Background: Clinical management of dyslipidemia is challenging, particularly hypertriglyceridemia in patients with HIV-infection. Changing combined anti-retroviral therapy (CART) and the use of lipid-lowering drugs have proven useful in treating dyslipidemia in HIV infected patients Objective: To assess the efficacy of lipid lowering drugs (LLDs) and/or CART switching, in the management of HIV-associated dyslipidemia Design: A retrospective, longitudinal cohort study Setting: Phidisa HIV research project, 6 sites in South Africa, period April 2008 and April 2011 Patients: HIV positive South African National Defence Force (SANDF) members and their dependents; who are on CART and are 18 years or older. Four hundred and forty eight participants with dyslipidemia had non-fasted, total serum cholesterol ≥ 8.0mmol/l, serum triglyceride levels ≥4.52 mmol/l and naïve to lipid lowering drugs at baseline. Measurements: Mean change over time of total serum cholesterol and serum triglyceride in the following treatment strategies were used: exercise and dietary advice, lipid-lowering drugs (statins or fibrates or both), CART switches separately and combined lipid lowering drug with ART switch was measured using panel data with first–order autoregressive-response and xtabond. Results: The mean age for a total of 448 participants was 39.9 years; males were 87%, females were only 13%. The participants contributed to 1861 follow-up visits. CD4 count was normally distributed with the baseline mean value of 402 cells/mm3 (18.5%). Mean change over time for total serum cholesterol and triglycerides increased by 0.099 mmol/l (p=0.007) and 0.248 mmol/l (p=0.018) respectively, with an increase in body mass index while an increase in CD4 cell percent decreased mean over time for total serum cholesterol by 0.045 mmol/l (p=0.002). Our hypothesis was confirmed when lipid lowering drugs and ART switch combined treatment strategy even more decrease in the mean total serum cholesterol and triglycerides levels over time by 0.754 mmol/l (p<0.001) and 2.073 mmol/l (p<0.001) respectively compared to the exercise and dietary advice treatment strategy. Our findings showed that combined treatment strategy maintained a decrease in both the mean total serum cholesterol and triglycerides levels over time of 0.283 mmol/l (p=0.038) and 0.941 mmol/l (p=0.016) respectively, when compared to lipid lowering drugs; the mean serum triglycerides over time were also reduced by 0.486 mmol/l (p=0.048) when the combined treatment strategy was compared to CART switch only. Furthermore combined treatment strategy of lipid lowering drugs with ART switch showed significant virological suppression by decreasing log of viral load, 0.486 (p<0.001) when compared to the exercise and dietary advice group. Conclusions: Combining lipid lowering drugs and ART switching as a treatment strategy in the management of HIV-associated dyslipidemia is effective in lowering the mean over time of both total serum cholesterol and triglycerides when compared to exercise and dietary advice strategy, while maintaining virological suppression. / Dissertation (MSc)--University of Pretoria, 2015. / tm2015 / School of Health Systems and Public Health (SHSPH) / MSc / Unrestricted

Robôs móveis dependem de dados provenientes de sensores para ter uma representação do seu ambiente. Porém, os sensores geralmente fornecem informações incompletas, inconsistentes ou imprecisas. Técnicas de fusão de sensores têm sido empregadas com sucesso para aumentar a precisão de medidas obtidas com sensores. Este trabalho propõe e investiga o uso de técnicas de inteligência artificial para fusão de sensores com o objetivo de melhorar a precisão e acurácia de medidas de distância entre um robô e um objeto no seu ambiente de trabalho, obtidas com diferentes sensores. Vários algoritmos de aprendizado de máquina são investigados para fundir os dados dos sensores. O melhor modelo gerado com cada algoritmo é chamado de estimador. Neste trabalho, é mostrado que a utilização de estimadores pode melhorar significativamente a performance alcançada por cada sensor isoladamente. Mas os vários algoritmos de aprendizado de máquina empregados têm diferentes características, fazendo com que os estimadores tenham diferentes comportamentos em diferentes situações. Objetivando atingir um comportamento mais preciso e confiável, os estimadores são combinados em comitês. Os resultados obtidos sugerem que essa combinação pode melhorar a confiança e precisão das medidas de distâncias dos sensores individuais e estimadores usados para fusão de sensores. / Mobile robots rely on sensor data to have a representation of their environment. However, the sensors usually provide incomplete, inconsistent or inaccurate information. Sensor fusion has been successfully employed to enhance the accuracy of sensor measures. This work proposes and investigates the use of artificial intelligence techniques for sensor fusion. Its main goal is to improve the accuracy and reliability of a distance between a robot and an object in its work environment using measures obtained from different sensors. Several machine learning algorithms are investigated to fuse the sensors data. The best model generated with each algorithm are called estimator. It is shown that the employment of the estimators based on artificial intelligence can improve significantly the performance achieved by each sensor alone. The machine learning algorithms employed have different characteristics, causing the estimators to have different behaviour in different situations. Aiming to achieve more accurate and reliable behavior, the estimators are combined in committees. The results obtained suggest that this combination can improve the reliability and accuracy of the distance measures by the individual sensors and estimators used for sensor fusion.

Nowadays, there is a wide range of forecasting methods and forecasters encounter several challenges during selection of an optimal method for volatility forecasting. In order to make use of wide selection of forecasts, this thesis tests multiple forecast combination methods. Notwithstanding, there exists a plethora of forecast combination literature, combination of traditional methods with machine learning methods is relatively rare. We implement the following combination techniques: (1) simple mean forecast combination, (2) OLS combination, (3) ARIMA on OLS combined fit, (4) NNAR on OLS combined fit and (5) KNN regression on OLS combined fit. To our best knowledge, the latter two combination techniques are not yet researched in academic literature. Additionally, this thesis should help a forecaster with three choice complication causes: (1) choice of volatility proxy, (2) choice of forecast accuracy measure and (3) choice of training sample length. We found that squared and absolute return volatility proxies are much less efficient than Parkinson and Garman-Klass volatility proxies. Likewise, we show that forecast accuracy measure (RMSE, MAE or MAPE) influences optimal forecasts ranking. Finally, we found that though forecast quality does not depend on training sample length, we see that forecast...

Objectives: This retrospective analysis was conducted to derive national estimates of typical, atypical, and combination (typical-atypical) antipsychotic use and to examine factors associated with their use at adult (age ≫-18 years) ambulatory care visits by patients with mental health disorders in the United States. Methods: Data on adult visits with an International Classification of Diseases, Ninth Revision, Clinical Modification diagnosis code for a mental health disorder were extracted from the office-based National Ambulatory Medical Care Survey and the outpatient facilitybased National Hospital Ambulatory Medical Care Survey from 1996 through 2003. The visits were categorized according to whether use of a typical, atypical, or combination antipsychotic was mentioned (either prescribed, supplied, administered, ordered, or continued at the visits). Total weighted visit estimates, weighted visit percentages, and 95% CIs were calculated across the 3 types of visit groups. Bivariate analysis was performed on the association between selected characteristics and the 3 visit groups. Multivariate logistic regression was performed on factors associated with atypical versus typical antipsychotic use. Results: During the 8-year period, there were an estimated 47.7 million adult ambulatory care visits involving a mental health disorder and mention of an antipsychotic (weighted percent: 0.83%; 95% CI, 0.73-0.93). From 1996/1997 to 2002/2003, visits involving atypical and combination antipsychotics increased by 195% and 149%, respectively, and visits involving typical antipsychotics decreased by 71%. Men, blacks, and those with public insurance made more visits in which combination antipsychotics rather than typical or atypical antipsychotics were mentioned. Relative to typical or combination antipsychotic visits, more atypical antipsychotic visits involved antide-pressants (weighted percent: 61.23% atypical, 37.29% typical, and 38.32% combination). Fewer atypical antipsychotic visits compared with typical or combination antipsychotic visits involved psychotic disorders (weighted percent: 32.94%, 51.23%, and 69.93%, respectively) and medications for extrapyramidal symptoms (weighted percent: 6.69%, 29.95%, and 36.64%). In multivariate analyses controlling for sex, race, diagnosis of schizophrenia, region, diagnosis of anxiety, and recent years, atypical versus typical antipsychotic use was significantly less likely at visits by those aged 41 to 64 years compared with those aged 18 to 40 years (adjusted odds ratio [OR] = 0.63; 95% CI, 0.47-0.84; P = 0.002); significantly less likely at visits by those with public compared with private insurance (Medicare OR = 0.59 [95% CI, 0.40-0.88], P = 0.010; Medicaid OR = 0.44 [95% CI, 0.28-0.69], P < 0.001); and significantly more likely at visits associated with depression compared with those not associated with depression (OR = 1.92; 95% CI, 1.26-2.93; P = 0.003) and those associated with bipolar disorder compared with those not associated with bipolar disorder (OR = 2.10; 95% CI, 1.32-3.36; P = 0.002). Conclusions: This retrospective analysis found more atypical than typical or combination antipsychotic use at US ambulatory care visits by adults with mental health disorders other than schizophrenia or psychoses in the period studied. Atypical versus typical antipsychotic use was significantly less likely at visits by adults aged 41 to 64 years and those with public insurance, but significantly more likely at visits by those with depression or bipolar disorder.

Purpose: To show the necessity of distinguishing several patterns of drug prescribing that may lead to co-medication. It is demonstrated how these different patterns can be investigated using large databases containing pharmacy data or reimbursement data. Methods: Two examples illustrate how the particular pattern of co-medication studied will influence the reported proportion of patients having co-medication, the use of antidepressants among people using anticonvulsants, and the use of antihistamines among people receiving penicittines. Results: Depending on definition and period considered, the percentage of anticonvulsant users co-medicated with antidepressants ranged from 5.8% (95%CI 5.0%, 6.8%) to 14.5% (95%CI 13.2%, 15.9%) in 2000. Comparing 2002 with 2000, the ratio of proportions ranged from 1.3 to 2.1. The percentage of people who received penicillines and were co-medicated with antihistamines ranged from 0.5% (95%CI 0.4%, 0.6%) to 9.7% (95%CI 9.3%,10.2%) in 2000. Comparing 2002 with 2000, the ratio of proportions ranged from 1.2 to 1.6. Conclusion: The co-medication patterns investigated yielded clinical as well as statistically significant different estimates. The estimates differed up to a factor 2.5 for the drugs usually prescribed for long periods, and a factor 12 for drugs prescribed for short periods. Hence, we propose to distinguish the patterns 'co-prescribing', 'concomitant medication,' and 'possibly concurrent medication.' The research question determines the co-medication pattern of interest, and the drug and disease under study determine the time window.

Invasive fungal infections (IFIs) are associated with considerable morbidity and mortality among high-risk individuals. Outcomes for IFI historically have been suboptimal and associated with a high mortality rate, hence global prophylaxis strategies have been applied to at-risk populations. Among certain populations, fluconazole prophylaxis has reduced systemic and superficial infections caused by Candida species. Newer azoles are currently being evaluated as prophylaxis and have the potential to provide protection against mould pathogens that are more troublesome to treat once they occur. Global prophylaxis strategies have the shortcoming of subjecting patients to therapy that ultimately will not need it. Targeted prophylaxis has the advantage of treating only patients at highest risk using some parameter of greater host susceptibility. Prophylaxis strategies are most suitable in patients at the highest risk for IFI. For patient groups whose risk is somewhat lower or when suspicion of IFI occurs in patients receiving prophylaxis, empirical antifungal therapy is often employed following a predefined period of fever. Again this approach subjects many non-infected patients to unnecessary and toxic therapy. A more refined approach such as presumptive or pre-emptive therapy whereby treatment is only initiated upon positive identification of a surrogate marker of infection in combination with clinical and radiological signs will subject fewer patients to toxic and expensive treatments.

京都大学 / 新制・課程博士 / 博士(工学) / 甲第23228号 / 工博第4872号 / 新制||工||1760(附属図書館) / 京都大学大学院工学研究科高分子化学専攻 / (主査)教授 山子 茂, 教授 大内 誠, 教授 中村 正治 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

京都大学 / 0048 / 新制・課程博士 / 博士(医学) / 甲第18683号 / 医博第3955号 / 新制||医||1007(附属図書館) / 31616 / 京都大学大学院医学研究科医学専攻 / (主査)教授 横出 正之, 教授 岩田 想, 教授 川口 義弥 / 学位規則第4条第1項該当 / Doctor of Medical Science / Kyoto University / DGAM

Most cancer cells rely on aerobic glycolysis to support the mitochondrial oxidative phosphorylation system (OXPHOS). The persistent oxic-anoxic cycle exerts selection pressures which lead to constitutive activation of glycolysis even in the presence of abundant oxygen. Expression of hypoxia-inducible factor 1 (HIF1) increases following hypoxia in neoplastic cells. This leads to the induction of pyruvate dehydrogenase kinase 1 (PDK1). The latter inactivates pyruvate dehydrogenase (PDH) that converts pyruvate to acetyl-coenzyme A for delivery to the tricarboxylic acid cycle (TAC). Dichloroacetic acid (DCA) is an inhibitor of PDK that forces cells into oxidative phosphorylation thereby suppressing cancer growth. 2-Ethyl-3-O-sulphamoyl-estra-1,3,5(10),15-tetraen-3-ol-17-one (C9), along with a few other 17β-estradiol analogs, are a novel class of in silico-designed inhibitors of microtubule dynamics. These newly designed and synthesized antimitotic compounds induce G2/M arrest and apoptosis by docking to colchicine binding site between α- and β-tubulin. These compounds are 5 to 20 times more potent than their source molecule, 2-methoxyestradiol (2ME). To improve bioavailability C9 has been in silico-modified at carbon positions C2, C3 and C17 compared to 2ME. The approach to investigate the anticancer potential of the in silico-designed antimitotic C9 in combination with the glycolytic inhibitor DCA in vitro is novel. Human breast carcinoma cell line MCF-7 and non-tumorigenic breast cells MCF-12A were used as an experimental model system. The present study demonstrated that DCA (7.5 mM) in combination with C9 (130 nM) selectively inhibited half of MCF-7 cells‘ population (50.8%). Under the same treatment conditions, MCF-12A cells displayed high number of cell survival (70% cell growth). Qualitative morphological studies revealed decreased cell density in both cell lines, as well as hallmarks of apoptosis and autophagic processes including formation of apoptotic bodies, DNA fragmentation and autophagic vacuoles. Cell cycle- and apoptosis quantification analyses revealed C9+DCA treatment induced apoptosis in both cell lines and exhibited selectivity towards tumorigenic cells. Presence of autophagosome was observed and microtubule-associated protein 1 light chain 3 (II) (LC3-II) expression was elevated. Reduction of mitochondrial membrane potential depolarization in tumorigenic MCF-7 cells was demonstrated, but not in MCF-12A cells. Oxidative stress tests suggested the combination treatment C9+DCA is able to induce lysosomal rupture and/or mitochondrial damage in tumorigenic MCF-7 cells. Kinase inhibition studies revealed that transient activation of c-Jun N-terminal kinase (JNK) plays an important role in cell proliferation. However, C9+DCA stimulated prolonged JNK activation and, in turn, promoted Bcl-2 phosphorylation, thereby facilitating autophagic and apoptotic cell death. C9+DCA induced expression of a number of genes related to stress in MCF-7 treated cells including TP53BP1, MDM2 and BBC3/PUMA. Genes related to cell motility and maintenance of the cytoskeleton such as ACTG1, MAP7, TUBA1, TUBA6, TUBA8 and TUBB2A genes were down-regulated. In MCF-12A cells, treatment of C9+DCA induced expression of multidrug resistance gene ABCB1. Moreover, genes involved in reactive oxygen species metabolism FTH1, GSTA2, NOS2A, SMOX, SOD1 and SOD2 were also up-regulated. In conclusion, the novel 17β-estradiol derivative, C9, in combination with DCA is a potent antiproliferative treatment. This study addressed the mechanisms of combination treatment at the basis of molecular and cellular level, warranting further research projects to develop viable and functional combination treatment as clinically useable anticancer agents. / Thesis (PhD)--University of Pretoria, 2014. / lk2014 / Physiology / PhD / Unrestricted

Two experiments examined processing of "near-nonsense" noun-noun combinations (e.g., dictionary treatment, olive signals). In the first experiment, readers’ eye movements were monitored as they read sentences containing such combinations, or control sentences containing easy-to-interpret adjective-noun combinations. A preceding context sentence either did or did not support a specific interpretation of the critical noun-noun combination. The earliest measures of processing difficulty were not modulated by the context manipulation, but on later measures, the potentially helpful context did alleviate difficulty. In the second experiment, participants provided detailed interpretations of the critical combinations, with and without the potentially helpful context sentence; the results confirmed that the context sentences encouraged specific interpretations of these combinations. The results suggest that a noun-noun combination is initially interpreted without taking into account the immediate context, but that this context may ultimately play a critical role.