• A Systematic Review of Social Contact Surveys to Inform Transmission Models of Close-contact Infections.

      Hoang, Thang; Coletti, Pietro; Melegaro, Alessia; Wallinga, Jacco; Grijalva, Carlos G; Edmunds, John W; Beutels, Philippe; Hens, Niel (2019-09-01)
    • Antibody Specificity Following a Recent Infection in Adolescence Is Correlated With the Pertussis Vaccine Received in Childhood.

      Raeven, René H M; van der Maas, Larissa; Pennings, Jeroen L A; Fuursted, Kurt; Jørgensen, Charlotte Sværke; van Riet, Elly; Metz, Bernard; Kersten, Gideon F A; Dalby, Tine (2019-01-01)
      Bordetella (B.) pertussis resurgence affects not only the unvaccinated, but also the vaccinated population. Different vaccines are available, however, it is currently unknown whether the type of childhood vaccination has an influence on antibody responses following a B. pertussis infection later in life. Therefore, the study aim was to profile serum antibody responses in young adults with suspected B. pertussis infections, immunized during childhood with either whole-cell (wPV) or monocomponent acellular pertussis (aPV) vaccines. Serum anti-pertussis toxin (PTx) IgG antibody levels served as an indicator for a recent B. pertussis infection. Leftover sera from a diagnostic laboratory from 36 Danish individuals were included and divided into four groups based on immunization background (aPV vs. wPV) and serum anti-PTx IgG levels (- vs. +). Pertussis-specific IgG/IgA antibody levels and antigen specificity were determined by using multiplex immunoassays (MIA), one- and two-dimensional immunoblotting (1 & 2DEWB), and mass spectrometry. Besides enhanced anti-PTx levels, wPV(+) and aPV(+) groups showed increased IgG and IgA levels against pertactin, filamentous hemagglutinin, fimbriae 2/3, and pertussis outer membrane vesicles (OMV). In the wPV(-) and aPV(-) groups, only low levels of anti-OMV antibodies were detected. 1DEWB demonstrated that antibody patterns differed between groups but also between individuals with the same immunization background and anti-PTx levels. 2DWB analysis for serum IgG revealed 133 immunogenic antigens of which 40 were significantly different between groups allowing to differentiate wPV(+) and aPV(+) groups. Similarly, for serum IgA, 7 of 47 immunogenic protein spots were significantly different. This study demonstrated that B. pertussis infection-induced antibody responses were distinct on antigen level between individuals with either wPV or aPV immunization background. Importantly, only 2DEWB and not MIA could detect these differences indicating the potential of this method. Moreover, in individuals immunized with an aPV containing only PTx in childhood, the infection-induced antibody responses were not limited to PTx alone.
    • Glucocorticoid receptor-dependent induction of () inhibits zebrafish caudal fin regeneration.

      Garland, Michael A; Sengupta, Sumitra; Mathew, Lijoy K; Truong, Lisa; de Jong, Esther; Piersma, Aldert H; La Du, Jane; Tanguay, Robert L (2019-01-01)
      We previously used a chemical genetics approach with the larval zebrafish to identify small molecule inhibitors of tissue regeneration. This led to the discovery that glucocorticoids (GC) block early stages of tissue regeneration by the inappropriate activation of the glucocorticoid receptor (GR). We performed a microarray analysis to identify the changes in gene expression associated with beclomethasone dipropionate (BDP) exposure during epimorphic fin regeneration. Oncofetal cripto-1 showed > eight-fold increased expression in BDP-treated regenerates. We hypothesized that the mis-expression of cripto-1 was essential for BDP to block regeneration. Expression of cripto-1 was not elevated in GR morphants in the presence of BDP indicating that cripto-1 induction was GR-dependent. Partial translational suppression of Cripto-1 in the presence of BDP restored tissue regeneration. Retinoic acid exposure prevented increased cripto-1 expression and permitted regeneration in the presence of BDP. We demonstrated that BDP exposure increased cripto-1 expression in mouse embryonic stem cells and that regulation of cripto-1 by GCs is conserved in mammals.
    • A comparison of linear regression, regularization, and machine learning algorithms to develop Europe-wide spatial models of fine particles and nitrogen dioxide.

      Chen, Jie; de Hoogh, Kees; Gulliver, John; Hoffmann, Barbara; Hertel, Ole; Ketzel, Matthias; Bauwelinck, Mariska; van Donkelaar, Aaron; Hvidtfeldt, Ulla A; Katsouyanni, Klea; et al. (2019-09-01)
      Empirical spatial air pollution models have been applied extensively to assess exposure in epidemiological studies with increasingly sophisticated and complex statistical algorithms beyond ordinary linear regression. However, different algorithms have rarely been compared in terms of their predictive ability. This study compared 16 algorithms to predict annual average fine particle (PM2.5) and nitrogen dioxide (NO2) concentrations across Europe. The evaluated algorithms included linear stepwise regression, regularization techniques and machine learning methods. Air pollution models were developed based on the 2010 routine monitoring data from the AIRBASE dataset maintained by the European Environmental Agency (543 sites for PM2.5 and 2399 sites for NO2), using satellite observations, dispersion model estimates and land use variables as predictors. We compared the models by performing five-fold cross-validation (CV) and by external validation (EV) using annual average concentrations measured at 416 (PM2.5) and 1396 sites (NO2) from the ESCAPE study. We further assessed the correlations between predictions by each pair of algorithms at the ESCAPE sites. For PM2.5, the models performed similarly across algorithms with a mean CV R2 of 0.59 and a mean EV R2 of 0.53. Generalized boosted machine, random forest and bagging performed best (CV R2~0.63; EV R2 0.58-0.61), while backward stepwise linear regression, support vector regression and artificial neural network performed less well (CV R2 0.48-0.57; EV R2 0.39-0.46). Most of the PM2.5 model predictions at ESCAPE sites were highly correlated (R2 > 0.85, with the exception of predictions from the artificial neural network). For NO2, the models performed even more similarly across different algorithms, with CV R2s ranging from 0.57 to 0.62, and EV R2s ranging from 0.49 to 0.51. The predicted concentrations from all algorithms at ESCAPE sites were highly correlated (R2 > 0.9). For both pollutants, biases were low for all models except the artificial neural network. Dispersion model estimates and satellite observations were two of the most important predictors for PM2.5 models whilst dispersion model estimates and traffic variables were most important for NO2 models in all algorithms that allow assessment of the importance of variables. Different statistical algorithms performed similarly when modelling spatial variation in annual average air pollution concentrations using a large number of training sites.
    • The effect of body mass index on the risk of surgical site infection.

      Meijs, Anouk P; Koek, Mayke B G; Vos, Margreet C; Geerlings, Suzanne E; Vogely, H Charles; de Greeff, Sabine C (2019-09-01)
    • Effect of a Russian-backbone live-attenuated influenza vaccine with an updated pandemic H1N1 strain on shedding and immunogenicity among children in The Gambia: an open-label, observational, phase 4 study.

      Lindsey, Benjamin B; Jagne, Ya Jankey; Armitage, Edwin P; Singanayagam, Anika; Sallah, Hadijatou J; Drammeh, Sainabou; Senghore, Elina; Mohammed, Nuredin I; Jeffries, David; Höschler, Katja; et al. (2019-08-01)
    • Associations between common respiratory viruses and invasive group A streptococcal infection: A time-series analysis.

      de Gier, Brechje; Vlaminckx, Bart J M; Woudt, Sjoukje H S; van Sorge, Nina M; van Asten, Liselotte (2019-09-01)
    • Obeticholic acid ameliorates dyslipidemia but not glucose tolerance in mouse model of gestational diabetes.

      McIlvride, Saraid; Nikolova, Vanya; Fan, Hei Man; McDonald, Julie A K; Wahlström, Annika; Bellafante, Elena; Jansen, Eugene; Adorini, Luciano; Shapiro, David; Jones, Peter; et al. (2019-08-01)
      Metabolism alters markedly with advancing gestation, characterized by progressive insulin resistance, dyslipidemia, and raised serum bile acids. The nuclear receptor farnesoid X receptor (FXR) has an integral role in bile acid homeostasis and modulates glucose and lipid metabolism. FXR is known to be functionally suppressed in pregnancy. The FXR agonist, obeticholic acid (OCA), improves insulin sensitivity in patients with type 2 diabetes with nonalcoholic fatty liver disease. We therefore hypothesized that OCA treatment during pregnancy could improve disease severity in a mouse model of gestational diabetes mellitus (GDM). C57BL/6J mice were fed a high-fat diet (HFD; 60% kcal from fat) for 4 wk before and throughout pregnancy to induce GDM. The impact of the diet supplemented with 0.03% OCA throughout pregnancy was studied. Pregnant HFD-fed mice displayed insulin resistance and dyslipidemia. OCA significantly reduced plasma cholesterol concentrations in nonpregnant and pregnant HFD-fed mice (by 22.4%, P < 0.05 and 36.4%, P < 0.001, respectively) and reduced the impact of pregnancy on insulin resistance but did not change glucose tolerance. In nonpregnant HFD-fed mice, OCA ameliorated weight gain, reduced mRNA expression of inflammatory markers in white adipose tissue, and reduced plasma glucagon-like peptide 1 concentrations (by 62.7%, P < 0.01). However, these effects were not evident in pregnant mice. OCA administration can normalize plasma cholesterol levels in a mouse model of GDM. However, the absence of several of the effects of OCA in pregnant mice indicates that the agonistic action of OCA is not sufficient to overcome many metabolic consequences of the pregnancy-associated reduction in FXR activity.
    • Public Perceptions of Contentious Risk: The Case of Rubber Granulate in the Netherlands.

      de Vries, Marion; Claassen, Liesbeth; Mennen, Marcel; Timen, Aura; Te Wierik, Margreet J M; Timmermans, Danielle R M (2019-06-25)
    • Corrigendum to "Simulation of mouse and rat spermatogenesis to inform genotoxicity testing using OECD test guideline 488" [Mutat. Res. 832-833 (2018) 19-28].

      Marchetti, Francesco; Aardema, Marilyn J; Beevers, Carol; van Benthem, Jan; Douglas, George R; Godschalk, Roger; Yauk, Carole L; Young, Robert; Williams, Andrew (2019-08-01)
    • Estimating the Human Papillomavirus Genotype Attribution in Screen-detected High-grade Cervical Lesions.

      Lissenberg-Witte, Birgit I; Bogaards, Johannes A; Quint, Wim G V; Berkhof, Johannes (2019-07-01)
    • Impact of maternal body mass index and gestational weight gain on pregnancy complications: an individual participant data meta-analysis of European, North American and Australian cohorts.

      Santos, S; Voerman, E; Amiano, P; Barros, H; Beilin, L J; Bergström, A; Charles, M-A; Chatzi, L; Chevrier, C; Chrousos, G P; et al. (2019-07-01)
    • Determinants of presence and removal of antibiotic resistance genes during WWTP treatment: A cross-sectional study.

      Pallares-Vega, Rebeca; Blaak, Hetty; van der Plaats, Rozemarijn; de Roda Husman, Ana M; Hernandez Leal, Lucia; van Loosdrecht, Mark C M; Weissbrodt, David G; Schmitt, Heike (2019-09-15)
    • A Novel Approach to Optimize Vitamin D Intake in Belgium through Fortification Based on Representative Food Consumption Data.

      Moyersoen, Isabelle; Devleesschauwer, Brecht; Dekkers, Arnold; Verkaik-Kloosterman, Janneke; de Ridder, Karin; Vandevijvere, Stefanie; Tafforeau, Jean; Van Oyen, Herman; Lachat, Carl; van Camp, John (2019-10-01)
    • Healthcare costs of patients on different renal replacement modalities - Analysis of Dutch health insurance claims data.

      Mohnen, Sigrid M; van Oosten, Manon J M; Los, Jeanine; Leegte, Martijn J H; Jager, Kitty J; Hemmelder, Marc H; Logtenberg, Susan J J; Stel, Vianda S; Hakkaart-van Roijen, Leona; de Wit, G Ardine (2019-01-01)
    • An improved life cycle impact assessment principle for assessing the impact of land use on ecosystem services.

      Othoniel, Benoit; Rugani, Benedetto; Heijungs, Reinout; Beyer, Marco; Machwitz, Miriam; Post, Pim (2019-07-13)
    • Making Vector-Borne Disease Surveillance Work: New Opportunities From the SDG Perspectives.

      Braks, Marieta; Giglio, Giorgia; Tomassone, Laura; Sprong, Hein; Leslie, Teresa (2019-01-01)
    • A deliberate choice? Exploring factors related to informed decision-making about childhood vaccination among acceptors, refusers, and partial acceptors.

      Romijnders, Kim A G J; van Seventer, Stephne L; Scheltema, Manon; van Osch, Liesbeth; de Vries, Hein; Mollema, Liesbeth (2019-09-03)