Uncertainties in Pharmacokinetic Modeling for Perchloroethylene: II. Comparison of Model Predictions with Data for a Variety of Different Parameters

In this paper we compare expectations derived from 10 different human physiologically based pharmacokinetic models for perchloroethylene with data on absorption via inhalation, and concentrations in alveolar air and venous blood. Our most interesting finding is that essentially all of the models show a time pattern of departures of predictions of air and blood levels relative to experimental data that might be corrected by more sophisticated model structures incorporating either (a) heterogeneity of the fat compartment (with respect to either perfusion or partition coefficients or both) or (b) intertissue diffusion of perchloroethylene between the fat and muscle/VRG groups. Similar types of corrections have recently been proposed to reduce analogous anomalies in the fits of pharmacokinetic models to the data for several volatile anesthetics.^(17-20) A second finding is that models incorporating resting values for alveolar ventilation in the region of 5.4 L/min seemed to be most compatible with the most reliable set of perchloroethylene uptake data.     

Variability in Physical Constant Parameter Values from Standard Data Sources and the Implication of This Variability for Risk Analysis

Physical property values are used in environmental risk assessments to estimate media and risk-based concentrations. However, considerable variability has recently been reported with such values. To evaluate potential variability in physical parameter values supporting a variety of regulatory programs, eight data sources were chosen for evaluation, and chemicals appearing in at least four sources were selected. There were 755 chemicals chosen. In addition, chemicals in seven environmentally important subgroups were also identified for evaluation. Nine parameters were selected for analysis-molecular weight (MolWt), melting point (MeltPt), boiling point (BoilPt), vapor pressure (VP), water solubility (AqSOL), Henry's law constant (HLC), octanol-water partition coefficient (Kow), and diffusion coefficients in air (Dair) and water (Dwater). Results show that while 71% of constituents had equal MolWts across data sources, <3% of the constituents had equivalent parameter values across data sources for AqSOL, VP, or HLC. Considerable dissimilarity between certain sources was also observed. Furthermore, measures of dispersion showed considerable variation in data sets for Kow, VP, AqSOL, and HLC compared to measures for MolWt, MeltPt, BoilPt, or Dwater. The magnitude of the observed variability was also noteworthy. For example, the 95th percentile ratio of maximum/minimum parameter values ranged from 1.0 for MolWt to well over 1.0E + 06 for VP, and HLC. Risk and exposure metrics also varied by similar magnitudes. Results with environmentally important subgroups were similar. These results show that there is considerable variability in physical parameter values from standard sources, and that the observed variability could affect potential risk estimates and perhaps risk management decisions.     

Career Planning Validity of Self‐Estimates and Test Estimates of Work‐Relevant Abilities

This study sought to determine whether self‐estimates of work‐relevant abilities can improve upon the validity of test estimates (scores). Validity for career planning applications was the focus. The study (final sample of 1,620 college students) used 9 self‐estimates and test estimates to predict certainty‐screened occupational choices grouped by J. L. Holland (1997) types. The addition of ability self‐estimates to test estimates substantially improved upon the validity of test estimates alone. Study results (together with previous research) suggest that ability self‐estimates can provide efficient additions or alternatives to test estimates during career planning, while substantially broadening the range of abilities under consideration.     

Improving Cancer Dose–Response Characterization by Using Physiologically Based Pharmacokinetic Modeling: An Analysis of Pooled Data for Acrylonitrile-Induced Brain Tumors to Assess Cancer Potency in the Rat

Historically, U.S. regulators have derived cancer slope factors by using applied dose and tumor response data from a single key bioassay or by averaging the cancer slope factors of several key bioassays. Recent changes in U.S. Environmental Protection Agency (EPA) guidelines for cancer risk assessment have acknowledged the value of better use of mechanistic data and better dose–response characterization. However, agency guidelines may benefit from additional considerations presented in this paper. An exploratory study was conducted by using rat brain tumor data for acrylonitrile (AN) to investigate the use of physiologically based pharmacokinetic (PBPK) modeling along with pooling of dose–response data across routes of exposure as a means for improving carcinogen risk assessment methods. In this study, two contrasting assessments were conducted for AN-induced brain tumors in the rat on the basis of (1) the EPA's approach, the dose–response relationship was characterized by using administered dose/concentration for each of the key studies assessed individually; and (2) an analysis of the pooled data, the dose–response relationship was characterized by using PBPK-derived internal dose measures for a combined database of ten bioassays. The cancer potencies predicted for AN by the contrasting assessments are remarkably different (i.e., risk-specific doses differ by as much as two to four orders of magnitude), with the pooled data assessments yielding lower values. This result suggests that current carcinogen risk assessment practices overestimate AN cancer potency. This methodology should be equally applicable to other data-rich chemicals in identifying (1) a useful dose measure, (2) an appropriate dose–response model, (3) an acceptable point of departure, and (4) an appropriate method of extrapolation from the range of observation to the range of prediction when a chemical's mode of action remains uncertain.     

'Pressed for time'– the differential impacts of a 'time squeeze'

The ‘time squeeze’ is a phrase often used to describe contemporary concerns about a shortage of time and an acceleration of the pace of daily life. This paper reviews analysis of the Health and Lifestyle Survey (HALS), 1985 and 1992, and draws upon in‐depth semi‐structured interviews conducted with twenty British suburban households, in order to shed light on ‘senses’ of time squeeze. 75% of HALS respondents felt at least ‘somewhat’ pressed for time, with variables of occupation, gender, age and consumption significantly increasing senses of being ‘pressed for time’. This is not surprising given theories of the ‘time squeeze’. However, identification of variables only offers insights into isolated causal effects and does little to explain how or why so many respondents reported feeling ‘usually pressed for time’. Using interview data to help interpret the HALS findings, this paper identifies three mechanisms associated with the relationship between practices and time (volume, co‐ordination and allocation), suggesting that ‘harriedness’ represents multiple experiences of time (substantive, temporal dis‐organisation, and temporal density). In conclusion, it is argued that when investigating ‘harriedness’ it is necessary to recognise the different mechanisms that generate multiple experiences of time in order for analysis to move beyond one‐dimensional interpretations of the ‘time squeeze’, and in order to account for the relationship between social practices and their conduct within temporalities (or the rhythms of daily life).     

Driving and Symbolic Interaction1

Although it is a prominent feature of modern experience, driving has received little attention from sociologists. Yet social interaction between motorists is an integral part of the traffic situation. This paper explores its bases and some of its typical dynamics. Other sociologically relevant aspects of driving are delineated and the issue of how driving may influence modern culture is addressed.     

Parametric discounting

A parametric approach to the problem of selection from amongst alternative investment opportunities is considered in a discounted cash flow framework. The approach employs differential cash flows, an uncertain planning horizon and a nested approach to composing cash flow parameters. This promotes consistent treatment of alternative investments, clarifies the effects of uncertainty, avoids some of the defects of internal rate of return and payback period criteria and allows direct comparison of best and next best options as primal and dual versions of the same model. Net present value, internal rate of return, annual average cost or payback period assessments may be selected post analysis. A domestic wall insulation example is used for illustrative purposes. This example is related to the hydroelectric power development decision which gave rise to the approach.