等毒性配比法研究甲醛与重金属的联合毒性效应

正分别测定甲醛与4种重金属的急性毒性EC50,并对等毒性配比条件下甲醛与4种重金属的二元混合体系的联合毒性进行研究,采用毒性单位法和相加指数法对其联合作用进行评价。结果表明,5种物质的急性毒性为Pb(Ⅱ)Zn(Ⅱ)Cu(Ⅱ)甲醛Cd(Ⅱ)。联合毒性结果显示,4种二元混合体系的联合作用方式类似,其中毒性单位法的评价结果均为部分相加作用,相加指数法均为拮抗作用,这主要是由于2种评价方法的评价标准等级划分范围不同造成的。     

不同方法对联合毒性作用的评价

采用毒性单位法(M)、相加指数法(AI)、混合毒性指数法(MTI)、相似性参数法(λ)和等效线图法评价二元混合物的联合毒性，并分析了各方法的优缺点，同时对混合毒性指数法中M0的计算进行了修正。     

固定毒性配比法研究重金属与土霉素的联合毒性

为了研究重金属与药物二元混合体系的联合毒性,选择3种重金属盐CdCl_2、K2Cr_2O_7、CuSO_4与土霉素(OTC)为混合物组分,以固定毒性配比法构建3组二元混合物体系:CdCl_2-OTC、K2Cr_2O_7-OTC和CuSO4-OTC。固定的毒性配比分别为4∶1、3∶2、1∶1、2∶3和1∶4。应用微板毒性分析法,测定单一物质及二元混合物对费氏弧菌(Vibrio.fishceri)的联合毒性,通过比较实验数据与浓度加和模型预测值,分析混合物的毒性作用方式。结果表明:依据单一物质EC50值,它们的毒性从大到小依次为:CuSO_4CdCl_2K_2Cr_2O_7OTC;重金属与OTC二元混合体系均表现出拮抗作用;在选取的毒性配比范围内,CdCl2-OTC和K_2Cr_2O_7-OTC混合物的拮抗作用强弱在一定范围内浮动,并不随毒性配比的变化而变化。然而,CuSO_4-OTC混合物中,联合毒性随着OTC比例的增大,作用方式由显著拮抗向加和趋近。这说明混合物中各组分的浓度组成影响CuSO_4-OTC混合物对V.fishceri的联合作用方式,但是CdCl_2-OTC和K_2Cr_2O_7-OTC并不受影响。     

基于枯草芽孢杆菌的CellSense生物传感器的重金属联合毒性分析

采用聚碳酸醑膜直接固定法制备了基于枯草芽孢杆菌(Bacillus Subtilis)的CellSense生物传感器,分别测定了Cd2+、Cu2+、Zn2+和Cr(Ⅵ)对Bacillus Subtilis的单一毒性,以及等毒性配比和等浓度配比下二元混合体系的联合毒性,并用相加指数法对其联合毒性效应进行了评价.结果表明,基于对数生长后期和稳定期的Bacillus Subtilis的CellSense生物传感器具有良好的毒性分析性能;2种联合毒性评价方法下4种重金属离子二元混合体系的联合作用结果一致,均表现出不同程度的拮抗作用.     

等浓度配比法研究苯酚、硝基苯和间硝基苯胺对发光菌的联合毒性作用

分别测定了苯酚、硝基苯和间硝基苯胺对发光菌的单一毒性,以及等浓度配比和等毒性配比的二元及三元混合体系的联合毒性,采用相加指数法对其联合效应进行了评价。结果表明,等浓度比和等毒性比混合体系的联合作用结果一致:苯酚+间硝基苯胺二元体系为协同作用,其他各体系为相加作用。为简化联合毒性实验方法,建议在研究相关系列化合物的联合毒性作用机制中,可采用等浓度配比方法。     

等浓度配比法研究苯酚、硝基苯和问硝基苯胺对发光菌的联合毒性作用

分别测定了苯酚、硝基苯和间硝基苯胺对发光菌的单一毒性，以及等浓度配比和等毒性配比的二元及三元混合体系的联合毒性，采用相加指数法对其联合效应进行了评价。结果表明，等浓度比和等毒性比混合体系的联合作用结果一致：苯酚＋间硝基苯胺二元体系为协同作用，其他各体系为相加作用。为简化联合毒性实验方法，建议在研究相关系列化合物的联合毒性作用机制中，可采用等浓度配比方法。     

城市污水石灰法深度处理工艺中有毒物质的变化规律

分别采用7-乙氧基异酚恶唑酮-脱乙基酶(EROD)活性测定法,重组人激素受体基因的酵母测试和Q67发光菌试验方法,对北京市某生活污水处理厂的进水、二沉出水以及经过石灰法深度处理后的出水中的类二恶英物质、类雌激素物质和急性毒性物质进行了分析.进水中的三类生物毒性效应物质中的急性毒性物质,可通过活性污泥法基本去除,而对类雌激素物质和类二恶英物质的去除率分别为76%和52%.经过石灰沉淀法的深度处理后,可使上述两类物质的总去除率达到95%和68%.出水中的雌激素当量水平与欧洲国家污水处理厂出水水平相当,而类二恶英物质的总浓度低于美国EPA饮用水中二恶英的最大允许浓度.展示了生物毒性测试方法在排水生态风险和工艺评价方面的应用潜力.     

基于GCM_CB模型的土壤重金属污染评价

灰色聚类法已经运用于土壤重金属污染评价中,然而此法在确定聚类权重时仅考虑重金属浓度,忽略了衡量重金属毒性强弱的重要指标生物毒性指数。为了更客观和准确地反映土壤重金属的污染程度,将生物毒性指数引入到聚类指标权重中,构建GCM_CB(grey clustering method_concentration and biotoxicity)土壤重金属污染评价模型。通过对华东某地区的10个区域土壤重金属污染进行分析评价,并与常用评价方法对比研究,表明:其多数样点的评价结果基本一致,但针对样品4和样品9中的元素Hg,因其强毒性,使得评价等级由I级定为II级,从而提高了评价方法的灵敏度,更加符合该区域的实际土壤污染情况。     

城市污水石灰法深度处理工艺中有毒物质的变化规律

分别采用7-乙氧基异酚恶唑酮．脱乙基酶（EROD）活性测定法，重组人激素受体基因的酵母测试和Q67发光菌试验方法，对北京市某生活污水处理厂的进水、二沉出水以及经过石灰法深度处理后的出水中的类二恶英物质、类雌激素物质和急性毒性物质进行了分析。进水中的三类生物毒性效应物质中的急性毒性物质，可通过活性污泥法基本去除，而对类雌激素物质和类二恶英物质的去除率分别为76％和52％。经过石灰沉淀法的深度处理后，可使上述两类物质的总去除率达到95％和68％。出水中的雌激素当量水平与欧洲国家污水处理厂出水水平相当，而类二恶英物质的总浓度低于美国EPA饮用水中二恶英的最大允许浓度。展示了生物毒性测试方法在排水生态风险和工艺评价方面的应用潜力。     

抗生素类污染物对活性污泥生物毒性测定方法的筛选与评价

尽管衡量化学物质生物毒性的标准方法很多,但关于环境中抗生素类污染物的生物毒性及其对污泥活性影响的科学数据较少。以磺胺和四环素两类作用机理和作用谱带不同的抗生素为研究对象,分别用发光细菌法、脱氢酶活性法、生长抑制法及呼吸速率法进行了抗生素类污染物生物毒性测定方法的筛选与评价。结果表明,发光细菌标准方法中30min的作用时间太短,延长作用时间不仅导致各种抗生素的EC50值大幅度降低,同时毒性排列顺序也发生了改变;以活性污泥为对象的脱氢酶活性和呼吸速率抑制实验的EC50值与抗生素类物质对敏感致病菌的MICs相比异常高,不适宜于作为单独方法准确评估抗生素类污染物的生物毒性。生长抑制实验中,活性污泥混合菌种增殖生长对磺胺类抗生素敏感,而假单胞杆菌对四环素类抗生素敏感。不同方法测定抗生素毒性的灵敏度顺序是发光细菌(24 h)>生长抑制(7 h)>呼吸速率(24 h)>脱氢酶活性(24 h)。用标准方法评价抗生素类污染物的生物毒性,可能导致对抗生素排放到水环境中所带来的风险估计不足。     

Novel approach to predicting hormetic effects of antibiotic mixtures on Vibrio fischeri

The determination of the hormetic effects of a mixture is quite difficult because of the moderate simulation and the complexity of measurement in low doses. In the present study, two typical models for mixture toxicity prediction, concentration additive (CA) and independent action (IA), were used to predict the hormetic effects of mixtures. The predictive power of those models was validated by the hormetic effects (24-h exposure) of antibiotic’s binary mixtures to Vibrio fischeri. The results showed that CA and IA were unable to predict the hormetic dose-response of mixture, especially those of the interactive mixtures. As an alternative, a novel model, which was named as “six-point” and developed based on the quantitative features in the determined dose-response curve and on the Quantitative Structure Activity Relationships (QSARs) approach, was proposed for predicting the hormetic effects of mixtures in low dose. The results indicated that the “six-point” model can accurately predict the mixture hormetic effects in low dose, not only for non-interactive mixtures but also for interactive mixtures. Therefore, the “six-point” model is a powerful tool to predict the mixture hormetic effects at low dose, and may offer an important approach in the environment risk assessment of mixtures.     

A comparison of mixture toxicity assessment: examining the chronic toxicity of atrazine, permethrin and chlorothalonil in mixtures to Ceriodaphnia cf. dubia

Pesticides predominantly occur in aquatic ecosystems as mixtures of varying complexity, yet relatively few studies have examined the toxicity of pesticide mixtures. Atrazine, chlorothalonil and permethrin are widely used pesticides that have different modes of action. This study examined the chronic toxicities (7-d reproductive impairment) of these pesticides in binary and ternary mixtures to the freshwater cladoceran Ceriodaphnia cf. dubia. The toxicity of the mixtures was compared to that predicted by the independent action (IA) model for mixtures, as this is the most appropriate model for chemicals with different modes of action. Following this they were compared to the toxicity predicted by the concentration addition (CA) model for mixtures. According to the IA model, the toxicity of the chlorothalonil plus atrazine mixture conformed to antagonism, while that of chlorothalonil and permethrin conformed to synergism. The toxicity of the atrazine and permethrin mixture as well as the ternary mixture conformed to IA implying there was either no interaction between the components of these mixtures and/or in the case of the ternary mixture the interactions cancelled each other out to result in IA. The synergistic and antagonistic mixtures deviated from IA by factors greater than 3 and less than 2.5, respectively. When the toxicity of the mixtures was compared to the predictions of the CA model, the binary mixture of chlorothalonil plus atrazine, permethrin plus atrazine and the ternary mixture all conformed to antagonism, while the binary mixture of chlorothalonil plus permethrin conformed to CA. Using the CA model provided estimates of mixture toxicity that did not markedly underestimate the measured toxicity, unlike the IA model, and therefore the CA model is the most suitable to use in ecological risk assessments of these pesticides.     

Prediction of mixture toxicity with its total hydrophobicity

Based on the C18 Empore disk/water partition coefficient of a mixture, quantitative structure-activity relationships (QSARs) are presented, which are used to predict the toxicity of mixed halogenated benzenes to P. phosphoreum. The predicted toxicity of 10 other related mixtures based on the QSAR model, agree well with the observed data with r2 = 0.973, SE = 0.113 and F = 287.785 at a level of significance P < 0.0001. The joint effect of these chemicals is simple similar action and the toxicity of the mixtures can be predicted from total hydrophobicity and is independent of hydrophobicity of the components or the ratio of the individual chemicals.     

Influence factors of multicomponent mixtures containing reactive chemicals and their joint effects

Organic chemicals usually coexist as a mixture in the environment, and the mixture toxicity of organic chemicals has received increased attention. However, research regarding the joint effects of reactive chemicals is lacking. In this study, we examined two kinds of reactive chemicals, cyanogenic toxicants and aldehydes and determined their joint effects on Photobacterium phosphoreum. Three factors were found to influence the joint effects of multicomponent mixtures containing reactive chemicals, including the number of components, the dominating components and the toxic ratios. With an increased number of components, the synergistic or antagonistic effects (interactions) will weaken to the additive effects (non-interactions) if the added component cannot yield a much stronger joint effect with an existing component. Contrarily, the joint effect of the mixture may become stronger instead of weaker if the added components can yield a much stronger joint effect than the existing joint effect of the multicomponent mixture. The components that yield the strongest interactions in their binary mixture can be considered the dominating components. These components contribute more to the interactions of multicomponent mixtures than other components. Moreover, the toxic ratios also influence the joint effects of the mixtures. This study provides an insight into what are the main factors and how they influence the joint effects of multicomponent mixtures containing reactive chemicals, and thus, the findings are beneficial to the study of mixture toxicology.     

A novel method dependent only on the mixture information (MIM) for evaluating the toxicity of mixture

Compound contamination and toxicity interaction necessitate the development of models that have an insight into the combined toxicity of chemicals. In this paper, a novel and simple model dependent only on the mixture information (MIM), was developed. Firstly, the concentration-response data of seven groups of binary and multi-component (pseudo-binary) mixtures with different mixture ratios to Vibrio qinghaiensis sp.-Q67 were determined using the microplate toxicity analysis. Then, a desirable non-linear function was selected to fit the data. It was found that there are good linear correlations between the location parameter (α) and mixture ratio (p) of a component and between the steepness (β) and p. Based on the correlations, a mixture toxicity model independent of pure component toxicity profiles was built. The model can be used to accurately estimate the toxicities of the seven groups of mixtures, which greatly simplified the predictive procedure of the combined toxicity.     

The interaction effects of binary mixtures of benzene and toluene on the developing heart of medaka (Oryzias latipes)

The United States Environmental Protection Agency (USEPA) has pursued the estimation of risk of adverse health effects from exposure to chemical mixtures since the early 1980s. Methods used to calculate risk estimates of mixtures were often based on single chemical information that required assumptions of dose-addition or response-addition and did not consider possible changes in response due to interaction effects among chemicals. Full factorial designs for laboratory studies can produce interactions information, but these are expensive to perform and may not provide the information needed to evaluate specific environmentally relevant mixtures. In this research, groups of Japanese medaka (Oryzias latipes) embryos were exposed to binary mixtures of benzene and toluene as well as to each of these chemicals alone. Endpoint specific dose-response models were built for the hydrocarbon mixture under an assumption of dose-additivity, using the single chemical dose-response information on benzene and toluene. The endpoints included heart rate, heart rate progression, and lethality. Results included a synergistic response for heart rate at 72 h of development, and either additivity or antagonism for all other endpoints at 96 h of development. This work uses an established statistical method to evaluate the toxicity of an environmentally relevant mixture to ascertain whether interaction effects are occurring, thus providing additional information on toxicity.     

Toxic masking and synergistic modulation of the estrogenic activity of chemical mixtures in a yeast estrogen screen (YES)

Background, aim and scope

Estrogenic and non-estrogenic chemicals typically co-occur in the environment. Interference by non-estrogenic chemicals may confound the assessment of the actual estrogenic activity of complex environmental samples. The aim of the present study was to investigate whether, in which way and how seriously the estrogenic activity of single estrogens and the observed and predicted joint action of estrogenic mixtures is influenced by toxic masking and synergistic modulation caused by non-estrogenic chemical confounders.

Materials and methods

The yeast estrogen screen (YES) was adapted so that toxicity and estrogenicity could be quantified simultaneously in one experimental run. Mercury, two organic solvents (dimethyl sulfoxide (DMSO) and 2,4-dinitroaniline), a surfactant (LAS-12) and the antibiotic cycloheximide were selected as toxic but non-estrogenic test chemicals. The confounding impact of selected concentrations of these toxicants on the estrogenic activity of the hormone 17ß-estradiol was determined by co-incubation experiments. In a second step, the impact of toxic masking and synergistic modulation on the predictability of the joint action of 17ß-estradiol, estrone and estriol mixtures by concentration addition was analysed.

Results

Each of the non-estrogenic chemicals reduced the apparent estrogenicity of both single estrogens and their mixtures if applied at high, toxic concentrations. Besides this common pattern, a highly substance- and concentration-dependent impact of the non-estrogenic toxicants was observable. The activity of 17ß-estradiol was still reduced in the presence of only low or non-toxic concentrations of 2,4-dinitroaniline and cycloheximide, which was not the case for mercury and DMSO. A clear synergistic modulation, i.e. an enhanced estrogenic activity, was induced by the presence of slightly toxic concentrations of LAS-12. The joint estrogenic activity of the mixture of estrogens was affected by toxic masking and synergistic modulation in direct proportion to the single estrogens, which allowed for an adequate adaptation of concentration addition and thus unaffected predictability of the joint estrogenicity in the presence of non-estrogenic confounders.

Discussion

The modified YES proved to be a reliable system for the simultaneous quantification of yeast toxicity and estrogen receptor activation. Experimental results substantiate the available evidence for toxic masking as a relevant phenomenon in estrogenicity assessment of complex environmental samples. Synergistic modulation of estrogenic activity by non-estrogenic confounders might be of lower importance. The concept of concentration addition is discussed as a valuable tool for estrogenicity assessment of complex mixtures, with deviations of the measured joint estrogenicity from predictions indicating the need for refined analyses.

Conclusions

Two major challenges are to be considered simultaneously for a reliable analysis of the estrogenic activity of complex mixtures: the identification of known and suspected estrogenic compounds in the sample as well as the substance- and effect-level-dependent confounding impact of non-estrogenic toxicants.

Recommendations and perspectives

The application of screening assays such as the YES to complex mixtures should be accompanied by measures that safeguard against false negative results which may be caused by non-estrogenic but toxic confounders. Simultaneous assessments of estrogenicity and toxicity are generally advisable.     

Joint action and lethal levels of toluene, ethylbenzene, and xylene on midge (Chironomus plumosus) larvae

Aquatic ecosystems are vulnerable to the exposure with petrochemicals such as toluene, ethylbenzene, and xylene (o-, m-, and p-xylene) (TEX) and their adverse effects. Considering the widespread use, occurrence, and high toxicity of TEX, the aim of this work was to investigate the differential toxicity of TEX against midge (Chironomus plumosus) larvae and reveal the joint action of binary and ternary mixtures of TEX using the predictive concentration addition model. More importantly, this research can afford the basic toxicity data and scientific reference for the establishment of water quality criteria or benchmark, water pollution control, and aquatic risk assessment. Single and joint toxic effects of TEX on C. plumosus larvae were investigated using a semi-static bioassay, and the type of joint effects of TEX was ascertained. In the single toxicant experiments, the toxicity of the three pollutants could be sequenced as ethylbenzene > xylene > toluene. Specifically, LC_50s of T, E, and X after a 48-h exposure were 64.9, 37.8, and 42.0 mg/L, respectively. In the binary mixture experiments, the interaction between toluene and ethylbenzene, ethylbenzene and xylene, and toluene and xylene was largely in conformity with partial additive or additive effect as determined by isobologram representation and toxic unit models. In the ternary mixture experiments, the interaction was basically dependent on the use of additive index and mixture toxicity index methods. However, the antagonistic and synergistic actions were not significant. Thus, the tertiary mixture interaction could be regarded as additive action. The concentration addition model could successfully predict the joint action of TEX mixtures on C. plumosus larvae. Particularly, the additive action of TEX on C. plumosus larvae can be further recommended to evaluate water quality criteria of TEX.     

Assessment of combined antiandrogenic effects of binary parabens mixtures in a yeast-based reporter assay

To date, toxicological studies of endocrine disrupting chemicals (EDCs) have typically focused on single chemical exposures and associated effects. However, exposure to EDCs mixtures in the environment is common. Antiandrogens represent a group of EDCs, which draw increasing attention due to their resultant demasculinization and sexual disruption of aquatic organisms. Although there are a number of in vivo and in vitro studies investigating the combined effects of antiandrogen mixtures, these studies are mainly on selected model compounds such as flutamide, procymidone, and vinclozolin. The aim of the present study is to investigate the combined antiandrogenic effects of parabens, which are widely used antiandrogens in industrial and domestic commodities. A yeast-based human androgen receptor (hAR) assay (YAS) was applied to assess the antiandrogenic activities of n-propylparaben (nPrP), iso-propylparaben (iPrP), methylparaben (MeP), and 4-n-pentylphenol (PeP), as well as the binary mixtures of nPrP with each of the other three antiandrogens. All of the four compounds could exhibit antiandrogenic activity via the hAR. A linear interaction model was applied to quantitatively analyze the interaction between nPrP and each of the other three antiandrogens. The isoboles method was modified to show the variation of combined effects as the concentrations of mixed antiandrogens were changed. Graphs were constructed to show isoeffective curves of three binary mixtures based on the fitted linear interaction model and to evaluate the interaction of the mixed antiandrogens (synergism or antagonism). The combined effect of equimolar combinations of the three mixtures was also considered with the nonlinear isoboles method. The main effect parameters and interaction effect parameters in the linear interaction models of the three mixtures were different from zero. The results showed that any two antiandrogens in their binary mixtures tended to exert equal antiandrogenic activity in the linear concentration ranges. The antiandrogenicity of the binary mixture and the concentration of nPrP were fitted to a sigmoidal model if the concentrations of the other antiandrogens (iPrP, MeP, and PeP) in the mixture were lower than the AR saturation concentrations. Some concave isoboles above the additivity line appeared in all the three mixtures. There were some synergistic effects of the binary mixture of nPrP and MeP at low concentrations in the linear concentration ranges. Interesting, when the antiandrogens concentrations approached the saturation, the interaction between chemicals were antagonistic for all the three mixtures tested. When the toxicity of the three mixtures was assessed using nonlinear isoboles, only antagonism was observed for equimolar combinations of nPrP and iPrP as the concentrations were increased from the no-observed-effect-concentration (NOEC) to effective concentration of 80 %. In addition, the interactions were changed from synergistic to antagonistic as effective concentrations were increased in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP. The combined effects of three binary antiandrogens mixtures in the linear ranges were successfully evaluated by curve fitting and isoboles. The combined effects of specific binary mixtures varied depending on the concentrations of the chemicals in the mixtures. At low concentrations in the linear concentration ranges, there was synergistic interaction existing in the binary mixture of nPrP and MeP. The interaction tended to be antagonistic as the antiandrogens approached saturation concentrations in mixtures of nPrP with each of the other three antiandrogens. The synergistic interaction was also found in the equimolar combinations of nPrP and MeP, as well as nPrP and PeP, at low concentrations with another method of nonlinear isoboles. The mixture activities of binary antiandrogens had a tendency towards antagonism at high concentrations and synergism at low concentrations.