Positive predictive value of automated database records for diabetic ketoacidosis (DKA) in children and youth exposed to antipsychotic drugs or control medications: a tennessee medicaid study

<p>Abstract</p> <p>Background</p> <p>Diabetic ketoacidosis (DKA) is a potentially life-threatening complication of treatment with some atypical antipsychotic drugs in children and <b>youth</b>. Because drug-associated DKA is rare, large automated health outcomes databases may be a valuable data source for conducting pharmacoepidemiologic studies of DKA associated with exposure to individual antipsychotic drugs. However, no validated computer case definition of DKA exists. We sought to assess the positive predictive value (PPV) of a computer case definition to detect incident cases of DKA, using automated records of Tennessee Medicaid as the data source and medical record confirmation as a "gold standard."</p> <p>Methods</p> <p>The computer case definition of DKA was developed from a retrospective cohort study of antipsychotic-related type 2 diabetes mellitus (1996-2007) in Tennessee Medicaid enrollees, aged 6-24 years. Thirty potential cases with any DKA diagnosis (ICD-9 250.1, ICD-10 E1x.1) were identified from inpatient encounter claims. Medical records were reviewed to determine if they met the clinical definition of DKA.</p> <p>Results</p> <p>Of 30 potential cases, 27 (90%) were successfully abstracted and adjudicated. Of these, 24 cases were confirmed by medical record review (PPV 88.9%, 95% CI 71.9 to 96.1%). Three non-confirmed cases presented acutely with severe hyperglycemia, but had no evidence of acidosis.</p> <p>Conclusions</p> <p>Diabetic ketoacidosis in children and youth can be identified in a computerized Medicaid database using our case definition, which could be useful for automated database studies in which drug-associated DKA is the outcome of interest.</p

Glucagon-Like Peptide-1 Protects Human Islets against Cytokine-Mediated β-Cell Dysfunction and Death: A Proteomic Study of the Pathways Involved

Glucagon-like peptide-1 (GLP-1) has been shown to protect pancreatic β-cells against cytokine-induced dysfunction and destruction. The mechanisms through which GLP-1 exerts its effects are complex and still poorly understood. The aim of this study was to analyze the protein expression profiles of human islets of Langerhans treated with cytokines (IL-1β and IFN-γ) in the presence or absence of GLP-1 by 2D difference gel electrophoresis and subsequent protein interaction network analysis to understand the molecular pathways involved in GLP-1-mediated β-cell protection. Co-incubation of cytokine-treated human islets with GLP-1 resulted in a marked protection of β-cells against cytokine-induced apoptosis and significantly attenuated cytokine-mediated inhibition of glucose-stimulated insulin secretion. The cytoprotective effects of GLP-1 coincided with substantial alterations in the protein expression profile of cytokine-treated human islets, illustrating a counteracting effect on proteins from different functional classes such as actin cytoskeleton, chaperones, metabolic proteins, and islet regenerating proteins. In summary, GLP-1 alters in an integrated manner protein networks in cytokine-exposed human islets while protecting them against cytokine-mediated cell death and dysfunction. These data illustrate the beneficial effects of GLP-1 on human islets under immune attack, leading to a better understanding of the underlying mechanisms involved, a prerequisite for improving therapies for diabetic patients.status: publishe

MicroScope: ChIP-seq and RNA-seq software analysis suite for gene expression heatmaps

BACKGROUND: Heatmaps are an indispensible visualization tool for examining large-scale snapshots of genomic activity across various types of next-generation sequencing datasets. However, traditional heatmap software do not typically offer multi-scale insight across multiple layers of genomic analysis (e.g., differential expression analysis, principal component analysis, gene ontology analysis, and network analysis) or multiple types of next-generation sequencing datasets (e.g., ChIP-seq and RNA-seq). As such, it is natural to want to interact with a heatmap’s contents using an extensive set of integrated analysis tools applicable to a broad array of genomic data types. RESULTS: We propose a user-friendly ChIP-seq and RNA-seq software suite for the interactive visualization and analysis of genomic data, including integrated features to support differential expression analysis, interactive heatmap production, principal component analysis, gene ontology analysis, and dynamic network analysis. CONCLUSIONS: MicroScope is hosted online as an R Shiny web application based on the D3 JavaScript library: http://microscopebioinformatics.org/. The methods are implemented in R, and are available as part of the MicroScope project at: https://github.com/Bohdan-Khomtchouk/Microscope

Met-Independent Hepatocyte Growth Factor-mediated regulation of cell adhesion in human prostate cancer cells

BACKGROUND: Prostate cancer cells communicate reciprocally with the stromal cells surrounding them, inside the prostate, and after metastasis, within the bone. Each tissue secretes factors for interpretation by the other. One stromally-derived factor, Hepatocyte Growth Factor (HGF), was found twenty years ago to regulate invasion and growth of carcinoma cells. Working with the LNCaP prostate cancer progression model, we found that these cells could respond to HGF stimulation, even in the absence of Met, the only known HGF receptor. The new HGF binding partner we find on the cell surface may help to clarify conflicts in the past literature about Met expression and HGF response in cancer cells. METHODS: We searched for Met or any HGF binding partner on the cells of the PC3 and LNCaP prostate cancer cell models, using HGF immobilized on agarose beads. By using mass spectrometry analyses and sequencing we have identified nucleolin protein as a novel HGF binding partner. Antibodies against nucleolin (or HGF) were able to ameliorate the stimulatory effects of HGF on met-negative prostate cancer cells. Western blots, RT-PCR, and immunohistochemistry were used to assess nucleolin levels during prostate cancer progression in both LNCaP and PC3 models. RESULTS: We have identified HGF as a major signaling component of prostate stromal-conditioned media (SCM) and have implicated the protein nucleolin in HGF signal reception by the LNCaP model prostate cancer cells. Antibodies that silence either HGF (in SCM) or nucleolin (on the cell surfaces) eliminate the adhesion-stimulatory effects of the SCM. Likewise, addition of purified HGF to control media mimics the action of SCM. C4-2, an LNCaP lineage-derived, androgen-independent human prostate cancer cell line, responds to HGF in a concentration-dependent manner by increasing its adhesion and reducing its migration on laminin substratum. These HGF effects are not due to shifts in the expression levels of laminin-binding integrins, nor can they be linked to expression of the known HGF receptor Met, as neither LNCaP nor clonally-derived C4-2 sub-line contain any detectable Met protein. Even in the absence of Met, small GTPases are activated, linking HGF stimulation to membrane protrusion and integrin activation. Membrane-localized nucelolin levels increase during cancer progression, as modeled by both the PC3 and LNCaP prostate cancer progression cell lines. CONCLUSION: We propose that cell surface localized nucleolin protein may function in these cells as a novel HGF receptor. Membrane localized nucleolin binds heparin-bound growth factors (including HGF) and appears upregulated during prostate cancer progression. Antibodies against nucleolin are able to ameliorate the stimulatory effects of HGF on met-negative prostate cancer cells. HGF-nucleolin interactions could be partially responsible for the complexity of HGF responses and met expression reported in the literature

Consensus guidelines for the use and interpretation of angiogenesis assays

The formation of new blood vessels, or angiogenesis, is a complex process that plays important roles in growth and development, tissue and organ regeneration, as well as numerous pathological conditions. Angiogenesis undergoes multiple discrete steps that can be individually evaluated and quantified by a large number of bioassays. These independent assessments hold advantages but also have limitations. This article describes in vivo, ex vivo, and in vitro bioassays that are available for the evaluation of angiogenesis and highlights critical aspects that are relevant for their execution and proper interpretation. As such, this collaborative work is the first edition of consensus guidelines on angiogenesis bioassays to serve for current and future reference