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CORD-19:1fe201bcf1ed66856f693846cb0d07ce48051ec1 JSONTXT 9 Projects

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Id Subject Object Predicate Lexical cue
T1 0-166 Sentence denotes Toxicology Gene expression profiling to identify potentially relevant disease outcomes and support human health risk assessment for carbon black nanoparticle exposure
T2 168-176 Sentence denotes Abstract
T3 177-277 Sentence denotes New approaches are urgently needed to evaluate potential hazards posed by exposure to nanomaterials.
T4 278-463 Sentence denotes Gene expression profiling provides information on potential modes of action and human relevance, and tools have recently become available for pathway-based quantitative risk assessment.
T5 464-565 Sentence denotes The objective of this study was to use toxicogenomics in the context of human health risk assessment.
T6 566-755 Sentence denotes We explore the utility of toxicogenomics in risk assessment, using published gene expression data from C57BL/6 mice exposed to 18, 54 and 162 g Printex 90 carbon black nanoparticles (CBNP).
T7 756-965 Sentence denotes Analysis of CBNP-perturbed pathways, networks and transcription factors revealed concomitant changes in predicted phenotypes (e.g., pulmonary inflammation and genotoxicity), that correlated with dose and time.
T8 966-1091 Sentence denotes Benchmark doses (BMDs) for apical endpoints were comparable to minimum BMDs for relevant pathway-specific expression changes.
T9 1092-1392 Sentence denotes Comparison to inflammatory lung disease models (i.e., allergic airway inflammation, bacterial infection and tissue injury and fibrosis) and human disease profiles revealed that induced gene expression changes in Printex 90 exposed mice were similar to those typical for pulmonary injury and fibrosis.
T10 1393-1494 Sentence denotes Very similar fibrotic pathways were perturbed in CBNP-exposed mice and human fibrosis disease models.
T11 1495-1728 Sentence denotes Our synthesis demonstrates how toxicogenomic profiles may be used in human health risk assessment of nanoparticles and constitutes an important step forward in the ultimate recognition of toxicogenomic endpoints in human health risk.
T12 1729-1984 Sentence denotes As our knowledge of molecular pathways, dose-response characteristics and relevance to human disease continues to grow, we anticipate that toxicogenomics will become increasingly useful in assessing chemical toxicities and in human health risk assessment.
T13 1985-1990 Sentence denotes Crown
T14 1992-2371 Sentence denotes Chronic inhalation of fine and ultrafine particulate matter has been associated with adverse pulmonary effects including fibrosis and cancer, as well as exacerbation of existing conditions such as asthma, bronchitis and chronic obstructive pulmonary disorder (Bonner, 2007; Knaapen et al., 2004) , in addition to cardiovascular disease (Dockery et al., 1993; Pope et al., 2004) .
T15 2372-2672 Sentence denotes Human exposure to manufactured nanomaterials (NMs), which have at least one size dimension that is less than 100 nm, may constitute an increased risk of adverse effects especially following inhalation exposure, and their potential to induce toxic effects is poorly understood (Handy and Shaw, 2007) .
T16 2673-2780 Sentence denotes Moreover, the human health risks associated with inhalation exposure have not been adequately investigated.
T17 2781-2992 Sentence denotes Methods that can be effective in screening for NM toxicities are paramount, due to the countless variations in physical and chemical properties of NMs in terms of size, shape, agglomeration and surface coatings.
T18 2993-3334 Sentence denotes Traditional assays used in human health risk assessment (HHRA) generally involve chronic and subchronic rodent exposures with concomitant analyses of tumour induction (e.g., two-year rodent cancer bioassay), in addition to various non-cancer endpoints, the most sensitive of which is used for regulatory decision-making (Meek et al., 1994) .
T19 3335-3440 Sentence denotes These approaches form the foundation of the chemical regulatory system and have been invaluable for HHRA.
T20 3441-3638 Sentence denotes However, some of these assays, such as those based on chronic animal exposures at the maximum tolerated dose, are time and resource intensive, thus limiting broad application (Suter et al., 2004) .
T21 3639-3942 Sentence denotes Recent discussions have identified gene expression profiling as a potentially rapid and cost-effective approach for identifying and assessing prospective hazard, characterizing chemical (or particle) mode of action, and assessing human relevance in support of HHRA (National Academy of Sciences, 2007) .
T22 3943-4295 Sentence denotes In order for gene expression data to become accepted for routine use in HHRA, it is necessary to demonstrate that mRNA/protein expression profiles can effectively predict the modes of action and biological outcomes of exposure at relevant doses, and to confirm that these data can be used to strengthen the foundation for HHRA and regulatory decisions.
T23 4296-4588 Sentence denotes In this regard, it has been hypothesized that gene expression profiling will be extremely useful in identifying effects at low doses, and moreover, useful for distinguishing between doses that elicit an adaptive response vs. those that yield adverse effects (Boverhof and Zacharewski, 2006) .
T24 4589-4812 Sentence denotes To date, the application of gene expression profiling in regulatory toxicology has largely focused on qualitative identification of chemical modes of action and transcription biomarkers that can predict specific toxicities.
T25 4813-4975 Sentence denotes However, the utility of gene expression profiling in quantitative determination of threshold values (e.g., benchmark doses) has not yet been rigorously explored .
T26 4976-5295 Sentence denotes In the present study we investigate the utility of gene expression profiles derived from mice exposed to Printex 90 carbon black nanoparticles (CBNPs) by intratracheal installation to identify potential hazards, modes of action, and doses above which adverse effects may be expected for specific toxicological outcomes.
T27 5296-5436 Sentence denotes In addition, we quantitatively compare benchmark doses for pathways to those of apical endpoints derived from the same experimental animals.
T28 5437-5571 Sentence denotes We employ Printex 90 as a model NM due to the rich database of traditional toxicity information on which our findings can be anchored.
T29 5572-6034 Sentence denotes Briefly, Printex 90 consists almost entirely of carbon, with very low levels of impurities in terms of polycyclic aromatic hydrocarbons and endotoxins (Bourdon et al., 2012b; Jacobsen et al., 2008; Saber et al., 2011) They generate reactive oxygen species (Jacobsen et al., 2008) , induce DNA strand breaks in vitro and in vivo (Jacobsen et al., 2009; Saber et al., 2005) and mutations in vitro (Jacobsen et al., 2007) that are associated with oxidative stress .
T30 6035-6321 Sentence denotes The data in this study are from previously published experiments investigating Printex 90 CBNP exposure in C57BL/6 mice at various doses (i.e., vehicle, 18, 54 and 162 g) collected at several time-points (1, 3 and 28 days) following a single acute instillation (Bourdon et al., 2012a) .
T31 6322-6597 Sentence denotes We previously characterized widespread changes in gene expression involving acute phase response and inflammation, supported by concomitant influxes of pulmonary bronchoalveolar lavage cells (BAL) and increases in tissue-specific DNA strand breaks (Bourdon et al., 2012a,b) .
T32 6598-6929 Sentence denotes In addition to the examination of BMDs and BMDLs, we compare CBNP-modified gene expression profiles to various models of lung disease in mice and humans reported in the literature, in order to explore the utility of our data in predicting the potential risk of adverse health outcomes and the human relevance of expression changes.
T33 6930-7129 Sentence denotes The work demonstrates one approach by which gene expression profiling may be integrated into HHRA to support or predict apical toxicological endpoints, dose-response, and relevance to human diseases.
T34 7130-7267 Sentence denotes Details of the mouse exposures, particle characterization and pulmonary phenotype were previously published in Bourdon et al. (2012a,b) .
T35 7268-7438 Sentence denotes Briefly, female C57BL/6 mice were exposed to a single installation of vehicle or Printex 90 (18, 54 or 162 g) and euthanized 1, 3 and 28 days post-exposure (n = 6/group).
T36 7439-7684 Sentence denotes The intratracheal instillation route of exposure allows for deposition of known doses directly in the lungs of the mice, and controls for potential dermal-and ingestion-related CBNP exposure that can occur during whole body inhalation exposures.
T37 7685-8134 Sentence denotes The doses were selected to represent 1, 3 and 9 working days of exposure at the occupational inhalation exposure limit of 3.5 mg/m 3 of CB (as established by the US Occupational Safety and Health Administration (OSHA) and the US National Institute for Occupational Safety and Health (NIOSH))) for a mouse (assuming 1.8 L/h inhalation rate and 33.8% particle deposition in mouse, for an 8 h working day) (Dybing et al., 1997; Jacobsen et al., 2009) .
T38 8135-8216 Sentence denotes Very limited filtration of CBNPs from the nose is expected during human exposure.
T39 8217-8292 Sentence denotes Printex 90 CBNPs were characterized and displayed the following properties:
T40 8293-8567 Sentence denotes 14 nm primary particle size, 295-338 m 2 /g Brunauer Emmett and Teller (BET) surface area, 74.2 g/g PAHs, 142 EU/g endotoxin, polydispersity index of 1, −10.7 mV zeta potential, 2.6 m peak hydrodynamic number and 3.1 m peak volume-size-distribution (Bourdon et al., 2012b) .
T41 8568-8728 Sentence denotes Analysis of pulmonary inflammatory cellular influx in bronchoalveolar lavage (BAL) revealed neutrophilic inflammation that was sustained to day 28 at all doses.
T42 8729-8942 Sentence denotes Tissue-specific genotoxicity, as observed by DNA strand breaks, persisted up to day 28 at the two highest doses and FPG-sensitive sites at all doses on day 1 and the highest dose on day 3 (Bourdon et al., 2012b) .
T43 8943-9144 Sentence denotes Whole mouse genome DNA microarray revealed 487 and 81 differentially expressed genes (FDR adjusted pvalue ≤ 0.1 and fold changes ≥ 1.5) overall in lung and liver, respectively (Bourdon et al., 2012a) .
T44 9145-9311 Sentence denotes The complete microarray dataset is available through the Gene Expression Omnibus at NCBI (http://www.ncbi.nlm.nih.gov/geo/, Superseries GSE35284, SubSeries GSE35193).
T45 9312-9446 Sentence denotes This dataset was previously used to examine molecular interactions between lung and liver upon CBNP exposure (Bourdon et al., 2012a) .
T46 9447-9658 Sentence denotes To determine the most affected processes of CBNP exposure, pathway analysis of gene expression data was conducted using a rank based test in R (R Development Core Team, 2011) as described in Alvo et al. (2010) .
T47 9659-9817 Sentence denotes The relative expression for the genes in a pathway was first aligned by subtracting the median expression value for the combined treatment and control groups.
T48 9818-9940 Sentence denotes These values were then ranked within each subject and the vector of average ranks was calculated for each treatment group.
T49 9941-10069 Sentence denotes The distance between the two treatments was calculated and a permutation analysis was used to obtain a p-value for each pathway.
T50 10070-10121 Sentence denotes Pathways with p < 0.05 were considered significant.
T51 10122-10126 Sentence denotes 2.3.
T52 10127-10483 Sentence denotes Benchmark dose (BMD)/lower confidence limit benchmark dose (BMDL) calculation for apical endpoints and RT-PCR data BMD10 (BMD representing an excess risk of 10% in exposed animals vs. controls) and BMDLs (95% confidence limit) were calculated for apical endpoint data (inflammation and genotoxicity) and for RT-PCR using EPA BMDS 2.2 (Davis et al., 2011) .
T53 10484-10594 Sentence denotes Only data that were statistically above control levels (p < 0.05) for at least two of the doses were included.
T54 10595-10792 Sentence denotes Prior to running the analysis, the data were screened for homogeneity of variance, and then fit against five continuous dose-response models (i.e., hill, polynomial, linear, power and exponential).
T55 10793-10953 Sentence denotes Goodness of fit >0.05 and scaled residuals within ±2.0 was applied as a cut off for selection of the appropriate model, and curves were also inspected visually.
T56 10954-11067 Sentence denotes When more than one model was suitable, the one with the lowest Akaike's information criterion (AIC) was selected.
T57 11068-11156 Sentence denotes In order to determine BMDs and BMDLs for gene expression data, BMDExpress was employed .
T58 11157-11246 Sentence denotes Briefly, microarray probes with more than one representation on each array were averaged.
T59 11247-11390 Sentence denotes Analyses were performed on genes that were identified as statistically significant by one-way ANOVA (p < 0.05) using the four following models:
T60 11391-11435 Sentence denotes Hill, Power, Linear 1 • and Polynomial 2 • .
T61 11436-11482 Sentence denotes The Power model had a power restriction of ≥1.
T62 11483-11603 Sentence denotes Selection on Linear and Polynomial 2 • was based on choosing a model which describes the data with the least complexity.
T63 11604-11773 Sentence denotes A nested Chi-square test, with cut-off of 0.05, first selects among linear and polynomial models, followed by comparing AIC, which measures the relative goodness of fit.
T64 11774-11909 Sentence denotes A Hill model was excluded if the "k" parameter of the model was less than 1/3 of the lowest positive dose (18 g) (Black et al., 2012) .
T65 11910-12066 Sentence denotes Other settings included maximum iterations of 250, confidence level of 0.95, benchmark response (BMR) of 1.349 (number of standard deviation defining BMD) .
T66 12067-12249 Sentence denotes For functional classifications and analyses, the resulting BMD datasets were mapped to KEGG pathways with promiscuous probes removed (probes that mapped to multiple annotated genes).
T67 12250-12385 Sentence denotes BMDs that exceeded the highest exposure dose (162 g) and that exceeded a goodness-of-fit p-value of 0.1 were removed from the analysis.
T68 12386-12686 Sentence denotes To determine the correlation between gene expression profiles of mice exposed to CBNPs with those of mouse pulmonary disease models, a prediction analysis for microarrays (PAM) (Tibshirani et al., 2002) was conducted in R (R Development Core Team, 2011) using the PAMR library (Hastie et al., 2011) .
T69 12687-12884 Sentence denotes Data for this analysis encompassed 13 mouse lung disease models, and were obtained from the National Centre for Biotechnology Information Gene Expression Omnibus (accession #GSE4231 and #GSE11037).
T70 12885-13063 Sentence denotes The samples were labelled as belonging to one of three models of lung inflammation: bacterial infection, lung injury and fibrosis, or Th2 response (allergic airway inflammation).
T71 13064-13172 Sentence denotes Probes with common GENBANK accessions were collapsed to a single measurement for each sample using the mean.
T72 13173-13267 Sentence denotes Using the common accession numbers, a prediction model using shrunken centroids was estimated.
T73 13268-13380 Sentence denotes Cross-validation of the nearest shrunken centroid classifier was conducted to identify an appropriate threshold.
T74 13381-13422 Sentence denotes PAMR implements 10-fold cross-validation.
T75 13423-13555 Sentence denotes This involves dividing the samples into ten approximately equal-size parts ensuring that the classes are distributed proportionally.
T76 13556-13687 Sentence denotes Ten-fold cross-validation works by fitting a model on 90% of the samples and then predicting the class labels of the remaining 10%.
T77 13688-13854 Sentence denotes This procedure is repeated ten times, with each part playing the role of the test samples and the errors on all ten parts added together to compute the overall error.
T78 13855-13936 Sentence denotes A threshold of 2 was selected, yielding a classifier with 753 GENBANK accessions.
T79 13937-14043 Sentence denotes The means of the nine CBNP treatment conditions were then classified using the estimated prediction model.
T80 14044-14212 Sentence denotes Functional analysis was conducted to establish molecular perturbations that were in common or discrepant between CBNP exposed mice and inflammatory lung disease models.
T81 14213-14436 Sentence denotes The analysis was conducted on genes that were common between CBNP and each lung disease model, then again for genes that were unique to CBNP, using a cut-off of FDR-adjusted p < 0.1 and a fold-change > 1.5 for all datasets.
T82 14437-14548 Sentence denotes The less stringent cut-off was employed for disease models because of the low power in several of the datasets.
T83 14549-14713 Sentence denotes DAVID Bioinformatics Resources 6.7 was used to identify enriched biological functions from terms with similar genes and biological meaning (Huang et al., 2009a,b) .
T84 14714-14863 Sentence denotes DAVID Biological functions with enrichment scores > 1.3 were considered significant, in accordance with DAVID recommendations (Huang et al., 2009a) .
T85 14864-15023 Sentence denotes Clusters with enrichment scores > 1.3 in our analysis contained at least one gene ontology term or pathway for which the Benjamini-corrected p-value was ≤0.05.
T86 15024-15165 Sentence denotes In order to predict potential disease outcomes of relevance to humans, gene expression profiles were mined against genomic data repositories.
T87 15166-15356 Sentence denotes Disease prediction analysis was done in NextBio (http://nextbio.com) using the high dose exposure profiles as differentially expressed genes were identified at all time-points for this dose.
T88 15357-15504 Sentence denotes Data from CBNP exposed mice were compared to curated datasets to identify disease studies with similar gene profiles, gene ranking and consistency.
T89 15505-15647 Sentence denotes Pairwise gene signature correlations and rank-based enrichment statistics were employed in the calculation of NextBio scores for each disease.
T90 15648-15823 Sentence denotes The disease that ranked highest in comparison with CBNP exposure was given a score of 100, and the rest of the results were normalized accordingly (Kupershmidt et al., 2010) .
T91 15824-15951 Sentence denotes Meta-analysis was performed using select disease models for mice, as well as for human studies representative of disease state.
T92 15952-16155 Sentence denotes The analysis identified, ranked and scored all genes and biogroups that were common between the studies according to the scoring method described above for disease prediction (Kupershmidt et al., 2010) .
T93 16156-16203 Sentence denotes Biogroups were filtered for canonical pathways.
T94 16204-16346 Sentence denotes The rank-based pathway analysis revealed a total of 151, 150 and 106 differentially expressed KEGG pathways on days 1, 3 and 28, respectively.
T95 16347-16553 Sentence denotes The most affected pathways according to statistical significance were primarily related to inflammation on day 1, to steroid biosynthesis and DNA repair on day 3 and to apoptosis and inflammation on day 28.
T96 16554-16748 Sentence denotes Significant pathways (p < 0.05) pertaining to genotoxicity (DNA damage and repair) and inflammatory and immune responses are summarized in Table 1 , along with previously established phenotypes.
T97 16749-16813 Sentence denotes All significant pathways are presented in Supplemental Table 1 .
T98 16814-16970 Sentence denotes Analysis of the number of common pathways between doses for each time-point revealed that most pathways occurring at lower doses also occur at higher doses.
T99 16971-17045 Sentence denotes However, the number of significant pathways increased with dose (Fig. 1) .
T100 17046-17249 Sentence denotes EPA BMDS 2.2 BMDs and BMDLs were generated for apical endpoints and RT-PCR data (BMD values for each endpoint and gene presented in Supplementary Table 2 ; curves are presented in Supplemental Fig. S1 ).
T101 17250-17413 Sentence denotes Although many of the apical endpoints and RT-PCR data were not suitable for modelling, BMD and BMDL values generally increased over post-exposure time as expected.
T102 17414-17555 Sentence denotes The mean BMDs for inflammatory apical endpoints were 0.9, 1.2 and 9.6 g, and BMDLs were 0.6, 0.9 and 6.5 g on days 1, 3 and 28, respectively.
T103 17556-17663 Sentence denotes BMD values for RT-PCR data of genes involved in inflammation tended to be higher than for apical endpoints.
T104 17664-17800 Sentence denotes Mean BMDs of inflammatory genes were 14.5, 16.7 and 29.0 g, and mean BMDLs were 10.4, 9.1 and 20.1 g, on days 1, 3 and 28, respectively.
T105 17801-17893 Sentence denotes BMDs and BMDLs were also generated for microarray gene expression profiles using BMDExpress.
T106 17894-18090 Sentence denotes Minimum BMDs for KEGG pathways relevant to inflammation, KEGG pathways relevant to genotoxicity, for the most sensitive KEGG pathways as well as for apical endpoint data are presented in Table 2 .
T107 18091-18280 Sentence denotes Minimum BMDs were calculated according to the median of all significant genes for each pathway and the 5th percentile of significant genes of all pathways, in order to increase sensitivity.
T108 18281-18382 Sentence denotes Even the 5th percentile BMDs tended to be higher than BMDs generated for apical endpoints (Table 2) .
T109 18383-18535 Sentence denotes However, minimum BMDs, representing the most sensitive gene for each relevant pathway, were much more comparable to BMDs of apical endpoints (Table 2) .
T110 18536-18858 Sentence denotes PAM was used to compare the Printex 90 gene expression dataset to 13 pulmonary gene expression profiles that represent a range of murine pulmonary disease models (e.g., transgene overexpression, treatments with infectious agents, toxic chemicals and allergens) as described in Lewis et al. (2008) , Thomson et al. (2012) .
T111 18859-19037 Sentence denotes The models were classified according to the three following subgroups: (1) bacterial infection, (2) lung injury and fibrosis, and (3) Th2 response (allergic airway inflammation).
T112 19038-19094 Sentence denotes Clustering of the models using PAM is shown in Fig. 2A .
T113 19095-19261 Sentence denotes Two CBNP exposure conditions (day 28 low and medium doses) did not cluster with other CBNP exposure condition or other disease models, likely due to lack of response.
T114 19262-19351 Sentence denotes Models of bacterial infection did not cluster with other disease models or CBNP exposure.
T115 19352-19461 Sentence denotes PAM analysis revealed an association between CBNP exposure, Th2 responses and lung injury/fibrotic responses.
T116 19462-19826 Sentence denotes Although Th2 response and lung injury/fibrotic responses were more closely associated with one another than with CBNP exposure, PAM analysis revealed that CBNP exposure was more closely related to lung injury/fibrotic responses than to Th2 responses, which is also supported by probability statistics comparing CBNP exposure with each disease sub-group (Fig. 2B) .
T117 19827-20078 Sentence denotes In order to examine commonalities and discrepancies between disease models and CBNP exposure in more detail, functional analysis was conducted on (1) genes that were in common between CBNP and each disease model and (2) genes that were unique to CBNP.
T118 20079-20172 Sentence denotes The number of significant genes used for each analysis is presented in Supplemental Table 3 .
T119 20173-20231 Sentence denotes The DAVID biological functions are summarized in Table 3 .
T120 20232-20359 Sentence denotes This analysis demonstrates that inflammation was common between most models at all time-points (excluding Aspergillus extract).
T121 20360-20585 Sentence denotes On day 1, commonalities for CBNP exposure were observed with bacterial infection models (i.e., due to the acute phase response) and with injury and fibrosis models (i.e., due to changes in tissue morphogenesis related genes).
T122 20586-20664 Sentence denotes Day 3 revealed inflammation and cell cycle disturbances in most of the models.
T123 20665-20824 Sentence denotes However, CBNP responses were more similar to bleomycin-induced lung injury as shown by the high degree of overlapping biological functions on day 3 (Table 3) .
T124 20825-20942 Sentence denotes CBNPs triggered an adaptive immune response on day 28 that was also only apparent in lung injury and fibrosis models.
T125 20943-21109 Sentence denotes Gene expression profiles from the high dose CBNP-exposed mice vs. control were analysed in NextBio to identify closely related respiratory disease profiles in humans.
T126 21110-21318 Sentence denotes On all post-exposure days, severe acute respiratory syndrome (SARS), congenital cystic Table 1 Summary of significant KEGG pathways (p ≤ 0.05) relating to phenotypes established in Bourdon et al. (2012a,b 1 .
T127 21319-21618 Sentence denotes Venn diagrams illustrating overlap of significant pathways (p < 0.05) according to dose, for each post-exposure day (1, 3 and 28 days) in C57BL/6 mice exposed to CBNPs. adenomatoid malformation, and injury of lung, were identified as the top three respiratory diseases associated with CBNP exposure.
T128 21619-21803 Sentence denotes Interestingly, fibrosis was identified as a predicted disease outcome of CBNP exposure that increased considerably with time (e.g., score of 14 on day 1, 35 on day 3 and 45 on day 28).
T129 21804-22005 Sentence denotes In order to examine the molecular mechanisms that may be involved in fibrosis in more detail, a meta-analysis was completed using curated studies within NextBio that identified fibrosis as a phenotype.
T130 22006-22273 Sentence denotes Meta-analysis in mouse employed 36 models that included fibrosis-induced by injury with naphthalene, bleomycin and ganciclovir, doxycyclineinduced over-expression, and TGF-␤ over-expression in a variety of mouse models (wild type, inflammation resistant/susceptible).
T131 22274-22527 Sentence denotes Meta-analysis using CBNP gene expression profiles in mouse ranked 473 canonical pathways and 21,277 genes present in at least one of the studies on select models of pulmonary fibrosis and lung injury (identified in NextBio disease correlation profiles).
T132 22528-22632 Sentence denotes In order to establish human-relevance, the analysis was repeated using human studies curated in NextBio.
T133 22633-22836 Sentence denotes Meta-analysis encompassed 4 studies from lung biopsies of patients affected with fibrosis, with intermediate to severe pulmonary hypertension, pneumonia and exacerbation of idiopathic pulmonary fibrosis.
T134 22837-22940 Sentence denotes Overall, 472 canonical pathways and 15,795 genes were ranked as present in at least one of the studies.
T135 22941-23039 Sentence denotes The top ranked pathways and genes for the mouse and human meta-analyses are presented in Table 4 .
T136 23040-23188 Sentence denotes Interestingly, comparison of fold-ranks between the mouse and human analysis revealed that the most affected pathways were the same in both species.
T137 23189-23487 Sentence denotes However, the genes that were most perturbed during fibrotic responses were considerably different in CBNP-exposed mice compared to human diseases, with the exception of glycerol-3-phosphate dehydrogenase (GDP1), kruppel-like factor 4 (KLF4), secreted phosphoprotein 1 (SPP1) and ceruloplasmin (CP).
T138 23488-23732 Sentence denotes It is now widely accepted that toxicity is preceded by, and accompanied by, transcriptional changes, thus providing molecular signatures of direct and indirect toxic effects (Auerbach et al., 2010; Fielden et al., 2011; Gatzidou et al., 2007) .
T139 23733-23970 Sentence denotes It is hypothesized that toxicogenomic profiling can be used as a screening tool to prioritize the specific assays that should be conducted from the standard battery of tests, thus minimizing animal use, cost and time (Dix et al., 2007) .
T140 23971-24182 Sentence denotes Moreover, global analyses of transcriptional changes provide a wealth of information that can be used to identify putative modes of action and to query relevance to human adverse health outcomes (Currie, 2012) .
T141 24183-24350 Sentence denotes This type of approach is the general premise of the widely supported paradigm outlined in 'Toxicity Testing in the 21st Century' (National Academy of Sciences, 2007) .
T142 24351-24649 Sentence denotes However, substantive work demonstrating the ability of gene expression profiles to identify hazards, to assess risk of exposure via quantitative dose-response analysis, and to identify adverse outcomes associated with specific modes of action is required before these endpoints can be used in HHRA.
T143 24650-24864 Sentence denotes The present study applies pathway-and network-based approaches, BMD modelling, and disease prediction tools to gene expression data to explore the relationship between apical endpoints and transcriptional profiles.
T144 24865-25147 Sentence denotes The work investigates the potential utility of gene expression profiling in determining hazard and mode of action of NPs, in characterizing dose-response relationships and in predicting the relevance of these findings to potential disease-outcomes and human health effects for HHRA.
T145 25148-25380 Sentence denotes The utility of gene expression profiling in hazard identification has been examined for a limited number of chemicals, including dibutyl phthalate and acetaminophen (Euling et al., 2011; Kienhuis et al., 2011; Makris et al., 2010) .
T146 25381-25855 Sentence denotes Toxicogenomic profiles of alachlor exposure in rat olfactory mucosa (Genter et al., 2002) and dimethylarsenic (DMA) exposure in human cultured bladder cells and rat bladder epithelium (Sen et al., 2005 ; US EPA, 2005) have also Table 3 Comparison of CBNP profiles with lung disease models using functional analysis for genes in common (grey) and genes unique to CBNP (black). provided useful information for two final assessments of acetochlor and arsenicals (US EPA, 2004 .
T147 25856-25993 Sentence denotes Our data demonstrate that gene expression profiles can also be viewed as effective predictors of the biological effects of CBNP exposure.
T148 25994-26382 Sentence denotes For example, inflammatory responses manifested at the gene expression level and detected using DNA microarrays and classified in this work using KEGG pathway analyses and previously in the same mice using ingenuity pathway analysis (Bourdon et al., 2012a) are entirely consistent with the observed pulmonary influx of inflammatory markers (e.g., neutrophils, eosinophils and lymphocytes).
T149 26383-26501 Sentence denotes The number of genes perturbed and the magnitude of expression changes in these pathways correlates with dose and time.
T150 26502-26967 Sentence denotes In addition, observed transcriptomic changes associated with perturbations of cell cycle networks, alterations of non-homologous end-joining, and p53 signalling support the sustained genotoxicity observed in the mice, although dose and time correlations were not as apparent (e.g., levels of DNA strand breaks remained relatively constant at the two highest exposure doses (Bourdon et al., 2012b) whereas induction of DNA repair genes decreased with dose and time).
T151 26968-27230 Sentence denotes The transcriptomic changes associated with alterations in glutathione metabolism and free radical scavenging correlate with induction of DNA formamidopyrimidine DNA glycoslase (FPG) sensitive sites (an indicator of oxidative DNA damage) early after the exposure.
T152 27231-27350 Sentence denotes The persistence of this response is an indication of an adaptive response to oxidative stress in the lungs of the mice.
T153 27351-27633 Sentence denotes Interestingly, CBNP-induced alterations in gene expression profiles also revealed a pulmonary acute phase response and unexpected changes in lipid homeostasis, which were subsequently supported by measured decreases in plasma high density lipoprotein (HDL) (Bourdon et al., 2012a) .
T154 27634-27897 Sentence denotes The strong association between CBNPinduced gene expression profiles and apical endpoints collectively support the use of toxicogenomics for hazard identification of Table 4 Meta-analyses in NextBio using mouse and human profiles in which fibrosis was a phenotype.
T155 27898-27976 Sentence denotes Values in parentheses represent rank in the opposite species (mouse or human).
T156 27977-28111 Sentence denotes Rank 1 (rank 2) Pathway Rank 1 (rank 2) Gene (symbol) NMs, and perhaps more importantly, for highlighting unexpected adverse outcomes.
T157 28112-28398 Sentence denotes Moreover, ongoing work within the Organization for Economic Co-operation and Development (OECD) is actively developing adverse outcome pathways (AOP) approaches that are expected to provide tangible methods by which systems biology endpoints can be used in human health risk assessment.
T158 28399-28571 Sentence denotes Toxicogenomics data that examine responses over dose and time in a variety of tissues can be very useful for such applications, as illustrated for CBNP exposure in Fig. 3 .
T159 28572-28753 Sentence denotes Overall, our data suggest that gene expression profiles can be effectively used to identify putative mode(s) of action and hazards of NP exposure, in the absence of phenotypic data.
T160 28754-28992 Sentence denotes In addition to identification of hazard, it has been suggested that gene expression profiles may be useful for quantitative assessment (e.g., establishment of reference doses) of responses related to both cancer and non-cancer endpoints .
T161 28993-29212 Sentence denotes Benchmark doses are generally considered more informative than the no observable adverse effect level (NOAEL) in deriving reference doses as they are based on the entire dose-response relationship (Crump et al., 1995) .
T162 29213-29486 Sentence denotes Because alterations in gene expression can be initiated in the absence of biological effects (e.g., adaptive or stress response pathways effective in mitigating toxic effects), it is expected that reference doses for genomics endpoints may be too sensitive for use in HHRA.
T163 29487-29836 Sentence denotes However, previous analyses of 5 chemicals (i.e., 1,4-dichlorobenzene, propylene glycol mono-t-butyl ether, 1,2,3-trichloropropane, methylene chloride and naphthalene) showed that median BMD and BMDLs for the most sensitive pathways and GO categories were highly correlated with BMD and BMDLs of cancer and non-cancer endpoints (Thomas et al., 2011 .
T164 29837-30114 Sentence denotes In the current study, rather than choosing the most sensitive (i.e., lowest) BMDs, we focussed on the analysis of pathways that were specific to biological outcomes observed in the mice (i.e., phenotypically anchored), and calculated BMDs for these relevant genes and pathways.
T165 30115-30279 Sentence denotes The pathway-based BMDs and BMDLs calculated here for relevant pathways were actually less sensitive (i.e., higher BMDs) than those of the observed apical endpoints.
T166 30280-30535 Sentence denotes However, the mean of the minimum BMDs and BMDLs across all the pathways that we assigned as relevant to the apical endpoints (i.e., corresponding to the most sensitive genes within the relevant pathways) were similar to those of relevant apical endpoints.
T167 30536-30714 Sentence denotes Median BMDs and BMDLs for the most sensitive pathways also correlate more closely with apical endpoints even though the pathways were not necessarily relevant to these endpoints.
T168 30715-30863 Sentence denotes This finding supports previous examples demonstrating a 1:1 correlation between BMDs for gene expression and apical endpoints (Thomas et al., 2011 .
T169 30864-30990 Sentence denotes These data indicate the potential utility of using gene expression profiles in determining acceptable exposure limits for NPs.
T170 30991-31208 Sentence denotes In order to determine the specific utility of pathway derived BMDs in HHRA, it will be necessary to establish a comprehensive catalogue of pathways that are actually perturbed in the event of specific adverse effects.
T171 31209-31507 Sentence denotes Perhaps the principal motivation for including gene expression profiling in HHRA is the wealth of information that can be used to identify key events that are correlated with adverse outcomes that are relevant to human disease, and moreover can be used to predict the likelihood of a human disease.
T172 31508-31810 Sentence denotes Identification of key events at the transcriptional level can facilitate the identification of processes that are critical for disease initiation and progression, thus allowing information from animal experiments to be queried and used for extrapolation to human scenarios (Edwards and Preston, 2008) .
T173 31811-32061 Sentence denotes Comparison of our data with specific models of lung disease, including bacterial infection, airway hypersensitivity and lung injury revealed that CBNPs induced responses that were more closely related to lung injury and fibrosis than to other models.
T174 32062-32261 Sentence denotes This finding was further supported by comparison of the expression profiles of CBNP exposed mice to those of curated studies of animals and humans exhibiting a myriad of pulmonary disease phenotypes.
T175 32262-32391 Sentence denotes This analysis demonstrates that CBNP exposure perturbs genes that are known to be involved in tissue injury and fibrosis in mice.
T176 32392-32661 Sentence denotes Although it is unclear if CBNP exposure would result in the same gene expression profile in humans, similar pathways including many involved in fibrotic responses were found in both mice and humans (52% of the top 50 pathways found were common between mouse and human).
T177 32662-32759 Sentence denotes Despite concordance of pathways, the top ranked genes differed considerably between both species.
T178 32760-33099 Sentence denotes However, many of the genes found in mice and humans had similar functions, including inflammatory and acute phase responses (e.g., Saa3, Socs3 and Mt2 in mice and CP, VNN2 and CXCL10 in humans), cell cycle progression (Cdkn1a in mice and KLF4 in humans) and bone and tissue modelling (Mmp14, Timp1, Eln and Ogn in mice and SPP1 in humans).
T179 33100-33335 Sentence denotes Thus, despite discordance in the gene expression profiles between species, the similar functions of top ranked genes and concordance between pathways supports the likelihood of similar responses in the event of CBNP exposure in humans.
T180 33336-33668 Sentence denotes In addition, fibrosis has been identified as an outcome of exposure to various particles and NPs in animals (Bermudez et al., 2004; Shvedova et al., 2008) , including Printex 90 (e.g., 28-day nose only inhalation in Wistar WU rats) (Bellmann et al., 2009) , as well as in humans (Lkhasuren et al., 2007; Wang and Christiani, 2003) .
T181 33669-33785 Sentence denotes The process of pulmonary fibrosis is closely related to progression of carcinogenic outcome (Hubbard et al., 2000) .
T182 33786-34099 Sentence denotes These data demonstrating very similar fibrotic pathways in mice and humans and a significant overlap with CBNP-induced gene expression changes thus support the use of pathway-based approaches in identifying molecular mechanisms of disease onset and progression, and using gene expression profiles to support HHRA.
T183 34100-34251 Sentence denotes This study confirms several key elements that are necessary for the application of gene expression profiling for HHRA of toxicant exposures in general.
T184 34252-34353 Sentence denotes First, transcriptional profiles can effectively predict the biological effects of chemical exposures.
T185 34354-34581 Sentence denotes Specifically, in the absence of data for any apical endpoints, our data would have suggested that mice exposed to CBNPs exhibit an inflammatory response, oxidative stress, DNA damage and perturbations in cholesterol metabolism.
T186 34582-34759 Sentence denotes Second, a comparison of BMDs and BMDLs of relevant pathways and apical endpoints confirms that minimum pathway BMDs and BMDLs are in the same range as those of apical endpoints.
T187 34760-35048 Sentence denotes Third, that expression profiles can be fairly easily mined to identify potential adverse outcomes (i.e., diseases) that are relevant to humans, and might reasonably be expected to occur in humans exposed to substances that elicit specific gene expression patterns in experimental animals.
T188 35049-35209 Sentence denotes We believe that our work constitutes a significant step towards the ultimate recognition of toxicogenomic endpoints for routine assessment of human health risk.
T189 35210-35319 Sentence denotes Gene expression profiling offers a promising approach to decipher the largely unknown hazards of NP exposure.
T190 35320-35605 Sentence denotes Due to the unique properties of NPs, powerful technologies that can assess a multitude of adverse outcome possibilities will be required to elucidate their modes of action and potential impacts on human health within a time-frame that is suitable for prompt regulatory decision making.
T191 35606-35724 Sentence denotes This same premise should hold true for any new chemical products, for which toxicity is largely or completely unknown.
T192 35725-36094 Sentence denotes In order to establish a strong foundation for the integration of gene expression profiling into HHRA, it will be necessary for the approach employed here to be applied to a variety of additional chemicals/particles that span a wide range of toxicological potencies and modes of action, and using a variety of experimental designs (e.g., multiple doses and time-points).
T193 36095-36454 Sentence denotes As our knowledge of molecular pathways, and of the diverse tools used to decipher their biological significance, dose-response characteristics and relevance to human disease continues to grow, we anticipate that toxicogenomics will become increasingly useful in assessing the toxicological hazards of a wide range of test articles, and by extension, for HHRA.
T194 36455-36584 Sentence denotes Marchetti, Lynn Berndt-Weis and Miriam Hill of Health Canada are thanked for reviewing and commenting on the original manuscript.
T195 36585-36709 Sentence denotes This work was supported by the Health Canada Genomics Research and Development Initiative, and the Chemical Management Plan.
T196 36710-36734 Sentence denotes Financial support for J.
T197 36735-36819 Sentence denotes Bourdon was through the Natural Sciences and Engineering Research Council of Canada.