption of MIFlowCyt by the scientific and publishing communities will facilitate third-party understanding and reuse of FCM data. ' 2008 International Society for Advancement of Cytometry Key termsimmunology; fluorescence-activated cell sorting; knowledge representation FLOW cytometry (FCM) systems have been available to investigators for over 30 years, and the field continues to advance at a rapid rate. FCM has been responsible for major progress in basic and clinical research by enabling the phenotypic and functional characterization of individual cells in a high-throughput manner. Advances in the technology now allow for automated, multiparametric analyses of thousands of samples per day (1). Each data set can consist of multidimensional descriptions of millions of individual cells, producing data similar in size and complexity to gene expression microarrays. Like the microarray field, the ability to collect FCM data is outpacing the computational means for data handling and analysis. Furthermore, the lack of reporting standardization limits collaboration, independent validation/refutation, and meta-analysis, and thus minimizes the value of the wealth

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Background: In immunofluorescence measurements and most other flow cytometry applications, fluorescence signals of interest can range down to essentially zero. After fluorescence compensation, some cell populations will have low means and include events with negative data values. Logarithmic presentation has been very useful in providing informative displays of wide-ranging flow cytometry data, but it fails to adequately display cell populations with low means and high variances and, in particular, offers no way to include negative data values. This has led to a great deal of difficulty in interpreting and understanding flow cytometry data, has often resulted in incorrect delineation of cell populations, and has led many people to question the correctness of compensation computations that were, in fact, correct. Results: We identified a set of criteria for creating data visualization methods that accommodate the scaling difficulties presented by flow cytometry data. On the basis of these, we developed a new data visualization method that provides important advantages over linear or logarithmic scaling for display of flow cytometry data, a scaling we refer to as ''Logicle'' scaling. Logicle functions represent a particular generalization of the hyperbolic sine function with one more adjustable parameter than linear or logarithmic functions. Finally, we developed methods for objectively and automatically selecting an appropriate value for this parameter. Conclusions: The Logicle display method provides more complete, appropriate, and readily interpretable representations of data that includes populations with low-to-zero means, including distributions resulting from fluorescence compensation procedures, than can be produced using either logarithmic or linear displays. The method includes a specific algorithm for evaluating actual data distributions and deriving parameters of the Logicle scaling function appropriate for optimal display of that data. It is critical to note that Logicle visualization does not change the data values or the descriptive statistics computed from them.

NAC treatment for 8 weeks safely replenishes whole blood GSH and T cell GSH in HIV-infected individuals. Thus, NAC offers useful adjunct therapy to increase protection against oxidative stress, improve immune system function and increase detoxification of acetaminophen and other drugs. These findings suggest that NAC therapy could be valuable in other clinical situations in which GSH deficiency or oxidative stress plays a role in disease pathology, e.g. rheumatoid arthritis, Parkinson's disease, hepatitis, liver cirrhosis, septic shock and diabetes.