Mendelian randomization of inorganic arsenic metabolism as a risk factor for hypertension- and diabetes-related traits among adults in the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) cohort

A Clinical Perspective on Arsenic Exposure and Development of Atherosclerotic Cardiovascular Disease

Cardiovascular risk has traditionally been defined by modifiable and non-modifiable risk factors, such as tobacco use, hyperlipidemia, and family history. However, chemicals and pollutants may also play a role in cardiovascular disease (CVD) risk. Arsenic is a naturally occurring element that is widely distributed in the Earth's crust. Inorganic arsenic (iAs) has been implicated in the pathogenesis of atherosclerosis, with chronic high-dose exposure to iAs (> 100 µg/L) being linked to CVD; however, whether low-to-moderate dose exposures of iAs (< 100 µg/L) are associated with the development of CVD is unclear. Due to limitations of the existing literature, it is difficult to define a threshold for iAs toxicity. Studies demonstrate that the effect of iAs on CVD is far more complex with influences from several factors, including diet, genetics, metabolism, and traditional risk factors such as hypertension and smoking. In this article, we review the existing data of low-to-moderate dose iAs exposure and its effect on CVD, along with highlighting the potential mechanisms of action.

Combined analysis of inorganic elements and flavonoid metabolites reveals the relationship between flower quality and maturity of Sophora japonica L

Flos Sophorae (FS), or the dried flower buds of Sophora japonica L., is widely used as a food and medicinal material in China. The quality of S. japonica flowers varies with the developmental stages (S1-S5) of the plant. However, the relationship between FS quality and maturity remains unclear. Inductively coupled plasma optical emission spectrometry (ICP-OES) and ultra-high performance liquid chromatography coupled with electrospray ionization-triple quadrupole-linear ion trap mass spectrometry (UPLC-ESI-Q TRAP-MS/MS) were used to analyze inorganic elements and flavonoid metabolites, respectively. A combined analysis of the inorganic elements and flavonoid metabolites in FS was conducted to determine the patterns of FS quality formation. Sixteen inorganic elements and 173 flavonoid metabolites that accumulated at different developmental stages were identified. Notably, 54 flavonoid metabolites associated with the amelioration of major human diseases were identified, and Ca, P, K, Fe, and Cu were postulated to influence flavonoid metabolism and synthesis. This study offers a novel perspective and foundation for the further exploration of the rules governing the quality of plant materials.

Arsenic metabolism, diabetes prevalence, and insulin resistance among Mexican Americans: A mendelian randomization approach

Background

Differences in arsenic metabolism capacity may influence risk for type 2 diabetes, but the mechanistic drivers are unclear. We evaluated the associations between arsenic metabolism with overall diabetes prevalence and with static and dynamic measures of insulin resistance among Mexican Americans living in Starr County, Texas.

Methods

We utilized data from cross-sectional studies conducted in Starr County, Texas, from 2010-2014. A Mendelian randomization approach was utilized to evaluate the associations between arsenic metabolism and type 2 diabetes prevalence using the intronic variant in the arsenic methylating gene, rs9527, as the instrumental variable for arsenic metabolism. To further assess mechanisms for diabetes pathogenesis, proportions of the urinary arsenic metabolites were employed to assess the association between arsenic metabolism and insulin resistance among participants without diabetes. Urinary biomarkers of arsenic metabolites were modeled as individual proportions of the total. Arsenic metabolism was evaluated both with a static outcome of insulin resistance, homeostatic measure of assessment (HOMA-IR), and a dynamic measure of insulin sensitivity, Matsuda Index.

Results

Among 475 Mexican American participants from Starr County, higher metabolism capacity for arsenic is associated with higher diabetes prevalence driven by worse insulin resistance. Presence of the minor T allele of rs9527 is independently associated with an increase in the proportion of monomethylated arsenic (MMA%) and is associated with an odds ratio of 0.50 (95% CI: 0.24, 0.90) for type 2 diabetes. This association was conserved after potential covariate adjustment. Furthermore, among participants without type 2 diabetes, the highest quartile of MMA% was associated with 22% (95% CI: -33.5%, -9.07%) lower HOMA-IR and 56% (95% CI: 28.3%, 91.3%) higher Matsuda Index for insulin sensitivity.

Conclusions

Arsenic metabolism capacity, indicated by a lower proportion of monomethylated arsenic, is associated with increased diabetes prevalence driven by an insulin resistant phenotype among Mexican Americans living in Starr County, Texas.

The Relationship of Arsenic Exposure with Hypertension and Wide Pulse Pressure: Preliminary Evidence from Coal-Burning Arsenicosis Population in Southwest China

Evidence from epidemiological studies suggests that chronic arsenic exposure may be associated with a higher incidence of hypertension in the population. However, the effect of arsenic exposure on blood pressure remains unexplored in different populations, regions, and regarding arsenic biomarkers. This study investigated 233 arsenicosis patients and 84 participants from a non-arsenic-exposed area to explore the relationship between arsenic exposure and blood pressure and the occurrence of hypertension and wide pulse pressure (WPP) in patients with coal-burning arsenicosis. The results show that arsenic exposure is related to an increased incidence of hypertension and WPP in the arsenicosis population, primarily due to an induced increase in systolic blood pressure (SBP) and pulse pressure (PP) (OR = 1.47, 1.65, all p < 0.05). The dose-effect relationships between monomethylated arsenicals (MMA), trivalent arsenic (As³⁺), hypertension, and WWP were characterized following trend analyses (all p-trend < 0.05) in the coal-burning arsenicosis population. After adjusting for age, gender, body mass index (BMI), smoking, and alcohol usage, compared with low-level exposure, the high level of MMA exposure increases the risk of hypertension by 1.99 times (CI: 1.04-3.80) and the WPP by 2.42 times (CI: 1.23-4.72). Similarly, the high level of As³⁺ exposure increases the hypertension risk by 3.68 times (CI: 1.86-7.30) and the WPP by 3.84 times (CI: 1.93-7.64). Together, the results revealed that urinary MMA and As³⁺ levels are mainly associated with increased SBP and induce a higher incidence of hypertension and WPP. This study provides preliminary population evidence that cardiovascular-related adverse events such as hypertension and WPP ought to be noticed in the coal-burning arsenicosis population.

Strengthening Causal Inference in Exposomics Research: Application of Genetic Data and Methods

Advances in technologies to measure a broad set of exposures have led to a range of exposome research efforts. Yet, these efforts have insufficiently integrated methods that incorporate genetic data to strengthen causal inference, despite evidence that many exposome-associated phenotypes are heritable. Objective: We demonstrate how integration of methods and study designs that incorporate genetic data can strengthen causal inference in exposomics research by helping address six challenges: reverse causation and unmeasured confounding, comprehensive examination of phenotypic effects, low efficiency, replication, multilevel data integration, and characterization of tissue-specific effects. Examples are drawn from studies of biomarkers and health behaviors, exposure domains where the causal inference methods we describe are most often applied. Discussion: Technological, computational, and statistical advances in genotyping, imputation, and analysis, combined with broad data sharing and cross-study collaborations, offer multiple opportunities to strengthen causal inference in exposomics research. Full application of these opportunities will require an expanded understanding of genetic variants that predict exposome phenotypes as well as an appreciation that the utility of genetic variants for causal inference will vary by exposure and may depend on large sample sizes. However, several of these challenges can be addressed through international scientific collaborations that prioritize data sharing. Ultimately, we anticipate that efforts to better integrate methods that incorporate genetic data will extend the reach of exposomics research by helping address the challenges of comprehensively measuring the exposome and its health effects across studies, the life course, and in varied contexts and diverse populations. https://doi.org/10.1289/EHP9098.

Relationship Analysis of Inorganic Arsenic Exposure and Metabolic Syndrome Based on Propensity Score Matching in Xinjiang, China

PURPOSE

The role of inorganic arsenic (iAs) in the risk of metabolic syndrome (MetS) remains unclear. This investigation focused on the effect of iAs exposure on MetS and whether the results are consistent in different subgroups.

PATIENTS AND METHODS

The present study was conducted on 629 men and 616 women aged 35-70 years and living in Xinjiang Uygur Autonomous Region, China. The 1:1 propensity score matching (PSM) was adopted to regulate the confounding factors, and the multivariate logistic regression was performed to assess the relationship between urinary iAs and MetS.

RESULTS

The median content of urinary iAs was examined as 2.20 μg/dL (interquartile range: 1.30-3.20 μg/dL), and the MetS prevalence reached 23.69% (295 cases/950 participants). After the confounding factors were adjusted, the ORs (95% CIs) for MetS from the minimal to the maximum urinary iAs quartiles reached 1.171 (0.736,1.863), 1.568 (1.008, 2.440) and 2.011 (1.296, 3.120), respectively (referencing 1.00) (P for trend=0.001). After the PSM, the urinary iAs content still plays a potential prediction role in MetS (P for trend=0.011). In addition, as revealed from the subgroup analysis, the urinary iAs content was a predictor of MetS in the female patients, whereas it did not serve as a significant predictor of MetS in the male patients (P for interaction<0.05).

CONCLUSION

The increased urinary iAs content was associated with the increased prevalence of MetS in Chinese population. More attention should be paid to female urinary iAs content to avoid the high prevalence of MetS.

A review of environmental metabolism disrupting chemicals and effect biomarkers associating disease risks: Where exposomics meets metabolomics

Humans are exposed to an ever-increasing number of environmental toxicants, some of which have gradually been elucidated to be important risk factors for metabolic diseases, such as diabetes and obesity. These metabolism-sensitive diseases typically occur when key metabolic and signaling pathways were disrupted, which can be influenced by the exposure to contaminants such as endocrine disrupting chemicals (EDCs), along with genetic and lifestyle factors. This promotes the concept and research on environmental metabolism disrupting chemicals (MDCs). In addition, identifying endogenous biochemical markers of effect linked to disease states is becoming an important tool to screen the biological targets following environmental contaminant exposure, as well as to provide an overview of toxicity risk assessment. As such, the current review aims to contribute to the further understanding of exposome and human health and disease by characterizing environmental exposure and effect metabolic biomarkers. We summarized MDC-associated metabolic biomarkers in laboratory animal and human cohort studies using high throughput targeted and nontargeted metabolomics techniques. Contaminants including heavy metals and organohalogen compounds, especially EDCs, have been repetitively associated with metabolic disorders, whereas emerging contaminants such as perfluoroalkyl substances and microplastics have also been found to disrupt metabolism. In addition, we found major limitations in the effective identification of metabolic biomarkers especially in human studies, toxicological research on the mixed effect of environmental exposure has also been insufficient compared to the research on single chemicals. Thus, it is timely to call for research efforts dedicated to the study of combined effect and metabolic alterations for the better assessment of exposomic toxicology and health risks. Moreover, advanced computational and prediction tools, further validation of metabolic biomarkers, as well as systematic and integrative investigations are also needed in order to reliably identify novel biomarkers and elucidate toxicity mechanisms, and to further utilize exposome and metabolome profiling in public health and safety management.

Arsenic exposure and metabolism in relation to blood pressure changes in pregnant women

Arsenic is concerned with cardiovascular diseases including hypertension, atherosclerosis, and endothelial dysfunction. However, what effects the arsenic exposure and the arsenic metabolism have on hypertensive disorders of pregnancy (HDP) and blood pressure changes during pregnancy remain largely unknown. Our goal was to assess the associations of arsenic exposure and arsenic metabolism with HDP and blood pressure changes in pregnant women through a prospective birth cohort study. A total of 1038 women who were pregnant (52 HDP, 986 non-HDP participants) were included. Arsenic species of spot urine samples collected at three trimesters were measured, which included inorganic arsenic (iAs), monomethylated arsenic (MMA), and dimethylated arsenic (DMA). Arsenic metabolism was evaluated as the percentages of iAs, MMA, and DMA respectively (i.e., iAs%, MMA%, and DMA%). Outcomes were HDP and systolic, diastolic, and mean arterial pressure changes during pregnancy. We employed mixed linear models to investigate the relationships between arsenic exposure and arsenic metabolism with changes in blood pressure during pregnancy. Poisson regression with a robust error variance with generalized estimating equations (GEE) estimation was used so that the associations of arsenic exposure and arsenic metabolism with HDP could be estimated. In this study, there was a significant relationship between the concentrations of urinary DMA and the weekly change in systolic blood pressure (SBP) (β = -0.10; 95% CI: -0.15, -0.05), diastolic blood pressure (DBP) (β = -0.07; 95% CI: -0.11, -0.02) and mean arterial pressure (MAP) (β = -0.08; 95% CI: -0.12, -0.04). Higher DMA% was accompanied with lesser weekly increase in SBP (β = -0.05; 95% CI: -0.10, 0.00), DBP (β = -0.06; 95% CI: -0.10, -0.01) and MAP (β = -0.06; 95% CI: -0.09, -0.01) during pregnancy. There was a positive association with the highest tertile of iAs% and weekly change of SBP (β = 0.08; 95% CI: 0.03, 0.13), DBP (β = 0.07; 95% CI: 0.03, 0.11) and MAP (β = 0.07; 95% CI: 0.03, 0.11). No association was found between each arsenic specie and arsenic metabolism marker in the first trimester and risk of HDP. Arsenic exposure and arsenic metabolism during pregnancy potentially change blood pressure of pregnant women. These findings may be significance as even modest elevation of blood pressure can increase the risk of cardiovascular disease.

Essential hypertension in patients exposed to high-arsenic exposed areas in western China: Genetic susceptibility and urinary arsenic metabolism characteristics

OBJECTIVE

To clarify the urinary arsenic metabolism characteristics in individuals with essential hypertension and to analyze the relationship between lipid metabolism gene polymorphisms and susceptibility to essential hypertension in individuals in high-arsenic areas in western China.

METHODS

A case-control study was conducted and involved individuals exposed to high arsenic levels (in this study, the arsenic content in the pressurized well water was 0-510.2 μg/L, and that in the mechanical well water was 167 μg/L) in two adjacent high-arsenic areas in Shanxi Province and the Inner Mongolia Autonomous Region, China. A total of 699 samples were collected, including 192 case samples (patients with hypertension) and 507 control samples (no hypertension). Blood pressure measurement data obtained from an epidemiological survey were used to determine whether the subjects had hypertension, and a logistic regression model was used to analyze the association between lipid metabolism gene polymorphisms and hypertension susceptibility. Blood and urine samples were collected based on epidemiological methods, single nucleotide polymorphisms (SNPs) were genotyped using a SNPscan™ multiple SNP typing kit, and urinary arsenic concentrations were determined using the hydride generation atomic fluorescence method (HG-AFS).

RESULTS

ADIPOQ/rs266729 was the dominant genetic model [(GC + GG) vs CC = 0.686:1, 95 % CI = 0.478-0.983], and FABP2/rs1799883 was the recessive genetic model [TT vs (CC + TC) = 1.690:1, 95 % CI = 1.014-2.816]. The distribution of the urinary arsenic secondary methylation ratio (SMR) [dimethylated arsenic (DMA)/monomethylated arsenic (MMA)] was different between hypertensive patients and controls.

CONCLUSION

ADIPOQ/rs266729 and FABP2/rs1799883 polymorphisms affect susceptibility to essential hypertension in individuals exposed to high levels of arsenic; there was a clear difference in the urinary arsenic metabolism pattern between hypertensive patients and controls.

Contribution of diet and other factors for urinary concentrations of total arsenic and arsenic species: data for US children, adolescents, and adults

A comprehensive analysis of the associations between the consumptions of 17 food products with urinary concentrations of arsenobetaine, total arsenic, arsenous acid, dimethylarsinic acid (UDMA), monomethylarsonic acid (UMMA), and total inorganic arsenic for US children aged 3-5 years (N = 439), children aged 6-11 years (N = 2139), adolescents aged 12-19 years (N = 2434), and adults aged >= 20 years (N = 10902) was conducted. Data from National Health and Nutrition Examination Survey for 2005-2016 were used for this study. Concentrations of arsenobetaine were as much as > 15 times higher among consumers of fish/shellfish than non-consumers for children aged 6-11 years, > 12 times higher for children aged 3-5 years, > 13 times higher for adolescents, and > 7 times higher for adults. Consumption of rice as opposed to non-consumption of rice was associated with as much as 36.5% higher concentrations of total arsenic, 12.7% higher concentrations of arsenous acid, 43.9% higher concentrations of UDMA, 18.2% higher concentrations of UMMA, and 14.1% higher concentrations of total inorganic arsenic. Thus, consumption of fish/shell fish and rice was associated with higher concentrations of organic/inorganic arsenic. In addition, consumption of alcohol was also found to be associated with higher concentrations of organic/inorganic arsenic. However, consumption of milk and milk products, vegetables, organ and other meats, and nutritional drinks was found to be associated with lower concentrations of organic/inorganic arsenic. Thus, while consumption of several foods is associated with higher concentrations of arsenic, there are also foods whose consumption is associated with decreased concentrations of arsenic. Further studies are needed to identify foods that may lead to decreased concentrations of arsenic and as such arsenic toxicity.

Mendelian randomization analysis of arsenic metabolism and pulmonary function within the Hispanic Community Health Study/Study of Latinos

Arsenic exposure has been linked to poor pulmonary function, and inefficient arsenic metabolizers may be at increased risk. Dietary rice has recently been identified as a possible substantial route of exposure to arsenic, and it remains unknown whether it can provide a sufficient level of exposure to affect pulmonary function in inefficient metabolizers. Within 12,609 participants of HCHS/SOL, asthma diagnoses and spirometry-based measures of pulmonary function were assessed, and rice consumption was inferred from grain intake via a food frequency questionnaire. After stratifying by smoking history, the relationship between arsenic metabolism efficiency [percentages of inorganic arsenic (%iAs), monomethylarsenate (%MMA), and dimethylarsinate (%DMA) species in urine] and the measures of pulmonary function were estimated in a two-sample Mendelian randomization approach (genotype information from an Illumina HumanOmni2.5-8v1-1 array), focusing on participants with high inferred rice consumption. Among never-smoking high inferred consumers of rice (n = 1395), inefficient metabolism was associated with past asthma diagnosis and forced vital capacity below the lower limit of normal (LLN) (OR 1.40, p = 0.0212 and OR 1.42, p = 0.0072, respectively, for each percentage-point increase in %iAs; OR 1.26, p = 0.0240 and OR 1.24, p = 0.0193 for %MMA; OR 0.87, p = 0.0209 and OR 0.87, p = 0.0123 for the marker of efficient metabolism, %DMA). Among ever-smoking high inferred consumers of rice (n = 1127), inefficient metabolism was associated with peak expiratory flow below LLN (OR 1.54, p = 0.0108/percentage-point increase in %iAs, OR 1.37, p = 0.0097 for %MMA, and OR 0.83, p = 0.0093 for %DMA). Less efficient arsenic metabolism was associated with indicators of pulmonary dysfunction among those with high inferred rice consumption, suggesting that reductions in dietary arsenic could improve respiratory health.

Machine Learning Models of Arsenic in Private Wells Throughout the Conterminous United States As a Tool for Exposure Assessment in Human Health Studies

Arsenic from geologic sources is widespread in groundwater within the United States (U.S.). In several areas, groundwater arsenic concentrations exceed the U.S. Environmental Protection Agency maximum contaminant level of 10 μg per liter (μg/L). However, this standard applies only to public-supply drinking water and not to private-supply, which is not federally regulated and is rarely monitored. As a result, arsenic exposure from private wells is a potentially substantial, but largely hidden, public health concern. Machine learning models using boosted regression trees (BRT) and random forest classification (RFC) techniques were developed to estimate probabilities and concentration ranges of arsenic in private wells throughout the conterminous U.S. Three BRT models were fit separately to estimate the probability of private well arsenic concentrations exceeding 1, 5, or 10 μg/L whereas the RFC model estimates the most probable category (≤5, >5 to ≤10, or >10 μg/L). Overall, the models perform best at identifying areas with low concentrations of arsenic in private wells. The BRT 10 μg/L model estimates for testing data have an overall accuracy of 91.2%, sensitivity of 33.9%, and specificity of 98.2%. Influential variables identified across all models included average annual precipitation and soil geochemistry. Models were developed in collaboration with public health experts to support U.S.-based studies focused on health effects from arsenic exposure.

Concentrations of selected arsenic species in urine across various stages of renal function including hyperfiltration

Data (N = 10,590) from National Health and Nutrition Examination Survey for 2005-2016 for US adults aged ≥ 20 years were analyzed to study how concentrations of arsenobetaine (UAB), monomethylarsonic acid (UMMA), dimethylarsenic acid (UDMA), and total arsenic (UAS) in urine vary across the stages of renal function (RF). Data were analyzed over RF-1A (eGFR > 110 mL/min/1.73 m²), RF-1B (eGFR between 90 and 110 mL/min/1.73 m²), RF-2 (eGFR between 60 and 90 mL/min/1.73 m²), RF-3A (eGFR between 45 and 60 mL/min/1.73 m²), and RF-3B/4 (eGFR between 15 and 45 mL/min/1.73 m²). Adjusted geometric mean (AGM) concentrations of the total population, males, and females for UAS, UAB, and UDMA were observed to follow inverted U-shaped distributions with points of inflection located at RF-3A. For example, adjusted concentrations for the total population for UAS were 8.8, 8.8, 9.5, 11.7, and 9.6 μg/L for those in RF-1A, RF-1B, RF-2, RF-3A, and RF-3B/4 respectively. While statistically significant differences were only occasionally observed, males, in general, had lower AGMs than females for UAS and UDMA, but females had lower AGMs than males for UAB. Among the various racial/ethnic groups, non-Hispanic whites had the lowest adjusted concentrations of all four arsenic variables. Adjusted levels of all four arsenic variables were observed to decrease over survey years of 2005-2006 through 2015-2016. However, statistical significance was not necessarily reached for all RF stages. Smoking was associated with reduced levels of four arsenic variables over RF-1A through RF-2. Diabetes was associated with increased levels of UMMA and UDMA at RF-2.

Adipose tissue concentrations of arsenic, nickel, lead, tin, and titanium in adults from GraMo cohort in Southern Spain: An exploratory study

BACKGROUND

Adipose tissue has been acknowledged as a potential target for obesogenic pollutants, including toxic metal(loid)s. However, the presence of these chemicals in the adipose tissue has been poorly characterized.

OBJECTIVE

To examine the distributions of adipose tissue concentrations of five toxic metal(loid)s (i.e., arsenic [As], nickel [Ni], lead [Pb], tin [Sn], and titanium [Ti]) in adults, and potential socio-demographic and lifestyle factors associated with metal(loid) concentrations.

METHODS

The study population consisted of a subsample of 228 subjects from GraMo cohort in Southern Spain (N = 387). Adipose tissue samples were intra-operatively collected from adults recruited in 2003-2004 in two public hospitals, and concentrations of metal(loid)s in adipose tissue were analyzed in 2015 by High-Resolution Inductively Coupled Plasma Mass Spectrometry. Data on socio-demographic and lifestyle factors were obtained by baseline questionnaire completion. Linear and multinomial regression was used to identify factors associated with metal(loid) levels.

RESULTS

Ni, Pb, Sn, and Ti were detected in all adipose tissue samples, and As in 51% of them. Ni was the metal showing the highest median concentration (0.56 μg/g), followed by Ti (0.31 μg/g), Pb (0.08 μg/g), Sn (0.06 μg/g), and As (0.003 μg/g). Predictors of As levels included area of residence, social class, and oily fish intake; for Ni: area of residence and consumption of cheese, meat, eggs, and canned food; for Pb: vegetables intake and industrial occupation; for Sn: age, body mass index, and consumption of lean fish, eggs, and milk; and cheese intake for Ti. Some of these predictors were sex-specific, particularly those regarding dietary intake.

CONCLUSIONS

This exploratory study provides the first evidence of the occurrence of Ni, Pb, Sn, Ti, and As in adipose tissue from adult population, and highlights the potential of this tissue as a biological matrix for studying exposure levels and chronic health effects of toxic metal(loid)s.

Rice Intake and Emerging Concerns on Arsenic in Rice: a Review of the Human Evidence and Methodologic Challenges

PURPOSE OF REVIEW

Rice is a major staple food worldwide and a dietary source of arsenic. We therefore summarized the state of the epidemiologic evidence on whether rice consumption relates to health outcomes associated with arsenic exposure.

RECENT FINDINGS

While epidemiologic studies have reported that higher rice consumption may increase the risk of certain chronic conditions, i.e., type 2 diabetes, most did not consider specific constituents of rice or other sources of arsenic exposure. Studies that examined rice intake stratified by water concentrations of arsenic found evidence of increasing trends in cardiovascular disease risk, skin lesions, and squamous cell skin cancers and bladder cancer associated with higher rice consumption. Further studies are needed to understand the health impacts of arsenic exposure from rice consumption taking into account all sources of rice intake and potential confounding by other dietary constituents or contaminants and arsenic exposure from sources such as water.