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

Decomposition Analysis for the Comparison and the Comprehension of Conventional Input-Output Impacts’ Indicators: An Empirical Paradigm

Sometimes, the priorities in the growing patterns create dubiousness, surprises and are proved unsuitable to re-form and redress the distortions of economy, magnifying them or even emerging news. When the external or the individual interferences are remained out of the planning, then the knowledge of why the various indices yield conflicting sectoral rankings can help the policy-makers to plan ameliorated strategies. In this paper a decomposition analysis for the components of conventional backward linkages’ (BLs’) indices and the corresponding type I multipliers (t.I-Ms’) has been taken place, in order to support the comparison and the comprehension of conflictions that are recorded on their derived sectoral rankings. For the empirical paradigm, data from the Greek economy have been used. The indicators’ appropriateness for the developmental planning has been scrutinized giving an emphasis on the model’s causality, the initial exogenous stimuli and the “intrasectoral initial trends for impacts’ generation”. The analysis provides a proof that the BL’s indices are strongly tendentious and the t.I-Ms’ are preferable for the medium-to-long run growing planning.JEL Codes - C18; C67; E61; O2

Input-Output Models and Derived Indicators: A Critical Review

Input-Output literature can be characterized as complicated and chaotic. The complications concern the nomenclature of concepts for the derived indices from the multipliers’ models, their mathematical expressions and computable applications. The terminologies’ inconsistencies often end up to a deviation between the description for these indices and their actual computation, or/and to a misunderstanding as for their usefulness and outcomes. The aim of the paper is to help the readers to face the weaknesses in the literature. In this way, the paper provide an overview with a critical look to the constructed multipliers’ matrices and their derived indicators from the I-O models, and elaborate the causes for the scrutinized confusions. The paper proposes both terminological and computational adjustments and differentiated approaches for the models and their indices, in order to ameliorate their capabilities and to exploit their peculiarities for the developmental patterns. Alternative interpretative ways and applicable expansions are suggested.JEL Codes - C18, C31, C67, F43, O2

The route to transcription initiation determines the mode of transcriptional bursting in E. coli

Transcription is fundamentally noisy, leading to significant heterogeneity across bacterial populations. Noise is often attributed to burstiness, but the underlying mechanisms and their dependence on the mode of promotor regulation remain unclear. Here, we measure E. coli single cell mRNA levels for two stress responses that depend on bacterial sigma factors with different mode of transcription initiation (sigma (70) and sigma (54)). By fitting a stochastic model to the observed mRNA distributions, we show that the transition from low to high expression of the sigma (70)-controlled stress response is regulated via the burst size, while that of the sigma (54)-controlled stress response is regulated via the burst frequency. Therefore, transcription initiation involving sigma (54) differs from other bacterial systems, and yields bursting kinetics characteristic of eukaryotic systems. Transcription noise in bacteria is often attributed to burstiness, but the mechanisms are unclear. Here, the authors show that the transition from low to high expression can be regulated via burst size or burst frequency, depending on the mode of transcription initiation determined by different sigma factors

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

Toxicity of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) in the developing male Wistar(Han) rat II: chronic dosing causes developmental delay

We have investigated whether fetal exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) causes defects in the male reproductive system of the rat, using chronically exposed rats to ensure continuous exposure of the fetus. 5-6 week old rats were exposed to control diet, or diet containing TCDD, to attain an average dose of 2.4, 8 and 46 ng TCDD kg-1 day-1 for twelve weeks, whereupon the rats were mated, and allowed to litter; rats were switched to control diet after parturition. Male offspring were allowed to develop until kills on PND70 (25 per group), or PND120 (all remaining animals). Offspring from the high dose group showed an increase in total litter loss, and the number of animals alive on post-natal day (PND) 4 in the high dose group was ~26% less than control. The high and medium dose offspring showed decreased weights at various ages. Balano-preputial separation was significantly delayed in all three dose groups, compared to control. There were no significant effects of maternal treatment when the offspring were subjected to a functional observational battery, or learning tests, with the exception that the high dose group showed a deficit in motor activity. 20 rats per group were mated to females, and there were no significant effects of maternal treatment on the fertility of these rats, nor on the F1 or F2 sex ratio. Sperm parameters at PND70 and 120 showed no significant effect of maternal treatment, with the exception that there was an increase in the proportion of abnormal sperm in the high dose group at PND70; this is associated with the developmental delay in puberty in this dose group. There were no remarkable findings of maternal treatment on organ weights, with the exception that testis weights were reduced by ~10% at PND70 (but not PND120), and although the experiment was sufficiently powered to detect small changes, ventral prostate weight was not reduced. There were no significant effects of maternal treatment upon histopathological comparison of high dose and control group organs. These data confirm that developmental exposure to TCDD shows no potent effect on adult sperm parameters or accessory sexual organs, but show that delay in BPS occurs after exposure to low doses of TCDD, and this is dependent upon whether TCDD is administered acutely or chronically

A stochastic model for the evolution of the web allowing link deletion

Recently several authors have proposed stochastic evolutionary models for the growth of the web graph and other networks that give rise to power-law distributions. These models are based on the notion of preferential attachment leading to the ``rich get richer'' phenomenon. We present a generalisation of the basic model by allowing deletion of individual links and show that it also gives rise to a power-law distribution. We derive the mean-field equations for this stochastic model and show that by examining a snapshot of the distribution at the steady state of the model, we are able to tell whether any link deletion has taken place and estimate the link deletion probability. Our model enables us to gain some insight into the distribution of inlinks in the web graph, in particular it suggests a power-law exponent of approximately 2.15 rather than the widely published exponent of 2.1