Uncertainty in financial models of large and complex government projects.

Government financial models, a particular type of deterministic computer model, are created in order to estimate the cost of expensive projects with large time frames. The model is a function of many inputs, most of which are taken to be known. However the value of a small number of inputs X is unknown. Whilst the precise value of X is unknown, subjective knowledge about X can be represented by a joint probability distribution G(x). As a result of the uncertainty in X, the scalar output of the financial model is the random variable, Y. The main focus of this thesis is in learning about the uncertainty in Y that results from uncertainty in X (uncertainty analysis), and in determining which elements of X are most (and least) important in driving the uncertainty in Y (sensitivity analysis). In principle both uncertainty and sensitivity analyses can be conducted using Monte Carlo. This method requires a large number of model evaluations. We are interested in the case where the computer model is too computationally expensive to make Monte Carlo practical. We consider a Bayesian approach, which uses the Gaussian Process prior for unknown functions in order to make inference about the computer model itself, using a small number of model evaluations. We then use this information about the structure of the computer model in order to perform uncertainty and sensitivity analyses using relatively few runs of the model. In this thesis, we adapt the standard Gaussian Process prior in order to utilize the additional information we have about the structure of government financial models. 'We develop methodology for calculating measures of uncertainty and sensitivity based upon a Gaussian Process model. The methodology also utilizes the additional structural information within government financial models. Finally, we develop elicitation methodology for use in determining the joint probability distribution G(x). We provide an example from the Private Finance Initiative

A Workflow for Global Sensitivity Analysis of PBPK Models

Physiologically based pharmacokinetic (PBPK) models have a potentially significant role in the development of a reliable predictive toxicity testing strategy. The structure of PBPK models are ideal frameworks into which disparate in vitro and in vivo data can be integrated and utilized to translate information generated, using alternative to animal measures of toxicity and human biological monitoring data, into plausible corresponding exposures. However, these models invariably include the description of well known non-linear biological processes such as, enzyme saturation and interactions between parameters such as, organ mass and body mass. Therefore, an appropriate sensitivity analysis (SA) technique is required which can quantify the influences associated with individual parameters, interactions between parameters and any non-linear processes. In this report we have defined the elements of a workflow for SA of PBPK models that is computationally feasible, accounts for interactions between parameters, and can be displayed in the form of a bar chart and cumulative sum line (Lowry plot), which we believe is intuitive and appropriate for toxicologists, risk assessors, and regulators

Quantitative global sensitivity analysis of a biologically based dose-response pregnancy model for the thyroid endocrine system

A deterministic biologically based dose-response model for the thyroidal system in a near-term pregnant woman and the fetus was recently developed to evaluate quantitatively thyroid hormone perturbations. The current work focuses on conducting a quantitative global sensitivity analysis on this complex model to identify and characterize the sources and contributions of uncertainties in the predicted model output. The workflow and methodologies suitable for computationally expensive models, such as the Morris screening method and Gaussian Emulation processes, were used for the implementation of the global sensitivity analysis. Sensitivity indices, such as main, total and interaction effects, were computed for a screened set of the total thyroidal system descriptive model input parameters. Furthermore, a narrower sub-set of the most influential parameters affecting the model output of maternal thyroid hormone levels were identified in addition to the characterization of their overall and pair-wise parameter interaction quotients. The characteristic trends of influence in model output for each of these individual model input parameters over their plausible ranges were elucidated using Gaussian Emulation processes. Through global sensitivity analysis we have gained a better understanding of the model behavior and performance beyond the domains of observation by the simultaneous variation in model inputs over their range of plausible uncertainties. The sensitivity analysis helped identify parameters that determine the driving mechanisms of the maternal and fetal iodide kinetics, thyroid function and their interactions, and contributed to an improved understanding of the system modeled. We have thus demonstrated the use and application of global sensitivity analysis for a biologically based dose-response model for sensitive life-stages such as pregnancy that provides richer information on the model and the thyroidal system modeled compared to local sensitivity analysis

Reconstruction of Exposure to m-Xylene from Human Biomonitoring Data Using PBPK Modelling, Bayesian Inference, and Markov Chain Monte Carlo Simulation

There are numerous biomonitoring programs, both recent and ongoing, to evaluate environmental exposure of humans to chemicals. Due to the lack of exposure and kinetic data, the correlation of biomarker levels with exposure concentrations leads to difficulty in utilizing biomonitoring data for biological guidance values. Exposure reconstruction or reverse dosimetry is the retrospective interpretation of external exposure consistent with biomonitoring data. We investigated the integration of physiologically based pharmacokinetic modelling, global sensitivity analysis, Bayesian inference, and Markov chain Monte Carlo simulation to obtain a population estimate of inhalation exposure to m-xylene. We used exhaled breath and venous blood m-xylene and urinary 3-methylhippuric acid measurements from a controlled human volunteer study in order to evaluate the ability of our computational framework to predict known inhalation exposures. We also investigated the importance of model structure and dimensionality with respect to its ability to reconstruct exposure

Individual calcium syntillas do not trigger spontaneous exocytosis from nerve terminals of the neurohypophysis

Recently, highly localized Ca(2+) release events, similar to Ca(2+) sparks in muscle, have been observed in neuronal preparations. Specifically, in murine neurohypophysial terminals (NHT), these events, termed Ca(2+) syntillas, emanate from a ryanodine-sensitive intracellular Ca(2+) pool and increase in frequency with depolarization in the absence of Ca(2+) influx. Despite such knowledge of the nature of these Ca(2+) release events, their physiological role in this system has yet to be defined. Such localized Ca(2+) release events, if they occur in the precise location of the final exocytotic event(s), may directly trigger exocytosis. However, directly addressing this hypothesis has not been possible, since no method capable of visualizing individual release events in these CNS terminals has been available. Here, we have adapted an amperometric method for studying vesicle fusion to this system which relies on loading the secretory granules with the false transmitter dopamine, thus allowing, for the first time, the recording of individual exocytotic events from peptidergic NHT. Simultaneous use of this technique along with high-speed Ca(2+) imaging has enabled us to establish that spontaneous neuropeptide release and Ca(2+) syntillas do not display any observable temporal or spatial correlation, confirming similar findings in chromaffin cells. Although these results indicate that syntillas do not play a direct role in eliciting spontaneous release, they do not rule out indirect modulatory effects of syntillas on secretion

miR-17 overexpression in cystic fibrosis airway epithelial cells decreases interleukin-8 production.

Interleukin (IL)-8 levels are higher than normal in cystic fibrosis (CF) airways, causing neutrophil infiltration and non-resolving inflammation. Overexpression of microRNAs that target IL-8 expression in airway epithelial cells may represent a therapeutic strategy for cystic fibrosis. IL-8 protein and mRNA were measured in cystic fibrosis and non-cystic fibrosis bronchoalveolar lavage fluid and bronchial brushings (n=20 per group). miRNAs decreased in the cystic fibrosis lung and predicted to target IL-8 mRNA were quantified in βENaC-transgenic, cystic fibrosis transmembrane conductance regulator (Cftr)-/- and wild-type mice, primary cystic fibrosis and non-cystic fibrosis bronchial epithelial cells and a range of cystic fibrosis versus non-cystic fibrosis airway epithelial cell lines or cells stimulated with lipopolysaccharide, Pseudomonas-conditioned medium or cystic fibrosis bronchoalveolar lavage fluid. The effect of miRNA overexpression on IL-8 protein production was measured. miR-17 regulates IL-8 and its expression was decreased in adult cystic fibrosis bronchial brushings, βENaC-transgenic mice and bronchial epithelial cells chronically stimulated with Pseudomonas-conditioned medium. Overexpression of miR-17 inhibited basal and agonist-induced IL-8 protein production in F508del-CFTR homozygous CFTE29o(-) tracheal, CFBE41o(-) and/or IB3 bronchial epithelial cells. These results implicate defective CFTR, inflammation, neutrophilia and mucus overproduction in regulation of miR-17. Modulating miR-17 expression in cystic fibrosis bronchial epithelial cells may be a novel anti-inflammatory strategy for cystic fibrosis and other chronic inflammatory airway diseases

Finite element investigation of the effect of spina bifida on loading of the vertebral isthmus

Background: Spondylolysis (SL) of the lower lumbar spine is frequently associated with spina bifida occulta (SBO). There has not been any study that has demonstrated biomechanical or genetic predispositions to explain the coexistence of these two pathologies. In axial rotation, the intact vertebral arch allows torsional load to be shared between the facet joints. In SBO, the load cannot be shared across the arch, theoretically increasing the mechanical demand of the vertebral isthmus during combined axial loading and rotation when compared to the normal state. Purpose: To test the hypothesis that fatigue failure limits will be exceeded in the case of a bifid arch, but not in the intact case, when the segment is subjected to complex loading corresponding to normal sporting activities. Study Design: Descriptive Laboratory Study. Methods: Finite element models of natural and SBO (L4-S1) including ligaments were loaded axially to 1kN and were combined with axial rotation of 3°. Bilateral stresses, alternating stresses and shear fatigue failure on intact and SBO L5 isthmus were assessed and compared. Results: Under 1kN axial load, the von Mises stresses observed in SBO and in the intact cases were very similar (differences <5MPa) having a maximum at the ventral end of the isthmus that decreases monotonically to the dorsal end. However, under 1kN axial load and rotation, the maximum von Mises stresses observed in the ipsilateral L5 isthmus in the SBO case (31MPa) was much higher than the intact case (24.2MPa) indicating a lack of load sharing across the vertebral arch in SBO. When assessing the equivalent alternating shear stress amplitude, this was found to be 22.6 MPa for the SBO case and 13.6 MPa for the intact case. From this it is estimated that shear fatigue failure will occur in less than 70,000 cycles, under repetitive axial load & rotation conditions in the SBO case, while for the intact case, fatigue failure will occur only over 10 million cycles. Conclusion: SBO predisposes spondylolysis by generating increased stresses across the inferior isthmus of the inferior articular process, specifically in combined axial rotation and anteroposterior shear. Clinical Relevance: Athletes with SBO who participate in sports that require repetitive lumbar rotation, hyperextension and/or axial loading are at a higher risk of developing spondylolysis compared to athletes with an intact spine

Mapping Physiological Suitability Limits for Malaria in Africa Under Climate Change

We mapped current and future temperature suitability for malaria transmission in Africa using a published model that incorporates nonlinear physiological responses to temperature of the mosquito vector Anopheles gambiae and the malaria parasite Plasmodium falciparum. We found that a larger area of Africa currently experiences the ideal temperature for transmission than previously supposed. Under future climate projections, we predicted a modest increase in the overall area suitable for malaria transmission, but a net decrease in the most suitable area. Combined with human population density projections, our maps suggest that areas with temperatures suitable for year-round, highest-risk transmission will shift from coastal West Africa to the Albertine Rift between the Democratic Republic of Congo and Uganda, whereas areas with seasonal transmission suitability will shift toward sub-Saharan coastal areas. Mapping temperature suitability places important bounds on malaria transmissibility and, along with local level demographic, socioeconomic, and ecological factors, can indicate where resources may be best spent on malaria control