Biomonitoring of deoxynivalenol and deoxynivalenol-3-glucoside in human volunteers : renal excretion profiles

Biomarkers for the determination of the dietary exposure to deoxynivalenol (DON) have been proposed in the past but so far no quantification of their use in humans has been carried out. Following a human intervention study with two mycotoxins, namely DON and deoxynivalenol-3-glucoside (DON3G), the renal excretion of these compounds, including their phase II metabolites, was analysed. The purpose was to develop biokinetic models that can be used to determine: (1) the preferred (set of) urinary biomarker(s), (2) the preferred urinary collection period, and (3) a method to estimate the dietary exposure to these mycotoxins. Twenty adult volunteers were restricted in consuming cereals and cereal-based foods for 4 days. At day 3, a single dose of 1 mu g/kg body weight of DON or DON3G was orally administered to 16 volunteers; 4 volunteers served as control. All individual urine discharges were collected during 24 h after administration. The metabolism and renal excretion could be described by a biokinetic model using three physiological compartments (gastrointestinal tract, liver, and kidneys). Kinetic analysis revealed a complete recovery of the renal excretion of total DON (mainly DON and its glucuronides) within 24 h after administration of DON or DON3G. The so-called 'reverse dosimetry' factor was used to determine the preferred (set of) biomarker(s) and to estimate the dietary intake of the parent compounds in the future. The fact that DON3G was absorbed and mainly excreted as DON and its glucuronides confirms that DON3G (as well as other modified forms) should be taken into account in the exposure and risk assessment of this group of mycotoxins

Do background levels of the pesticide pirimiphosmethyl in plant-based aquafeeds affect food safety of farmed Atlantic salmon?

The substitution of fish oil and fishmeal with plant-based ingredients in commercial aquafeeds for Atlantic salmon, may introduce novel contaminants that have not previously been associated with farmed fish. The organophosphate pesticide pirimiphos-methyl (PM) is one of the novel contaminants that is most prevalent in commercial salmon feed. In this study, the feed-to-fillet transfer of dietary PM and its main metabolites was investigated in Atlantic salmon fillet. Based on the experimental determined PM and metabolite uptake, metabolisation, and elimination kinetics, a physiologically based toxicokinetic (PBTK) compartmental model was developed. Fish fed PM had a relatively low (~4%) PM retention and two main metabolites (2-DAMP and Desethyl-PM) were identified in liver, muscle, kidney and bile. The absence of more metabolised forms of 2-DAMP and Desethyl-PM in Atlantic salmon indicates different metabolism in cold-water fish compared to previous studies on ruminants. The model was used to simulate the long term (>1.5 years) feed-to-fillet transfer of PM + metabolite in Atlantic salmon under realistic farming conditions including seasonal fluctuations in feed intake, growth, and fat deposition in muscle tissue. The model predictions show that with the constant presence of the highest observed PM concentration in commercial salmon feed, fillet PM+ metabolite levels were approximately 5 nmol kg−1, with highest levels for the metabolite 2-DAMP. No EU maximum residue levels (MRL) for PM and its main metabolites exist in seafood to date, but the predicted levels were lower than the MRL for PM in swine of 32.7 nmol kg−1.publishedVersio

Dynamic effects of smoking cessation on disease incidence, mortality and quality of life: The role of time since cessation

<p>Abstract</p> <p>Background</p> <p>To support health policy makers in setting priorities, quantifying the potential effects of tobacco control on the burden of disease is useful. However, smoking is related to a variety of diseases and the dynamic effects of smoking cessation on the incidence of these diseases differ. Furthermore, many people who quit smoking relapse, most of them within a relatively short period.</p> <p>Methods</p> <p>In this paper, a method is presented for calculating the effects of smoking cessation interventions on disease incidence that allows to deal with relapse and the effect of time since quitting. A simulation model is described that links smoking to the incidence of 14 smoking related diseases. To demonstrate the model, health effects are estimated of two interventions in which part of current smokers in the Netherlands quits smoking.</p> <p>To illustrate the advantages of the model its results are compared with those of two simpler versions of the model. In one version we assumed no relapse after quitting and equal incidence rates for all former smokers. In the second version, incidence rates depend on time since cessation, but we assumed still no relapse after quitting.</p> <p>Results</p> <p>Not taking into account time since smoking cessation on disease incidence rates results in biased estimates of the effects of interventions. The immediate public health effects are overestimated, since the health risk of quitters immediately drops to the mean level of all former smokers. However, the long-term public health effects are underestimated since after longer periods of time the effects of past smoking disappear and so surviving quitters start to resemble never smokers. On balance, total health gains of smoking cessation are underestimated if one does not account for the effect of time since cessation on disease incidence rates. Not taking into account relapse of quitters overestimates health gains substantially.</p> <p>Conclusion</p> <p>The results show that simulation models are sensitive to assumptions made in specifying the model. The model should be specified carefully in accordance with the questions it is supposed to answer. If the aim of the model is to estimate effects of smoking cessation interventions on mortality and morbidity, one should include relapse of quitters and dependency on time since cessation of incidence rates of smoking-related chronic diseases. A drawback of such models is that data requirements are extensive.</p

Association between lung function and exacerbation frequency in patients with COPD

To quantify the relationship between severity of chronic obstructive pulmonary disease (COPD) as expressed by Global Initiative for Chronic Obstructive Lung Disease (GOLD) stage and the annual exacerbation frequency in patients with COPD. We performed a systematic literature review to identify randomized controlled trials and cohort studies reporting the exacerbation frequency in COPD patients receiving usual care or placebo. Annual frequencies were determined for total exacerbations defined by an increased use of health care (event-based), total exacerbations defined by an increase of symptoms, and severe exacerbations defined by a hospitalization. The association between the mean forced expiratory volume in one second (FEV(1))% predicted of study populations and the exacerbation frequencies was estimated using weighted log linear regression with random effects. The regression equations were applied to the mean FEV(1)% predicted for each GOLD stage to estimate the frequency per stage. Thirty-seven relevant studies were found, with 43 reports of total exacerbation frequency (event-based, n = 19; symptom-based, n = 24) and 14 reports of frequency of severe exacerbations. Annual event-based exacerbation frequencies per GOLD stage were estimated at 0.82 (95% confidence interval 0.46-1.49) for mild, 1.17 (0.93-1.50) for moderate, 1.61 (1.51-1.74) for severe, and 2.10 (1.51-2.94) for very severe COPD. Annual symptom-based frequencies were 1.15 (95% confidence interval 0.67-2.07), 1.44 (1.14-1.87), 1.76 (1.70-1.88), and 2.09 (1.57-2.82), respectively. For severe exacerbations, annual frequencies were 0.11 (95% confidence interval 0.02-0.56), 0.16 (0.07-0.33), 0.22 (0.20-0.23), and 0.28 (0.14-0.63), respectively. Study duration or type of study (cohort versus trial) did not significantly affect the outcomes. This study provides an estimate of the exacerbation frequency per GOLD stage, which can be used for health economic and modeling purposes

Cost-effectiveness analysis of face-to-face smoking cessation interventions by professionals

Objectives: To estimate the cost-effectiveness of five face-to-face smoking cessation interventions: 1) Telephone Counseling (TC), 2) Minimal counseling by a general practitioner (H-MIS), 3) Minimal counseling by a general practitioner combined with Nicotine Replacement Therapy (H-MIS+NRT), 4) Intensive Counseling combined with Nicotine Replacement Therapy (IC+NRT) and 5) Intensive Counseling combined with Bupropion (IC+Bupr), in terms of costs per quitter, costs per life-year gained and costs per quality-adjusted life-year (QALY) gained. Methods: Scenarios on increased implementation of smoking cessation interventions were compared to current practice. Base-case scenarios assumed that one of the five interventions was implemented for a period of either 1 year, 10 years or 75 years and reached 25% of the smokers. A computer simulation model, the RIVM Chronic Disease Model, was used to project future gains in life-years and Quality Adjusted Life Years (QALYs), and savings of health care costs from a decrease in the incidence of smoking-related diseases. Regardless of the duration for which the intervention was implemented, our time horizon was 75 years, i.e. costs and effects were studied over a period of 75 years. Intervention costs were computed based on bottom up estimates of resource use and costs per unit of resource use. Cost calculations of smoking cessation interventions were carried out from a health care perspective, i.e. total direct medical costs were calculated based on estimates of real resource use. Effectiveness in terms of cessation rates was obtained from Cochrane meta-analyses. For the base-case scenarios, future costs and effects were discounted at an annual percentage of 4%. Incremental cost-effectiveness ratios were calculated as: (additional intervention costs minus the savings from a reduced incidence of smoking related diseases) / (gain in health outcomes). A series of one-way sensitivity analyses were performed to assess the robustness of the cost-effectiveness ratios with regard to variations in cessation rates, intervention costs, discount rates, time horizon, and the percentage of smokers reached by the intervention. Results: Base-case estimates for costs per quitter ranged from Euro 443 for H-MIS to Euro 2800 for IC+NRT. Compared to current practice H-MIS is a dominant intervention regardless of the duration of implementation. This means that H-MIS not onl

Cost-effectiveness of face-to-face smoking cessation interventions: A dynamic modeling study

Objectives: To estimate the cost-effectiveness of five face-to-face smoking cessation interventions (i.e., minimal counseling by a general practitioner (GP) with, or without nicotine replacement therapy (NRT), intensive counseling with NRT, or bupropion, and telephone counseling) in terms of costs per quitter, costs per life-year gained, and costs per quality-adjusted life-year (QALY) gained. Methods: Scenarios on increased implementation of smoking cessation interventions were compared with current practice in The Netherlands. One of the five interventions was implemented for a period of 1, 10, or 75 years reaching 25% of the smokers each year. A dynamic population model, the RIVM chronic disease model, was used to project future gains in life-years and QALYs, and savings of health-care costs from a decrease in the incidence of 11 smoking-related diseases over a time horizon of 75 years. This model allows the repetitive application of increased cessation rates to a population with a changing demographic and risk factor mix. Sensitivity analyses were performed for variations in costs, effects, time horizon, program size, and discount rates. Results: Compared with current practice, minimal GP counseling was a dominant intervention, generating both gains in life-years and QALYs and savings that were highe

Future Burden and Costs of Smoking-Related Disease in the Netherlands: A Dynamic Modeling Approach

AbstractObjectivesIn this article, we explore the future health gain of different policy measures to reduce smoking prevalence: health education campaigns specifically aimed at keeping (young) people from starting to smoke, campaigns aimed at persuading smokers to quit, and tax measures.MethodsWe drew up different policy scenarios based on evaluations of several health promotion campaigns. Implementing these into the dynamic multistate models, we simulated smoking prevalence, loss of life-years, and costs for several decades into the next century.ResultsIn the short run, campaigns aimed at potential “quitters” appear to be most effective in terms of health gain. However, their effect fades away after several decades, while campaigns aimed at young “starters” or tax measures in the end yield a larger and more lasting decrease in smoking attributable disease burden.ConclusionDynamic modeling is very useful tool in calculating costs and effects of preventive public health measures

Environmental Impact Determinants: An Empirical Analysis based on the STIRPAT Model

AbstractThis paper attempt to investigate the impact of economic and population growth, urbanization level, energy intensity and Kyoto protocol obligations on carbon dioxide emissions using the STIRPAT model (STochastic Impacts by Regression on Population, Affluence and Technology). Our sample of countries is decomposed into groups according to the revenue level and the analyzed period extends from 1980 through 2010. Using several methods to estimate panel data, we find that there is a significant effect of economic growth, population growth, urbanization level and Kyoto protocol on emissions level and this effect depends on the revenue level

Bounded-width polynomial-size branching programs recognize exactly those languages in NC1

AbstractWe show that any language recognized by an NC1 circuit (fan-in 2, depth O(log n)) can be recognized by a width-5 polynomial-size branching program. As any bounded-width polynomial-size branching program can be simulated by an NC1 circuit, we have that the class of languages recognized by such programs is exactly nonuniform NC1. Further, following Ruzzo (J. Comput. System Sci. 22 (1981), 365–383) and Cook (Inform. and Control 64 (1985) 2–22), if the branching programs are restricted to be ATIME(logn)-uniform, they recognize the same languages as do ATIME(log n)-uniform NC1 circuits, that is, those languages in ATIME(log n). We also extend the method of proof to investigate the complexity of the word problem for a fixed permutation group and show that polynomial size circuits of width 4 also recognize exactly nonuniform NC1

Co-occurrence of diabetes, myocardial infarction, stroke, and cancer: quantifying age patterns in the Dutch population using health survey data

<p>Abstract</p> <p>Background</p> <p>The high prevalence of chronic diseases in Western countries implies that the presence of multiple chronic diseases within one person is common. Especially at older ages, when the likelihood of having a chronic disease increases, the co-occurrence of distinct diseases will be encountered more frequently. The aim of this study was to estimate the age-specific prevalence of multimorbidity in the general population. In particular, we investigate to what extent specific pairs of diseases cluster within people and how this deviates from what is to be expected under the assumption of the independent occurrence of diseases (i.e., sheer coincidence).</p> <p>Methods</p> <p>We used data from a Dutch health survey to estimate the prevalence of pairs of chronic diseases specified by age. Diseases we focused on were diabetes, myocardial infarction, stroke, and cancer. Multinomial P-splines were fitted to the data to model the relation between age and disease status (single versus two diseases). To assess to what extent co-occurrence cannot be explained by independent occurrence, we estimated observed/expected co-occurrence ratios using predictions of the fitted regression models.</p> <p>Results</p> <p>Prevalence increased with age for all disease pairs. For all disease pairs, prevalence at most ages was much higher than is to be expected on the basis of coincidence. Observed/expected ratios of disease combinations decreased with age.</p> <p>Conclusion</p> <p>Common chronic diseases co-occur in one individual more frequently than is due to chance. In monitoring the occurrence of diseases among the population at large, such multimorbidity is insufficiently taken into account.</p