Control and model-based analysis of microaerobic processes - using Rhodospirillum rubrum as model organism

Magdeburg, Univ., Fak. für Elektrotechnik und Informationstechnik, Diss., 2015

Challenging recommended oral and intravenous voriconazole doses for improved efficacy and safety: population pharmacokinetics-based analysis of adult patients with invasive fungal infections.

BACKGROUND: Recommended oral voriconazole (VRC) doses are lower than intravenous doses. Because plasma concentrations impact efficacy and safety of therapy, optimizing individual drug exposure may improve these outcomes. METHODS: A population pharmacokinetic analysis (NONMEM) was performed on 505 plasma concentration measurements involving 55 patients with invasive mycoses who received recommended VRC doses. RESULTS: A 1-compartment model with first-order absorption and elimination best fitted the data. VRC clearance was 5.2 L/h, the volume of distribution was 92 L, the absorption rate constant was 1.1 hour(-1), and oral bioavailability was 0.63. Severe cholestasis decreased VRC elimination by 52%. A large interpatient variability was observed on clearance (coefficient of variation [CV], 40%) and bioavailability (CV 84%), and an interoccasion variability was observed on bioavailability (CV, 93%). Lack of response to therapy occurred in 12 of 55 patients (22%), and grade 3 neurotoxicity occurred in 5 of 55 patients (9%). A logistic multivariate regression analysis revealed an independent association between VRC trough concentrations and probability of response or neurotoxicity by identifying a therapeutic range of 1.5 mg/L (>85% probability of response) to 4.5 mg/L (<15% probability of neurotoxicity). Population-based simulations with the recommended 200 mg oral or 300 mg intravenous twice-daily regimens predicted probabilities of 49% and 87%, respectively, for achievement of 1.5 mg/L and of 8% and 37%, respectively, for achievement of 4.5 mg/L. With 300-400 mg twice-daily oral doses and 200-300 mg twice-daily intravenous doses, the predicted probabilities of achieving the lower target concentration were 68%-78% for the oral regimen and 70%-87% for the intravenous regimen, and the predicted probabilities of achieving the upper target concentration were 19%-29% for the oral regimen and 18%-37% for the intravenous regimen. CONCLUSIONS: Higher oral than intravenous VRC doses, followed by individualized adjustments based on measured plasma concentrations, improve achievement of the therapeutic target that maximizes the probability of therapeutic response and minimizes the probability of neurotoxicity. These findings challenge dose recommendations for VRC.

A cohort-based analysis of the evolution of lifetime prevalence of recourse to prostitution by men in the general population of Switzerland, 1987-2000

Background: Despite their relevance to the prevention of sexually transmitted infections, there are few data on the frequency of recourse to prostitution in the male population in Switzerland. Using data gathered for the evaluation of the Swiss AIDS prevention strategy, we analysed net aggregate change and cohort-based change in lifetime prevalence of recourse to prostitution. Methods: Seven repeated cross-sectional telephone surveys of the general population aged 17-45 years (17-30 years only for the 1987 and 1988 surveys) were undertaken from 1987 to 2000 providing information on sexual behaviour including men's recourse to prostitution (total n¼9318). Age categories were: 17-20, 21-25, 26-30, 31-35, 36-40 and 41-45 years. Prevalence at 17-30 years was available in all surveys and prevalence at 41-45 was available for 1989-2000, though not for the same cohorts. Intra-cohort increase in prevalence over 10 years was analysed using truncated information for cohorts aged 21-25 and 26-30 years in 1987 and 1990. Population estimates were computed with 95% confidence intervals (CI). Results: No net change occurred in the 17-45 years male population prevalence between 1989 (17.6%, CI ¼ 15.4; 20.0) and 2000 (17.7%, CI ¼ 15.6; 20.0). The median starting prevalence of recourse to prostitution at age 17-20 was 4.8% (in 1989, CI ¼ 2.0; 9.7) and the range was from 1.8 (in 1994) to 10.4% (in 1990). The median ending prevalence at age 41-45 was 21.9% (in 1994, CI 16.7; 27.9) and the range was from 17.9 (in 2000) to 26.1% (in 1992). No clear trend was observed in either starting or ending prevalence. Intra-cohort evolution of the 1997 and 1990 cohorts was very similar. Conclusions: Based on available data, there was no net (aggregate) change in the prevalence of recourse to prostitution by males in Switzerland between 1989 and 2000. Within the time frame available, intra-cohort evolution was also very similar.

Positional scanning-synthetic peptide library-based analysis of self- and pathogen-derived peptide cross-reactivity with tumor-reactive Melan-A-specific CTL.

Synthetic combinatorial peptide libraries in positional scanning format (PS-SCL) have recently emerged as a useful tool for the analysis of T cell recognition. This includes identification of potentially cross-reactive sequences of self or pathogen origin that could be relevant for the understanding of TCR repertoire selection and maintenance, as well as of the cross-reactive potential of Ag-specific immune responses. In this study, we have analyzed the recognition of sequences retrieved by using a biometric analysis of the data generated by screening a PS-SCL with a tumor-reactive CTL clone specific for an immunodominant peptide from the melanocyte differentiation and tumor-associated Ag Melan-A. We found that 39% of the retrieved peptides were recognized by the CTL clone used for PS-SCL screening. The proportion of peptides recognized was higher among those with both high predicted affinity for the HLA-A2 molecule and high predicted stimulatory score. Interestingly, up to 94% of the retrieved peptides were cross-recognized by other Melan-A-specific CTL. Cross-recognition was at least partially focused, as some peptides were cross-recognized by the majority of CTL. Importantly, stimulation of PBMC from melanoma patients with the most frequently recognized peptides elicited the expansion of heterogeneous CD8(+) T cell populations, one fraction of which cross-recognized Melan-A. Together, these results underline the high predictive value of PS-SCL for the identification of sequences cross-recognized by Ag-specific T cells.

Impact of inadequate empirical therapy on the mortality of patients with bloodstream infections: a propensity score-based analysis.

The impact of the adequacy of empirical therapy on outcome for patients with bloodstream infections (BSI) is key for determining whether adequate empirical coverage should be prioritized over other, more conservative approaches. Recent systematic reviews outlined the need for new studies in the field, using improved methodologies. We assessed the impact of inadequate empirical treatment on the mortality of patients with BSI in the present-day context, incorporating recent methodological recommendations. A prospective multicenter cohort including all BSI episodes in adult patients was performed in 15 hospitals in Andalucía, Spain, over a 2-month period in 2006 to 2007. The main outcome variables were 14- and 30-day mortality. Adjusted analyses were performed by multivariate analysis and propensity score-based matching. Eight hundred one episodes were included. Inadequate empirical therapy was administered in 199 (24.8%) episodes; mortality at days 14 and 30 was 18.55% and 22.6%, respectively. After controlling for age, Charlson index, Pitt score, neutropenia, source, etiology, and presentation with severe sepsis or shock, inadequate empirical treatment was associated with increased mortality at days 14 and 30 (odds ratios [ORs], 2.12 and 1.56; 95% confidence intervals [95% CI], 1.34 to 3.34 and 1.01 to 2.40, respectively). The adjusted ORs after a propensity score-based matched analysis were 3.03 and 1.70 (95% CI, 1.60 to 5.74 and 0.98 to 2.98, respectively). In conclusion, inadequate empirical therapy is independently associated with increased mortality in patients with BSI. Programs to improve the quality of empirical therapy in patients with suspicion of BSI and optimization of definitive therapy should be implemented.

On-axis joint transform correlation based on a four-level power spectrum

We propose a method to obtain a single centered correlation with use of a joint transform correlator. We analyze the required setup to carry out the whole process optically, and we also present experimental results.

Individual prediction of cognitive decline in mild cognitive impairment using support vector machine-based analysis of diffusion tensor imaging data.

Although cross-sectional diffusion tensor imaging (DTI) studies revealed significant white matter changes in mild cognitive impairment (MCI), the utility of this technique in predicting further cognitive decline is debated. Thirty-five healthy controls (HC) and 67 MCI subjects with DTI baseline data were neuropsychologically assessed at one year. Among them, there were 40 stable (sMCI; 9 single domain amnestic, 7 single domain frontal, 24 multiple domain) and 27 were progressive (pMCI; 7 single domain amnestic, 4 single domain frontal, 16 multiple domain). Fractional anisotropy (FA) and longitudinal, radial, and mean diffusivity were measured using Tract-Based Spatial Statistics. Statistics included group comparisons and individual classification of MCI cases using support vector machines (SVM). FA was significantly higher in HC compared to MCI in a distributed network including the ventral part of the corpus callosum, right temporal and frontal pathways. There were no significant group-level differences between sMCI versus pMCI or between MCI subtypes after correction for multiple comparisons. However, SVM analysis allowed for an individual classification with accuracies up to 91.4% (HC versus MCI) and 98.4% (sMCI versus pMCI). When considering the MCI subgroups separately, the minimum SVM classification accuracy for stable versus progressive cognitive decline was 97.5% in the multiple domain MCI group. SVM analysis of DTI data provided highly accurate individual classification of stable versus progressive MCI regardless of MCI subtype, indicating that this method may become an easily applicable tool for early individual detection of MCI subjects evolving to dementia.

Methadone treatments in a Swiss Region, 2001-2008: a registry-based analysis.

ABSTRACT: BACKGROUND: To determine, in a region of Switzerland, the duration of retention in opioid substitution treatments with methadone (OSTM), duration of treatment interruptions, probability of re-entry to treatment after a treatment interruption, and associated factors. METHODS: A secondary analysis of registry-based data was performed with patients (n = 2880) registered in the methadone treatment register database of the Public Health Service of the canton of Vaud between January 1, 2001 and June 30, 2008. Survival analysis and multivariate analysis was conducted. RESULTS: The probability of remaining on treatment was 69% at 1 year and 45% at 3 years (n =1666). One-third of patients remained on treatment beyond 5 years. The estimated hazard of leaving treatment was increased by a ratio of 1.31 in the case of a first treatment (P = 0.001), 1.83 for those without a fixed home (P < 0.001), and 1.29 for those younger than 30 years old (P < 0.001). The probability of having begun a new treatment after a first interruption was 21% at one year, 38% at 3 years, and 43% at 5 years (n = 1581). Factors at the interruption of treatment associated with a higher probability of re-entering were: interruption not due to methadone withdrawal, bad physical health, and higher methadone dose. CONCLUSIONS: OSTM are long-term (maintenance) treatments in Switzerland. Younger age, bad living conditions at entry, and first treatment are predictors of lower retention. Approximately one-half of patients who interrupt treatment will re-enter treatment within 5 years.

Neutralizing antibodies in Multiple Sclerosis a model-based analysis of Interferon beta signaling pathway in macrophages

Multiple Sclerosis is the most common non-traumatic cause of neurologicaldisability in young people. There is no cure yet, and until recently, few long-termtherapies existed. Interferon beta (IFNβ) was the first treatment, and remains the mostcommonly prescribed. One of the most significant problems of IFNβ therapy is theproduction of drug specific antibodies. Up to 45% of patients develop neutralizingantibodies (NAbs) to IFNβ products. The neutralizing antibody binds to the biologicalagent preventing its interaction with its receptor, inhibiting the biological action of theprotein, which abrogates the clinical efficacy of IFNβ treatment. Interferon-betamediates its response by binding to its high affinity cell surface receptor and initiatingthe JAK/STAT signalling cascade. In this project we have analyzed the IFNβ signalingpathway in macrophages when neutralizing antibodies are present. The response tothis pathway after IFNβ stimulation shows a transient oscillatory rhythm of STAT1phosphorylation, which varies as NAbs concentration increases. To improve ourunderstanding of that behavior, we extended an existing mathematical model based onnonlinear ordinary differential equations of JAK/STAT pathway by including IFN-NAbassociation and IFN-activation receptor. Combining our theoretical model withexperimental data we could study the role of neutralizing antibodies on the molecularresponse and determine its lifetime after cytokine stimulation.

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Model based analysis of the post-combustion calcium looping process for carbon dioxide capture

This thesis presents a one-dimensional, semi-empirical dynamic model for the simulation and analysis of a calcium looping process for post-combustion CO2 capture. Reduction of greenhouse emissions from fossil fuel power production requires rapid actions including the development of efficient carbon capture and sequestration technologies. The development of new carbon capture technologies can be expedited by using modelling tools. Techno-economical evaluation of new capture processes can be done quickly and cost-effectively with computational models before building expensive pilot plants. Post-combustion calcium looping is a developing carbon capture process which utilizes fluidized bed technology with lime as a sorbent. The main objective of this work was to analyse the technological feasibility of the calcium looping process at different scales with a computational model. A one-dimensional dynamic model was applied to the calcium looping process, simulating the behaviour of the interconnected circulating fluidized bed reactors. The model incorporates fundamental mass and energy balance solvers to semi-empirical models describing solid behaviour in a circulating fluidized bed and chemical reactions occurring in the calcium loop. In addition, fluidized bed combustion, heat transfer and core-wall layer effects were modelled. The calcium looping model framework was successfully applied to a 30 kWth laboratory scale and a pilot scale unit 1.7 MWth and used to design a conceptual 250 MWth industrial scale unit. Valuable information was gathered from the behaviour of a small scale laboratory device. In addition, the interconnected behaviour of pilot plant reactors and the effect of solid fluidization on the thermal and carbon dioxide balances of the system were analysed. The scale-up study provided practical information on the thermal design of an industrial sized unit, selection of particle size and operability in different load scenarios.