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1.
Epidemiology ; 30(5): 756-767, 2019 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-31373935

RESUMO

BACKGROUND: Within-subject biospecimens pooling can theoretically reduce bias in dose-response functions from biomarker-based studies when exposure assessment suffers from classical-type error. However, collecting many urine voids each day is cumbersome. We evaluated the empirical validity of a within-subject pooling approach and compared several options to avoid sampling each void. METHODS: In 16 pregnant women who collected a spot of each urine void over several nonconsecutive weeks, we compared concentrations of 10 phenols in daily, weekly, and pregnancy within-subject pools. We pooled either three or all daily samples. In a simulation study using these data, we quantified bias in dose-response functions when using one to 20 urine samples per subject to assess methylparaben (a compound with moderate within-subject variability) and bisphenol A (high variability) exposures. RESULTS: Correlations between exposure estimates from pools of all and of only three voids per day were above 0.80 for all time windows and compounds, except for benzophenone-3 and triclosan in the daily time window (correlations, 0.57-0.68). With one spot sample to assess pregnancy exposure, correlations were all below 0.74. Using only one biospecimen led to attenuation bias in the dose-response functions of 29% (methylparaben) and 69% (bisphenol A); four samples for methylparaben and 18 for bisphenol A decreased bias to 10%. CONCLUSIONS: For nonpersistent chemicals, collecting and pooling three samples per day instead of all daily samples efficiently estimates exposures over a week or more. Collecting around 20 biospecimens can strongly limit attenuation bias for nonpersistent chemicals such as bisphenol A.

2.
Environ Health Perspect ; 127(4): 47007, 2019 Apr.
Artigo em Inglês | MEDLINE | ID: mdl-31009264

RESUMO

BACKGROUND: The exposome is defined as the totality of environmental exposures from conception onwards. It calls for providing a holistic view of environmental exposures and their effects on human health by evaluating multiple environmental exposures simultaneously during critical periods of life. OBJECTIVE: We evaluated the association of the urban exposome with birth weight. METHODS: We estimated exposure to the urban exposome, including the built environment, air pollution, road traffic noise, meteorology, natural space, and road traffic (corresponding to 24 environmental indicators and 60 exposures) for nearly 32,000 pregnant women from six European birth cohorts. To evaluate associations with either continuous birth weight or term low birth weight (TLBW) risk, we primarily relied on the Deletion-Substitution-Addition (DSA) algorithm, which is an extension of the stepwise variable selection method. Second, we used an exposure-by-exposure exposome-wide association studies (ExWAS) method accounting for multiple hypotheses testing to report associations not adjusted for coexposures. RESULTS: The most consistent statistically significant associations were observed between increasing green space exposure estimated as Normalized Difference Vegetation Index (NDVI) and increased birth weight and decreased TLBW risk. Furthermore, we observed statistically significant associations among presence of public bus line, land use Shannon's Evenness Index, and traffic density and birth weight in our DSA analysis. CONCLUSION: This investigation is the first large urban exposome study of birth weight that tests many environmental urban exposures. It confirmed previously reported associations for NDVI and generated new hypotheses for a number of built-environment exposures. https://doi.org/10.1289/EHP3971.

3.
Lancet Planet Health ; 3(2): e81-e92, 2019 Feb.
Artigo em Inglês | MEDLINE | ID: mdl-30737192

RESUMO

BACKGROUND: Several single-exposure studies have documented possible effects of environmental factors on lung function, but none has relied on an exposome approach. We aimed to evaluate the association between a broad range of prenatal and postnatal lifestyle and environmental exposures and lung function in children. METHODS: In this analysis, we used data from 1033 mother-child pairs from the European Human Early-Life Exposome (HELIX) cohort (consisting of six existing longitudinal birth cohorts in France, Greece, Lithuania, Norway, Spain, and the UK of children born between 2003 and 2009) for whom a valid spirometry test was recorded for the child. 85 prenatal and 125 postnatal exposures relating to outdoor, indoor, chemical, and lifestyle factors were assessed, and lung function was measured by spirometry in children at age 6-12 years. Two agnostic linear regression methods, a deletion-substitution-addition (DSA) algorithm considering all exposures simultaneously, and an exposome-wide association study (ExWAS) considering exposures independently, were applied to test the association with forced expiratory volume in 1 s percent predicted values (FEV1%). We tested for two-way interaction between exposures and corrected for confounding by co-exposures. FINDINGS: In the 1033 children (median age 8·1 years, IQR 6·5-9·0), mean FEV1% was 98·8% (SD 13·2). In the ExWAS, prenatal perfluorononanoate (p=0·034) and perfluorooctanoate (p=0·030) exposures were associated with lower FEV1%, and inverse distance to nearest road during pregnancy (p=0·030) was associated with higher FEV1%. Nine postnatal exposures were associated with lower FEV1%: copper (p=0·041), ethyl-paraben (p=0·029), five phthalate metabolites (mono-2-ethyl 5-carboxypentyl phthalate [p=0·016], mono-2-ethyl-5-hydroxyhexyl phthalate [p=0·023], mono-2-ethyl-5-oxohexyl phthalate [p=0·0085], mono-4-methyl-7-oxooctyl phthalate [p=0·040], and the sum of di-ethylhexyl phthalate metabolites [p=0·014]), house crowding (p=0·015), and facility density around schools (p=0·027). However, no exposure passed the significance threshold when corrected for multiple testing in ExWAS, and none was selected with the DSA algorithm, including when testing for exposure interactions. INTERPRETATION: Our systematic exposome approach identified several environmental exposures, mainly chemicals, that might be associated with lung function. Reducing exposure to these ubiquitous chemicals could help to prevent the development of chronic respiratory disease. FUNDING: European Community's Seventh Framework Programme (HELIX project).

4.
Environ Int ; 123: 189-200, 2019 02.
Artigo em Inglês | MEDLINE | ID: mdl-30530161

RESUMO

Characterization of the "exposome", the set of all environmental factors that one is exposed to from conception onwards, has been advocated to better understand the role of environmental factors on chronic diseases. Here, we aimed to describe the early-life exposome. Specifically, we focused on the correlations between multiple environmental exposures, their patterns and their variability across European regions and across time (pregnancy and childhood periods). We relied on the Human Early-Life Exposome (HELIX) project, in which 87 environmental exposures during pregnancy and 122 during the childhood period (grouped in 19 exposure groups) were assessed in 1301 pregnant mothers and their children at 6-11 years in 6 European birth cohorts. Some correlations between exposures in the same exposure group reached high values above 0.8. The median correlation within exposure groups was >0.3 for many exposure groups, reaching 0.69 for water disinfection by products in pregnancy and 0.67 for the meteorological group in childhood. Median correlations between different exposure groups rarely reached 0.3. Some correlations were driven by cohort-level associations (e.g. air pollution and chemicals). Ten principal components explained 45% and 39% of the total variance in the pregnancy and childhood exposome, respectively, while 65 and 90 components were required to explain 95% of the exposome variability. Correlations between maternal (pregnancy) and childhood exposures were high (>0.6) for most exposures modeled at the residential address (e.g. air pollution), but were much lower and even close to zero for some chemical exposures. In conclusion, the early life exposome was high dimensional, meaning that it cannot easily be measured by or reduced to fewer components. Correlations between exposures from different exposure groups were much lower than within exposure groups, which have important implications for co-exposure confounding in multiple exposure studies. Also, we observed the early life exposome to be variable over time and to vary by cohort, so measurements at one time point or one place will not capture its complexities.


Assuntos
Exposição Ambiental , Poluição do Ar , Criança , Doença Crônica , Estudos de Coortes , Exposição Ambiental/análise , Europa (Continente) , Feminino , Humanos , Mães , Gravidez , Purificação da Água
5.
BMJ Open ; 8(9): e021311, 2018 Sep 10.
Artigo em Inglês | MEDLINE | ID: mdl-30206078

RESUMO

PURPOSE: Essential to exposome research is the collection of data on many environmental exposures from different domains in the same subjects. The aim of the Human Early Life Exposome (HELIX) study was to measure and describe multiple environmental exposures during early life (pregnancy and childhood) in a prospective cohort and associate these exposures with molecular omics signatures and child health outcomes. Here, we describe recruitment, measurements available and baseline data of the HELIX study populations. PARTICIPANTS: The HELIX study represents a collaborative project across six established and ongoing longitudinal population-based birth cohort studies in six European countries (France, Greece, Lithuania, Norway, Spain and the UK). HELIX used a multilevel study design with the entire study population totalling 31 472 mother-child pairs, recruited during pregnancy, in the six existing cohorts (first level); a subcohort of 1301 mother-child pairs where biomarkers, omics signatures and child health outcomes were measured at age 6-11 years (second level) and repeat-sampling panel studies with around 150 children and 150 pregnant women aimed at collecting personal exposure data (third level). FINDINGS TO DATE: Cohort data include urban environment, hazardous substances and lifestyle-related exposures for women during pregnancy and their offspring from birth until 6-11 years. Common, standardised protocols were used to collect biological samples, measure exposure biomarkers and omics signatures and assess child health across the six cohorts. Baseline data of the cohort show substantial variation in health outcomes and determinants between the six countries, for example, in family affluence levels, tobacco smoking, physical activity, dietary habits and prevalence of childhood obesity, asthma, allergies and attention deficit hyperactivity disorder. FUTURE PLANS: HELIX study results will inform on the early life exposome and its association with molecular omics signatures and child health outcomes. Cohort data are accessible for future research involving researchers external to the project.

6.
Environ Int ; 118: 334-347, 2018 Sep.
Artigo em Inglês | MEDLINE | ID: mdl-29935799

RESUMO

BACKGROUND: Air pollution exposure represents a major health threat to the developing foetus. DNA methylation is one of the most well-known molecular determinants of the epigenetic status of cells. Blood DNA methylation has been proven sensitive to air pollutants, but the molecular impact of air pollution on new-borns has so far received little attention. OBJECTIVES: We investigated whether nitrogen dioxide (NO2), particulate matter (PM10), temperature and humidity during pregnancy are associated with differences in placental DNA methylation levels. METHODS: Whole-genome DNA-methylation was measured using the Illumina's Infinium HumanMethylation450 BeadChip in the placenta of 668 newborns from the EDEN cohort. We designed an original strategy using a priori biological information to focus on candidate genes with a specific expression pattern in placenta (active or silent) combined with an agnostic epigenome-wide association study (EWAS). We used robust linear regression to identify CpGs and differentially methylated regions (DMR) associated with each exposure during short- and long-term time-windows. RESULTS: The candidate genes approach identified nine CpGs mapping to 9 genes associated with prenatal NO2 and PM10 exposure [false discovery rate (FDR) p < 0.05]. Among these, the methylation level of 2 CpGs located in ADORA2B remained significantly associated with NO2 exposure during the 2nd trimester and whole pregnancy in the EWAS (FDR p < 0.05). EWAS further revealed associations between the environmental exposures under study and variations of DNA methylation of 4 other CpGs. We further identified 27 DMRs significantly (FDR p < 0.05) associated with air pollutants exposure and 13 DMRs with meteorological conditions. CONCLUSIONS: The methylation of ADORA2B, a gene whose expression was previously associated with hypoxia and pre-eclampsia, was consistently found here sensitive to atmospheric pollutants. In addition, air pollutants were associated to DMRs pointing towards genes previously implicated in preeclampsia, hypertensive and metabolic disorders. These findings demonstrate that air pollutants exposure at levels commonly experienced in the European population are associated with placental gene methylation and provide some mechanistic insight into some of the reported effects of air pollutants on preeclampsia.

7.
Environ Health ; 16(1): 74, 2017 07 14.
Artigo em Inglês | MEDLINE | ID: mdl-28709428

RESUMO

BACKGROUND: There is growing interest in examining the simultaneous effects of multiple exposures and, more generally, the effects of mixtures of exposures, as part of the exposome concept (being defined as the totality of human environmental exposures from conception onwards). Uncovering such combined effects is challenging owing to the large number of exposures, several of them being highly correlated. We performed a simulation study in an exposome context to compare the performance of several statistical methods that have been proposed to detect statistical interactions. METHODS: Simulations were based on an exposome including 237 exposures with a realistic correlation structure. We considered several statistical regression-based methods, including two-step Environment-Wide Association Study (EWAS2), the Deletion/Substitution/Addition (DSA) algorithm, the Least Absolute Shrinkage and Selection Operator (LASSO), Group-Lasso INTERaction-NET (GLINTERNET), a three-step method based on regression trees and finally Boosted Regression Trees (BRT). We assessed the performance of each method in terms of model size, predictive ability, sensitivity and false discovery rate. RESULTS: GLINTERNET and DSA had better overall performance than the other methods, with GLINTERNET having better properties in terms of selecting the true predictors (sensitivity) and of predictive ability, while DSA had a lower number of false positives. In terms of ability to capture interaction terms, GLINTERNET and DSA had again the best performances, with the same trade-off between sensitivity and false discovery proportion. When GLINTERNET and DSA failed to select an exposure truly associated with the outcome, they tended to select a highly correlated one. When interactions were not present in the data, using variable selection methods that allowed for interactions had only slight costs in performance compared to methods that only searched for main effects. CONCLUSIONS: GLINTERNET and DSA provided better performance in detecting two-way interactions, compared to other existing methods.


Assuntos
Exposição Ambiental , Saúde Ambiental/métodos , Monitoramento Ambiental/métodos , Poluentes Ambientais/toxicidade , Modelos Estatísticos , Humanos
8.
Int J Infect Dis ; 54: 103-112, 2017 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-27826113

RESUMO

OBJECTIVES: Neisseria meningitidis is the major cause of seasonal meningitis epidemics in the African meningitis belt. In the changing context of a reduction in incidence of serogroup A and an increase in incidence of serogroups W and C and of Streptococcus pneumoniae, a better understanding of the determinants driving the disease transmission dynamics remains crucial to improving bacterial meningitis control. METHODS: The literature was searched to provide a multi-disciplinary overview of the determinants of meningitis transmission dynamics in the African meningitis belt. RESULTS: Seasonal hyperendemicity is likely predominantly caused by increased invasion rates, sporadic localized epidemics by increased transmission rates, and larger pluri-annual epidemic waves by changing population immunity. Carriage likely involves competition for colonization and cross-immunity. The duration of immunity likely depends on the acquisition type. Major risk factors include dust and low humidity, and presumably human contact rates and co-infections; social studies highlighted environmental and dietary factors, with supernatural explanations. CONCLUSIONS: Efforts should focus on implementing multi-country, longitudinal seroprevalence and epidemiological studies, validating immune markers of protection, and improving surveillance, including more systematic molecular characterizations of the bacteria. Integrating climate and social factors into disease control strategies represents a high priority for optimizing the public health response and anticipating the geographic evolution of the African meningitis belt.


Assuntos
Meningite Meningocócica/epidemiologia , Neisseria meningitidis/isolamento & purificação , África/epidemiologia , Animais , Humanos , Meningite Meningocócica/microbiologia , Neisseria meningitidis/genética , Neisseria meningitidis/fisiologia , Estudos Soroepidemiológicos
9.
Part Fibre Toxicol ; 13(1): 39, 2016 07 26.
Artigo em Inglês | MEDLINE | ID: mdl-27460165

RESUMO

BACKGROUND: Airborne pollution is a rising concern in urban areas. Epidemiological studies in humans and animal experiments using rodent models indicate that gestational exposure to airborne pollution, in particular diesel engine exhaust (DE), reduces birth weight, but effects depend on exposure duration, gestational window and nanoparticle (NP) concentration. Our aim was to evaluate the effects of gestational exposure to diluted DE on feto-placental development in a rabbit model. Pregnant females were exposed to diluted (1 mg/m(3)), filtered DE (NP diameter ≈ 69 nm) or clean air (controls) for 2 h/day, 5 days/week by nose-only exposure (total exposure: 20 days in a 31-day gestation). RESULTS: DE exposure induced early signs of growth retardation at mid gestation with decreased head length (p = 0.04) and umbilical pulse (p = 0.018). Near term, fetal head length (p = 0.029) and plasma insulin and IGF1 concentrations (p = 0.05 and p = 0.019) were reduced. Placental function was also affected, with reduced placental efficiency (fetal/placental weight) (p = 0.049), decreased placental blood flow (p = 0.009) and fetal vessel volume (p = 0.002). Non-aggregated and "fingerprint" NP were observed at various locations, in maternal blood space, in trophoblastic cells and in the fetal blood, demonstrating transplacental transfer. Adult female offspring were bred with control males. Although fetoplacental biometry was not affected near term, second generation fetal metabolism was modified by grand-dam exposure with decreased plasma cholesterol (p = 0.008) and increased triglyceride concentrations (p = 0.015). CONCLUSIONS: Repeated daily gestational exposure to DE at levels close to urban pollution can affect feto-placental development in the first and second generation.


Assuntos
Exposição Materna , Placenta/efeitos dos fármacos , Efeitos Tardios da Exposição Pré-Natal , Emissões de Veículos/toxicidade , Animais , Feminino , Placenta/fisiologia , Gravidez , Coelhos
10.
Eur Respir Rev ; 25(140): 124-9, 2016 Jun.
Artigo em Inglês | MEDLINE | ID: mdl-27246588

RESUMO

The exposome concept was defined in 2005 as encompassing all environmental exposures from conception onwards, as a new strategy to evidence environmental disease risk factors. Although very appealing, the exposome concept is challenging in many respects. In terms of assessment, several hundreds of time-varying exposures need to be considered, but increasing the number of exposures assessed should not be done at the cost of increased exposure misclassification. Accurately assessing the exposome currently requires numerous measurements, which rely on different technologies; resulting in an expensive set of protocols. In the future, high-throughput 'omics technologies may be a promising technique to integrate a wide range of exposures from a small numbers of biological matrices. Assessing the association between many exposures and health raises statistical challenges. Due to the correlation structure of the exposome, existing statistical methods cannot fully and efficiently untangle the exposures truly affecting the health outcome from correlated exposures. Other statistical challenges relate to accounting for exposure misclassification or identifying synergistic effects between exposures. On-going exposome projects are trying to overcome technical and statistical challenges. From a public health perspective, a better understanding of the environmental risk factors should open the way to improved prevention strategies.


Assuntos
Pesquisa Biomédica/métodos , Suscetibilidade a Doenças , Exposição Ambiental/efeitos adversos , Saúde Ambiental/métodos , Poluentes Ambientais/efeitos adversos , Estilo de Vida , Fatores Etários , Biologia Computacional , Monitoramento Ambiental , Ensaios de Triagem em Larga Escala , Humanos , Medição de Risco , Fatores de Risco , Fatores de Tempo
11.
Environ Health Perspect ; 124(12): 1848-1856, 2016 12.
Artigo em Inglês | MEDLINE | ID: mdl-27219331

RESUMO

BACKGROUND: The exposome constitutes a promising framework to improve understanding of the effects of environmental exposures on health by explicitly considering multiple testing and avoiding selective reporting. However, exposome studies are challenged by the simultaneous consideration of many correlated exposures. OBJECTIVES: We compared the performances of linear regression-based statistical methods in assessing exposome-health associations. METHODS: In a simulation study, we generated 237 exposure covariates with a realistic correlation structure and with a health outcome linearly related to 0 to 25 of these covariates. Statistical methods were compared primarily in terms of false discovery proportion (FDP) and sensitivity. RESULTS: On average over all simulation settings, the elastic net and sparse partial least-squares regression showed a sensitivity of 76% and an FDP of 44%; Graphical Unit Evolutionary Stochastic Search (GUESS) and the deletion/substitution/addition (DSA) algorithm revealed a sensitivity of 81% and an FDP of 34%. The environment-wide association study (EWAS) underperformed these methods in terms of FDP (average FDP, 86%) despite a higher sensitivity. Performances decreased considerably when assuming an exposome exposure matrix with high levels of correlation between covariates. CONCLUSIONS: Correlation between exposures is a challenge for exposome research, and the statistical methods investigated in this study were limited in their ability to efficiently differentiate true predictors from correlated covariates in a realistic exposome context. Although GUESS and DSA provided a marginally better balance between sensitivity and FDP, they did not outperform the other multivariate methods across all scenarios and properties examined, and computational complexity and flexibility should also be considered when choosing between these methods. Citation: Agier L, Portengen L, Chadeau-Hyam M, Basagaña X, Giorgis-Allemand L, Siroux V, Robinson O, Vlaanderen J, González JR, Nieuwenhuijsen MJ, Vineis P, Vrijheid M, Slama R, Vermeulen R. 2016. A systematic comparison of linear regression-based statistical methods to assess exposome-health associations. Environ Health Perspect 124:1848-1856; http://dx.doi.org/10.1289/EHP172.


Assuntos
Exposição Ambiental , Monitoramento Ambiental/métodos , Poluentes Ambientais/toxicidade , Humanos , Modelos Lineares
12.
Environ Sci Technol ; 49(17): 10632-41, 2015 Sep 01.
Artigo em Inglês | MEDLINE | ID: mdl-26168307

RESUMO

The "exposome" is defined as "the totality of human environmental exposures from conception onward, complementing the genome" and its holistic approach may advance understanding of disease etiology. We aimed to describe the correlation structure of the exposome during pregnancy to better understand the relationships between and within families of exposure and to develop analytical tools appropriate to exposome data. Estimates on 81 environmental exposures of current health concern were obtained for 728 women enrolled in The INMA (INfancia y Medio Ambiente) birth cohort, in Sabadell, Spain, using biomonitoring, geospatial modeling, remote sensors, and questionnaires. Pair-wise Pearson's and polychoric correlations were calculated and principal components were derived. The median absolute correlation across all exposures was 0.06 (5th-95th centiles, 0.01-0.54). There were strong levels of correlation within families of exposure (median = 0.45, 5th-95th centiles, 0.07-0.85). Nine exposures (11%) had a correlation higher than 0.5 with at least one exposure outside their exposure family. Effectively all the variance in the data set (99.5%) was explained by 40 principal components. Future exposome studies should interpret exposure effects in light of their correlations to other exposures. The weak to moderate correlation observed between exposure families will permit adjustment for confounding in future exposome studies.


Assuntos
Exposição Ambiental/análise , Estudos de Coortes , Feminino , Humanos , Gravidez , Análise de Componente Principal , Espanha
13.
Trans R Soc Trop Med Hyg ; 107(1): 30-6, 2013 Jan.
Artigo em Inglês | MEDLINE | ID: mdl-23296695

RESUMO

BACKGROUND: Bacterial meningitis is a major public health problem in the African 'Meningitis Belt', where recurrent unpredictable epidemics occur. Despite the introduction in 2010 of the conjugate A vaccine, the reactive strategy remains important for responding to epidemics caused by other bacteria and in areas not yet vaccinated. Review of weekly numbers of suspected cases in Niger, Mali and Burkina Faso identified spatial disparities in the annual patterns of meningitis, which suggested a more local way of defining epidemics and initiating a timely vaccination campaign. METHOD: We defined an epidemic district-year as an excess of cases compared to the incidence previously experienced in the given district. Groups of similar districts in terms of seasonal patterns were identified by cluster analysis. We investigated a cluster-specific criterion of early epidemic onset to anticipate epidemic district-years. RESULTS: These were encouraging, as epidemic district-years were fairly efficiently captured, with an average time gained of 2.5 weeks over the current strategy. CONCLUSION: This early-onset criterion could help ensure timely implementation of vaccination campaigns without the need to modify the implemented surveillance system. The next step is to extend this study to other countries of the Meningitis Belt, and to explain the differences in seasonal patterns in the different clusters.


Assuntos
Meningites Bacterianas/epidemiologia , Burkina Faso/epidemiologia , Análise por Conglomerados , Humanos , Incidência , Mali/epidemiologia , Níger/epidemiologia
14.
Proc Natl Acad Sci U S A ; 109(21): 8196-201, 2012 May 22.
Artigo em Inglês | MEDLINE | ID: mdl-22570501

RESUMO

Carrying out statistical analysis over an extensive dataset of human plague reports in Chinese villages from 1772 to 1964, we identified plague endemic territories in China (i.e., plague foci). Analyses rely on (i) a clustering method that groups time series based on their time-frequency resemblances and (ii) an ecological niche model that helps identify plague suitable territories characterized by value ranges for a set of predefined environmental variables. Results from both statistical tools indicate the existence of two disconnected plague territories corresponding to Northern and Southern China. Altogether, at least four well defined independent foci are identified. Their contours compare favorably with field observations. Potential and limitations of inferring plague foci and dynamics using epidemiological data is discussed.


Assuntos
Reservatórios de Doenças/estatística & dados numéricos , Epidemias/história , Peste/epidemiologia , Peste/história , Yersinia pestis/isolamento & purificação , China/epidemiologia , Análise por Conglomerados , Ecossistema , História do Século XVIII , História do Século XIX , História do Século XX , Humanos , Análise de Ondaletas
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