Evaluating robustness of a generalized linear model when applied to electronic health record data accessed using an Open API.

The Integrated Clinical and Environmental Exposures Service (ICEES) provides open regulatory-compliant access to clinical data, including electronic health record data, that have been integrated with environmental exposures data. While ICEES has been validated in the context of an asthma use case and several other use cases, the regulatory constraints on the ICEES open application programming interface (OpenAPI) result in data loss when using the service for multivariate analysis. In this study, we investigated the robustness of the ICEES OpenAPI through a comparative analysis, in which we applied a generalized linear model (GLM) to the OpenAPI data and the constraint-free source data to examine factors predictive of asthma exacerbations.

Open Application of Statistical and Machine Learning Models to Explore the Impact of Environmental Exposures on Health and Disease: An Asthma Use Case.

ICEES (Integrated Clinical and Environmental Exposures Service) provides a disease-agnostic, regulatory-compliant approach for openly exposing and analyzing clinical data that have been integrated at the patient level with environmental exposures data. ICEES is equipped with basic features to support exploratory analysis using statistical approaches, such as bivariate chi-square tests. We recently developed a method for using ICEES to generate multivariate tables for subsequent application of machine learning and statistical models.

An approach for open multivariate analysis of integrated clinical and environmental exposures data.

The Integrated Clinical and Environmental Exposures Service (ICEES) provides regulatory-compliant open access to sensitive patient data that have been integrated with public exposures data. ICEES was designed initially to support dynamic cohort creation and bivariate contingency tests. The objective of the present study was to develop an open approach to support multivariate analyses using existing ICEES functionalities and abiding by all regulatory constraints.

R/DWD: distance-weighted discrimination for classification, visualization and batch adjustment.

Unlabelled: R/DWD is an extensible package for classification. It is built based on a recently developed powerful classification method called distance weighted discrimination (DWD). DWD is related to, and has been shown to be superior to, the support vector machine in situations that are fundamental to bioinformatics, such as very high dimensional data.

Flow-based combinatorial antibody profiling: an integrated approach to cell characterization.

BD FACS™ CAP (CAP = combinatorial antibody profile) is a screening tool for rapid characterization of human cell surface protein expression profiles using semi-automated high-throughput flow cytometry. The current configuration consists of 229 directly conjugated antibodies arrayed in a 96-well plate as three-color cocktails, which enables the characterization of each of the 229 individual surface markers. Each individual cell type of interest is analyzed on the 96-well screening plates and the data are acquired on a flow cytometer equipped with a high-throughput sampler.

Analysis of High-Throughput Flow Cytometry Data Using plateCore.

Flow cytometry (FCM) software packages from R/Bioconductor, such as flowCore and flowViz, serve as an open platform for development of new analysis tools and methods. We created plateCore, a new package that extends the functionality in these core packages to enable automated negative control-based gating and make the processing and analysis of plate-based data sets from high-throughput FCM screening experiments easier. plateCore was used to analyze data from a BD FACS CAP screening experiment where five Peripheral Blood Mononucleocyte Cell (PBMC) samples were assayed for 189 different human cell surface markers.

flowCore: a Bioconductor package for high throughput flow cytometry.

Background: Recent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates.

Results: We developed a set of flexible open source computational tools in the R package flowCore to facilitate the analysis of these complex data.

Functional T cell responses to tumor antigens in breast cancer patients have a distinct phenotype and cytokine signature.

The overall prevalence with which endogenous tumor Ags induce host T cell responses is unclear. Even when such responses are detected, they do not usually result in spontaneous remission of the cancer. We hypothesized that this might be associated with a predominant phenotype and/or cytokine profile of tumor-specific responses that is different from protective T cell responses to other chronic Ags, such as CMV.

The use of the BD oxygen biosensor system to assess isolated human islets of langerhans: oxygen consumption as a potential measure of islet potency.

The measurement of cellular oxygen consumption rate (OCR) is a potential tool for the assessment of metabolic potency of isolated islets of Langerhans prior to clinical transplantation. We used a commercially available 96-well plate fluoroprobe, the BD Oxygen Biosensor System (OBS), to estimate OCR in 27 human islet preparations, and compared these results to those of concurrent mouse transplantations. OCR was estimated both from the dO2 at steady state and from the transient rate of change of dO2 during the initial culture period immediately after seeding ("dO2 slope").

Data standards for flow cytometry.

Flow cytometry (FCM) is an analytical tool widely used for cancer and HIV/AIDS research, and treatment, stem cell manipulation and detecting microorganisms in environmental samples. Current data standards do not capture the full scope of FCM experiments and there is a demand for software tools that can assist in the exploration and analysis of large FCM datasets. We are implementing a standardized approach to capturing, analyzing, and disseminating FCM data that will facilitate both more complex analyses and analysis of datasets that could not previously be efficiently studied.

IL-2 production correlates with effector cell differentiation in HIV-specific CD8+ T cells.

Background: Diminished IL-2 production and lack of effector differentiation have been reported for HIV-specific T cells. In this study, we examined the prevalence of these phenomena using 8-color cytokine flow cytometry, and tested the hypothesis that these two findings were causally related. We analyzed cytokine profiles and memory/effector phenotypes of HIV-specific and CMV-specific T cells using short-term in vitro stimulation with HIV or CMV peptide pools.

Identification of compounds that enhance the anti-lymphoma activity of rituximab using flow cytometric high-content screening.

In this report, we describe a new flow cytometry technique termed flow cytometric high-content screening (FC-HCS) which involves semi-automated processing and analysis of multiparameter flow cytometry samples. As a first test of the FC-HCS technique, we used it to screen a 2000-compound library, called the National Cancer Institute (NCI) Diversity Set, to identify agents that would enhance the anti-lymphoma activity of the therapeutic monoclonal antibody rituximab. FC-HCS identified 15 compounds from the Diversity Set that significantly enhanced the ability of rituximab to inhibit cell cycle progression and induce apoptosis in lymphoma cells.

Modeling individual variation in biomarker response to combination immunosuppression with stimulated lymphocyte responses-potential clinical implications.

Background: In mitogen-stimulated lymphocyte responses (sLR), cytokines and cell-surface receptors in peripheral human blood lymphocytes (PBL) are sensitive to cyclosporine (CsA), and can predict its in vivo effect with pharmacodynamic (PD) modeling. This is not known for multiple-agent combinations.

Methods: Twenty-five concentration mixtures of CsA (0-1200 ng/ml) plus sirolimus (SRL, 0-30 ng/ml) were added to whole blood from five normal human subjects (NHS) for effect on a limited array of six targets.