Development of a model-based transient calibration process for diesel engine electronic control module tables – Part 1: data requirements, processing, and analysis

This is the first part of a study investigating a model-based transient calibration process for diesel engines. The motivation is to populate hundreds of parameters (which can be calibrated) in a methodical and optimum manner by using model-based optimization in conjunction with the manual process so that, relative to the manual process used by itself, a significant improvement in transient emissions and fuel consumption and a sizable reduction in calibration time and test cell requirements is achieved. Empirical transient modelling and optimization has been addressed in the second part of this work, while the required data for model training and generalization are the focus of the current work. Transient and steady-state data from a turbocharged multicylinder diesel engine have been examined from a model training perspective. A single-cylinder engine with external air-handling has been used to expand the steady-state data to encompass transient parameter space. Based on comparative model performance and differences in the non-parametric space, primarily driven by a high engine difference between exhaust and intake manifold pressures (ΔP) during transients, it has been recommended that transient emission models should be trained with transient training data. It has been shown that electronic control module (ECM) estimates of transient charge flow and the exhaust gas recirculation (EGR) fraction cannot be accurate at the high engine ΔP frequently encountered during transient operation, and that such estimates do not account for cylinder-to-cylinder variation. The effects of high engine ΔP must therefore be incorporated empirically by using transient data generated from a spectrum of transient calibrations. Specific recommendations on how to choose such calibrations, how many data to acquire, and how to specify transient segments for data acquisition have been made. Methods to process transient data to account for transport delays and sensor lags have been developed. The processed data have then been visualized using statistical means to understand transient emission formation. Two modes of transient opacity formation have been observed and described. The first mode is driven by high engine ΔP and low fresh air flowrates, while the second mode is driven by high engine ΔP and high EGR flowrates. The EGR fraction is inaccurately estimated at both modes, while EGR distribution has been shown to be present but unaccounted for by the ECM. The two modes and associated phenomena are essential to understanding why transient emission models are calibration dependent and furthermore how to choose training data that will result in good model generalization.

A Decision-Tree-Based Approach to Smoke Spike Detection in a Heavy-Duty Diesel Engine

Smoke spikes occurring during transient engine operation have detrimental health effects and increase fuel consumption by requiring more frequent regeneration of the diesel particulate filter. This paper proposes a decision tree approach to real-time detection of smoke spikes for control and on-board diagnostics purposes. A contemporary, electronically controlled heavy-duty diesel engine was used to investigate the deficiencies of smoke control based on the fuel-to-oxygen-ratio limit. With the aid of transient and steady state data analysis and empirical as well as dimensional modeling, it was shown that the fuel-to-oxygen ratio was not estimated correctly during the turbocharger lag period. This inaccuracy was attributed to the large manifold pressure ratios and low exhaust gas recirculation flows recorded during the turbocharger lag period, which meant that engine control module correlations for the exhaust gas recirculation flow and the volumetric efficiency had to be extrapolated. The engine control module correlations were based on steady state data and it was shown that, unless the turbocharger efficiency is artificially reduced, the large manifold pressure ratios observed during the turbocharger lag period cannot be achieved at steady state. Additionally, the cylinder-to-cylinder variation during this period were shown to be sufficiently significant to make the average fuel-to-oxygen ratio a poor predictor of the transient smoke emissions. The steady state data also showed higher smoke emissions with higher exhaust gas recirculation fractions at constant fuel-to-oxygen-ratio levels. This suggests that, even if the fuel-to-oxygen ratios were to be estimated accurately for each cylinder, they would still be ineffective as smoke limiters. A decision tree trained on snap throttle data and pruned with engineering knowledge was able to use the inaccurate engine control module estimates of the fuel-to-oxygen ratio together with information on the engine control module estimate of the exhaust gas recirculation fraction, the engine speed, and the manifold pressure ratio to predict 94% of all spikes occurring over the Federal Test Procedure cycle. The advantages of this non-parametric approach over other commonly used parametric empirical methods such as regression were described. An application of accurate smoke spike detection in which the injection pressure is increased at points with a high opacity to reduce the cumulative particulate matter emissions substantially with a minimum increase in the cumulative nitrogrn oxide emissions was illustrated with dimensional and empirical modeling.

Cardiac transplantation with hearts from donors after circulatory declaration of death: haemodynamic and biochemical parameters at procurement predict recovery following cardioplegic storage in a rat model

OBJECTIVES: Donation after circulatory declaration of death (DCDD) could significantly improve the number of cardiac grafts for transplantation. Graft evaluation is particularly important in the setting of DCDD given that conditions of cardio-circulatory arrest and warm ischaemia differ, leading to variable tissue injury. The aim of this study was to identify, at the time of heart procurement, means to predict contractile recovery following cardioplegic storage and reperfusion using an isolated rat heart model. Identification of reliable approaches to evaluate cardiac grafts is key in the development of protocols for heart transplantation with DCDD. METHODS: Hearts isolated from anaesthetized male Wistar rats (n = 34) were exposed to various perfusion protocols. To simulate DCDD conditions, rats were exsanguinated and maintained at 37°C for 15-25 min (warm ischaemia). Isolated hearts were perfused with modified Krebs-Henseleit buffer for 10 min (unloaded), arrested with cardioplegia, stored for 3 h at 4°C and then reperfused for 120 min (unloaded for 60 min, then loaded for 60 min). Left ventricular (LV) function was assessed using an intraventricular micro-tip pressure catheter. Statistical significance was determined using the non-parametric Spearman rho correlation analysis. RESULTS: After 120 min of reperfusion, recovery of LV work measured as developed pressure (DP)-heart rate (HR) product ranged from 0 to 15 ± 6.1 mmHg beats min(-1) 10(-3) following warm ischaemia of 15-25 min. Several haemodynamic parameters measured during early, unloaded perfusion at the time of heart procurement, including HR and the peak systolic pressure-HR product, correlated significantly with contractile recovery after cardioplegic storage and 120 min of reperfusion (P < 0.001). Coronary flow, oxygen consumption and lactate dehydrogenase release also correlated significantly with contractile recovery following cardioplegic storage and 120 min of reperfusion (P < 0.05). CONCLUSIONS: Haemodynamic and biochemical parameters measured at the time of organ procurement could serve as predictive indicators of contractile recovery. We believe that evaluation of graft suitability is feasible prior to transplantation with DCDD, and may, consequently, increase donor heart availability.

First trimester markers for pre-eclampsia: placental vs. non-placental protein serum levels

BACKGROUND/AIM: Parallel investigation, in a matched case-control study, of the association of different first-trimester markers with the risk of subsequent pre-eclampsia (PE). METHOD: The levels of different first trimester serum markers and fetal nuchal translucency thickness were compared between 52 cases of PE and 104 control women by non-parametric two-group comparisons and by calculating matched odds ratios. RESULTS: In univariable analysis increased concentrations of inhibin A and activin A were associated with subsequent PE (p < 0.02). Multivariable conditional logistic regression models revealed an association between increased risk of PE and increased inhibin A and translucency thickness and respectively reduced pregnancy-associated plasma protein A (PAPP-A) and placental lactogen . However, these associations varied with the gestational age at sample collection. For blood samples taken in pregnancy weeks 12 and 13 only, increased levels of activin A, inhibin A and nuchal translucency thickness, and lower levels of placenta growth factor and PAPP-A were associated with an increased risk of PE. CONCLUSIONS: Members of the inhibin family and to some extent PAPP-A and placental growth factor are superior to other serum markers, and the predictive value of these depends on the gestational age at blood sampling. The availability of a single, early pregnancy 'miracle' serum marker for PE risk assessment seems unlikely in the near future.

Choosing Smoothness Parameters for Smoothing Splines by Minimizing and Estimate of Risk

Smoothing splines are a popular approach for non-parametric regression problems. We use periodic smoothing splines to fit a periodic signal plus noise model to data for which we assume there are underlying circadian patterns. In the smoothing spline methodology, choosing an appropriate smoothness parameter is an important step in practice. In this paper, we draw a connection between smoothing splines and REACT estimators that provides motivation for the creation of criteria for choosing the smoothness parameter. The new criteria are compared to three existing methods, namely cross-validation, generalized cross-validation, and generalization of maximum likelihood criteria, by a Monte Carlo simulation and by an application to the study of circadian patterns. For most of the situations presented in the simulations, including the practical example, the new criteria out-perform the three existing criteria.

Effect of mechanical and antiseptic therapy on peri-implant mucositis: an experimental study in monkeys

OBJECTIVES: This experiment was performed to evaluate clinically and histologically the effect of mechanical therapy with or without antiseptic therapy on peri-implant mucositis lesions in nine cynomolgus monkeys. MATERIAL AND METHODS: Two ITI titanium implants were inserted into each side of the mandibles. After 90 days of plaque control and soft tissue healing, a baseline clinical examination was completed. Peri-implant lesions were induced by placing silk ligatures and allowing plaque to accumulate for 6 weeks. The clinical examination was then repeated, and the monkeys were randomly assigned to three treatment groups: group A, mechanical cleansing only; group B, mechanical cleansing and local irrigation with 0.12% chlorhexidine (CHX) and application of 0.2% CHX gel; and group C, control, no treatment. The implants in treatment groups A and B were treated and maintained according to the assigned treatment for two additional months. At the end of the maintenance period, a final clinical examination was performed and the animals were sacrificed for biopsies. RESULTS: The mean probing depths (PD) values at mucositis were: 3.5, 3.7, and 3.4 mm, and clinical attachment level (CAL) = 3.8, 4.1, and 3.9 mm for treatment groups A, B and C, respectively. The corresponding values after treatment were: PD = 1.7, 2.1, and 2.5 mm, and CAL=2.6, 2.6, and 3.1 mm. ANOVA of mean changes (Delta) in PD and CAL after treatment showed no statistical difference between the treatment groups. Comparison of the mean changes in PD and CAL after treatment yielded statistical differences between the control and treatment groups P < 0.01. According to the t-test, no statistical difference was found between treatment groups A and B for the PD reduction but there was a significant difference for the CAL change, P < 0.03. Group A had significantly more recession and less CAL gain than group B. Non-parametric tests yielded no significant differences in modified plaque index (mPlI) and gingival index (GI) after treatment between both treatment groups. Frequencies and percent distributions of the mPlI and GI scores changed considerably for both treatment groups when compared with the changes in the control group after treatment. With regard to the histological evaluation, no statistical differences existed between the treatments for any linear measurement. The proportion of inflammation found in the mucosal tissues of the control implants was greater than the one found for both treatment groups, P < 0.01. More importantly, both treatment groups showed a similar low proportion of inflammation after 2 months of treatment. CONCLUSIONS: Within the limitations of this experiment, and considering the supportive plaque control rendered, it can be concluded that for pockets of 3-4 mm: (1) mechanical therapy alone or combined with CHX results in the clinical resolution of peri-implant mucositis lesions, (2) histologically, both treatments result in minimal inflammation compatible with health, and (3) the mechanical effect alone is sufficient to achieve clinical and histologic resolution of mucositis lesions.

Modeling multilevel sleep transitional data via Poisson log-linear multilevel models

This paper proposes Poisson log-linear multilevel models to investigate population variability in sleep state transition rates. We specifically propose a Bayesian Poisson regression model that is more flexible, scalable to larger studies, and easily fit than other attempts in the literature. We further use hierarchical random effects to account for pairings of individuals and repeated measures within those individuals, as comparing diseased to non-diseased subjects while minimizing bias is of epidemiologic importance. We estimate essentially non-parametric piecewise constant hazards and smooth them, and allow for time varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming piecewise constant hazards. This relationship allows us to synthesize two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed.

Truncated recombinant human SP-D attenuates emphysema and type II cell changes in SP-D deficient mice

BACKGROUND: Surfactant protein D (SP-D) deficient mice develop emphysema-like pathology associated with focal accumulations of foamy alveolar macrophages, an excess of surfactant phospholipids in the alveolar space and both hypertrophy and hyperplasia of alveolar type II cells. These findings are associated with a chronic inflammatory state. Treatment of SP-D deficient mice with a truncated recombinant fragment of human SP-D (rfhSP-D) has been shown to decrease the lipidosis and alveolar macrophage accumulation as well as production of proinflammatory chemokines. The aim of this study was to investigate if rfhSP-D treatment reduces the structural abnormalities in parenchymal architecture and type II cells characteristic of SP-D deficiency. METHODS: SP-D knock-out mice, aged 3 weeks, 6 weeks and 9 weeks were treated with rfhSP-D for 9, 6 and 3 weeks, respectively. All mice were sacrificed at age 12 weeks and compared to both PBS treated SP-D deficient and wild-type groups. Lung structure was quantified by design-based stereology at the light and electron microscopic level. Emphasis was put on quantification of emphysema, type II cell changes and intracellular surfactant. Data were analysed with two sided non-parametric Mann-Whitney U-test. MAIN RESULTS: After 3 weeks of treatment, alveolar number was higher and mean alveolar size was smaller compared to saline-treated SP-D knock-out controls. There was no significant difference concerning these indices of pulmonary emphysema within rfhSP-D treated groups. Type II cell number and size were smaller as a consequence of treatment. The total volume of lamellar bodies per type II cell and per lung was smaller after 6 weeks of treatment. CONCLUSION: Treatment of SP-D deficient mice with rfhSP-D leads to a reduction in the degree of emphysema and a correction of type II cell hyperplasia and hypertrophy. This supports the concept that rfhSP-D might become a therapeutic option in diseases that are characterized by decreased SP-D levels in the lung.

EVALUATING INFRASTRUCTURE PERFORMANCE TO ASSIST FACILITY MANAGEMENT TOWARD SUSTAINABLE SYSTEMS

Civil infrastructure provides essential services for the development of both society and economy. It is very important to manage systems efficiently to ensure sound performance. However, there are challenges in information extraction from available data, which also necessitates the establishment of methodologies and frameworks to assist stakeholders in the decision making process. This research proposes methodologies to evaluate systems performance by maximizing the use of available information, in an effort to build and maintain sustainable systems. Under the guidance of problem formulation from a holistic view proposed by Mukherjee and Muga, this research specifically investigates problem solving methods that measure and analyze metrics to support decision making. Failures are inevitable in system management. A methodology is developed to describe arrival pattern of failures in order to assist engineers in failure rescues and budget prioritization especially when funding is limited. It reveals that blockage arrivals are not totally random. Smaller meaningful subsets show good random behavior. Additional overtime failure rate is analyzed by applying existing reliability models and non-parametric approaches. A scheme is further proposed to depict rates over the lifetime of a given facility system. Further analysis of sub-data sets is also performed with the discussion of context reduction. Infrastructure condition is another important indicator of systems performance. The challenges in predicting facility condition are the transition probability estimates and model sensitivity analysis. Methods are proposed to estimate transition probabilities by investigating long term behavior of the model and the relationship between transition rates and probabilities. To integrate heterogeneities, model sensitivity is performed for the application of non-homogeneous Markov chains model. Scenarios are investigated by assuming transition probabilities follow a Weibull regressed function and fall within an interval estimate. For each scenario, multiple cases are simulated using a Monte Carlo simulation. Results show that variations on the outputs are sensitive to the probability regression. While for the interval estimate, outputs have similar variations to the inputs. Life cycle cost analysis and life cycle assessment of a sewer system are performed comparing three different pipe types, which are reinforced concrete pipe (RCP) and non-reinforced concrete pipe (NRCP), and vitrified clay pipe (VCP). Life cycle cost analysis is performed for material extraction, construction and rehabilitation phases. In the rehabilitation phase, Markov chains model is applied in the support of rehabilitation strategy. In the life cycle assessment, the Economic Input-Output Life Cycle Assessment (EIO-LCA) tools are used in estimating environmental emissions for all three phases. Emissions are then compared quantitatively among alternatives to support decision making.

Geospatial analysis of western juniper (Juniperus occidentalis) encroachment utilizing remotely sensed data

Utilizing remote sensing methods to assess landscape-scale ecological change are rapidly becoming a dominant force in the natural sciences. Powerful and robust non-parametric statistical methods are also actively being developed to compliment the unique characteristics of remotely sensed data. The focus of this research is to utilize these powerful, robust remote sensing and statistical approaches to shed light on woody plant encroachment into native grasslands--a troubling ecological phenomenon occurring throughout the world. Specifically, this research investigates western juniper encroachment within the sage-steppe ecosystem of the western USA. Western juniper trees are native to the intermountain west and are ecologically important by means of providing structural diversity and habitat for many species. However, after nearly 150 years of post-European settlement changes to this threatened ecosystem, natural ecological processes such as fire regimes no longer limit the range of western juniper to rocky refugia and other areas protected from short fire return intervals that are historically common to the region. Consequently, sage-steppe communities with high juniper densities exhibit negative impacts, such as reduced structural diversity, degraded wildlife habitat and ultimately the loss of biodiversity. Much of today's sage-steppe ecosystem is transitioning to juniper woodlands. Additionally, the majority of western juniper woodlands have not reached their full potential in both range and density. The first section of this research investigates the biophysical drivers responsible for juniper expansion patterns observed in the sage-steppe ecosystem. The second section is a comprehensive accuracy assessment of classification methods used to identify juniper tree cover from multispectral 1 m spatial resolution aerial imagery.

Virtual implant planning in the edentulous maxilla: criteria for decision making of prosthesis design

OBJECTIVES To evaluate prosthetic parameters in the edentulous anterior maxilla for decision making between fixed and removable implant prosthesis using virtual planning software. MATERIAL AND METHODS CT- or DVT-scans of 43 patients (mean age 62 ± 8 years) with an edentulous maxilla were analyzed with the NobelGuide software. Implants (≥3.5 mm diameter, ≥10 mm length) were virtually placed in the optimal three-dimensional prosthetic position of all maxillary front teeth. Anatomical and prosthetic landmarks, including the cervical crown point (C-Point), the acrylic flange border (F-Point), and the implant-platform buccal-end (I-Point) were defined in each middle section to determine four measuring parameters: (1) acrylic flange height (FLHeight), (2) mucosal coverage (MucCov), (3) crown-Implant distance (CID) and (4) buccal prosthesis profile (ProsthProfile). Based on these parameters, all patients were assigned to one of three classes: (A) MucCov ≤ 0 mm and ProsthProfile≥45(0) allowing for fixed prosthesis, (B) MucCov = 0-5 mm and/or ProsthProfile = 30(0) -45(0) probably allowing for fixed prosthesis, and (C) MucCov ≥ 5 mm and/or ProsthProfile ≤ 30(0) where removable prosthesis is favorable. Statistical analyses included descriptive methods and non-parametric tests. RESULTS Mean values were for FLHeight 10.0 mm, MucCov 5.6 mm, CID 7.4 mm, and ProsthProfile 39.1(0) . Seventy percent of patients fulfilled class C criteria (removable), 21% class B (probably fixed), and 2% class A (fixed), while in 7% (three patients) bone volume was insufficient for implant planning. CONCLUSIONS The proposed classification and virtual planning procedure simplify the decision-making process regarding type of prosthesis and increase predictability of esthetic treatment outcomes. It was demonstrated that in the majority of cases, the space between the prosthetic crown and implant platform had to be filled with prosthetic materials.

In vitro precision of fit of computer-aided designed and computer-aided manufactured titanium screw-retained fixed dental prostheses before and after ceramic veneering

OBJECTIVE To compare the precision of fit of full-arch implant-supported screw-retained computer-aided designed and computer-aided manufactured (CAD/CAM) titanium-fixed dental prostheses (FDP) before and after veneering. The null-hypothesis was that there is no difference in vertical microgap values between pure titanium frameworks and FDPs after porcelain firing. MATERIALS AND METHODS Five CAD/CAM titanium grade IV frameworks for a screw-retained 10-unit implant-supported reconstruction on six implants (FDI tooth positions 15, 13, 11, 21, 23, 25) were fabricated after digitizing the implant platforms and the cuspid-supporting framework resin pattern with a laser scanner (CARES(®) Scan CS2; Institut Straumann AG, Basel, Switzerland). A bonder, an opaquer, three layers of porcelain, and one layer of glaze were applied (Vita Titankeramik) and fired according to the manufacturer's preheating and fire cycle instructions at 400-800°C. The one-screw test (implant 25 screw-retained) was applied before and after veneering of the FDPs to assess the vertical microgap between implant and framework platform with a scanning electron microscope. The mean microgap was calculated from interproximal and buccal values. Statistical comparison was performed with non-parametric tests. RESULTS All vertical microgaps were clinically acceptable with values <90 μm. No statistically significant pairwise difference (P = 0.98) was observed between the relative effects of vertical microgap of unveneered (median 19 μm; 95% CI 13-35 μm) and veneered FDPs (20 μm; 13-31 μm), providing support for the null-hypothesis. Analysis within the groups showed significantly different values between the five implants of the FDPs before (P = 0.044) and after veneering (P = 0.020), while a monotonous trend of increasing values from implant 23 (closest position to screw-retained implant 25) to 15 (most distant implant) could not be observed (P = 0.169, P = 0.270). CONCLUSIONS Full-arch CAD/CAM titanium screw-retained frameworks have a high accuracy. Porcelain firing procedure had no impact on the precision of fit of the final FDPs. All implant microgap measurements of each FDP showed clinically acceptable vertical misfit values before and after veneering. Thus, the results do not only show accurate performance of the milling and firing but show also a reproducible scanning and designing process.

Gonadotrophin stimulation for in vitro fertilization significantly alters the hormone milieu in follicular fluid: a comparative study between natural cycle IVF and conventional IVF.

STUDY QUESTION Is the steroid hormone profile in follicular fluid (FF) at the time of oocyte retrieval different in naturally matured follicles, as in natural cycle IVF (NC-IVF), compared with follicles stimulated with conventional gonadotrophin stimulated IVF (cIVF)? SUMMARY ANSWER Anti-Mullerian hormone (AMH), testosterone (T) and estradiol (E2) concentrations are ∼3-fold higher, androstenedione (A2) is ∼1.5-fold higher and luteinizing hormone (LH) is ∼14-fold higher in NC-IVF than in cIVF follicles, suggesting an alteration of the follicular metabolism in conventional gonadotrophin stimulated IVF. WHAT IS KNOWN ALREADY In conventional IVF, the implantation rate of unselected embryos appears to be lower than in NC-IVF, which is possibly due to negative effects of the stimulation regimen on follicular metabolism. In NC-IVF, the intrafollicular concentration of AMH has been shown to be positively correlated with the oocyte fertilization and implantation rates. Furthermore, androgen treatment seems to improve the ovarian response in low responders. STUDY DESIGN, SIZE, DURATION This cross-sectional study involving 36 NC-IVF and 40 cIVF cycles was performed from 2011 to 2013. Within this population, 13 women each underwent 1 NC-IVF and 1 cIVF cycle. cIVF was performed by controlled ovarian stimulation with HMG and GnRH antagonists. PARTICIPANTS/MATERIALS, SETTING, METHODS Follicular fluid was collected from the leading follicles. AMH, T, A2, dehydroepiandrosterone (DHEA), E2, FSH, LH and progesterone (P) were determined by immunoassays in 76 women. Aromatase activity in follicular fluid cells was analysed by a tritiated water release assay in 33 different women. For statistical analysis, the non-parametric Mann-Whitney U or Wilcoxon tests were used. MAIN RESULTS AND ROLE OF CHANCE In follicular fluid from NC-IVF and from cIVF, median levels were 32.8 and 10.7 pmol/l for AMH (P < 0.0001), 47.2 and 18.8 µmol/l for T (P < 0.0001), 290 and 206 nmol/l for A2 (P = 0.0035), 6.7 and 5.6 pg/ml for DHEA (n.s.), 3292 and 1225 nmol/l for E2 (P < 0.0001), 4.9 and 7.2 mU/ml for FSH (P < 0.05), 14.4 and 0.9 mU/ml for LH (P < 0.0001) and 62 940 and 54 710 nmol/l for P (n.s.), respectively. Significant differences in follicular fluid concentrations for AMH, E2 and LH were also found in the 13 patients who underwent both NC-IVF and cIVF when they were analysed separately in pairs. Hormone analysis in serum excluded any relevant impact of AMH, T, A2, and E2 serum concentration on the follicular fluid hormone concentrations. Median serum concentrations were 29.4 and 0.9 mU/ml for LH (P < 0.0001) and 2.7 and 23.5 nmol/l for P (P < 0.0001) after NC-IVF and c-IVF, respectively. Positive correlations were seen for FF-AMH with FF-T (r = 0.35, P = 0.0002), FF-T with FF-LH (r = 0.48, P < 0.0001) and FF-E2 with FF-T (r = 0.75, P < 0.0001). The analysis of aromatase activity was not different in NC-IVF and cIVF follicular cells. LIMITATION, REASONS FOR CAUTION Any association between the hormone concentrations and the implantation potential of the oocytes could not be investigated as the oocytes in cIVF were not treated individually in the IVF laboratory. Since both c-IVF and NC-IVF follicles were stimulated by hCG before retrieval, the endocrine milieu in the natural cycle does not represent the pure physiological situation. WIDER IMPLICATIONS OF THE FINDINGS The endocrine follicular milieu and the concentration of putative markers of oocyte quality, such as AMH, are significantly different in gonadotrophin-stimulated conventional IVF compared with natural cycle IVF. This could be a cause for the suggested lower oocyte quality in cIVF compared with naturally matured oocytes. The reasons for the reduced AMH concentration might be low serum and follicular fluid LH concentrations due to LH suppression, leading initially to low follicular androgen concentrations and then to low follicular AMH production. STUDY FUNDING/COMPETING INTERESTS Funding for this study was obtained from public universities (for salaries) and private industry (for consumables). Additionally, the study was supported by an unrestricted grant from MSD Merck Sharp & Dohme GmbH and IBSA Institut Biochimique SA. The authors are clinically involved in low-dose monofollicular stimulation and IVF therapies, using gonadotrophins from all gonadotrophin distributors on the Swiss market, including Institut Biochimique SA and MSD Merck Sharp & Dohme GmbH. Otherwise, the authors have no competing interests. TRIAL REGISTRATION NUMBER Not applicable.

A BAYESIAN APPROACH TO DOSE-RESPONSE ASSESSMENT AND DRUG-DRUG INTERACTION ANALYSIS: APPLICATION TO IN VITRO STUDIES

The considerable search for synergistic agents in cancer research is motivated by the therapeutic benefits achieved by combining anti-cancer agents. Synergistic agents make it possible to reduce dosage while maintaining or enhancing a desired effect. Other favorable outcomes of synergistic agents include reduction in toxicity and minimizing or delaying drug resistance. Dose-response assessment and drug-drug interaction analysis play an important part in the drug discovery process, however analysis are often poorly done. This dissertation is an effort to notably improve dose-response assessment and drug-drug interaction analysis. The most commonly used method in published analysis is the Median-Effect Principle/Combination Index method (Chou and Talalay, 1984). The Median-Effect Principle/Combination Index method leads to inefficiency by ignoring important sources of variation inherent in dose-response data and discarding data points that do not fit the Median-Effect Principle. Previous work has shown that the conventional method yields a high rate of false positives (Boik, Boik, Newman, 2008; Hennessey, Rosner, Bast, Chen, 2010) and, in some cases, low power to detect synergy. There is a great need for improving the current methodology. We developed a Bayesian framework for dose-response modeling and drug-drug interaction analysis. First, we developed a hierarchical meta-regression dose-response model that accounts for various sources of variation and uncertainty and allows one to incorporate knowledge from prior studies into the current analysis, thus offering a more efficient and reliable inference. Second, in the case that parametric dose-response models do not fit the data, we developed a practical and flexible nonparametric regression method for meta-analysis of independently repeated dose-response experiments. Third, and lastly, we developed a method, based on Loewe additivity that allows one to quantitatively assess interaction between two agents combined at a fixed dose ratio. The proposed method makes a comprehensive and honest account of uncertainty within drug interaction assessment. Extensive simulation studies show that the novel methodology improves the screening process of effective/synergistic agents and reduces the incidence of type I error. We consider an ovarian cancer cell line study that investigates the combined effect of DNA methylation inhibitors and histone deacetylation inhibitors in human ovarian cancer cell lines. The hypothesis is that the combination of DNA methylation inhibitors and histone deacetylation inhibitors will enhance antiproliferative activity in human ovarian cancer cell lines compared to treatment with each inhibitor alone. By applying the proposed Bayesian methodology, in vitro synergy was declared for DNA methylation inhibitor, 5-AZA-2'-deoxycytidine combined with one histone deacetylation inhibitor, suberoylanilide hydroxamic acid or trichostatin A in the cell lines HEY and SKOV3. This suggests potential new epigenetic therapies in cell growth inhibition of ovarian cancer cells.

A nonparametric method of comparing the partial areas under two correlated receiver operating characteristic curves

A non-parametric method was developed and tested to compare the partial areas under two correlated Receiver Operating Characteristic curves. Based on the theory of generalized U-statistics the mathematical formulas have been derived for computing ROC area, and the variance and covariance between the portions of two ROC curves. A practical SAS application also has been developed to facilitate the calculations. The accuracy of the non-parametric method was evaluated by comparing it to other methods. By applying our method to the data from a published ROC analysis of CT image, our results are very close to theirs. A hypothetical example was used to demonstrate the effects of two crossed ROC curves. The two ROC areas are the same. However each portion of the area between two ROC curves were found to be significantly different by the partial ROC curve analysis. For computation of ROC curves with large scales, such as a logistic regression model, we applied our method to the breast cancer study with Medicare claims data. It yielded the same ROC area computation as the SAS Logistic procedure. Our method also provides an alternative to the global summary of ROC area comparison by directly comparing the true-positive rates for two regression models and by determining the range of false-positive values where the models differ. ^