Evaluating the conduct and reporting of the T-cell dependent antibody response in the Extended One-Generation Reproductive Toxicity study provided under the EU REACH regulation.

The European Union (EU) Chemicals Strategy for Sustainability regards chemicals that affect the immune system among the most harmful ones. The Extended One-Generation Reproductive Toxicity study (EOGRTS; Organisation for Economic Co-Operation and Development (OECD) Test Guideline (TG) 443), addresses, among others, potential effects of chemicals on development. In specific cases, the EOGRTS is performed with addition of a so-called cohort 3, that addresses potential effects on the developing immune system, by means of a central assay measuring the T-cell dependent antibody response (TDAR). This assay is based on an interplay of antigen presentation, T-cell help and antibody production by B-cells, and together comprises a functional immune response. In the context of the EOGRTS review project of the European Chemicals Agency (ECHA), we evaluated 15 available TDARs for compliance with conduct and reporting requirements. Collectively, the majority of the TDAR studies were considered to be adequately conducted. We however observed: (i) the protocols differed by the antigen used (sheep red blood cells (SRBC) or KLH), the route of administration (intravenous, intraperitoneal, or subcutaneous), prime or prime/boost immunizations, and whether IgG was measured. (ii) There was major variation in the effects of the positive control for immunosuppression, cyclophosphamide. (iii) Proficiency was not always shown. (iv) Statistical analysis was not always done or reported. (v) Results of effects on lymphocyte populations or other immunotoxicity observations obtained in cohort 1 (or 2) of the EOGRTS were not always discussed together with results of the TDAR. Taken together, next to an improved quality of reporting, this may suggest a need to better define the conduct of the TDAR in OECD TG 443 and OECD Guidance Document (GD) 151, at least for certain aspects.

Reducing attractiveness of e-liquids: proposal for a restrictive list of tobacco-related flavourings.

OBJECTIVE: Electronic cigarettes are addictive and harmful, and flavour is a key factor determining their abuse liability. Both adult smokers and young non-smokers like sweet and fruity flavours in particular. In order to discourage e-cigarette use among youth, the Dutch government announced in 2020 to only allow tobacco flavours in e-liquids. We propose a restrictive list of flavourings that will only enable the production of e-liquids with a tobacco flavour. METHODS: We used e-liquid ingredient data notified via the European Common Entry Gate system before the government's announcement. First, we classified all e-liquids into flavour categories, and continued with the set of flavourings present in tobacco e-liquids. Five selection criteria related to prevalence of use, chemical composition, flavour description and health effects were defined to compile a restrictive list of tobacco flavourings. RESULTS: E-liquids marketed as having tobacco flavour contained 503 different flavourings, some with tobacco flavour, but also other (such as sweet) flavours. We excluded (1) 330 flavourings used in <0.5% of e-liquids, (2) 77 used less frequently in tobacco than in all e-liquids, (3) 13 plant extracts, (4) 60 that are sweet or not associated with a tobacco flavour and (5) 7 flavourings with hazardous properties. This resulted in a final list of 16 flavourings. CONCLUSIONS: Implementing this restrictive list will likely discourage e-cigarette use among youth, but could also make e-cigarettes less attractive as smoking cessation aid.

The role of trust in the use of artificial intelligence for chemical risk assessment.

Risk assessment of chemicals is a time-consuming process and needs to be optimized to ensure all chemicals are timely evaluated and regulated. This transition could be stimulated by valuable applications of in silico Artificial Intelligence (AI)/Machine Learning (ML) models. However, implementation of AI/ML models in risk assessment is lagging behind. Most AI/ML models are considered 'black boxes' that lack mechanistical explainability, causing risk assessors to have insufficient trust in their predictions. Here, we explore 'trust' as an essential factor towards regulatory acceptance of AI/ML models. We provide an overview of the elements of trust, including technical and beyond-technical aspects, and highlight elements that are considered most important to build trust by risk assessors. The results provide recommendations for risk assessors and computational modelers for future development of AI/ML models, including: 1) Keep models simple and interpretable; 2) Offer transparency in the data and data curation; 3) Clearly define and communicate the scope/intended purpose; 4) Define adoption criteria; 5) Make models accessible and user-friendly; 6) Demonstrate the added value in practical settings; and 7) Engage in interdisciplinary settings. These recommendations should ideally be acknowledged in future developments to stimulate trust and acceptance of AI/ML models for regulatory purposes.

Apigenin as a Candidate Prenatal Treatment for Trisomy 21: Effects in Human Amniocytes and the Ts1Cje Mouse Model.

Human fetuses with trisomy 21 (T21) have atypical brain development that is apparent sonographically in the second trimester. We hypothesize that by analyzing and integrating dysregulated gene expression and pathways common to humans with Down syndrome (DS) and mouse models we can discover novel targets for prenatal therapy. Here, we tested the safety and efficacy of apigenin, identified with this approach, in both human amniocytes from fetuses with T21 and in the Ts1Cje mouse model. In vitro, T21 cells cultured with apigenin had significantly reduced oxidative stress and improved antioxidant defense response. In vivo, apigenin treatment mixed with chow was administered prenatally to the dams and fed to the pups over their lifetimes. There was no significant increase in birth defects or pup deaths resulting from prenatal apigenin treatment. Apigenin significantly improved several developmental milestones and spatial olfactory memory in Ts1Cje neonates. In addition, we noted sex-specific effects on exploratory behavior and long-term hippocampal memory in adult mice, and males showed significantly more improvement than females. We demonstrated that the therapeutic effects of apigenin are pleiotropic, resulting in decreased oxidative stress, activation of pro-proliferative and pro-neurogenic genes (KI67, Nestin, Sox2, and PAX6), reduction of the pro-inflammatory cytokines INFG, IL1A, and IL12P70 through the inhibition of NFκB signaling, increase of the anti-inflammatory cytokines IL10 and IL12P40, and increased expression of the angiogenic and neurotrophic factors VEGFA and IL7. These studies provide proof of principle that apigenin has multiple therapeutic targets in preclinical models of DS.

An Adverse Outcome Pathway Network for Chemically Induced Oxidative Stress Leading to (Non)genotoxic Carcinogenesis.

Nongenotoxic (NGTX) carcinogens induce cancer via other mechanisms than direct DNA damage. A recognized mode of action for NGTX carcinogens is induction of oxidative stress, a state in which the amount of oxidants in a cell exceeds its antioxidant capacity, leading to regenerative proliferation. Currently, carcinogenicity assessment of environmental chemicals primarily relies on genetic toxicity end points. Since NGTX carcinogens lack genotoxic potential, these chemicals may remain undetected in such evaluations. To enhance the predictivity of test strategies for carcinogenicity assessment, a shift toward mechanism-based approaches is required. Here, we present an adverse outcome pathway (AOP) network for chemically induced oxidative stress leading to (NGTX) carcinogenesis. To develop this AOP network, we first investigated the role of oxidative stress in the various cancer hallmarks. Next, possible mechanisms for chemical induction of oxidative stress and the biological effects of oxidative damage to macromolecules were considered. This resulted in an AOP network, of which associated uncertainties were explored. Ultimately, development of AOP networks relevant for carcinogenesis in humans will aid the transition to a mechanism-based, human relevant carcinogenicity assessment that involves a substantially lower number of laboratory animals.

Flavours and flavourings in waterpipe products: a comparison between tobacco, herbal molasses and steam stones.

ObjectivesFlavoured products are especially appealing to youth and contribute to the onset of waterpipe smoking and continued use of waterpipe tobacco. The goal of database and chemical analysis was to provide a clear overview of commonly used flavours and flavourings in tobacco and related waterpipe products, that is, herbal molasses and steam stones. METHODS: In 2019, 249 waterpipe tobacco products were registered in the European Common Entry Gate by manufacturers to be marketed in The Netherlands. Flavour categories were assigned to the registered products based on their brand names and product descriptions. Nicotine and eleven 1111 flavourings were identified and quantified in waterpipe tobacco (n=8), herbal molasses (n=7) and steam stones (n=4) by extraction and gas chromatography-mass spectrometry (GC-MS) analysis. RESULTS: Flavour categories could be assigned to 237 of 249 registered waterpipe tobacco products. Eight flavour main categories and 48 unique subcategories were identified and presented in a flavour wheel. All registered waterpipe tobacco products were flavoured, and the majority (78%) was fruit flavoured. Herbal molasses contained similar median flavouring levels, and steam stones contained lower median levels compared with waterpipe tobacco. Flavourings in waterpipe products were almost exclusively fruity and sweet, often in combination with menthol/mint flavourings. CONCLUSIONS: This study is the first to present a waterpipe tobacco flavour wheel, providing a quick overview of waterpipe tobacco flavours and thereby aiding communication among experts around the globe. GC-MS analysis revealed that the most prevalent flavourings are present in similar levels in herbal and tobacco waterpipe products. Banning flavourings in all waterpipe products would be a good strategy to reduce waterpipe smoking among youth.

Variations in cigarette brand characteristics: can consumers tell the difference?

OBJECTIVES: Sensory experience is an important determinant of smoking initiation, brand choice and harm perception, but little is known about how cigarette design shapes sensory experience. This study reports which variations in tobacco blend and design characteristics available on the market are likely to be perceived as different by consumers. METHODS: Truth Tobacco Industry Documents was reviewed for studies showing noticeable sensory differences resulting from variations in tobacco blend and design characteristics. These differences were compared with tobacco product data as available in the Dutch section of the European Common Entry Gate (EU-CEG) system on 30 April 2020. RESULTS: Industry documents identified discrimination thresholds for ventilation, pressure drop, tobacco weight, filter length, and tar and nicotine levels in smoke while evidence for other design characteristics was less conclusive. In the 103 different cigarette varieties in the EU-CEG database, five main types of cigarettes could be identified by principal component analysis, differing in (combinations of) design characteristics. The most significant differences between brand varieties were tar, nicotine and carbon monoxide emissions and associated parameters filter ventilation, filter length, cigarette length and tobacco weight. CONCLUSIONS: While some clusters of brand varieties provided a noticeably different product for consumers, in many cases design differences within these clusters did not exceed the expected discrimination threshold. This indicates that many products on the market are not discernibly different for consumers, and that proliferation of brand varieties has a non-sensory purpose, such as marketing. Policy makers should consider limiting available brand varieties and regulating design characteristics to reduce product appeal.

Comprehensive Dutch market data analysis shows that e-liquids with nicotine salts have both higher nicotine and flavour concentrations than those with free-base nicotine.

OBJECTIVES: Recent years have seen an increase in e-liquids containing nicotine salts. Nicotine salts are less harsh and bitter than free-base nicotine and therefore can facilitate inhalation. Because inhalation-facilitating ingredients are banned in the European Union, we assessed the occurrence and characteristics of nicotine salt-containing e-liquids notified for the Netherlands. METHODS: We analysed data for 39 030 products, submitted by manufacturers in the European Union Common Entry Gate system, as extracted on 30 June 2020. RESULTS: Nicotine salts were present in 13% of e-liquids, especially in pod-related e-liquids (73%) and e-liquids registered from 2018 onwards (over 25%). We found six nicotine salt ingredients (NSIs): nicotine lactate, salicylate, benzoate, levulinate, ditartrate and malate. Nicotine salts also occurred as nicotine-organic acid ingredient combination (NAIC), like nicotine and benzoic acid. Nicotine concentrations were twofold higher in e-liquids with NSI (median 14 mg/mL) and NAIC (11 mg/mL) than for free-base nicotine (6 mg/mL). E-liquids with NSI contained a fourfold higher number (median n=17) and concentration (median 31.0 mg/mL) of flavour ingredients than e-liquids with free-base nicotine (n=4, 7.4 mg/mL). In NAIC-containing e-liquids, these were threefold higher (n=12, 21.5 mg/mL). E-liquids with nicotine salts were less often tobacco flavoured but more often had fruity or sweet flavours. CONCLUSIONS: A substantial and increasing share of e-liquids in the Netherlands contains nicotine salts. Their characteristics can make such e-liquids more addictive and more attractive, especially to young and beginning users. Policymakers are advised to consider regulating products containing nicotine salts.

Pathways Related to NLRP3 Inflammasome Activation Induced by Gold Nanorods.

The widespread and increasing use of engineered nanomaterials (ENM) increases the risk of human exposure, generating concern that ENM may provoke adverse health effects. In this respect, their physicochemical characteristics are critical. The immune system may respond to ENM through inflammatory reactions. The NLRP3 inflammasome responds to a wide range of ENM, and its activation is associated with various inflammatory diseases. Recently, anisotropic ENM have become of increasing interest, but knowledge of their effects on the immune system is still limited. The objective of the study was to compare the effects of gold ENM of different shapes on NLRP3 inflammasome activation and related signalling pathways. Differentiated THP-1 cells (wildtype, ASC- or NLRP3-deficient), were exposed to PEGylated gold nanorods, nanostars, and nanospheres, and, thus, also different surface chemistries, to assess NLRP3 inflammasome activation. Next, the exposed cells were subjected to gene expression analysis. Nanorods, but not nanostars or nanospheres, showed NLRP3 inflammasome activation. ASC- or NLRP3-deficient cells did not show this effect. Gene Set Enrichment Analysis revealed that gold nanorod-induced NLRP3 inflammasome activation was accompanied by downregulated sterol/cholesterol biosynthesis, oxidative phosphorylation, and purinergic receptor signalling. At the level of individual genes, downregulation of Paraoxonase-2, a protein that controls oxidative stress, was most notable. In conclusion, the shape and surface chemistry of gold nanoparticles determine NLRP3 inflammasome activation. Future studies should include particle uptake and intracellular localization.

Both Nonsmoking Youth and Smoking Adults Like Sweet and Minty E-liquid Flavors More Than Tobacco Flavor.

Smokers may reduce their health risk by switching to electronic cigarette (e-cigarette) use. As e-cigarettes are not harmless, concerns exist about e-cigarette use by nonsmokers and youth. E-liquids are available in many different flavors that increase sensory appeal. Flavor preferences may differ between user groups, which could open doors for product regulation. We investigated which e-liquid flavors are attractive to specific user groups by comparing liking between adolescent nonsmokers (n = 41; mean age 16.9 ± 0.8), young adult nonsmokers (n = 42; mean age 22.7 ± 1.7), and adult smokers (n = 56; mean age 39.7 ± 11.1). Participants smelled tobacco- (n = 6) and nontobacco (n = 24)-flavored e-liquids and rated liking on a 9-point labeled hedonic scale, and familiarity, overall intensity, perceived sweetness, perceived bitterness, and irritation of the odors on a 100-unit Visual Analog Scale. Mean liking ranged from 2.3 (whiskey) to 6.7 (peppermint). Within all groups, the typically sweet and minty flavors (e.g., wine gum, watermelon, peppermint, menthol) were liked significantly more than the tobacco-flavored e-liquids. The set of tobacco-flavored e-liquids was significantly, but slightly, less disliked by adult smokers (3.9 ± 0.2) than adolescent (3.1 ± 0.3) and young adult (3.4 ± 0.3) nonsmokers (P < 0.001). No between-group differences were observed for sweet and minty flavors. Liking correlated significantly positively with odor sweetness (R = 0.49) and familiarity (R = 0.48) and negatively with odor bitterness (R = -0.58), irritation (R = -0.47), and overall intensity (R = -0.27). Thus, sweet- and minty-flavored e-liquids are liked equally by young nonsmokers and adult smokers, and more than tobacco flavors. Banning all flavors except tobacco will likely reduce e-cigarette appeal; potentially more for young nonsmokers than adult smokers.

Relevance of In Vitro Transcriptomics for In Vivo Mode of Action Assessment.

Recently, we reported an in vitro toxicogenomics comparison approach to categorize chemical substances according to similarities in their proposed toxicological modes of action. Use of such an approach for regulatory purposes requires, among others, insight into the extent of biological concordance between in vitro and in vivo findings. To that end, we applied the comparison approach to transcriptomics data from the Open TG-GATEs database for 137 substances with diverging modes of action and evaluated the outcomes obtained for rat primary hepatocytes and for rat liver. The results showed that a relatively small number of matches observed in vitro were also observed in vivo, whereas quite a large number of matches between substances were found to be relevant solely in vivo or in vitro. The latter could not be explained by physicochemical properties, leading to insufficient bioavailability or poor water solubility. Nevertheless, pathway analyses indicated that for relevant matches the mechanisms perturbed in vitro are consistent with those perturbed in vivo. These findings support the utility of the comparison approach as tool in mechanism-based risk assessment.

Nearly 20 000 e-liquids and 250 unique flavour descriptions: an overview of the Dutch market based on information from manufacturers.

OBJECTIVES: Flavours increase attractiveness of electronic cigarettes and stimulate use among vulnerable groups such as non-smoking adolescents. It is important for regulators to monitor the market to gain insight in, and regulate the range of e-liquid flavours that is available to consumers. E-liquid manufacturers are required to report key product information to authorities in the European Member States in which they plan to market their products. This information was used to provide an overview of e-liquid flavour descriptions marketed in the Netherlands in 2017. METHODS: Two researchers classified 19 266 e-liquids into the 16 main categories of the e-liquid flavour wheel, based on information from four variables in the European Common Entry Gate system. Flavour descriptions were further specified in subcategories. RESULTS: For 16 300 e-liquids (85%), sufficient information was available for classification. The categories containing the highest number of e-liquids were fruit (34%), tobacco (16%) and dessert (10%). For all e-liquids, excluding unflavoured ones, 245 subcategories were defined within the main categories. In addition to previously reported subcategories, various miscellaneous flavours such as sandwich, buttermilk and lavender were identified. CONCLUSIONS: In 2017, ~20 000 e-liquids were reported to be marketed in the Netherlands, in 245 unique flavour descriptions. The variety of marketed flavour descriptions reflects flavour preference of e-cigarette users as described in literature. Our systematic classification of e-liquids by flavour description provides a tool for organising the huge variety in market supply, serves as an example for other countries to generate similar overviews and can support regulators in developing flavour regulations.

Comprehensive overview of common e-liquid ingredients and how they can be used to predict an e-liquid's flavour category.

OBJECTIVES: Flavours increase e-cigarette attractiveness and use and thereby exposure to potentially toxic ingredients. An overview of e-liquid ingredients is needed to select target ingredients for chemical analytical and toxicological research and for regulatory approaches aimed at reducing e-cigarette attractiveness. Using information from e-cigarette manufacturers, we aim to identify the flavouring ingredients most frequently added to e-liquids on the Dutch market. Additionally, we used flavouring compositions to automatically classify e-liquids into flavour categories, thereby generating an overview that can facilitate market surveillance. METHODS: We used a dataset containing 16 839 e-liquids that were manually classified into 16 flavour categories in our previous study. For the overall set and each flavour category, we identified flavourings present in more than 10% of the products and their median quantities. Next, quantitative and qualitative ingredient information was used to predict e-liquid flavour categories using a random forest algorithm. RESULTS: We identified 219 unique ingredients that were added to more than 100 e-liquids, of which 213 were flavourings. The mean number of flavourings per e-liquid was 10±15. The most frequently used flavourings were vanillin (present in 35% of all liquids), ethyl maltol (32%) and ethyl butyrate (28%). In addition, we identified 29 category-specific flavourings. Moreover, e-liquids' flavour categories were predicted with an overall accuracy of 70%. CONCLUSIONS: Information from manufacturers can be used to identify frequently used and category-specific flavourings. Qualitative and quantitative ingredient information can be used to successfully predict an e-liquid's flavour category, serving as an example for regulators that have similar datasets available.

Aldehyde and Volatile Organic Compound Yields in Commercial Cigarette Mainstream Smoke Are Mutually Related and Depend on the Sugar and Humectant Content in Tobacco.

INTRODUCTION: The World Health Organization (WHO) Framework Convention on Tobacco control recognizes the need for tobacco product regulation. In line with that, the WHO Study Group on Tobacco Product Regulation (TobReg) proposed to regulate nine toxicants in mainstream cigarette smoke, including aldehydes, volatile organic compounds (VOCs), and carbon monoxide (CO). We analyzed their relations in 50 commercially available cigarette brands, using two different smoking regimes, and their dependence on sugar and humectant concentrations in tobacco filler. METHODS: We measured sugar and humectant in tobacco filler and aldehydes, VOCs, and tar, nicotine, and CO (TNCO) in mainstream smoke. The general statistics, correlations between emission yields, and correlations between contents and emissions yields were determined for these data. RESULTS: For aldehydes, several significant correlations were found with precursor ingredients in unburnt tobacco when smoked with the Intense regime, most prominently for formaldehyde with sucrose, glucose, total sugars, and glycerol. For VOCs, 2,5-dimethylfuran significantly correlates with several sugars under both International Standards Organization (ISO) and Intense smoking conditions. A correlation network visualization shows connectivity between a sugar cluster, an ISO cluster, and an Intense cluster, with Intense formaldehyde as a central highest connected hub. CONCLUSIONS: Our multivariate analysis showed several strong connections between the compounds determined. The toxicants proposed by WHO, in particular, formaldehyde, can be used to monitor yields of other toxicants under Intense conditions. Emissions of formaldehyde, acetaldehyde, acrolein, and 2,5-dimethylfuran may decrease when sugar and humectants contents are lowered in tobacco filler. IMPLICATIONS: Our findings suggest that the aldehydes and VOCs proposed by TobReg are a representative selection for smoke component market monitoring purposes. In particular, formaldehyde yields may be useful to monitor emissions of other toxicants under Intense conditions. Since the most and strongest correlations were observed with the Intense regime, policymakers are advised to prescribe this regime for regulatory purposes. Policymakers should also consider sugars and humectants contents as targets for future tobacco product regulations, with the additional advantage that consumer acceptance of cigarette smoke is proportional to their concentrations in the tobacco blend.

Sensory Evaluation of E-Liquid Flavors by Smelling and Vaping Yields Similar Results.

INTRODUCTION: Sensory research on e-liquid flavors can be performed by means of smelling and vaping. However, data comparing smelling versus vaping e-liquid flavors are lacking. This study aims to investigate if smelling could be an alternative to vaping experiments by determining the correlation for hedonic flavor assessment between orthonasal smelling and vaping of e-liquids, for smokers and nonsmokers. METHODS: Twenty-four young adult smokers (mean age 24.8 ± 9.3) and 24 nonsmokers (mean age 24.9 ± 7.7) smelled and vaped 25 e-liquids in various flavors. Participants rated liking, intensity, familiarity, and irritation on a 100-mm Visual Analog Scale. Pearson correlations within and between smelling and vaping were calculated. Differences between user groups were calculated using t tests. RESULTS: Correlation coefficients between smelling and vaping based on mean group ratings were 0.84 for liking, 0.82 for intensity, 0.84 for familiarity, and 0.73 for irritation. Means of the within-subjects correlation coefficients were, respectively, 0.51, 0.37, 0.47, and 0.25. Correlations between smelling and vaping varied across individuals (ranging from -0.27 to 0.87) and flavors (-0.33 to 0.81). Correlations and mean liking ratings did not differ between smokers and nonsmokers. CONCLUSIONS: The strong group-level correlations between orthonasal smelling and vaping e-liquid flavors justify the use of smelling instead of vaping in future research. For example, smelling could be used to investigate differences in e-liquid flavor liking between (potential) user groups such as nicotine-naïve adolescents. The more modest within-subject correlations and variation across individuals and flavors merit caution in using smelling instead of vaping in other types of experiments. IMPLICATIONS: This study supports the use of orthonasal smelling (instead of vaping) e-liquids to measure hedonic flavor perception in some studies where vaping would be inappropriate or not feasible. Examples of research situations where smelling e-liquids may be sufficient are (1) investigating nicotine-naïve individuals (ie, nonusers), (2) investigating individuals under legal age for e-cigarette use (ie, youth and adolescents), (3) investigating brain responses to exposure of e-liquid flavors using functional magnetic resonance imaging or electroencephalogram, and (4) comparing hedonic flavor assessment between adolescent nonusers and current smokers to provide support for future regulations on e-liquid flavors.

A next-generation sequencing based method for determining genetic stability in Clostridium tetani vaccine strains.

Production of tetanus and other clostridial vaccines highly depends on the stable and reproducible production of high toxin levels. This creates a need to ensure the genetic stability of seed strains. We developed a two-stage method for improved assessment of the genetic stability of Clostridium seed strains. This method is based on next-generation sequencing (NGS) of strain DNA and mapping the sequence reads to a reference sequence. The output allows analysis of global genome consistency followed, if necessary, by detailed expert judgement of potential deviations at the gene level. The limit of detection of our method is an order of magnitude better than that of the currently established pulsed-field gel electrophoresis (PFGE). Improved genetic characterization of bacterial seed lots will have a positive impact on the characterization of the production process. This will be a first step towards applying the consistency approach to vaccine batch release of established vaccines. This can contribute to the reduction and ultimately replacement of routinely used animal tests in vaccine production. This work was carried out as part of the Innovative Medicines Initiative 2 (IMI2) project VAC2VAC (Vaccine batch to vaccine batch comparison by consistency testing).

Cigarette Filter Ventilation and Smoking Protocol Influence Aldehyde Smoke Yields.

The WHO study group on tobacco product regulation (TobReg) advised regulating and lowering toxicant levels in cigarette smoke. Aldehydes are one of the chemical classes on the TobReg smoke toxicants priority list. To provide insight in factors determining aldehyde yields, the levels of 12 aldehydes in mainstream cigarette smoke of 11 Dutch brands were quantified. Variations in smoking behavior and cigarette design affecting human exposure to aldehydes were studied by using four different machine testing protocols. Machine smoking was based on the International Standardization Organization (ISO) and Health Canada Intense (HCI) regime, both with and without taping the filter vents. The 11 cigarette brands differed in (i) design and blend characteristics; (ii) tar, nicotine, and carbon monoxide (TNCO) levels; (iii) popularity; and (iv) manufacturer. Cigarette smoke was trapped on a Cambridge filter pad and carboxen cartridge. After being dissolved in methanol/CS2 and derivatization with DNPH, the aldehyde yields were determined using HPLC-DAD. Using an intense smoking regime (increased puff volume, shorter puff interval) significantly increased aldehyde yields, following the pattern: ISO < ISO-taped < HCI-untaped < HCI. For all of the regimes, acetaldehyde and acrolein yields were strongly correlated ( r = 0.804). The difference in TNCO and aldehyde levels between regular and highly ventilated low-TNCO cigarettes (as measured using ISO) diminished when smoking intensely; this effect is stronger when combined with taping filter vents. The highly ventilated low-TNCO brands showed six times more aldehyde production per mg nicotine for the intense smoking regimes. In conclusion, acetaldehyde and acrolein can be used as representatives for the class of volatile aldehydes for the different brands and smoking regimes. The aldehyde-to-nicotine ratio increased when highly ventilated cigarettes were smoked intensely, similar to real smokers. Thus, a smoker of highly ventilated low-TNCO cigarettes has an increased potential for higher aldehyde exposures compared to a smoker of regular cigarettes.

Identification of flavour additives in tobacco products to develop a flavour library.

OBJECTIVES: This study combines chemical analysis and flavour descriptions of flavour additives used in tobacco products, and provides a starting point to build an extensive library of flavour components, useful for product surveillance. METHODS: Headspace gas chromatography-mass spectrometry (GC-MS) was used to compare 22 commercially available tobacco products (cigarettes and roll-your-own) expected to have a characterising flavour and 6 commercially available products not expected to have a characterising flavour with 5 reference products (natural tobacco leaves and research cigarettes containing no flavour additives). The flavour components naturally present in the reference products were excluded from components present in commercially available products containing flavour additives. A description of the remaining flavour additives was used for categorisation. RESULTS: GC-MS measurements of the 33 tobacco products resulted in an overview of 186 chemical compounds. Of these, 144 were solely present in commercially available products. These 144 flavour additives were described using 62 different flavour descriptors extracted from flavour databases, which were categorised into eight groups largely based on the definition of characterising flavours from the European Tobacco Product Directive: fruit, spice, herb, alcohol, menthol, sweet, floral and miscellaneous. CONCLUSIONS: We developed a method to identify and describe flavour additives in tobacco products. Flavour additives consist of single flavour compounds or mixtures of multiple flavour compounds, and different combinations of flavour compounds can cause a certain flavour. A flavour library helps to detect flavour additives that are characteristic for a certain flavour, and thus can be useful for regulation of flavours in tobacco and related products.

Recommendations of the VAC2VAC workshop on the design of multi-centre validation studies.

Within the Innovative Medicines Initiative 2 (IMI 2) project VAC2VAC (Vaccine batch to vaccine batch comparison by consistency testing), a workshop has been organised to discuss ways of improving the design of multi-centre validation studies and use the data generated for product-specific validation purposes. Moreover, aspects of validation within the consistency approach context were addressed. This report summarises the discussions and outlines the conclusions and recommendations agreed on by the workshop participants.

Absence of Prenatal Forebrain Defects in the Dp(16)1Yey/+ Mouse Model of Down Syndrome.

Studies in humans with Down syndrome (DS) show that alterations in fetal brain development are followed by postnatal deficits in neuronal numbers, synaptic plasticity, and cognitive and motor function. This same progression is replicated in several mouse models of DS. Dp(16)1Yey/+ (hereafter called Dp16) is a recently developed mouse model of DS in which the entire region of mouse chromosome 16 that is homologous to human chromosome 21 has been triplicated. As such, Dp16 mice may more closely reproduce neurodevelopmental changes occurring in humans with DS. Here, we present the first comprehensive cellular and behavioral study of the Dp16 forebrain from embryonic to adult stages. Unexpectedly, our results demonstrate that Dp16 mice do not have prenatal brain defects previously reported in human fetal neocortex and in the developing forebrains of other mouse models, including microcephaly, reduced neurogenesis, and abnormal cell proliferation. Nevertheless, we found impairments in postnatal developmental milestones, fewer inhibitory forebrain neurons, and deficits in motor and cognitive performance in Dp16 mice. Therefore, although this new model does not express prenatal morphological phenotypes associated with DS, abnormalities in the postnatal period appear sufficient to produce significant cognitive deficits in Dp16.