A comparison of sediment deposition in two adjacent floodplains of the River Adour in southwest France.

Two floodplains within the catchment of the River Adour (SW France) have been examined in order to analyse spatio-temporal variations in discharge and suspended matter flux. Both floodplain zones were found to be excellent sites for the interception of suspended sediment. The narrow riparian vegetative strips (RVS) within each zone were found to retain 92-98% of the sediment trapped within the floodplain during each of three separate flood events. The precise level of sediment deposited within the floodplain was found to be dependent on micro-topographical features and the nature of the vegetation: the wooded areas within the RVS being particularly effective at trapping sediment. Mean masses of sediment collected in the flood plains ranged from 75 kg m(-2) in the RVS to 0.02 kg m(-2) in the areas of the floodplain inundated by back-up flows. Using data on discharge and sediment fluxes within the catchment gathered over a period of 25 years it is possible to discern how hydroclimatic fluctuations have affected the watershed with periods of sediment retention within the floodplain zones alternating with periods of sediment export. Anthropogenic activity, involving river management, including the cutting of meanders, the construction of dykes for flood prevention and the use of water for agricultural purposes, has also had a major impact during this period, particularly in the downstream areas of the catchment.

A biologically based dynamic model for predicting the disposition of methanol and its metabolites in animals and humans.

A multicompartment biologically based dynamic model was developed to describe the time evolution of methanol and its metabolites in the whole body and in accessible biological matrices of rats, monkeys, and humans following different exposure scenarios. The dynamic of intercompartment exchanges was described mathematically by a mass balance differential equation system. The model's conceptual and functional representation was the same for rats, monkeys, and humans, but relevant published data specific to the species of interest served to determine the critical parameters of the kinetics. Simulations provided a close approximation to kinetic data available in the published literature. The average pulmonary absorption fraction of methanol was estimated to be 0.60 in rats, 0.69 in monkeys, and 0.58-0.82 in human volunteers. The corresponding average elimination half-life of absorbed methanol through metabolism to formaldehyde was estimated to be 1.3, 0.7-3.2, and 1.7 h. Saturation of methanol metabolism appeared to occur at a lower exposure in rats than in monkeys and humans. Also, the main species difference in the kinetics was attributed to a metabolism rate constant of whole body formaldehyde to formate estimated to be twice as high in rats as in monkeys. Inversely, in monkeys and in humans, a larger fraction of body burden of formaldehyde is rapidly transferred to a long-term component. The latter represents the formaldehyde that (directly or after oxidation to formate) binds to various endogenous molecules or is taken up by the tetrahydrofolic-acid-dependent one-carbon pathway to become the building block of synthetic pathways. This model can be used to quantitatively relate methanol or its metabolites in biological matrices to the absorbed dose and tissue burden at any point in time in rats, monkeys, and humans for different exposures, thus reducing uncertainties in the dose-response relationship, and animal-to-human and exposure scenario comparisons. The model, adapted to kinetic data in human volunteers exposed acutely to methanol vapors, predicts that 8-h inhalation exposures ranging from 500 to 2000 ppm, without physical activities, are needed to increase concentrations of blood formate and urinary formic acid above mean background values reported by various authors (4.9-10.3 and 6.3-13 mg/liter, respectively). This leaves blood and urinary methanol concentrations as the most sensitive biomarkers of absorbed methanol.

A toxicokinetic model for predicting the tissue distribution and elimination of organic and inorganic mercury following exposure to methyl mercury in animals and humans. II. Application and validation of the model in humans.

The objective of this study was to develop a biologically based dynamical model describing the disposition kinetics of methyl mercury and its inorganic mercury metabolites in humans following different methyl mercury exposure scenarios. The model conceptual and functional representation was similar to that used for rats but relevant data on humans served to determine the critical parameters of the kinetic behavior. It was found that the metabolic rate of methyl mercury was on average 3 to 3.5 times slower in humans than in rats. Also, excretion rates of organic mercury from the whole body into feces and hair were 100 and 40 times smaller in humans, respectively, and urinary excretion of organic mercury in humans was found to be negligible. The human transfer rate of inorganic mercury from blood to hair was found to be 5 times lower than that of rats. On the other hand, retention of inorganic mercury in the kidney appeared more important in humans than in rats: the transfer rate of inorganic mercury from blood to kidney was 19 times higher than in rats and that from kidney to blood 19 times smaller. The excretion rate of inorganic mercury from the kidney to urine in humans was found to be twice that of rats. With these model parameters, simulations accurately predicted human kinetic data available in the published literature for different exposure scenarios. The model relates quantitatively mercury species in biological matrices (blood, hair, and urine) to the absorbed dose and tissue burden at any point in time. Thus, accessible measurements on these matrices allow inferences of past, present, and future burdens. This could prove to be a useful tool in assessing the health risks associated with various circumstances of methyl mercury exposure.

A toxicokinetic model for predicting the tissue distribution and elimination of organic and inorganic mercury following exposure to methyl mercury in animals and humans. I. Development and validation of the model using experimental data in rats.

The objective of this study was to develop a biologically based dynamic model for predicting the distribution and elimination of methyl mercury and its metabolite, inorganic mercury, under a variety of exposure scenarios in rats. A model is proposed based on a multicompartment approach; each compartment represents an organ or a group of organs or an excreta. The model translates into a set of coupled differential equations taking into account interorgan rates of exchanges and excretion together with the biotransformation process. The free parameters of the model are determined from statistical fits to the experimental data of the Farris et al. (Toxicol. Appl. Pharmacol. 119, 74-90, 1993) study on the time profiles of blood and tissue concentrations and cumulative excretions. The vast range of time scales that govern tissue absorption, distribution, biotransformation, and excretion served to solve the model step by step. This interplay of time scales in the rates explains the buildups and slow attrition of inorganic mercury in certain key organs such as the brain and the kidney, which are also the sites of the more important toxic effects. The model was validated on additional experimental data provided by Norseth and Clarkson (Arch. Environ. Health 21, 717-727, 1970) and Thomas et al. (Environ. Res. 41, 219-234, 1986; Environ. Res. 43, 203-216, 1987). This approach, when adapted to humans, allows the reconstruction of the time course of blood and tissue concentrations, starting from easily accessible data on hair, urine, and feces.

A method for estimating time dependent intervention benefits under arbitrarily varying age and exogenous components of hazard.

A method for estimating the dependence of intrinsic intervention benefits on time elapsed since the intervention took place is proposed. The method is aimed at intervention programs against diseases where one or all of the following components of hazard intensity may undergo important and unknown variations: 1) the intervention benefits to a subject are a function of the time elapsed since the intervention took place, or since inception for a continuing treatment, 2) the subjects vulnerability is an unknown function of their age, 3) the exogenous or environmental baseline intensity, to which all are assumed subjected, fluctuates arbitrarily with calendar time. During the time span of a study, these variables interact in a complex way, possibly masking the real contribution of the intervention. However, with very general assumptions about how hazard components interact, the cumulative hazards of subpopulations treated at different times in the past are shown to be described mathematically by a convolution of the time elapsed dependent intervention benefit function with the age and calendar time dependent baseline intensity. Starting from the cumulative hazards of untreated and treated subpopulations that had the intervention at different times in the past, a method of deconvolution through regularization is proposed to reconstruct the time elapsed dependence of the intervention benefit function. The regularization technique used is of the 'penalized least square smoothing' type, it is applied to the solution of Volterra integral equations of the first kind under noisy inputs. Simulations, to test for the reconstruction of different modes of time elapsed variation of the intervention benefits, are carried out on realistically noisy 'data sets' taken to be available at a limited number of time points. The stability of the estimated reconstructions, to measurement errors, is examined through repeated simulations with random noise added to inputs. The method is applied to a Brazilian data set where BCG vaccination resulted in a small reduction in the cumulated risk of leprosy infection.

A non-parametric method for the reconstruction of age- and time-dependent incidence from the prevalence data of irreversible diseases with differential mortality.

A method is proposed for reconstructing the time and age dependence of incidence rates from successive age-prevalence cross sections taken from the sentinel surveys of irreversible diseases when there is an important difference in mortality between the infected and susceptible subpopulations. The prevalence information at different time-age points is used to generate a surface; the time-age variations along the life line profiles of this surface and the difference in mortality rates are used to reconstruct the time and age dependence of the incidence rate. Past attempts were based on specified parametric forms for the incidence or on the hypothesis of time-invariant forms for the age-prevalence cross sections. The proposed method makes no such assumptions and is thus capable of coping with rapidly evolving prevalence situations. In the simulations carried out, it is found to be resilient to important random noise components added to a prescribed incidence rate input. The method is also tested on a real data set of successive HIV age-prevalence cross sections from Burundi coupled to differential mortality data on HIV(+) and HIV(-) individuals. The often-made assumption that the incidence rate can be written as the product of a calendar time component and an age component is also examined. In this case, a pooling procedure is proposed to estimate the time and the age profiles of the incidence rate using the reconstructed incidence rates at all time-age points.

A toxicokinetic model to assess the risk of azinphosmethyl exposure in humans through measures of urinary elimination of alkylphosphates.

Azinphosmethyl (APM) is one of the most common insecticides used in fruit farming. The object of this paper is to develop a quick and practical test for assessing the risk for humans coming into contact with APM. It has been shown that the principal component of occupational and/or accidental exposure is through the skin (C. A. Franklin et al., 1981, J. Toxicol. Environ. Health 7, 715-731), but our approach is applicable to exposures via any route or a combination of routes. The method proposed in the present paper can accommodate a single-event exposure or repeated exposures over long periods. Urinary alkylphosphate (AP) metabolites are reliable bioindicators of the presence of APM in the body; they are easily accessible and can be used to estimate APM body burden. We developed a simple toxicokinetic model to link the time varying APM body burden to absorbed doses and to rates of elimination in the form of AP urinary metabolites. Using this model and data available in the literature, we are able to propose a "no observed adverse effect level" (NOAEL) for APM body levels and for corresponding absorbed doses. We have established that after a single exposure, the safe limit corresponding to the NOAEL is reached at a cumulative 0.215 mumoles AP/kg bw eliminated in urine in the first 24 hours following the beginning of exposure. For repeated daily exposures at steady state, the corresponding urinary AP metabolite level is equal to a cumulative 0.266 mumoles AP/kg bw eliminated per 24 hours.

Rate estimation from prevalence information on a simple epidemiologic model for health interventions.

Health intervention control programs, such as vaccination, can be evaluated by comparing incidence rates of infection between unprotected and protected individuals in a population. The ratio of incidence rates is usually estimated by following up control and treated groups in order to collect information on person-time and cases in each group. This approach can be expensive and time consuming. An alternative approach is to use prevalence data to reconstitute incidence. Current-status are readily available or easily gathered and can be used to estimate incidence rates. Under certain assumptions of irreversibility for the outcome of interest, we discuss a simple transmission model appropriate to evaluate health interventions that confer long term protection. Rates and populations are parameter-free functions of age and calendar time. We develop general mathematical relationships that link incidence and intervention rates to prevalence which could be estimated from sampling without requiring knowledge of subpopulation demographics.

High dose folinic acid and 5-fluorouracil bolus and continuous infusion for patients with advanced colorectal cancer.

BACKGROUND: Palliative chemotherapy remains a challenge for oncologists. The combination of high dose folinic acid (HDFA) with 5-fluorouracil (5-FU) improves response rates, as do continuous infusions of 5-FU. These protocols have limiting toxicities such as diarrhea, stomatitis, and leukopenia. Another schedule of 5-FU and folinic acid has proven effective and is very well tolerated. The results of a similar regimen are reported. METHODS: Eighty-six eligible patients with evolutive advanced colorectal cancer were treated, after informed consent was obtained, with chemotherapy consisting of HDFA (200 mg/m2 in a 2-hour infusion, followed by 5-FU (400 mg/m2 IV bolus injection, then 600 mg/m2 in a 22-hour infusion) on days 1 and 2, every 15 days. Seven of 86 had received prior therapy for metastatic disease. RESULTS: Two complete and 31 partial responses were noted for an overall response rate of 38.3% (95% confidence interval, 0.25-0.45). Toxicity was low, as more than 60% of the patients had no or minor toxicity. Grade III or IV World Health Organization toxicities included stomatitis (7 patients), leukopenia (3 patients), diarrhea (2 patients), and cardiac toxicity (3 patients). The overall median survival was 10.3 months, and for those having a response, 17.1 months. CONCLUSIONS: High dose folinic acid combined with 5-FU bolus and continuous infusion for 2 days every 2 weeks is an effective regimen. Its toxicity appears low. Moreover, this chemotherapy is feasible on an outpatient basis.

Modeling of the toxicokinetics of polychlorinated dibenzo-p-dioxins and dibenzofurans in mammalians, including humans. I. Nonlinear distribution of PCDD/PCDF body burden between liver and adipose tissues.

Mixtures of polychlorinated dibenzo-p-dioxins and dibenzofurans, globally called PCDXs, are ubiquitously present in the environment. They accumulate in the human organism, especially through uptake from food. In view of their long residence time in the body and their potential adverse health effects for humans, it is therefore important to develop toxicokinetic models capable of predicting their distribution in human tissues. In the present study a physiologically based model which describes the distribution kinetics of PCDXs in various mammalian species is proposed. The approach is both theoretical and empirical. First, a plausible and general dynamical model that takes into account intercellular diffusion, PCDX-receptor and PCDX-protein binding, and PCDX-dependent enzyme induction in the liver is developed. Simplified formulas are proposed to predict the functional dependencies fh(Cb) and f(at)(Cb), which establish the fractions of the total PCDX body burden contained in liver and adipose tissues as a function of overall body concentration at any one moment. These formulas have fewer free parameters that can be determined for various species with the use of already available data. Model simulations are in agreement with published data on the distribution kinetics of PCDXs in rodents and monkeys and clinical data in humans. In rodents and monkeys as well as in humans, the respective relations fh(Cb) and f(at)(Cb) follow a similar nonlinear pattern. These varying distribution functions constitute the basis for a generalized toxicokinetic model of absorption and disposition described in a companion article (G. Carrier, R. C. Brunet, and J. Brodeur, 1995, Toxicol. Appl. Pharmacol. 131, 267-276).

Modeling of the toxicokinetics of polychlorinated dibenzo-p-dioxins and dibenzofurans in mammalians, including humans. II. Kinetics of absorption and disposition of PCDDs/PCDFs.

In the present study, a physiologically based model which describes the absorption and disposition kinetics of PCDDs/PCDFs (globally called PCDXs) in mammalian species, including humans, is developed. The model integrates the distribution model developed in the first article of this series, which described the fractional distribution of total PCDXs between liver and adipose tissues as a function of overall body concentration (G. Carrier, R. C. Brunet, and J. Brodeur, 1995, Toxicol. Appl. Pharmacol. 131, 253-266). In particular it is shown that the liver fraction of the total body burden decreases as overall body concentration decreases. Since elimination is principally through the liver, this leads to lower global elimination rates and longer half-lives of PCDXs. Absorption and disposition kinetics of PCDXs are captured using nonlinear differential equations with anatomically and biochemically relevant input parameters which are readily available. These are solved to predict the fate of PCDXs in liver, adipose tissues, and the body as a whole, as a function of time. Model simulations are in agreement with published data on absorption and disposition kinetics of these substances in rats and in humans. The kinetic profiles are similar for rats and humans, but the varying half-lives differ considerably in both species: weeks with rats, years with humans. For a given body burden, the adipose tissue concentrations vary in an inversely proportional manner to the mass of the adipose tissues; this observation has considerable relevance for interpretation of clinical data for humans. The interest of the proposed model rests upon the fact that it is generalized and broadly applicable: it allows the study of the kinetics of PCDXs for any pattern of exposure from background to highly toxic levels, taking into account variations in time of anatomical and biochemical parameters.

Exposure efficacy and change in contact rates in evaluating prophylactic HIV vaccines in the field.

Field studies of the efficacy of prophylactic vaccines in reducing susceptibility rely on the assumption of equal exposure to infection in the vaccinated and unvaccinated groups. Differential exposure to infection could, however, be the goal of other types of intervention programme, or it could occur secondary to belief in the protective effects of a prophylactic measure, such as vaccination. We call this differential exposure the exposure efficacy, or behaviour efficacy. To study the relative contribution of unequal exposure to infection and differential susceptibility to the estimate of vaccine efficacy, we formulate a simple model that explicitly includes both susceptibility and exposure to infection. We illustrate this on the example of randomized field trials of prophylactic human immunodeficiency virus vaccines. Increased exposure to infection in the vaccinated group may bias the estimated reduction in susceptibility. The bias in the estimate depends on the choice of efficacy parameter, the amount of information used in the analysis, the distribution and level of protection in the population, and the imbalance in exposure to infection. Sufficient increase in contacts in the vaccinated could result in the vaccine being interpreted as having an immunosuppressive effect. Estimates of vaccine efficacy are generally more robust to imbalances in exposure to infection when the detailed history of exposure to infection can be used in the analysis or at high levels of protection. The bias also depends on the relationship between the distribution of vaccine protection and the distribution of behaviour change, which could differ between blinded and unblinded trials.

Malaria vaccines: lessons from field trials.

Malaria vaccine candidates have already been tested and new trials are being carried out. We present a brief description of specific issues of validity that are relevant when assessing vaccine efficacy in the field and illustrate how the application of these principles might improve our interpretation of the data being gathered in actual malaria vaccine field trials. Our discussion assumes that vaccine evaluation shares the same general principles of validity with epidemiologic causal inference, i.e., the process of drawing inferences from epidemiologic data aiming at the identification of causes of diseases. Judicious exercise of these principles indicates that, for meaningful interpretation, measures of vaccine efficacy require definitions based upon arguments conditional on the amount of exposure to infection, and specification of the initial and final states in which one believes the effect of interest takes place.

On the distribution of vaccine protection under heterogeneous response.

We assume that individuals in a vaccinated cohort respond heterogeneously and acquire a continuous spectrum of effective protection against an environmental exposure to infection that can be varying in time. The notion of dynamical invariants is applied to a proportional hazard model with an unvaccinated or placebo cohort as baseline. The hazard is expressed as a susceptibility factor times a measure of environmental exposure to infection. Using the time-evolving information for the aggregated vaccinated cohort and the unvaccinated cohort, it is possible to reconstruct the distribution of effective protection imparted by the vaccination at the beginning of observation. Efficacy is defined in terms of the hazard ratio at the beginning of observation.

The dynamics of simultaneous infections with altered susceptibilities.

We describe a model in which individuals can be infected simultaneously by multiple diseases or parasites, taking into account the fact that individuals already infected by a subset of n co-circulating diseases may see their susceptibility to concurrent infection by another disease from the pool either enhanced or reduced. We propose an n-dimensional approximation to the 2n dimensional model required to describe the dynamics of each possible subset of the pool of n co-circulating diseases, using as state variables the overall prevalence of each infection. Analysis of the two disease case shows that the reduced model provides a very good approximation throughout the full dynamics for small alterations of susceptibility, and, after a transient error, a good approximation to the complete model when susceptibilities are highly enhanced. As the number of diseases becomes large, the approximation remains close for small alterations of susceptibility.