The Prevalence and Factors Associated with Drug-induced Hepatitis in HIV-positive Tuberculosis Patients

Introduction: Tuberculosis (TB) have demonstrated a global increase since 1990 along with the increase of world's population and the transmission of human immunodeficiency virus (HIV). Anti- tuberculosis drugs are very effective, but it may cause drug-induced hepatitis (DIH). The aim of this study was to assess the prevalence and association of several risk factos with the occurence of drug-induced hepatitis in HIV-positive tuberculosis patients. Method: We conducted a retrospective case-control study based on medical records of HIV-positive TB patients who seek medical attention to HIV Referral Center at Cipto Mangunkusumo Hospital between July 2008 and December 2010. Overall, we enrolled 168 medical records with 42 cases and 126 controls. Chi-square and logistic regression test analysis were conducted for analyzing risk factors of drug-induced hepatitis in HIV-positive tuberculosis patients. Results: Drug-induced hepatitis were found in 42 (8.04%) patients.The prevalence of DIH was highest among 35 (25.2%) male patients, aged < 35 years old in 32 (26.0%) patients, with albumin level < 3.5 g% in 10 (11.2%) patients, body mass index (BMI) < 18.5 kg/m2 in 14 (18.4%) patients, CD4+ count < 100 cells/mm3 in 29 (24.4%) patients, and those who received rifampicin (R), isoniazid (H), and pirazinamid (Z) regiments for their anti-tuberculosis drugs 24 (31.2%) patients. No risk factors were found to have statistically significant association with DIH. Conclusion: The prevalence of DIH is quite high. Although no risk factor was found statistically significant, but evaluation and liver biochemical examination should be carried out regularly in patients with DIH risk factors

Montage: a grid portal and software toolkit for science-grade astronomical image mosaicking

Montage is a portable software toolkit for constructing custom, science-grade mosaics by composing multiple astronomical images. The mosaics constructed by Montage preserve the astrometry (position) and photometry (intensity) of the sources in the input images. The mosaic to be constructed is specified by the user in terms of a set of parameters, including dataset and wavelength to be used, location and size on the sky, coordinate system and projection, and spatial sampling rate. Many astronomical datasets are massive, and are stored in distributed archives that are, in most cases, remote with respect to the available computational resources. Montage can be run on both single- and multi-processor computers, including clusters and grids. Standard grid tools are used to run Montage in the case where the data or computers used to construct a mosaic are located remotely on the Internet. This paper describes the architecture, algorithms, and usage of Montage as both a software toolkit and as a grid portal. Timing results are provided to show how Montage performance scales with number of processors on a cluster computer. In addition, we compare the performance of two methods of running Montage in parallel on a grid.Comment: 16 pages, 11 figure

Montage: a grid-enabled engine for delivering custom science-grade mosaics on demand

This paper describes the design of a grid-enabled version of Montage, an astronomical image mosaic service, suitable for large scale processing of the sky. All the re-projection jobs can be added to a pool of tasks and performed by as many processors as are available, exploiting the parallelization inherent in the Montage architecture. We show how we can describe the Montage application in terms of an abstract workflow so that a planning tool such as Pegasus can derive an executable workflow that can be run in the Grid environment. The execution of the workflow is performed by the workflow manager DAGMan and the associated Condor-G. The grid processing will support tiling of images to a manageable size when the input images can no longer be held in memory. Montage will ultimately run operationally on the Teragrid. We describe science applications of Montage, including its application to science product generation by Spitzer Legacy Program teams and large-scale, all-sky image processing projects

Montage: a grid-enabled engine for delivering custom science-grade mosaics on demand

This paper describes the design of a grid-enabled version of Montage, an astronomical image mosaic service, suitable for large scale processing of the sky. All the re-projection jobs can be added to a pool of tasks and performed by as many processors as are available, exploiting the parallelization inherent in the Montage architecture. We show how we can describe the Montage application in terms of an abstract workflow so that a planning tool such as Pegasus can derive an executable workflow that can be run in the Grid environment. The execution of the workflow is performed by the workflow manager DAGMan and the associated Condor-G. The grid processing will support tiling of images to a manageable size when the input images can no longer be held in memory. Montage will ultimately run operationally on the Teragrid. We describe science applications of Montage, including its application to science product generation by Spitzer Legacy Program teams and large-scale, all-sky image processing projects

Optimizing Workflow Data Footprint

In this paper we examine the issue of optimizing disk usage and scheduling large-scale scientific workflows onto distributed resources where the workflows are data-intensive, requiring large amounts of data storage, and the resources have limited storage resources. Our approach is two-fold: we minimize the amount of space a workflow requires during execution by removing data files at runtime when they are no longer needed and we demonstrate that workflows may have to be restructured to reduce the overall data footprint of the workflow. We show the results of our data management and workflow restructuring solutions using a Laser Interferometer Gravitational-Wave Observatory (LIGO) application and an astronomy application, Montage, running on a large-scale production grid-the Open Science Grid. We show that although reducing the data footprint of Montage by 48% can be achieved with dynamic data cleanup techniques, LIGO Scientific Collaboration workflows require additional restructuring to achieve a 56% reduction in data space usage. We also examine the cost of the workflow restructuring in terms of the application's runtime

Type 1 interferon-inducible gene expression in QuantiFERON Gold TB-positive uveitis: A tool to stratify a high versus low risk of active tuberculosis?

QuantiFERON-Gold TB (QFT)-positive patients with undetermined cause of uveitis are problematic in terms of whether to diagnose and treat them for tuberculosis (TB). Here, we investigated whether peripheral blood expression of type 1 interferon (IFN)-inducible genes may be of use to stratify QFT-positive patients with uveitis into groups of high versus low risk of having active TB-associated uveitis. We recruited all new uveitis patients in Cipto Mangunkusumo Hospital, Jakarta, Indonesia for one year. We included 12 patients with uveitis and clinically diagnosed active pulmonary TB, 58 QFT-positive patients with uveitis of unknown cause, 10 newly diagnosed sputum-positive active pulmonary TB patients without uveitis and 23 QFT-negative healthy controls. Expression of 35 type 1 IFN-inducible genes was measured in peripheral blood cells from active pulmonary TB patients without uveitis and healthy controls. Differentially expressed genes were identified and used for further clustering analyses of the uveitis groups. A type-1 IFN gene signature score was calculated and the optimal cut-off value for this score to differentiate active pulmonary TB from healthy controls was determined and applied to QFT-positive patients with uveitis of unknown cause. Ten type 1 IFN-inducible genes were differentially expressed between active pulmonary TB and healthy controls. Expression of these 10 genes in QFT-positive patients with uveitis of unknown cause revealed three groups: 1); patients resembling active pulmonary TB, 2); patients resembling healthy controls, and 3); patients displaying an in-between gene expression pattern. A type 1 IFN gene signature score ≥5.61 displayed high sensitivity (100%) and specificity (91%) for identification of active TB. Application of this score to QFT-positive patients with uveitis of unknown cause yielded two groups with expected different likelihood (high vs. low) of having active-TB uveitis, and therefore may be useful in clinical management decisions

Random sampling techniques for space efficient online computation of order statistics of large datasets

In a recent paper [MRL98], we had described a general framework for single pass approximate quantile nding algorithms. This framework included several known algorithms as special cases. We had identi ed a new algorithm, within the framework, which had a signi cantly smaller requirement for main memory than other known algorithms. In this paper, we address two issues left open in our earlier paper. First, all known and space e cient algorithms for approximate quantile nding require advance knowledge of the length of the input sequence. Many important database applications employing quantiles cannot provide this information. In this paper, we present anovel non-uniform random sampling scheme and an extension of our framework. Together, they form the basis of a new algorithm which computes approximate quantiles without knowing the input sequence length. Second, if the desired quantile is an extreme value (e.g., within the top 1 % of the elements), the space requirements of currently known algorithms are overly pessimistic. We provide a simple algorithm which estimates extreme values using less space than required by the earlier more general technique for computing all quantiles. Our principal observation here is that random sampling is quanti ably better when estimating extreme values than is the case with the median