Biomedical subjects

Jeff Swartout

Publications and source records attributed to Jeff Swartout.

4 recordsLinked to original sources

PubMed2006

Predictive Bayesian microbial dose-response assessment based on suggested self-organization in primary illness response: Cryptosporidium parvum.

The probability of illness caused by very low doses of pathogens cannot generally be tested due to the numbers of subjects that would be needed, though such assessments of illness dose response are needed to evaluate drinking water standards. A predictive Bayesian dose-response assessment method was proposed previously to assess the unconditional probability of illness from available information and avoid the inconsistencies of confidence-based approaches. However, the method uses knowledge of the conditional dose-response form, and this form is not well established for the illness endpoint. A conditional parametric dose-response function for gastroenteric illness is proposed here based on simple numerical models of self-organized host-pathogen systems and probabilistic arguments. In the models, illnesses terminate when the host evolves by processes of natural selection to a self-organized critical value of wellness. A generalized beta-Poisson illness dose-response form emerges for the population as a whole. Use of this form is demonstrated in a predictive Bayesian dose-response assessment for cryptosporidiosis. Results suggest that a maximum allowable dose of 5.0 x 10(-7) oocysts/exposure (e.g., 2.5 x 10(-7) oocysts/L water) would correspond with the original goals of the U.S. Environmental Protection Agency Surface Water Treatment Rule, considering only primary illnesses resulting from Poisson-distributed pathogen counts. This estimate should be revised to account for non-Poisson distributions of Cryptosporidium parvum in drinking water and total response, considering secondary illness propagation in the population.

Animals↗

PubMed2003

The impact of cytochrome P450 2E1-dependent metabolic variance on a risk-relevant pharmacokinetic outcome in humans.

Risk assessments include assumptions about sensitive subpopulations, such as the fraction of the general population that is sensitive and the extent that biochemical or physiological attributes influence sensitivity. Uncertainty factors (UF) account for both pharmacokinetic (PK) and pharmacodynamic (PD) components, allowing the inclusion of risk-relevant information to replace default assumptions about PK and PD variance (uncertainty). Large numbers of human organ donor samples and recent advances in methods to extrapolate in vitro enzyme expression and activity data to the intact human enable the investigation of the impact of PK variability on human susceptibility. The hepatotoxicity of trichloroethylene (TCE) is mediated by acid metabolites formed by cytochrome P450 2E1 (CYP2E1) oxidation, and differences in the CYP2E1 expression are hypothesized to affect susceptibility to TCE's liver injury. This study was designed specifically to examine the contribution of statistically quantified variance in enzyme content and activity on the risk of hepatotoxic injury among adult humans. We combined data sets describing (1) the microsomal protein content of human liver, (2) the CYP2E1 content of human liver microsomal protein, and (3) the in vitro Vmax for TCE oxidation by humans. The 5th and 95th percentiles of the resulting distribution (TCE oxidized per minute per gram liver) differed by approximately sixfold. These values were converted to mg TCE oxidized/h/kg body mass and incorporated in a human PBPK model. Simulations of 8-hour inhalation exposure to 50 ppm and oral exposure to 5 micro g TCE/L in 2 L drinking water showed that the amount of TCE oxidized in the liver differs by 2% or less under extreme values of CYP2E1 expression and activity (here, selected as the 5th and 95th percentiles of the resulting distribution). This indicates that differences in enzyme expression and TCE oxidation among the central 90% of the adult human population account for approximately 2% of the difference in production of the risk-relevant PK outcome for TCE-mediated liver injury. Integration of in vitro metabolism information into physiological models may reduce the uncertainties associated with risk contributions of differences in enzyme expression and the UF that represent PK variability.

Adult↗

PubMedDate not supplied

Predictive population dose-response assessment for Cryptosporidium parvum: infection endpoint.

Data validation of safe doses of pathogens in drinking water consistent with public health goals is not possible due to the number of subjects that would be needed at each dose. Because of this problem, together with the difficulty in extrapolating pathogenic response between species, and the ability of microbes to adapt rapidly, confidence-level-dependent assessments of Cryptosporidium parvum dose-response have been developed. However, these results, even on a relative basis, are dependent on confidence level, and the lack of scientific basis for this choice hampers efforts to set water quality standards. Therefore, a predictive Bayesian dose-response assessment method was proposed previously. In this article, a hierarchical predictive population dose-response Bayesian assessment for C. parvum is presented for the infection endpoint. Available data on the infectivity of three isolates of C. parvum, genotype C, were adjusted for sensitive and antibody-positive subpopulations not proportionately represented in the data, by bootstrap analysis. The diverse mean infectivities of the isolates were used to obtain a predictive distribution for population infectivity, used in turn to obtain the predictive population dose-response function. The predictive result is a distribution of unconditional probability of infection, based on available dose-response information. Information includes theoretical and empirical evidence for the conditional beta-Poisson parametric dose-response function. Results indicate that a dose of 6 x 10(-6) oocysts per exposure corresponds to 10(-4) infections per capita year. An allowable dose corresponding to goals of the SWTR should be increased over this value to reflect the illness endpoint, while potentially being reduced to account for secondary transmission among hosts if important for gastroenteritis in developed countries.

Animals↗

PubMedDate not supplied

Estimating the frequency of tap-water exposures to Mycobacterium avium complex in the U.S. population with advanced AIDS.

Mycobacterium avium complex (MAC) is a group of ubiquitous and opportunistic bacterial pathogens included on the U.S. Environmental Protection Agency Drinking Water Contaminant Candidate List. The risk of contracting a disseminated MAC infection is primarily limited to the immunocompromised, including those with advanced acquired immunodeficiency syndrome (AIDS). These infections likely result from exposures to MAC-contaminated tap water, food, or soil, although the epidemiologic evidence is insufficient to implicate a specific medium. The objective of this study was to assess tap water exposure to MAC in the U.S. population with advanced AIDS, defined here as having fewer than 100 CD4(+) cells/mm(3) of blood. Using limited data on the detection of MAC and self-reported post-tap treatment practices, two exposure models were developed to simulate the likelihood of exposure to MAC via tap water consumption in this sensitive population. The first model integrated data from studies that described sources of water for consumption and post-tap treatment rates in cohorts infected with human immunodeficiency virus (HIV(+)). The second model used data from a study that categorized the fraction of water intake consisting of tap water that was not further treated. Approximately 1500 individuals with advanced AIDS were estimated to ingest tap water with detectable concentrations of MAC organisms daily. Additional studies on tap-water use in U.S. HIV(+) populations are needed to confirm these findings. Longitudinal and cross-sectional studies on the occurrence of MAC in tap water, particularly in regions with large HIV(+)/AIDS populations, would help address some of the uncertainty in these exposure estimates.

AIDS-Related Opportunistic Infections↗