Bilthoven, Netherlands
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Viana M.,CSIC - Institute of Environmental Assessment And Water Research | Pey J.,CSIC - Institute of Environmental Assessment And Water Research | Querol X.,CSIC - Institute of Environmental Assessment And Water Research | Alastuey A.,CSIC - Institute of Environmental Assessment And Water Research | And 2 more authors.
Science of the Total Environment | Year: 2014

Atmospheric aerosols are emitted by natural and anthropogenic sources. Contributions from natural sources to ambient aerosols vary widely with time (inter-annual and seasonal variability) and as a function of the distance to source regions. This work aims to identify the main natural sources of atmospheric aerosols affecting air quality across Europe. The origin, frequency, magnitude, and spatial and temporal variability of natural events were assessed for the years 2008 and 2009. The main natural sources of atmospheric aerosols identified were African dust, sea spray and wildfires. Primary biological particles were not included in the present work. Volcanic eruptions did not affect air quality significantly in Europe during the study period. The impact of natural episodes on air quality was significant in Southern and Western Europe (Cyprus, Spain, France, UK, Greece, Malta, Italy and Portugal), where they contributed to surpass the PM10 daily and annual limit values. In Central and Northern Europe (Germany, Austria and Latvia) the impact of these events was lower, as it resulted in the exceedance of PM daily but not annual limit values. Contributions from natural sources to mean annual PM10 levels in 2008 and 2009 ranged between 1 and 2μg/m3 in Italy, France and Portugal, between 1 and 4μg/m3 in Spain (10μg/m3 when including the Canary Islands), 5μg/m3 in UK, between 3 and 8μg/m3 in Greece, and reached up to 13μg/m3 in Cyprus. The evaluation of the number of monitoring stations per country reporting natural exceedances of the daily limit value (DLV) is suggested as a potential tool for air quality monitoring networks to detect outliers in the assessment of natural contributions. It is strongly suggested that a reference methodology for the identification and quantification of African dust contributions should be adopted across Europe. © 2013 Elsevier B.V.

The generation and characterization of Ercc1∆/+ and Ercc1+/−mice have been previously described16. Ercc1∆/− mice were obtained by crossing Ercc1∆/+ (in a pure C57BL6J or FVB background) with Ercc1+/− mice (in a pure FVB or C57BL6J background respectively) to yield Ercc1∆/− offspring with a genetically uniform F1 C57BL6J/FVB hybrid background (see ref. 6 for motivation). Wild-type F1 littermates were used as controls. Xpg−/− mice have been characterized previously6 and were generated by crossing Xpg+/− (in a pure C57BL6J background) with Xpg+/− mice (in a pure FVB background). Hence, all animals used in the studies described here were of the same F1 C57BL6J/FVB hybrid background. Typical unfavourable characteristics, such as blindness in an FVB background or deafness in a C57BL6J background, do not occur in this hybrid background. Mice were weighed, visually inspected weekly, and scored in a blinded fashion for gross morphological and motor abnormalities. Since the Ercc1∆/− and Xpg−/− mice were smaller, food was administered within the cages and water bottles with long nozzles were used from around two weeks of age. Animals were maintained in a controlled environment (20–22 °C, 12 h light:12 h dark cycle) and were housed in individual ventilated cages under specific pathogen free conditions. Animals were individually housed at the EMC location and group housed at the RIVM location. Experiments were performed in accordance with the Principles of Laboratory Animal Care and with the guidelines approved by the Dutch Ethical Committee in full accordance with European legislation. For the lifespan studies the indicated number of mice per group for ad libitum and 30% dietary restriction were generated. Additionally, several cross-sectional cohorts were generated. For Ercc1∆/− mice we generated groups which were killed at 7, 11, 16 or 30 weeks of age. The 7-week group consisted only of ad libitum-fed animals while the 30-week group consisted only of dietary restriction-treated mice. For wild-type mice, ad libitum-fed and dietary restriction-treated groups were sacrificed at 11, 16 or 20 weeks. Sample size of the lifespan cohorts were based on power analysis. No statistical methods were used to predetermine sample size of cross-sectional cohorts. Animals were divided randomly over all groups to prevent selection bias. All mice were clinically diagnosed daily in a blinded manner and, when moribund, killed, after which necropsy was performed. Animals from cross-sectional cohorts were killed when necropsy age was reached. Organs were stored at −80°C for molecular analysis or (perfusion) fixated in (para)formaldehyde for pathological examinations. Statistics was performed with survival curve analysis using the product-limit method of Kaplan and Meier in GraphPad Prism. All animals were bred and maintained on AIN93G synthetic pellets (Research Diet Services B.V.; gross energy content 4.9 kcal/g dry mass, digestible energy 3.97 kcal/g). The initial lifespan cohort, shown in Fig. 1a, were fed standard AIN93G pellets containing 2.5 g/kg choline bitartrate. To avoid potential formation of bladder and kidney stones, we replaced choline bitartrate with choline chloride in all subsequent experiments. The amount of dietary restriction was determined in a prior pilot study and food intake of the ad libitum-fed mice was continuously monitored. On average, Ercc1∆/− and Xpg−/− mice ate 2.3 g food per day. Dietary restriction was initiated at 7 weeks of age with 10% food reduction (2.1 g/day), when animals reached almost-maximum bodyweight and development was completed. Dietary restriction was increased weekly by 10%, until it reached 30% dietary restriction (1.6 g/day) from 9 weeks of age onward. Temporary dietary restriction was initiated directly with 30% food reduction at 6 weeks of age. These mice received ad libitum food again from 12 weeks onward. Wild-type mice ate on average 3.0 g food per day, resulting in 2.1 g/day for 30% dietary restriction. Food was given to the animals just before the start of the dark (active) period to avoid alteration of the biological clock. Representative sections from the liver, kidneys, sciatic nerve, testes and femur were processed, stained with haematoxylin and eosin, and microscopically examined in a blinded manner by two board-certified pathologists (SAY, AdB) for the presence of histopathologic lesions. The severity score of lesions was semi-quantitatively assessed. Scores were given as absent (0), subtle (1), mild (2), moderate (3), severe (4), and massive (5). Digital images from the kidneys and femur cortical bone at mid-shaft area were taken for morphometric analysis using Labsense image analysis software (Olympus). Ageing characteristics were assessed in >5 animals per group per sex. Groups were compared with nonparametric Mann–Whitney U and Kruskal–Wallis tests. Polyploidy levels were assessed based on propidium iodide (PI) fluorescence using FACS analysis31, 32. A small part of the left lobe (approximately 5 mm3) was dissected from ad libitum- and dietary restriction-treated Ercc1∆/− mice (7, 11, 16 and 30 weeks, n = 5) and wild-type mice (11 weeks, n = 5), cut into small fragments and suspended in 800 μl PBS using a syringe (21G). 300 μl homogenate was added to 300 μl 100% ethanol for fixation. Samples were stored for at least 24 h before further processing. After fixation the liver homogenate was washed with ice-cold PBS and subsequently incubated with a pepsin solution for 20 min. After washing in PBS/Tween-20, cells were collected in 500 μl PBS supplemented with 5 μg/ml PI and 250 μg/ml RNase and samples were measured using the FACS (FACSCalibur, Becton Dickinson). Differences between groups were assessed with a two-way ANOVA, with age and diet as fixed factors. Ad libitum- and diet-restricted mice were killed by cervical dislocation at scheduled ages, femora were excised and non-osseous tissue was removed. Two days after fixation in 4% formalin, the right femora were scanned using Skyscan 1076 in vivo X-Ray computed tomography (Bruker microCT) with a voxel size of 8.88 μm. Osseous tissue was distinguished from non-osseous tissue by segmenting the reconstructed grayscale images with an automated algorithm using local thresholds33. The region of interest (ROI) (the distal metaphysis of the femora) was selected using 3D data analysis software. To compensate for bone length differences, the length of each ROI was determined relative to the largest specimen femur of the cohort. The cortex and trabeculae of the metaphysis were separated using automated software developed in-house. The thickness of the trabeculae and cortices were assessed using 3D analysis software as described34 using the CT analyser software package (Bruker microCT). A bone specimen with known bone morphometrics was included within each scan as a quantitative control. Statistical significance was calculated using one-way Anova with Bonferroni’s multiple comparison test. The responses of isolated aortic tissue were ex vivo measured in small-wire myograph organ baths containing oxygenated Krebs-Henseleit buffer at 37 °C. After preconstriction with 30 nmol/l U46619, relaxation concentration–response curves to acetylcholine were constructed35. Single-cell suspensions were prepared from spleen by passing the cells through a cell strainer with HEPES-buffered saline solution (HBSS) supplemented with 2% FBS and washed. Erythrocytes were eliminated with ACK buffer. For CD4+CD25+Foxp3+ staining, cells were first stained for the expression of cell surface markers and then fixed, permeabilised, and stained using the Foxp3 kit (eBiosciences) according to the manufacturer’s instructions. FACS analysis was performed using FACS (Becton Dickinson) and analysed with FlowJo Software (TreeStar). Mice were killed by CO asphyxiation and blood was immediately collected from the heart. Glucose levels were measured using a Freestyle mini blood glucose metre. Insulin and albumin levels were measured in blood plasma using an ultrasensitive mouse insulin Elisa (Mercodia AB) or mouse albumin ELISA kit (Immunology Consultants Laboratory, Inc.), respectively. Insulin levels were determined after overnight fasting. Glucose levels were determined after feeding, at the beginning of the dark period. Euthanasia of moribund or cross-sectional animals was performed by intramuscular injection of a ketamine–rompun mixture, followed by exsanguination3. IgA immunoglobulin was measured in blood serum using the commercially available bead-based multiplexed panel Mouse Immunoglobulin Isotyping (Millipore Corporation). Standard analysis protocols were followed and all samples were analysed at least in duplo. The mice were weighed and visually inspected weekly, and were scored in a blinded manner by two experienced research technicians (R.M.C.B. and S.B.) for the onset of various phenotypical parameters. Clasping was measured by suspending mice by their tails for 20 s. A clasping event was scored when retraction of both hind limbs towards the body was observed for at least 5 s. Whole-body tremor was scored if mice were trembling for a combined total of at least 10 s when put on a flat surface for 20 s. Impaired balance was determined by observing the mice walking on a flat surface for 20 s. Mice that had difficulties in maintaining an upright orientation during this period were scored as having imbalance. If mice showed a partial loss of function of the hind limbs, they were scored as having paresis. Statistics were performed with survival-curve analysis using the product-limit method of Kaplan and Meier in GraphPad Prism. Rotarod performance was assessed by measuring the average time spent on an accelerating rotarod (Ugo Basile). All animals were given four consecutive trials of a maximum of 5 min with inter-trial intervals of 1 h. For weekly monitoring, the motor coordination performance was measured with two consecutive trials of a maximum of 5 min. Grip strength was determined by placing mice with forelimbs or all limbs on a grid attached to a force gauge, and steadily pulling the mice by their tail. Grip strength is defined as the maximum strength produced by the mouse before releasing the grid. For each value the test was performed in triplicate. To quantify apoptotic cells in the retina, eyes were fixed overnight in 10% phosphate-buffered formalin (JT Baker), paraffin-embedded, sectioned at 5 mm, and mounted on Superfrost Plus slides. Paraffin sections were employed for TdT-mediated dUTP nick-end labelling (TUNEL) assay using an Apoptag Plus Peroxidase in situ apoptosis detection kit (Millipore). Sections were deparaffinised and incubated as described by the manufacturer. Statistical differences were calculated with a t-test. Primary antibodies (supplier; catalogue number; dilutions) used in this study were as follows: rabbit anti-ATF3 (Santa Cruz; sc-188; 1:2,000), goat anti-ChAT (Millipore; AB144P; 1:500); rabbit anti-GFAP (DAKO; Z0334; 1:8,000); mouse anti-GM130 (BD Transduction; 610823; 1:100); rabbit anti-Iba-1 (Wako; 019-19741; 1:5,000); rat anti-Mac2 (Cedarlane; CL8942AP; 1:2,000); mouse anti-NeuN (Millipore; MAB377; 1:1,000); rabbit anti-p53 (Leica; NCL-p53-CM5p; 1:1,000); mouse anti-γH2AX (Millipore; 05-636; 1:4,000). For avidin-biotin-peroxidase immunocytochemistry biotinylated secondary antibodies from Vector Laboratories, diluted 1:200 were used. Alexa488-, Cy3-, and Cy5-conjugated secondary antibodies raised in donkey (Jackson ImmunoResearch) diluted at 1:200 were used for confocal immunofluorescence. Mice were anaesthetized with pentobarbital and perfused transcardially with 4% paraformaldehyde. The brain and spinal cord were carefully dissected out, post-fixed for 1 h in 4% paraformaldehyde, cryoprotected, embedded in 12% gelatin, rapidly frozen, and sectioned at 40 μm using a freezing microtome or stored at −80 °C until use. Frozen sections were processed free floating using the ABC method (ABC, Vector Laboratories) or single-, double-, and triple-labelling immunofluorescence. Immunoperoxidase-stained sections were analysed and photographed using an Olympus BX40 microscope. Immunofluorescence sections were analysed using a Zeiss LSM700 confocal microscope. Mean intensities were quantified using Fiji. Statistical differences were calculated with a t-test. Total RNA was extracted using QIAzol lysis Reagent from mouse tissue specimens. For increased purity, miRNAeasy Mini Kits (QIAGEN) were used. Addition of wash buffers RPE and RWT (QIAGEN) was done mechanically by using the QIAcube (QIAGEN) via the miRNeasy program and tissue was stored at −80 °C. The concentration of RNA was measured by Nanodrop (Thermo Fisher Scientific). Gene expression analyses were performed with gene-specific real-time PCR primers (see below) using SYBR Green (Sigma-Aldrich) and Platinum Taq polymerase (Life Technologies) on a Bio-Rad CFX96 thermocycler or with pre-designed TaqMan Gene Expression Assays (given below) with a 7500 Fast Real-Time PCR System (Applied Biosystems). Relative gene expressions were calculated as previously described6. For SYBR Green method the following primers were used (forward primer 5′ to 3′; reverse primer 5′ to 3′): Gsta1 (CTTCTGACCCCTTTCCCTCT; ATCCATGGGAGGCTTTCTCT), Nqo1 (GGTAGCGGCTCCATGTACTC; GAGTGTGGCCAATGCTGTAA), Nfe2l2 (AGGACATGGAGCAAGTTTGG; TCTGTCAGTGTGGCTTCTGG), Gstt2 (CGAGCAATTCTCCCAGGTGA; TATTCGTGGACTTGGGCACG), Fkbp5 (TGTTCAAGAAGTTCGCAGAGC; CCTTCTTGCTCCCAGCTTT), Srxn1 (TGAGCAGCTCCTCTGATGTG; GCTGAGGTGACAATTGACTATGG), Gsta4 (TCGATGGGATGATGCTGAC; CATCTGCATACATGTCAATCCTG), Gclm (TGGAGCAGCTGTATCAGTGG; CAAAGGCAGTCAAATCTGGTG), Hmox1 (CAGGTGATGCTGACAGAGGA; ATGGCATAAATTCCCACTGC), Gclc (AGATGATAGAACACGGGAGGAG; TGATCCTAAAGCGATTGTTCTTC), Ephx1 (GAGTGGAGGAACTGCACACC; AGCACAGAAGCCAGGATGA), Mgst1 (CTCGGCAGGACAACTTGC; CCATGCTTCCAATCTTGGTC), TubG2 (CAGACCAACCACTGCTACAT; AGGGAATGAAGTTGGCCAGT), Hprt (TGATAGATCCATTCCTATGACTGTAGA; AAGACATTCTTTCCAGTTAAAGTTGAG), Rps9 (ATCCGCCAACGTCACATTA; TCTTCACTCGGCCTGGAC). As pre-designed TaqMan assays we used (order number; sequence 5′ to 3′): Ghr (Mm00439093_m1; GACAAGCTGCAAGAATTGCTCATGA), Igf1r (Mm00802831_m1; GGCCAGAAGTGGAGCAGAATAATCT), HPRT-E2_3 (HPRT-E2_3_F; GCCGAGGATTTGGAAAAAGTGTTTA, HPRT-E2_3_R; TTCATGACATCTCGAGCAAGTCTTT, HPRT-E2_3_M; CAGTCCTGTCCATAATCA), POLR2A-E2_3 (POLR2A-E2_3F; GCAGTTCGGAGTCCTGAGT, POLR2A-E2_3R; CCCTCTGTTGTTTCTGGGTATTTGA, POLR2A-E2_3M2; CATCCGCTTCAATTCAT). RNA quality was assessed using the 2100 Bio-Analyzer (Agilent Technologies) following the manufacturer’s instructions. The quality of the RNA is expressed as the RNA integrity number (RIN, range 0–10). Samples with a RIN below 8 were excluded from analysis. Hybridization to Affymetrix HT MG-430 p.m. Array Plates was performed at the Microarray Department of the University of Amsterdam according to Affymetrix protocols. Quality control and normalization were performed using the pipeline at the website (Maastricht University). The same total RNA extracts were used as extracted for mRNA analysis (above). miRNA expression levels were assessed using a miRNA micro-array (miRCURY LNA microRNA Array (7th Gen.), Exiqon). All probes with more than three calls were selected for assessing differential expression between groups. Differences in mean expression were compared using a one-way ANOVA. Probes with a FDR of 5% were considered as significantly differentially expressed. RNA expression analysis was also performed with the next-generation sequencing approach on one animal per treatment as described in ref. 36. Raw data (CEL files) were normalized by robust multichip average (RMA) in the oligo BioConductor package, which summarizes perfect matches through median polish and collapses probes into core transcripts based on.CDF annotation file provided by Affymetrix using the R open statistical package ( All data files have been submitted to the NCBI gene expression omnibus under accession number GSE77495. Principal component analysis (PCA) was performed using all the probe sets in the array. A graphical representation was generated to show the relationship among the different samples. PCA is a linear projection method that defines a new dimensional space to capture the maximum information present in the initial data set. It is an unsupervised exploratory technique used to remove noise, reduce dimensionality and identify common/dominant signals oriented to try to find biological meaning37. The two principal components with the highest amount of variance were plotted. PCA was performed using the prcomp package and the plot was drawn with gplots, both from the Bioconductor project ( The linear model from Limma38 implemented in R was used to identify the DEGs. Pairwise comparisons for each genotype between ad libitum and dietary restriction samples were applied to calculate the fold change (FC), P value and false discovery rate (FDR) for each probe in the microarray. Cut-off values for a DEG were put at FDR < 5% with FC ≥ |1.5|. For all mouse analyses, differentially expressed probes were considered as DEGs. Overlap between lists of DEGs was identified looking by the intersection between pair of lists. To determine if the overlap was higher than expected by chance the hypergeometric distribution was used as is implemented in phyper function in R. Additionally the factor of enrichment was calculated with the formula: EF = nAB/((nA × nB)/nC). Where: nA = Number of DEG in experimental group A; nB = Number of DEG in experimental group B; nC = Number of total genes in the microarray; nAB = Number of common DEG between A and B. Pathway enrichment analysis was conducted via overrepresentation analysis (ORA). ORA was performed in the Interactive pathway analysis (IPA) of complex genomics data software (Ingenuity Systems, Qiagen) by employing a pre-filtered list of differentially expressed genes. Genes were selected as differentially expressed if they had a fold change ≥ 1.5 and an FDR lower than 0.05. The over-represented canonical pathways were generated based on information in the Ingenuity Pathways Knowledge Base. A pathway was selected as deregulated when the P value in the Fisher test was lower than 0.01. Additionally, IPA transcription factor (TF) analysis was performed to identify the cascade of upstream transcriptional regulators that can explain the observed gene expression changes in the different lists of DEGs. To do this, data stored in the Ingenuity Knowledge Base, with prior information on the expected effects between TF and their target genes, were used. The analysis examines how many known targets of each TF are present in the list of DEGs, and also compares their direction of change to what is expected from the literature, in order to predict likely relevant transcriptional regulators. If the observed direction of change is mostly consistent with a particular activation state of the transcriptional regulator (‘activated’ or ‘inhibited’), then a prediction is made about that activation state. For each TF two statistical measures are computed (overlap P value and activation z-score). The overlap P value labels upstream regulators based on significant overlap between data set genes and known targets regulated by a TF. The activation z-score is used to infer the likely activation states of upstream regulators based on comparison with a model that assigns random regulation directions. Overlap P value lower than 0.05 and z-score higher than |2| were selected as thresholds to identify a TF as relevant. Limma was used to identify the DEGs among ALWT samples compared with the other experimental conditions (DRWT, ALErcc1 and DRErcc1). Next, probe-sets in the Affymetrix array with multiple gene annotation were filtered out. BiomaRt39 was used to retrieve the gene length for the remaining probe sets (32,930 probe-sets from 45,142 probe-sets in the original microarray). Differentially expressed genes were selected using an FDR of <0.05 and a linear fold change of ±1.5. The Shapiro–Wilk test was applied to contrast the normality of the distribution of gene length in the different lists of DEGs. Because most of the distributions were not normal, a Mann–Whitney test for non-paired samples test was used to evaluate whether the distributions of DEGs were different between the different comparisons. Finally, a relative frequency (kernel density) plot of gene length and probability density for DEG in each comparison was drawn using the density function implemented in R. Kernel density estimates are related to histograms, but with the possibility to smooth and continuity by using a kernel function. The y axis represents the density probability for a specific range of values in the x axis. Liver extracts from ad libitum- and dietary restriction-treated Ercc1∆/− and wild type mice (n = 6, 11 weeks) were prepared by mechanical disruption in lysis buffer (150 mM NaCl, 1% Triton X-100, 50 mM Tris), which was supplemented with mini complete protease inhibitor (Roche Diagnostics) and phosphate inhibitors (5 mM NaF, 1 mM Na-orthovanadate). After mechanical disruption, lysates were incubated on ice for 1 h and subsequently centrifuged at 4 °C for 20 min. Lysate (25–50 μg) was loaded on a 10% SDS–PAGE gel (Life Technologies LTD) and transferred to a PVDF transfer membrane (GE-Healthcare Life Sciences). Levels of S6 (#2217S Lot5; 1:2,000), S6(Ser240/244; #2215 Lot14; 1:500), Akt (#9272 Lot25; 1:500), Akt(Ser473; #9271S Lot13; 1:250) and Akt(Thr308; #9275S Lot19; 1:500) were detected (Cell Signaling Technology), semi-quantified using the ImageJ software package ( and phosphorylated:total ratios relative to ad libitum samples were calculated. Differences between groups were assessed with a t-test. β-Actin was used as loading control (Sigma; A5441 Lot064M4789V; 1:25,000).

Home > Press > The Sustainable Nanotechnologies Project’s Final Events: Bringing Nano Environmental Health and Safety Assessment to the Wider Discussion on Risk Governance of Key Enabling Technologies Abstract: The EU FP7 Sustainable Nanotechnologies (SUN) Project is coming to its end in March 2017. The project has designed its final events to serve as an effective platform to communicate the main results achieved in its course within the Nanosafety community and bridge them to a wider audience addressing the emerging risks of Key Enabling Technologies (KETs). The series of events include the New Tools and Approaches for Nanomaterial Safety Assessment: A joint conference organized by NANOSOLUTIONS, SUN, NanoMILE, GUIDEnano and eNanoMapper to be held on 7 – 9 February 2017 in Malaga, Spain, the SUN-CaLIBRAte Stakeholders workshop to be held on 28 February – 1 March 2017 in Venice, Italy and the SRA Policy Forum: Risk Governance for Key Enabling Technologies to be held on 1- 3 March in Venice, Italy. Jointly organized by the Society for Risk Analysis (SRA) and the SUN Project, the SRA Policy Forum will address current efforts put towards refining the risk governance of emerging technologies through the integration of traditional risk analytic tools alongside considerations of social and economic concerns. The parallel sessions will be organized in 4 tracks: Risk analysis of engineered nanomaterials along product lifecycle, Risks and benefits of emerging technologies used in medical applications, Challenges of governing SynBio and Biotech, and Methods and tools for risk governance. The SRA Policy Forum has announced its speakers and preliminary Programme. Confirmed speakers include: Keld Alstrup Jensen (National Research Centre for the Working Environment, Denmark) Elke Anklam (European Commission, Belgium) Adam Arkin (University of California, Berkeley, USA) Phil Demokritou (Harvard University, USA) Gerard Escher (École polytechnique fédérale de Lausanne, Switzerland) Lisa Friedersdor (National Nanotechnology Initiative, USA) James Lambert (President, Society for Risk Analysis, USA) Andre Nel (The University of California, Los Angeles, USA) Bernd Nowack (EMPA, Switzerland) Ortwin Renn (University of Stuttgart, Germany) Vicki Stone (Heriot-Watt University, UK) Theo Vermeire (National Institute for Public Health and the Environment (RIVM), Netherlands) Tom van Teunenbroek (Ministry of Infrastructure and Environment, The Netherlands) Wendel Wohlleben (BASF, Germany) The New Tools and Approaches for Nanomaterial Safety Assessment (NMSA) conference aims at presenting the main results achieved in the course of the organizing projects fostering a discussion about their impact in the nanosafety field and possibilities for future research programmes. The conference welcomes consortium partners, as well as representatives from other EU projects, industry, government, civil society and media. Accordingly, the conference topics include: Hazard assessment along the life cycle of nano-enabled products, Exposure assessment along the life cycle of nano-enabled products, Risk assessment & management, Systems biology approaches in nanosafety, Categorization & grouping of nanomaterials, Nanosafety infrastructure, Safe by design. The NMSA conference key note speakers include: Harri Alenius (University of Helsinki, Finland,) Antonio Marcomini (Ca’ Foscari University of Venice, Italy) Wendel Wohlleben (BASF, Germany) Danail Hristozov (Ca’ Foscari University of Venice, Italy) Eva Valsami-Jones (University of Birmingham, UK) Socorro Vázquez-Campos (LEITAT Technolоgical Center, Spain) Barry Hardy (Douglas Connect GmbH, Switzerland) Egon Willighagen (Maastricht University, Netherlands) Nina Jeliazkova (IDEAconsult Ltd., Bulgaria) Haralambos Sarimveis (The National Technical University of Athens, Greece) During the SUN-caLIBRAte Stakeholder workshop the final version of the SUN user-friendly, software-based Decision Support System (SUNDS) for managing the environmental, economic and social impacts of nanotechnologies will be presented and discussed with its end users: industries, regulators and insurance sector representatives. The results from the discussion will be used as a foundation of the development of the caLIBRAte’s Risk Governance framework for assessment and management of human and environmental risks of MN and MN-enabled products. The SRA Policy Forum: Risk Governance for Key Enabling Technologies and the New Tools and Approaches for Nanomaterial Safety Assessment conference are now open for registration. Abstracts for the SRA Policy Forum can be submitted till 15th November 2016. For more information, please click If you have a comment, please us. Issuers of news releases, not 7th Wave, Inc. or Nanotechnology Now, are solely responsible for the accuracy of the content.

News Article | December 8, 2016

Algorithms used to track 2014 Ebola epidemic could be used to control future outbreaks of infectious diseases New research on the 2014 Ebola epidemic tracks the rate at which infections move from one district to another and how often infections cross the borders between countries. This study, published in PLOS Computational Biology, could be used to analyze breakouts of new infectious diseases - even when little is known about the transmission characteristics of the new infection. The 2014 Ebola epidemic hit some West African districts very hard, while leaving other districts untouched. Yet there is no evidence that the transmission of the Ebola virus differed between those districts, according to Drs Backer and Wallinga at the Dutch National Institute for Public Health (RIVM). By comparing the notification records in all districts of three affected countries (Guinea, Sierra Leone and Liberia), the researchers could trace back how the virus spread through each district and how it traveled from one district to another. Their research shows that each infective infected on average two new cases in the beginning of the epidemic, and that most of the infected individuals (at least 90%) did not leave their district. Some districts were hit harder because infection was introduced earlier and because infections were introduced more often. To extract this information from notification records the researchers developed novel algorithms, which represent an epidemic as a network of local outbreaks that are interconnected through travelers that transport infection from one district to another. The main advantages of this representation are that it avoids making strong assumptions on transmission characteristics, and that it requires few data beyond the number of inhabitants per district and the notification records. In the future, the researchers hope that their algorithms will help to effectively control any new emerging epidemic, even when we don't know much about the transmission characteristics of the new infection. "Monitoring epidemics is crucial if we want to assess the required effectiveness of control measures" says Dr. Backer, the lead author on this paper. "Now we show that when we monitor a local epidemic together with the epidemic in neighboring districts, we can inform decisions on movement bans or even border closures. In this way, our algorithms can help to effectively control emerging infections." In your coverage please use this URL to provide access to the freely available article in PLOS Computational Biology: http://journals. Citation: Backer JA, Wallinga J (2016) Spatiotemporal Analysis of the 2014 Ebola Epidemic in West Africa. PLoS Comput Biol 12(11): e1005210. doi:10.1371/journal.pcbi.1005210 Funding: The authors received no specific funding for this work. Competing Interests: The authors have declared that no competing interests exist.

Wichink Kruit R.J.,TNO | Schaap M.,TNO | Sauter F.J.,RIVM | Van Zanten M.C.,RIVM | Van Pul W.A.J.,RIVM
Biogeosciences | Year: 2012

A large shortcoming of current chemistry transport models (CTM) for simulating the fate of ammonia in the atmosphere is the lack of a description of the bi-directional surface-atmosphere exchange. In this paper, results of an update of the surface-atmosphere exchange module DEPAC, i.e. DEPosition of Acidifying Compounds, in the chemistry transport model LOTOS-EUROS are discussed. It is shown that with the new description, which includes bi-directional surface-atmosphere exchange, the modeled ammonia concentrations increase almost everywhere, in particular in agricultural source areas. The reason is that by using a compensation point the ammonia lifetime and transport distance is increased. As a consequence, deposition of ammonia and ammonium decreases in agricultural source areas, while it increases in large nature areas and remote regions especially in southern Scandinavia. The inclusion of a compensation point for water reduces the dry deposition over sea and allows reproducing the observed marine background concentrations at coastal locations to a better extent. A comparison with measurements shows that the model results better represent the measured ammonia concentrations. The concentrations in nature areas are slightly overestimated, while the concentrations in agricultural source areas are still underestimated. Although the introduction of the compensation point improves the model performance, the modeling of ammonia remains challenging. Important aspects are emission patterns in space and time as well as a proper approach to deal with the high concentration gradients in relation to model resolution. In short, the inclusion of a bi-directional surface-atmosphere exchange is a significant step forward for modeling ammonia. © Author(s) 2012. CC Attribution 3.0 License.

Smid J.H.,RIVM | Verloo D.,European Food Safety Authority | Barker G.C.,UK Institute of Food Research | Havelaar A.H.,RIVM
International Journal of Food Microbiology | Year: 2010

We discuss different aspects of farm-to-fork risk assessment from a modelling perspective. Stochastic simulation models as they are presented today represent a mathematical representation of nature. In food safety risk assessment, a common modelling approach consists of a logic chain beginning at the source of the hazard and ending with the unwanted consequences of interest. This 'farm-to-fork' approach usually begins with the hazard on the farm, sometimes with different compartments presenting different parts of the production chain, and ends with the 'dose' received by the consumer or in case a dose response model is available the number of cases of illness. These models are typically implemented as Monte Carlo simulations, which are unidirectional in nature, and the link between statistics and simulation model is not interactive. A possible solution could be the use of Bayesian belief networks (BBNs) and this paper tries to discuss in an intuitive way the possibilities of using BBNs as an alternative for Monte Carlo modelling. An inventory is made of the strengths and weaknesses of both approaches, and an example is given showing an additional use of BBNs in biotracing problems. © 2009 Elsevier B.V.

Blanckaert P.,Scientific Institute of Public Health | Van Amsterdam J.G.C.,RIVM | Brunt T.M.,Trimbos Institute | Van Den Berg J.D.J.,Netherlands Forensic Institute | And 3 more authors.
Journal of Psychopharmacology | Year: 2013

4-Methylamphetamine (4-MA) was originally developed as an appetite suppressant, but development was halted due to side effects. It has recently resurfaced as a new psychoactive substance in Europe, and is mostly found together with amphetamine. Around 11.5% of tested Dutch speed samples were positive for 4-MA. In Belgium, 4-MA was also found in speed samples. In 2011 and 2012, several fatal incidents after amphetamine use were observed in Belgium, the United Kingdom and The Netherlands. In all victims, toxicological analysis confirmed the presence of 4-MA, in addition to amphetamine. The observed blood amphetamine levels were too low to be fatal. Contrary to amphetamine, which displays noradrenergic and dopaminergic activity, 4-MA also shows serotonergic activity, which may contribute to the observed toxicity. Other mechanisms of toxicity are put forward in this paper as well. To conclude, the observed toxicity is most likely the result of the combined dopaminergic activity of amphetamine and the serotonergic activity of 4-MA. In addition, the presence of 4-MA may have dampened the psychoactive effects of amphetamine by attenuation of the amphetamine-induced dopamine release, potentially inclining users to ingest higher doses of contaminated speed. Also, slower metabolism of 4-MA and its MAO-inhibiting properties can also contribute to the unusual high toxicity of 4-MA. © The Author(s) 2013.

To establish the prevalence of human echinococcosis in the Netherlands by using data from laboratories carrying out diagnostic procedures and data from pathology registries from 1997-2008. Descriptive. Data on serological diagnostic tests for Echinococcus granulosus carried out from 1997 to 2008 were gathered from the National Institute for Public Health and the Environment (RIVM) in Bilthoven and Leiden University Medical Center (LUMC). Additionally, all echinococcosis patients registered on the pathology database of the Dutch pathological anatomy national automated archive (PALGA) were analysed. A total of 7314 serum samples from 5125 patients were examined for antibodies. Cyst material from 39 patients was examined using molecular methods. The number of serum samples sent in annually was stable at 550 to 600. Over the period investigated, 1997-2008, on serological investigation a total of 485 patients were found to have a positive result on IgG-ELISA. Of these, the diagnosis of echinococcosis was confirmed in 445 patients by further serological investigation (on average 37 new patients each year (range: 19-59)) and/or a positive PCR result. Over the duration of the study period the number of new patients decreased from over 40 to fewer than 30 patients per year. Going by the family name, 95.5% of the 445 patients were probably imported cases of disease. In the Netherlands, echinococcosis is primarily seen as an imported disease with the majority of patients originating from areas around the Mediterranean Sea where it is endemic. Each year there are nearly 30 confirmed cases.

Thomassen Y.E.,RIVM | Van Der Welle J.E.,RIVM | Van Eikenhorst G.,RIVM | Van Der Pol L.A.,RIVM | Bakker W.A.M.,RIVM
Process Biochemistry | Year: 2012

Rapid and simple cell and virus cultivation can currently be carried out using disposable bioreactors. The CELL-tainer ® (CELLution Biotech BV) disposable bioreactor is a rocking-type bioreactor which not only has vertical movement but horizontal displacement as well. Due to this two-directional movement relatively high mass-transfer capacities can be reached when compared with conventional rocking motion-type bioreactors. Using the design of experiments (DoE) approach we have developed models for the mixing times in both the CELL-tainer ® and the BIOSTAT ® CultiBag RM (Sartorius Stedim Biotech) bioreactor (standard rocking motion-type). The conditions for cultivation of Vero cells in the CELL-tainer ® bioreactor were chosen based on comparable mixing times. Vero cells growing adherent to Cytodex 1 microcarriers were cultivated in the CELL-tainer ® and in the BIOSTAT ® CultiBag RM. Both bioreactors were controlled with regard to temperature, pH and % dissolved oxygen. Vero cell growth in both bioreactors was comparable with respect to the growth characteristics and main metabolite production and consumption rates. Additionally, polio virus production in both bioreactors was shown to be similar. © 2011 Elsevier Ltd. All rights reserved.

Tiktak A.,Netherlands Environmental Assessment Agency | Hendriks R.F.A.,Wageningen University | Boesten J.J.T.I.,Wageningen University | van der Linden A.M.A.,RIVM
Journal of Hydrology | Year: 2012

In the Netherlands, a spatially distributed version of the pesticide fate model PEARL is routinely used to assess the leaching potential of pesticides to groundwater. Recently, the model was modified to simulate the movement of pesticides to surface water. The peak concentration is considered to be the most important exposure endpoint for the ecotoxicological effect assessment for aquatic organisms. Macropore flow is an important driver for the peak concentration, so the leaching model PEARL was extended with a macropore module. Macropore parameters were derived from generally available soil data such as organic matter content and clay content using newly developed pedotransfer functions. These pedotransfer functions were constructed using a wide range of Dutch clayey soils. Results indicate a good correlation between these variables and soil structural parameters, which is due to the homogeneous mineralogical composition of Dutch clayey soils. Results of the spatially distributed modelling indicate that due to rapid transport through macropores, the concentration of pesticides in drainage water is generally higher in clayey soils than in light textured soils. In clayey soils, the boundary hydraulic conductivity and organic matter content were the most important drivers for the concentration in drainage water. Results further indicate that the concentration of pesticide in drainage water increases with increasing half-life and decreases with increasing sorption coefficient. However, the effect of these parameters is much less than obtained with the convection-dispersion equation because due to preferential flow most of the reactive part of the soil profile is bypassed. © 2012 Elsevier B.V.

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