Algorithmic skeleton framework for the orchestration of GPU computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A system’s approach to cache hierarchy-aware decomposition of data-parallel computations

Dissertação para obtenção do Grau de Mestre em Engenharia Informática

A questionnaire to evaluate the impact of chronic diseases: validated translation and Illness Effects Questionnaire (IEQ) reliability study

INTRODUCTION: Patients' perception about their health condition, mainly involving chronic diseases, has been investigated in many studies and it has been associated to depression, compliance with the treatment, quality of life and prognosis. The Illness Effects Questionnaire (IEQ) is a tool which makes the standardized evaluation of patients' perception about their illness possible, so that it is brief and accessible to the different clinical settings. This work aims to begin the transcultural adaptation of the IEQ to Brazil through the validated translation and the reliability study. METHODS: The back-translation method and the test-retest reliability study were used in a sample of 30 adult patients under chronic hemodialysis. The reliability indexes were estimated using the Pearson, Spearman, Weighted Kappa and Cronbach's alpha coefficients. RESULTS: The semantic equivalence was reached through the validated translation. In this study, the reliability indexes obtained were respectively: 0.85 and 0.75 (p < 0.001); 0.68 and 0.92 (p < 0.0001). DISCUSSION: The reliability indexes obtained attest to the stability of responses in both evaluations. Additional procedures are necessary for the transcultural adaptation of the IEQ to be complete. CONCLUSION: The results indicate the translation validity and the reliability of the Brazilian version of the IEQ for the sample studied.

Cytochemical characterization of gill and hepatopancreatic cells of the crab Ucides cordatus (Crustacea, Brachyura) validated by cell metal transport

Ucides cordatus (Linnaeus, 1763) is a hypo-hyper-regulating mangrove crab possessing gills for respiratory and osmoregulatory processes, separated in anterior and posterior sections. They also have hepatopancreas, which is responsible for digestion and absorption of nutrients and detoxification of toxic metals. Each of these organs has specific cells that are important for in vitro studies in cell biology, ion and toxic metals transport. In order to study and characterize cells from gills and hepatopancreas, both were separated using a Sucrose Gradient (SG) from 10 to 40% and cells in each gradient were characterized using the vital mitochondrial dye DASPEI (2-(4-dimethylaminostyryl)-N- ethylpyridinium iodide) and Trichrome Mallory's stain. Both in 20 and 40% SG for gill cells and 30% SG for hepatopancreatic cells, a greater number of cells were colored with DASPEI, indicating a larger number of mitochondria in these cells. It is concluded that the gill cells present in 20% and 40% SG are Thin cells, responsible for respiratory processes and Ionocytes responsible for ion transport, respectively. For hepatopancreatic cells, the 30% SG is composed of Fibrillar cells that possess larger number of membrane ion and nutrient transporters. Moreover, the transport of toxic metal cadmium (Cd) by isolated hepatopancreatic cells was performed as a way of following cell physiological integrity after cell separation and to study differences in transport among the cells. All hepatopancreatic cells were able to transport Cd. These findings are the first step for further work on isolated cells of these important exchange epithelia of crabs, using a simple separation method and to further develop successful in vitro cell culture in crabs.

User-friendly parallel computations with econometric examples

This paper shows how a high level matrix programming language may be used to perform Monte Carlo simulation, bootstrapping, estimation by maximum likelihood and GMM, and kernel regression in parallel on symmetric multiprocessor computers or clusters of workstations. The implementation of parallelization is done in a way such that an investigator may use the programs without any knowledge of parallel programming. A bootable CD that allows rapid creation of a cluster for parallel computing is introduced. Examples show that parallelization can lead to important reductions in computational time. Detailed discussion of how the Monte Carlo problem was parallelized is included as an example for learning to write parallel programs for Octave.

Inverse problems for invariant algebraic curves: explicit computations

Given an algebraic curve in the complex affine plane, we describe how to determine all planar polynomial vector fields which leave this curve invariant. If all (finite) singular points of the curve are nondegenerate, we give an explicit expression for these vector fields. In the general setting we provide an algorithmic approach, and as an alternative we discuss sigma processes.

A validated clinical approach for the management of aspergillosis in critically ill patients: ready, steady, go!

The clinical relevance of recovering Aspergillus species in intensive care unit patients is unknown. Diagnosis of invasive pulmonary aspergillosis is extremely difficult because there are no specific tests sensitive enough to detect it. The rapidly fatal prognosis of this infection without treatment justifies early antifungal therapy. A clinical algorithm may aid clinicians to manage critically ill patients from whose respiratory specimens Aspergillus spp. have been isolated. This new tool needs to be validated in a large cohort of patients before it can be recommended.

Validated SNPs for eGFR and their associations with albuminuria.

Albuminuria and reduced glomerular filtration rate are manifestations of chronic kidney disease (CKD) that predict end-stage renal disease, acute kidney injury, cardiovascular disease and death. We hypothesized that SNPs identified in association with the estimated glomerular filtration rate (eGFR) would also be associated with albuminuria. Within the CKDGen Consortium cohort (n= 31 580, European ancestry), we tested 16 eGFR-associated SNPs for association with the urinary albumin-to-creatinine ratio (UACR) and albuminuria [UACR >25 mg/g (women); 17 mg/g (men)]. In parallel, within the CARe Renal Consortium (n= 5569, African ancestry), we tested seven eGFR-associated SNPs for association with the UACR. We used a Bonferroni-corrected P-value of 0.003 (0.05/16) in CKDGen and 0.007 (0.05/7) in CARe. We also assessed whether the 16 eGFR SNPs were associated with the UACR in aggregate using a beta-weighted genotype score. In the CKDGen Consortium, the minor A allele of rs17319721 in the SHROOM3 gene, known to be associated with a lower eGFR, was associated with lower ln(UACR) levels (beta = -0.034, P-value = 0.0002). No additional eGFR-associated SNPs met the Bonferroni-corrected P-value threshold of 0.003 for either UACR or albuminuria. In the CARe Renal Consortium, there were no associations between SNPs and UACR with a P< 0.007. Although we found the genotype score to be associated with albuminuria (P= 0.0006), this result was driven almost entirely by the known SHROOM3 variant, rs17319721. Removal of rs17319721 resulted in a P-value 0.03, indicating a weak residual aggregate signal. No alleles, previously demonstrated to be associated with a lower eGFR, were associated with the UACR or albuminuria, suggesting that there may be distinct genetic components for these traits.

A combined molecular clinical predictor of survival validated with the rtog-0525 cohort

For glioblastoma (GBM), survival classification has primarily relied on clinical criteria, exemplified by the Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA). We sought to improve tumor classification by combining tumor biomarkers with the clinical RPA data. To accomplish this, we first developed 4 molecular biomarkers derived from gene expression profiling, a glioma CpG island methylator phenotype, a novel MGMT promoter methylation assay, and IDH1 mutations. A molecular predictor (MP) model was created with these 4 biomarkers on a training set of 220 retrospectively collected archival GBMtumors. ThisMPwas further combined with RPA classification to develop a molecular-clinical predictor (MCP). The median survivals for the combined, 4-class MCP were 65 months, 31 months, 13 months, and 9 months, which was significantly improved when compared with the RPA alone. The MCP was then applied to 725 samples from the RTOG-0525 cohort, showing median survival for each risk group of NR, 26 months, 16 months, and 11 months. The MCP was significantly improved over the RPA at outcome prediction in the RTOG 0525 cohort with a 33%increase in explained variation with respect to survival, validating the result obtained in the training set. To illustrate the benefit of the MCP for patient stratification, we examined progression-free survival (PFS) for patients receiving standard-dose temozolomide (SD-TMZ) vs. dose-dense TMZ (DD-TMZ) in RPA and MCP risk groups. A significant difference between DD-TMZ and SD-TMZ was observed in the poorest surviving MCP risk group with a median PFS of 6 months vs. 3 months (p ¼ 0.048, log-rank test). This difference was not seen using the RPA classification alone. In summary, we have developed a combined molecular-clinical predictor that appears to improve outcome prediction when compared with clinical variables alone. This MCP may serve to better identify patients requiring intensive treatments beyond the standard of care.

New validated prognostic models and prognostic calculators in patients with low-grade gliomas diagnosed by central pathology review: a pooled analysis of EORTC/RTOG/NCCTG phase III clinical trials.

Background In a previous study, the European Organisation for Research and Treatment of Cancer (EORTC) reported a scoring system to predict survival of patients with low-grade gliomas (LGGs). A major issue in the diagnosis of brain tumors is the lack of agreement among pathologists. New models in patients with LGGs diagnosed by central pathology review are needed. Methods Data from 339 EORTC patients with LGGs diagnosed by central pathology review were used to develop new prognostic models for progression-free survival (PFS) and overall survival (OS). Data from 450 patients with centrally diagnosed LGGs recruited into 2 large studies conducted by North American cooperative groups were used to validate the models. Results Both PFS and OS were negatively influenced by the presence of baseline neurological deficits, a shorter time since first symptoms (<30 wk), an astrocytic tumor type, and tumors larger than 5 cm in diameter. Early irradiation improved PFS but not OS. Three risk groups have been identified (low, intermediate, and high) and validated. Conclusions We have developed new prognostic models in a more homogeneous LGG population diagnosed by central pathology review. This population better fits with modern practice, where patients are enrolled in clinical trials based on central or panel pathology review. We could validate the models in a large, external, and independent dataset. The models can divide LGG patients into 3 risk groups and provide reliable individual survival predictions. Inclusion of other clinical and molecular factors might still improve models' predictions.

A validated assay for measuring doxorubicin in biological fluids and tissues in an isolated lung perfusion model: matrix effect and heparin interference strongly influence doxorubicin measurements.

Doxorubicin is an antineoplasic agent active against sarcoma pulmonary metastasis, but its clinical use is hampered by its myelotoxicity and its cumulative cardiotoxicity, when administered systemically. This limitation may be circumvented using the isolated lung perfusion (ILP) approach, wherein a therapeutic agent is infused locoregionally after vascular isolation of the lung. The influence of the mode of infusion (anterograde (AG): through the pulmonary artery (PA); retrograde (RG): through the pulmonary vein (PV)) on doxorubicin pharmacokinetics and lung distribution was unknown. Therefore, a simple, rapid and sensitive high-performance liquid chromatography method has been developed to quantify doxorubicin in four different biological matrices (infusion effluent, serum, tissues with low or high levels of doxorubicin). The related compound daunorubicin was used as internal standard (I.S.). Following a single-step protein precipitation of 500 microl samples with 250 microl acetone and 50 microl zinc sulfate 70% aqueous solution, the obtained supernatant was evaporated to dryness at 60 degrees C for exactly 45 min under a stream of nitrogen and the solid residue was solubilized in 200 microl of purified water. A 100 microl-volume was subjected to HPLC analysis onto a Nucleosil 100-5 microm C18 AB column equipped with a guard column (Nucleosil 100-5 microm C(6)H(5) (phenyl) end-capped) using a gradient elution of acetonitrile and 1-heptanesulfonic acid 0.2% pH 4: 15/85 at 0 min-->50/50 at 20 min-->100/0 at 22 min-->15/85 at 24 min-->15/85 at 26 min, delivered at 1 ml/min. The analytes were detected by fluorescence detection with excitation and emission wavelength set at 480 and 550 nm, respectively. The calibration curves were linear over the range of 2-1000 ng/ml for effluent and plasma matrices, and 0.1 microg/g-750 microg/g for tissues matrices. The method is precise with inter-day and intra-day relative standard deviation within 0.5 and 6.7% and accurate with inter-day and intra-day deviations between -5.4 and +7.7%. The in vitro stability in all matrices and in processed samples has been studied at -80 degrees C for 1 month, and at 4 degrees C for 48 h, respectively. During initial studies, heparin used as anticoagulant was found to profoundly influence the measurements of doxorubicin in effluents collected from animals under ILP. Moreover, the strong matrix effect observed with tissues samples indicate that it is mandatory to prepare doxorubicin calibration standard samples in biological matrices which would reflect at best the composition of samples to be analyzed. This method was successfully applied in animal studies for the analysis of effluent, serum and tissue samples collected from pigs and rats undergoing ILP.

Validated prediction of clinical outcome in sarcomas and multiple types of cancer on the basis of a gene expression signature related to genome complexity.

Sarcomas are heterogeneous and aggressive mesenchymal tumors. Histological grading has so far been the best predictor for metastasis-free survival, but it has several limitations, such as moderate reproducibility and poor prognostic value for some histological types. To improve patient grading, we performed genomic and expression profiling in a training set of 183 sarcomas and established a prognostic gene expression signature, complexity index in sarcomas (CINSARC), composed of 67 genes related to mitosis and chromosome management. In a multivariate analysis, CINSARC predicts metastasis outcome in the training set and in an independent 127 sarcomas validation set. It is superior to the Fédération Francaise des Centres de Lutte Contre le Cancer grading system in determining metastatic outcome for sarcoma patients. Furthermore, it also predicts outcome for gastrointestinal stromal tumors (GISTs), breast carcinomas and lymphomas. Application of the signature will permit more selective use of adjuvant therapies for people with sarcomas, leading to decreased iatrogenic morbidity and improved outcomes for such individuals.

Multiplan Spreadsheets for Highway and Hydraulic Engineering Computations in County Engineering Offices, HR-284, 1987

Multiplan spreadsheet solutions were developed for a set of hydraulic and highway engineering computations of common interest to county engineers. These include earthwork, vertical and horizontal curves, staking superelevated curves and sign inventories for highways. The hydraulic applications were ditch flow, runoff, culvert size and stage discharge.