Scientific basis for uncertainty factors used to establish occupational exposure limits for pharmaceutical active ingredients

The traditional “safety factor”; method has been used for years to establish occupational exposure limits (OELs) for active ingredients used in drugs. In the past, a single safety factor was used to address all sources of uncertainty in the limit setting process. The traditional 100‐fold safety factor commonly used to derive an acceptable daily intake value incorporates a default factor of 10 each to account for interindividual variability and interspecies extrapolation. Use of these defaults can lead to overly conservative health‐based limits, especially when they are combined with other (up to 10‐fold) factors to adjust for inadequacies in the available database. In recent years, attempts have been made to quantitate individual sources of uncertainty and variability to improve the scientific basis for OELs. In this paper we discuss the science supporting reductions in the traditional default uncertainty factors. A number of workplace‐specific factors also support reductions in these factors. Recently proposed alternative methodologies provide a framework to make maximum use of preclinical and clinical information, e.g., toxicokinetic and toxicodynamic data, to reduce uncertainties when establishing OELs for pharmaceutical active ingredients.     

Reasoning in uncertainties. An analysis of five strategies and their suitability in pathology

In reasoning systems, uncertainty plays a crucial part, especially for those fields in which judgements are essential, as in pathology. Uncertainty has several aspects, such as prevalence of diseases, occurrence of findings and the sensitivity and predictive value of findings. For the functioning of a reasoning system, two aspects are crucial: (1) the internal representation of the uncertainty and (2) the way in which the uncertainty is propagated in the reasoning process when combining formal statements. Five well-known reasoning strategies (Bayes' probability theory, MYCIN's certainty factor model, fuzzy set theory, the theory of Dempster-Shafer and Pathfinder's scoring mechanism) are compared, with particular attention to: (1) Under what conditions will the model function? In particular, what information is to be specified a priori to the system? (2) Can the different aspects of uncertainty be dealt with as separate entities? (3) How are unknown uncertainties dealt with? (4) How is evidence in favor of a hypothesis combined with evidence against it? (5) How does the model treat the simultaneous occurrence of more than one disorder, that is, how does the model support reasoning with compound hypotheses? It is preliminarily concluded that the different aspects of uncertainty are expressed as separate entities only in Pathfinder and probability theory. Hence, the other models do not accurately represent uncertain knowledge. Also, such theoretically attractive models as the Bayes, MYCIN and Dempster-Shafer theory can only function properly under the tight condition of mutual exclusiveness of hypotheses, which is not always suited for broader areas of pathology. They may, however, be suited for smaller areas, with a limited number of defined diseases and a limited number of features. All models but the Bayes model lack a predictable performance since there is no (or only a partial) underlying theory to guarantee minimization of the overall error.     

Use, misuse and extensions of "ideal gas" models of animal encounter

Biologists have repeatedly rediscovered classical models from physics predicting collision rates in an ideal gas. These models, and their two-dimensional analogues, have been used to predict rates and durations of encounters among animals or social groups that move randomly and independently, given population density, velocity, and distance at which an encounter occurs. They have helped to separate cases of mixed-species association based on behavioural attraction from those that simply reflect high population densities, and to detect cases of attraction or avoidance among conspecifics. They have been used to estimate the impact of population density, speeds of movement and size on rates of encounter between members of the opposite sex, between gametes, between predators and prey, and between observers and the individuals that they are counting. One limitation of published models has been that they predict rates of encounter, but give no means of determining whether observations differ significantly from predictions. Another uncertainty is the robustness of the predictions when animal movements deviate from the model's assumptions in specific, biologically relevant ways. Here, we review applications of the ideal gas model, derive extensions of the model to cover some more realistic movement patterns, correct several errors that have arisen in the literature, and show how to generate confidence limits for expected rates of encounter among independently moving individuals. We illustrate these results using data from mangabey monkeys originally used along with the ideal gas model to argue that groups avoid each other. Although agent-based simulations provide a more flexible alternative approach, the ideal gas model remains both a valuable null model and a useful, less onerous, approximation to biological reality.     

慢性支气管炎动物模型研究进展

慢性支气管炎是呼吸系统发病率和死亡率高的一种重要原因,临床和基础研究进展缓慢。吸入烟雾、空气污染物与职业接触慢性刺激传导气道是慢性支气管炎发病的关键因素。近年来虽提出各种各样动物模型,但具实用价值者仍极有限。复制慢性支气管炎动物模型有周期长、个体差异大、检测困难及可靠性差等问题。本文简要介绍烟熏、吸入SO2与气管内滴注脂多糖等最常用的慢性支气管炎动物模型的研究进展。将有益于抗慢性支气管炎药物研究时的更多选择应用。     

Evaluating the Relationship Between Variance in Enzyme Expression and Toxicant Concentration in Health Risk Assessment

The replacement of default uncertainty factors with those based on chemical-specific data is a topic of interest to a growing number of government-based organizations and those in affiliated professional societies. The division of the uncertainty factors for animal-to-human extrapolation and human interindividual variance (UF_A and UF_H, respectively) into their pharmacodynamic (PD) and pharmacokinetic (PK) components invites additional and specific considerations. Where data are available, or substantiated PK models have been developed, the animal-to-human chemical-specific differences have been quantified and utilized to replace the PK component of the uncertainty factor. The increasing degree to which the genome is being characterized has stimulated additional interest in describing the impact of genetic polymorphisms on susceptibility. Frequently, proteins for which the genes are being evaluated are the group of xenobiotic metabolizing enzymes. In-depth understanding of the genetic polymorphisms of genes coding for Aldehyde dehydrogenase, glucuronyl transferase and cytochrome P450 enzyme forms has been combined with information on the bioactivation or detoxication of environmental contaminants. The preliminary conclusion of some of these considerations is that alterations in enzyme content or enzyme activity result in a de facto alteration of risk. While this may be true of the “all-or-none” genetic alterations, the impact of more subtle changes in enzyme content and/or activity are more difficult to predict. The hepatotoxicity of trichloroethylene (TCE) is dependent upon an initial, cytochrome P450 2E1 (CYP2E1)-mediated oxidative step. Variance of CYP2E1 content of human liver has been characterized from a bank of tissues from human organ donors and combined with data describing the in vitro Michaelis-Menten kinetic parameters in order to extrapolate the metabolic capacity (and variance thereof) from in vitro to in vivo and assess its impact on PK through incorporation in a physiologically based pharmacokinetic (PBPK) model. This presentation summarizes that work, and demonstrates and discusses why extremes of CYP2E1-mediated metabolic capacity in adult humans has virtually no impact on the PK metric most closely related to hepatotoxic injury from TCE exposure.     

Establishing Data-Derived Adjustment Factors from Published Pharmaceutical Clinical Trial Data

In non-cancer risk assessment the goal traditionally has been to protect the majority of people by setting limits that account for interindividual variability in the human population. The Environmental Protection Agency (EPA) has assigned a default uncertainty factor (?UF) of 10 to account for interindividual variability in response to toxic agents in the general population. Previous studies have suggested that it is appropriate to equally divide this factor into sub-factors of 3.2 each for variability in human pharmacokinetics (PK) and pharmacodynamics (PD). As an extension of this model, one can envision using scientific data from the literature to modify the default sub-factors with compound-specific adjustment factors (AFs) and to create new and more scientifically based defaults. In this paper, data from published clinical trials on six pharmaceutical compounds were used to further illustrate how to calculate and interpret data-derived AFs. The clinical trial data were analyzed for content and the reported mean and standard deviation values for two key PK parameters, area under the curve of blood concentration by time (AUC) and peak plasma concentration (C_max), were evaluated. The mean PK values for each study were subsequently analyzed for variability within the population (unimodal distributions) and for the presence of potentially susceptible sub-populations (bimodal distributions). A method based on the proportion of the population covered was applied and data-derived AFs were calculated for these six compounds. Our results showed that, of the 15 possible data-derived AFs calculated using unimodal and bimodal distributions, only three exceeded a value of 3.2. This study further illustrates the value of calculating data-derived values when sufficient PK data are available.     

Morphological relationship between the cranial and supraorbital regions in Homo sapiens

Although some hypotheses that attempt to explain the variation in supraorbital region morphology in modern humans have been proposed, this issue is still not well understood. In this study, the craniofacial size and spatial models were tested using a sample of modern human crania from geographically diverse populations, and the co‐occurrence of the degrees of glabella (GL) and superciliary arch (ST) expression were analyzed. The two supraorbital structures were examined by visual assessment, and eight quantitative variables were included in the three‐way ANOVA, canonical variates analysis and partial rank correlation. The influences of sex and the region of origin of the cranial samples on the relationships between the examined variables and the degrees of supraorbital structures expression were also considered. The results only partially supported the craniofacial size and spatial models and suggested that GL and ST experienced separate influences during development. In the sample of all crania, the neurocranial size more strongly influenced the morphological variation of the ST than of the GL, and sex influenced both of these structures the most. The results suggest that sex may be the main factor (having an influence independent of the other traits) on the morphological variation of the GL and ST. Am J Phys Anthropol 156:110–124, 2015 © 2014 Wiley Periodicals, Inc.     

Rationale for the Chemical-Specific Adjustment Factors Used to Derive an Occupational Exposure Limit for Timolol Maleate

Timolol maleate is a non-selective beta-adrenergic blocking agent currently used primarily to reduce intraocular pressure in the treatment of glaucoma. It also produces effects on the heart and bronchial smooth muscle and all of these effects are of potential concern in workers handling this active pharmaceutical ingredient. The disposition of timolol maleate is influenced by a polymorphism in oxidative metabolism by CYP2D6 and two distinct phenotypes have been identified (i.e., poor and extensive metabolizers). These properties of timolol maleate provided an opportunity to use the compound as a case study to demonstrate the derivation of chemical-specific adjustment factors for pharmacokinetics and pharmacodynamics to replace the default uncertainty factor for interindividual variability. Overall, the available data on the pharmacodynamic endpoints showed very little variability and most pharmacokinetic studies failed to discern significant differences in relatively small groups of healthy volunteers or patients. Reports of bradycardia and bronchoconstriction in patients receiving therapeutic doses are relatively rare. In one study, there was a significant reduction in heart rate 24 hours post-dose that was associated with elevated area under the curve (AUC) values. A chemical-specific adjustment factor (CSAF) for kinetics of 9.8 based on these AUC data was combined with a CSAF for dynamics of 1.2 and applied to the extrapolated no-effect level for clinically significant cardiovascular effects (with correction for oral bioavailability) to establish an occupational exposure limit (OEL) for timolol maleate which is expected to be protective of workers that may be poor metabolizers or asthmatics.     

Colony size and not nest density drives reproductive output in the Common Tern Sterna hirundo

Density is known to be an important factor in population size regulation. Several mechanisms of density limitation have been identified in colonial birds. We studied competition in Common Terns Sterna hirundo to assess whether the factor limiting reproductive output was competition for nest‐sites, which is dependent on local nest density, or density‐dependent competition for food resources, which is dependent on overall colony size using the same foraging area. We found strong associations of both colony size and nest density with reproductive output in five colonies of Common Terns in three different habitats (one marine, two freshwater). Based on detailed long‐term datasets of six separate sub‐colonies of the Banter See colony that differed in nest density, we found that reproductive success was not related to nest density but to overall colony size, possibly a result of resource depletion and food competition. We also found carry‐over effects of colony size during rearing on post‐fledging return rate. These results have important implications for the conservation management plans aimed at recovering declining populations of Common Terns.     

Higher order structure of chromatin: evidence from photochemically detected linear dichroism

We have used photochemically detected linear dichroism to measure the separate average angular orientations of nucleosomes and linker DNA in 30-nm chromatin fibers of varying linker size (20-80 base pairs). Our results indicate that the average tilt angles vary with linker size, but not in a monotonic manner, suggesting that the constancy of geometry of the 30-nm fiber is maintained by compensatory changes of nucleosomal tilt which accommodate packing of variable lengths of linker DNA. We discuss the compatibility of our results with the various classes of models that have been proposed for the 30-nm fiber, including the continuous solenoid model and models built from the basic unit of the zig-zag ribbon. Many models can be eliminated, and all have to be modified to fit our results for chromatins with very long linkers.     

Genome size variation in pumpkin (Cucurbita sp.)

Pumpkins, a subgroup of the domesticated Cucurbita species, have been reported to range in fruit type (related to size) from miniature (<100 g) to jumbo (>273 kg). In order to obtain a wide range of fruit types it is hypothesised that all potential factors affecting fruit type must be used. One factor that is often overlooked in plant studies is genome size. In various plant species, genome size variation has been associated with characteristics such as cell size, plant size and flowering time. Such characteristics are referred to as nucleotypic parameters. In order to determine if nucleotypic selection is occurring in pumpkin, 17 varieties were analysed for genome size variation in two separate experiments. The species selected encompass the total range of fruit types reported in pumpkin. Significant nuclear DNA content variation was observed in pumpkin. There was no significant correlation between genome size and fruit type. In fact, the miniature pumpkin types were found to have the same genome size as the jumbo pumpkin types. In addition, a positive correlation between genome size and stomata length (an estimate of cell size in plants) was observed. Both the miniature and jumbo types were observed to have the smallest genome size and the smallest cell size. Thus, nucleotypic selection does appear to occur in pumpkin and appears to be involved in determining fruit type, although it may not be the only factor involved.     

Distance models in ecological network management: A case study of patch connectivity in a grassland network

Landscape connectivity is a key issue of nature conservation and distance parameters are essential for the calculation of patch level metrics. For such calculations the so-called Euclidean and the least cost distance are the most widespread models. In the present work we tested both distance models for landscape connectivity, using connectivity metrics in the case of a grassland mosaic, and the ground beetle Pterostichus melas as a focal species. Our goal was to explore the dissimilarity between the two distance models and the consequent divergence from the calculated values of patch relevance in connectivity. We found that the two distance models calculated the distances similarly, but their estimations were more reliable over short distances (circa 500 m), than long distances (circa 3000 m). The variability in the importance of habitat patches (i.e. patch connectivity indices) was estimated by the difference between the two distance models (Euclidean vs. least cost) according to the patch size. The location of the habitat patches in the matrix seemed to be a more important factor than the habitat size in the estimation of connectivity. The uncertainty of three patch connectivity indices (Integral Index of Connectivity, Probability of Connectance and Flux) became high above a habitat size of 5 ha. Relevance of patches in maintaining connectivity varied even within small ranges depending on the estimator of distance, revealing the careful consideration of these methods in conservation planning.     

A global analysis of the determinants of alien geographical range size in birds

Aim Determining the causes of range size variation in the distributions of alien species is important for understanding the spread of invasive species. Factors influencing alien range size have been explored for some species at a regional level, but to date there has been no global analysis of an entire class. Here, we present such an analysis for birds, testing for the effects of introduction event, location and species‐level variables on alien range sizes. Location Global. Methods We used a novel dataset on the global distributions of alien bird species to test for relationships between alien range size and colonization pressure, residence time, extent of the global climatic niche, native range size, body mass and specialization, using a statistical approach based on phylogenetic generalized least squares models. We performed this analysis globally, and for separate biogeographical realms. Results Approximately half of the variation in alien bird range size is explained by colonization pressure in univariate analysis. We identified consistent effects of higher colonization pressure at global and realm levels, as well as support for effects of native range size and residence time. We found less support for effects of body mass, specialization or extent of the global climatic niche on alien range size. Main conclusions Alien bird range sizes are generally small relative to their native range sizes, and many are continuing to expand. Nevertheless, current variation is predictable, most strongly by the event‐level factor of colonization pressure. Whether a species is widespread is a better predictor of alien range size than whether a species could be widespread (estimated by global climatic niche extent), while we also find effects of residence time on alien range size. These relationships may help to identify those alien species that are more likely to spread and hence have greater environmental and economic impacts where they have been introduced.     

The basic reproductive number of Ebola and the effects of public health measures: the cases of Congo and Uganda

Despite improved control measures, Ebola remains a serious public health risk in African regions where recurrent outbreaks have been observed since the initial epidemic in 1976. Using epidemic modeling and data from two well-documented Ebola outbreaks (Congo 1995 and Uganda 2000), we estimate the number of secondary cases generated by an index case in the absence of control interventions R0. Our estimate of R0 is 1.83 (SD 0.06) for Congo (1995) and 1.34 (SD 0.03) for Uganda (2000). We model the course of the outbreaks via an SEIR (susceptible-exposed-infectious-removed) epidemic model that includes a smooth transition in the transmission rate after control interventions are put in place. We perform an uncertainty analysis of the basic reproductive number R0 to quantify its sensitivity to other disease-related parameters. We also analyse the sensitivity of the final epidemic size to the time interventions begin and provide a distribution for the final epidemic size. The control measures implemented during these two outbreaks (including education and contact tracing followed by quarantine) reduce the final epidemic size by a factor of 2 relative the final size with a 2-week delay in their implementation.     

Differential responses to growth factors by normal human mesothelial cultures from individual donors

A significant interindividual variation in the growth rates is found in normal cultured human mesothelial (NHM) cells derived from different donors. This variation is observed when the mesothelial cells are incubated in medium containing serum and when the potencies of several separate growth factors are measured by using defined media. Depending on the donor, gamma-interferon and interleukin-2 can be toxic, have no effect, or stimulate the growth rate of NHM cells. Cultured NHM cells can be induced to multiply by growth factors that are released by activated macrophages. Thus, interindividual variation in NHM cell growth control could play a role in the pathogenesis of mesothelioma for a person exposed to asbestos.     

Ecological correlates of interindividual distance in the St. Kitts veret (Cercopithecus aethiops sabaeus)

Field data were collected on a free ranging population of vervet monkeys (Cercopithecus aethiops sabaeus) on St. Kitts to test four hypotheses relating cover, risk of predation, and food density to interindividual distance. The results indicated that when food was not a factor, interindividual distance was positively related to the amount of cover in the immediate environment, and therefore to risk of predation. When cover was held constant, distance was inversely related to food density. When the minimum distance for optimal foraging was greater than that required for safety, a compromise distance intermediate between the two predicted values was observed. Cover and food density also predicted the inverse relationship found between age-sex class and interindividual distance. Implications of the above in relation to interindividual competition are discussed.     

A novel comparative method for identifying shifts in the rate of character evolution on trees

Evolutionary biologists since Darwin have been fascinated by differences in the rate of trait-evolutionary change across lineages. Despite this continued interest, we still lack methods for identifying shifts in evolutionary rates on the growing tree of life while accommodating uncertainty in the evolutionary process. Here we introduce a Bayesian approach for identifying complex patterns in the evolution of continuous traits. The method (auteur) uses reversible-jump Markov chain Monte Carlo sampling to more fully characterize the complexity of trait evolution, considering models that range in complexity from those with a single global rate to potentially ones in which each branch in the tree has its own independent rate. This newly introduced approach performs well in recovering simulated rate shifts and simulated rates for datasets nearing the size typical for comparative phylogenetic study (i.e., ≥64 tips). Analysis of two large empirical datasets of vertebrate body size reveal overwhelming support for multiple-rate models of evolution, and we observe exceptionally high rates of body-size evolution in a group of emydid turtles relative to their evolutionary background. auteur will facilitate identification of exceptional evolutionary dynamics, essential to the study of both adaptive radiation and stasis.     

A Longitudinal Study of the Effects of Uncertainty on Reproductive Behaviors

Uncertainty exerts powerful influences on life history decisions. This has been demonstrated in experiments on nonhumans and in mathematical models. Studies of human populations are suggestive of the effects of uncertainty, but they rely on measures of environmental stress. In this paper, we derive a new measure of uncertainty, upsilon (υ), for use in non-experimental studies. We estimate its association with reproductive behaviors in a longitudinal panel sample of adolescents in the United States. Results show upsilon’s internal structure is consistent with theoretical models of uncertainty. Its associations with reproductive outcomes are also consistent with theoretical predictions. Upsilon seems to have its largest effect on the timing of fertility—increasing the odds of early fertility by a factor of 7, net of the effects of control variables. We discuss our findings for the association between υ and the timing of reproductive effort as well as our future research on υ.     

Integrating species distribution models (SDMs) and phylogeography for two species of Alpine Primula

The major intention of the present study was to investigate whether an approach combining the use of niche-based palaeodistribution modeling and phylo-geography would support or modify hypotheses about the Quaternary distributional history derived from phylogeographic methods alone. Our study system comprised two closely related species of Alpine Primula. We used species distribution models based on the extant distribution of the species and last glacial maximum (LGM) climate models to predict the distribution of the two species during the LGM. Phylogeographic data were generated using amplified fragment length polymorphisms (AFLPs). In Primula hirsuta, models of past distribution and phylogeographic data are partly congruent and support the hypothesis of widespread nunatak survival in the Central Alps. Species distribution models (SDMs) allowed us to differentiate between alpine regions that harbor potential nunatak areas and regions that have been colonized from other areas. SDMs revealed that diversity is a good indicator for nunataks, while rarity is a good indicator for peripheral relict populations that were not source for the recolonization of the inner Alps. In P. daonensis, palaeo-distribution models and phylogeographic data are incongruent. Besides the uncertainty inherent to this type of modeling approach (e.g., relatively coarse 1-km grain size), disagreement of models and data may partly be caused by shifts of ecological niche in both species. Nevertheless, we demonstrate that the combination of palaeo-distribution modeling with phylogeographical approaches provides a more differentiated picture of the distributional history of species and partly supports (P. hirsuta) and partly modifies (P. daonensis and P. hirsuta) hypotheses of Quaternary distributional history. Some of the refugial area indicated by palaeodistribution models could not have been identified with phylogeographic data.