低浓度下4个取代苯污染物与硝酸铅的混合对发光菌的联合毒性

多种污染物混合特别是低浓度下的混合对生物的联合毒性是生态毒理学研究的热点之一。选择了3类污染物苯酚、间甲基苯酚、苯胺、对硝基苯胺、硝酸铅，采用美国微板光度计测定了它们对发光菌青海弧菌．Q67（Vibrio-qinghaiensissp-Q67）的单一及联合毒性。应用非线性拟合技术模拟了这5种物质及其混合物的剂量．效应曲线，硝酸铅可用Logit模型模拟，其它4个物质能用Weibull模型准确描述，所有拟合相关系数在0．98以上，均方根误差在O．02以下。根据纯物质的EC50值，获得这5个物质的毒性强弱顺序：硝酸铅〉对硝基苯胺〉间甲基苯酚〉苯酚〉苯胺。混合实验设计了各物质在EC50、EC1、无观察效应浓度（noobserved effectcon centration，NOEC）比例的混合。用浓度加和（doseaddition，DA）和独立作用模型（independentaction，IA）对混合物毒性进行预测。IA基本准确预测了这5个物质在各自EC50混合的毒性。DA与队模型都稍微过高地预测了以EC。及NOEC浓度比例混合的联合毒性，但都在毒理学实验容许的范围之内。这5个物质以NOEC混合时对测试生物Q67没有产生明显毒性，但是还不能判定这些物质在此浓度下混合是安全的。污染物在各自的NOEC浓度下混合是否对其它生物有潜在的威胁还需更多毒理学实验支持。     

多组分苯胺类混合物对发光菌的抑制毒性

以淡水发光菌——青海弧菌(Q67)为指示生物,96微孔板为实验反应载体,微板光度计为发光强度测试设备,测定了苯胺、邻甲基苯胺、对甲基苯胺、邻硝基苯胺、对硝基苯胺及其混合物对发光菌的发光抑制毒性,应用非线性最小二乘拟合技术与剂量加和(DA)及独立作用(IA)原理研究了混合物的毒性规律.1)分别测定每种化合物的剂量-效应数据并进行非线性拟合.结果表明,5种苯胺类化合物的剂量-效应曲线(DRC)均可用Logit与Weibull函数有效表征,从这些模型估算的半数效应浓度负对数值(-logEC50)分别为2.11、2.35、2.49、3.60和3.88(EC50单位:mol·L-1),可知其对发光菌的毒性大小顺序为:苯胺<邻甲基苯胺<对甲基苯胺<邻硝基苯胺<对硝基苯胺.2)根据组分EC50、EC10和EC1设计3个等效应浓度比混合物进行混合物毒性实验,并对混合物剂量-效应数据进行非线性拟合得到混合物DRC.结果表明,混合物DRC可用Box-Cox-Logit与Box-Cox-Weibull函数有效表征.3)根据单一化合物DRC模型,分别应用剂量加和(DA)与独立作用(IA)模型对混合物DRC进行预测.结果表明,无论考察混合浓度比例还是效应水平,剂量加和模型都能准确预测苯胺类混合物的毒性,而独立作用模型倾向于高估混合物毒性.     

5种取代酚化合物对淡水发光菌的联合毒性

以新型淡水发光菌——青海弧菌Q67(Vibrio-qinghaiensissp.—Q67)为检验生物,以VeritasTM微孔板光度计为发光强度测试设备,分别测定了3,5-二羟基甲苯、2,3-二甲基苯酚、对氯苯酚、邻氯苯酚、2,4-二氯苯酚对淡水发光菌的发光抑制毒性及其混合物的联合毒性.结果表明,5种取代酚的剂量-效应关系都可用Weibull模型有效描述,从这些模型估算的半数效应浓度负对数值(-logEC50)分别为2.69、3.08、3.43、2.81和3.66,可知其对发光菌的毒性大小顺序为:2,4-二氯苯酚>对氯苯酚>2,3-二甲基苯酚>邻氯苯酚>3,5-二羟基甲苯.分别设计浓度等于各自之EC50和EC10的2个等效应浓度比混合物以及3个不同效应浓度比混合物进行联合毒性实验,结果发现,在所实验的浓度范围内各个混合物的剂量加和(DA)模型与独立作用(IA)模型具有相似的作用规律,其联合毒性既可用DA模型也可用IA模型进行预测.     

等毒性配比法研究镉、铬和铅对淡水发光细菌的联合毒性

当待测生物暴露在混合污染物中时,由于混合物中各组分相互影响,会产生联合毒性作用,表现为加和作用、协同作用和拮抗作用。为了深入了解重金属混合物的联合毒性对发光细菌的作用,利用淡水发光细菌——青海弧菌Q67(Vibrio qinghaiensis sp.nov-Q67)发光值的测定方法,采用联合毒性单位法,在测定了硝酸镉、重铬酸钾和硝酸铅单一毒性EC50的基础上,对硝酸镉 重铬酸钾、硝酸镉 硝酸铅、硝酸铅 重铬酸钾3种重金属二元混合物的联合毒性进行了评价。结果表明,硝酸镉 重铬酸钾、硝酸铅 重铬酸钾是拮抗作用,硝酸铅 硝酸镉是协同作用。     

定性与定量评估4种重金属及2种农药混合物对费氏弧菌的毒性相互作用

重金属与农药共同暴露产生的联合毒性作用可以对实际环境产生潜在的风险。为了研究重金属与农药混合物在不同浓度比毒性相互作用(协同、拮抗与加和)及其定量评估相互作用大小,根据单个物质无观测浓度(NOEC)、5%效应浓度(EC5)、10%效应浓度(EC10)和50%效应浓度(EC50),设计3组混合物体系(即农药-农药、重金属-重金属和农药-重金属)分别按NOEC、EC5、EC10和EC50浓度比的12条混合物射线,测试单个化合物及混合物对以费氏弧菌的发光抑制急性毒性,利用浓度加和(CA)、独立作用(IA)、模型偏差比(MDR)及其观测值置信区间定性和定量评估12条混合物射线的毒性相互作用。结果表明,农药-农药二元混合物体系和农药-重金属六元混合物体系均产生明显的协同作用,其中农药-农药混合物体系中,混合物射线EE-NOEC在50%效应下协同作用大小达到30.6(MDRCA和MDRIA数值);混合物射线EE5、EE10的协同作用大小接近于混合物射线EE-NOEC,混合物射线EE50的效应大于15%时CA和IA计算的MDR值均在置信区间上限的上方,即混合物发生协同作用;农药-重金属混合物体系的4条混合物射线EE-NOEC、EE5、EE10和EE50在所有测试浓度水平的MDR值均在置信区间上限的上方,呈现出明显的协同作用;在50%效应下,混合物射线EE-NOEC、EE5、EE10和EE50的MDRCA和MDRIA值分别为4.05和4.91、6.12和7.98、3.70和4.60、2.62和2.59。重金属-重金属四元混合物体系除了EC50浓度比混合物表现出拮抗作用,其余混合物在所有测试浓度范围的MDR值均在置信区间范围内,均为加和作用。因此,混合物的毒性相互作用大小随着组分浓度比变化而发生变化。     

重金属与有机磷农药二元混合物对卤虫联合毒性的评价及预测

重金属和有机磷农药污染物在水域环境中普遍存在。以卤虫(Artemiasalina)为受试生物,采用固定浓度比法,研究了重金属Zn、Cd与辛硫磷和敌百虫2种农药以毒性单位比为4∶1、3∶2、1∶1、2∶3和1∶4构成的二元混合体系对卤虫的联合毒性,采用等效线图解法判定毒物间的相互作用类型。同时,基于单一化合物的浓度-效应曲线,运用浓度加和(CA)和独立作用(IA)2种模型对不同配比二元混合物的联合毒性进行预测。结果表明,Zn-Cd混合物联合毒性随Zn比例的增加而增强。低Zn比例的混合物(1∶4、2∶3)表现为拮抗效应,中、高Zn比例的混合物(1∶1、3∶2和4∶1)为加和效应。5种不同配比的有机磷农药混合物均表现为加和效应。金属-农药混合物则均为拮抗作用。模型预测结果表明,CA能够较好地预测辛硫磷与敌百虫二元混合物的联合毒性,而IA则更适用于对金属-农药混合物联合毒性的预测。以上结果表明,混合体系中各组分的比例是影响联合毒性的因素之一,毒性评估时应该充分考虑其影响。CA及IA模型同样适用于评估和预测包含相同或完全独立作用机制组分的混合物对非单细胞生物体(如卤虫)的联合毒性。     

邻苯二甲酸酯类雌激素活性联合作用模型分析

环境雌激素对生命健康影响受到广泛关注,现行污染物环境标准制订和风险评价只针对单一化合物而非混合物效应,不足以保护生命安全与人类健康。为探讨环境雌激素的混合物效应,选择对雌激素敏感的人乳腺癌MCF-7细胞增殖实验,检测雌二醇(E2)、邻苯二甲酸酯类化合物(DBP和DEHP)的单一及其联合雌激素活性;基于单一化合物的浓度-反应曲线,运用浓度相加(CA)和独立作用(IA)模型对混合物的毒性进行预测,并将模型预测结果与混合物实验数据进行比较分析。结果表明,E2、DBP、DEHP对MCF-7细胞的单一作用数据可通过Weibull方程拟合,由拟合方程得到的半数效应浓度(EC50)及95%置信区间分别为3.450×10-6(2.373×10-6~1.675×10-5)、5.138(1.489~1.082×10)、1.186(4.478×10-1~2.24)μmol·L-1;3种化合物的混合物数据亦可通过Weibull、Logistic和Exp Gro1方程进行有效拟合,混合物效应与化合物单独作用产生的效应具有显著性差异;3种化合物表现非相似联合作用,利用独立作用(IA)模型预测混合物效应较为可靠,外源性环境雌激素与内源性雌激素联合作用产生的混合效应显著。环境雌激素混合物毒性可以通过相加作用模型预测,为环境复合污染的风险评价和管理提供基础数据。     

组合指数在环境混合物联合毒性研究中的初步应用

化学品在实际环境中总是以组分繁杂多变的混合物形式存在,其混合物的毒性评估与预测一直是环境毒理学研究重点。在环境毒理学领域,浓度加和(concentration addition,CA)及独立作用(independent action,IA)是评估与预测化学混合物联合毒性的经典模型,一般认为CA适用于作用模式相似的混合物体系而IA适用于作用模式相异的混合物体系,但如何使用CA与IA一直存在争议。组合指数(combination index,CI)是在半数效应方程基础上发展起来的不依赖于作用模式的用于混合物联合毒性评估的混合物毒性指数,具有坚实的理论基础,不仅能定性地评估毒理学相互作用,也能定量地评估相互作用的大小,已在药物组合研究中得以广泛应用,近年来已引起环境毒理学研究者兴趣。本文就组合指数及药物组合应用、进入环境毒理学领域、与CA及IA的关系、存在的问题等几个方面进行评述,以期推进CI在化学混合物毒性评估与预测领域中的应用。     

拓展等效线图法评估离子液体与杀菌剂多果定之间的拮抗作用

等效线图法(isobologram)是评估化学混合物毒性相互作用的经典方法之一,然而该方法仅能评估混合物在某一特殊浓度效应水平(通常为50%的浓度效应水平,即EC50)的联合毒性作用情况。因此,拓展等效线图法并用于不同效应水平下混合物毒性的评估显得尤为必要。以杀菌剂多果定(Dod)和3种离子液体(ILs)包括溴化丁基吡啶([bpy]Br)、溴化己基吡啶([hpy]Br)和溴化辛基吡啶([opy]Br)为混合物组分,采用直线均分射线法设计3组二元混合物体系(Dod-[bpy]Br、Dod-[hpy]Br和Dod-[opy]Br)共15条射线,应用微板毒性分析法系统测定各污染物及其混合物射线对青海弧菌Q67(Vibro qinghaisiense sp. Q67,Q67)的毒性,应用拓展等效线图法分析15条混合物射线在5个不同效应水平(EC20、EC30、EC40、EC50和EC60)的毒性相互作用,并与经典等效线图法和浓度加和模型(CA)评估的结果进行比较。结果表明:以p EC50为毒性指标,3种吡啶ILs对Q67的毒性具有烷基链效应,即毒性大小顺序为Dod-[opy]BrDod-[hpy]BrDod-[bpy]Br; 3组二元混合物体系的15条射线的毒性,随农药Dod浓度比的减少而减弱;拓展等效线图法可以比较直观地表征3组Dod-ILs混合物体系在5个不同效应水平的拮抗作用,且拮抗作用强度随Dod浓度比的增加而变化,即先增强后减弱;拓展等效线图法可以有效地评估二元混合物在多个效应水平的联合毒性相互作用。     

部分重金属化合物对淡水发光菌的毒性研究

应用微板毒性分析方法,分别测定了CdCl2·2.5H2O、CoSO4·5H2O、Cr(NO3)3·3H2O、Cu(NO3)2·3H2O、Fe(NO3)3·3H2O、MnCl2·9H2O、Na2SeO3、ZnSO4·7H2O、Ni(NO3)2·6H2O9种重金属离子化合物及其混合物对淡水发光菌—青海弧菌Q67(Vibrio-qinghaiensissp.—Q67)的发光抑制毒性.结果表明,9种重金属离子化合物对Q67的剂量-效应关系均可用Weibull或Logit模型有效描述.由拟合剂量-效应曲线得到这9种重金属离子化合物的半数效应浓度EC50的负对数值(-logEC50)分别为4.35、3.08、2.39、3.83、3.34、2.39、3.32、3.93和2.76,说明其毒性顺序为:CdCl2·2.5H2O>ZnSO4·7H2O>Cu(NO3)2·3H2O>Fe(NO3)3·3H2O>Na2SeO3>CoSO4·5H2O>Ni(NO3)2·6H2O>Cr(NO3)3·3H2O≈MnCl2·9H2O.为了研究重金属混合物的毒性规律,设计了4组等效应浓度(EC50、EC15、EC10和EC5)比混合物,测试了其混合物毒性,并应用剂量加和(DA)、独立作用(IA)原理及经典联合毒性评价方法进行了分析.DA与IA分析表明,所研究的4种混合物的毒性具有拮抗特征,而毒性单位法(TU)和混合指数法(MTI)的评价结果均为部分相加作用,相加指数法(AI)的评价结果则为拮抗作用.所选评价方法不同,混合物毒性评价结果可能也不同.     

有机磷农药对蛋白核小球藻的毒性相互作用研究

水体中农药复合污染产生的毒性效应具有潜在风险。为系统考察有机磷农药(OPs)混合物对淡水生态系统中绿藻的联合毒性效应,以马拉硫磷(MIT)、敌敌畏(DDVP)、敌百虫(TRC)、乐果(DIT)和氧乐果(OMT)等5种OPs作为混合物组分,运用直接均分射线法设计9组二元混合物体系共45条混合物射线。利用96孔微板测定5种OPs及其二元混合物对蛋白核小球藻(C. pyrenoidosa)的生长抑制毒性,通过基于置信区间的组合指数法分析混合物的联合毒性及毒性相互作用。结果表明,以p EC50为毒性指标,5种OPs对C. pyrenoidosa的毒性大小顺序为:TRCMITDDVPOMTDIT,OPs对C. pyrenoidosa的毒性大小受其中心磷原子的电正性影响;因混合组分的不同,部分OPs混合物对C. pyrenoidosa的联合毒性依赖于组分浓度比; OPs混合物对C. pyrenoidosa的毒性相互作用以加和为主,部分发生拮抗作用,发生拮抗作用的混合体系具有低效应区域呈加和作用,高效应区域呈拮抗作用的规律;与MIT混合的体系均有发生拮抗作用,且依赖于MIT浓度,MIT浓度比例越高,拮抗作用越强,OPs混合物的毒性相互作用与组分浓度比相关; OPs混合物的毒性相互作用组分浓度比依赖性与其联合毒性的组分浓度比依赖性规律不相关。     

Water Quality Criteria for European Freshwater Fish

1. For water pollution control purposes, the concentration-addition model for describing the joint effects of mixtures of toxicants on aquatic organisms is appropriate; in this model the contribution of each component in the mixture is expressed as a proportion of the aqueous concentration producing a given response in a given time (e.g. p 96-h LC50).

2. Examination of available data using this model shows that for mixtures of toxicants found in sewage and industrial effluents, the joint acutely-lethal toxicity to fish and other aquatic organisms is close to that predicted, assuming simple addition of the proportional contribution from each toxicant. The observed median value for the joint effect of these toxicants on fish is 0.95 of that predicted, and the corresponding collective value for sewage effluents, river waters, and a few industrial wastes, based on the toxicity of their constituents, is 0.85, while that for pesticides is 1.3.

3. The less-than-predicted effect of commonly-occurring toxicants in some mixtures may be partly attributable to small fractions of their respective LC50 values having a less-than-additional effect. However, recent research has shown that for some organic chemicals which have a common quantitative structure-activity relationship (QSAR), their joint action as determined by acute toxicity is additive at all concentrations.

4. The few (unpublished) data available for the long-term lethal joint effect on fish of toxicants in mixtures suggest that they may be markedly more than additive, a phenomenon that needs confirmation and further investigation.

5. In the few studies on the sub-lethal effects on fish (eg growth), the joint effect of toxicants has been consistently less-than-additive which suggests that as concentrations of toxicants are reduced towards the levels of no effect, their potential for addition is also reduced. There appear to be no marked and consistent differences between the response of different species to mixtures of toxicants.

6. Field studies have shown that reasonably accurate toxicity predictions based on chemical analysis can be made if the waters which are polluted are acutely lethal to fish, and that a fish population of some kind can exist where the median 2 p t LCSOs (rainbow trout) is < 0.2. It is not known whether this condition is equivalent to a C p NOEC of 4.0 (ie the sum of the individual fractions of the NOEC for the species present), or to a NOEC of < 1.0 for each individual toxicant (i.e. fractions of the NOEC are not summed).

7. In general, the joint effect of the common toxicants on lethal and sub-lethal responses of fish is not explained by variations in the uptake of the individual toxicants concerned; this may not apply for those chemicals with a common QSAR, although there is little experimental evidence in this field.

8. There is an immediate need for more empirical studies on the joint effect of mixtures of toxic units of individual components, and the relation between long- and short-term lethal and non-lethal joint effects. This applies to mixtures of commonly occurring toxicants as well as to mixtures of organic chemicals with a common QSAR. The data obtained should be reinforced by studies on the mechanisms of interaction of toxicants. More field studies which relate water quality to the structure and productivity of fish populations are also required, involving direct measurements of fractional toxicity of the river water wherever possible.

9. The concentration-addition model appears to be adequate to describe the joint effect of commonly-occurring constituents of sewage and industrial wastes, and for tentative predictions of the joint effect on fish populations of toxicants present at concentrations higher than the EIFAC recommended values. However, concentrations lower than the EIFAC recommended values may make an increasingly lesser contribution to the toxicity of mixtures of toxicants and there may be a need to adjust the tentative water quality criteria downwards where two or more toxicants are present at concentrations close to these values. For toxicants with a common QSAR, their additive joint action may necessitate the setting of water quality criteriafor this group as a whole and not on the basis of individual compounds. However, too little is known of their precise joint action where the combined concentration produces a sub-lethal response.     

Assessment of toxicity of two nitroaromatic compounds in the freshwater fish Cyprinus carpio

This study was conducted to evaluate the toxicological response of p-nitrotoluene and p-nitroaniline to the key fish species, Cyprinus carpio. A freshwater fish bioassay based on the 96 h LC ₅₀ was used to estimate the single and joint toxicity of the two chemicals. The toxicity of p-nitrotoluene was greater than that of p-nitroaniline based on 96 h LC ₅₀ values of 40.74 mg·L^?1 and 48.99 mg·L^?1, respectively. Both compounds had moderate toxicity toward Cyprinus carpio, and this toxicity increased with the exposure duration and concentration. Binary mixtures of the compounds were more toxic than the individual compounds at 96 h, and they acted upon partial addition. When the exposure time was longer, the toxicity increased for mixtures of compounds with the same concentration or toxicity. The results of this study suggest that exposure to a combination of these chemicals would result in a higher environmental risk in aquatic systems than exposure to either compound alone. Further research is needed to investigate the combined effects and sublethal toxicity of p-nitrotoluene and p-nitroaniline, since they are both still used in China.     

Additive und synergistische Kombinationswirkungen von Xenobiotika in subtoxischen Konzentrationen auf menschliche Fibroblasten

The toxic combination effects of xenobiotics of different substance classes were investigated in human fibroblasts. Subtoxic concentrations of 4-chloroaniline enhanced the toxicity of 2,4-dichlorophenoxyacetic acid (2,4-D, dimethylammonium salt) in an additive manner. A mixture of 4-chloroaniline, dicofol and 4-chlorophenol increased the toxicity of 2,4-D synergistically. The concentrations of the components used in the mixture were one third of their ?no observed effect concentrations” (NOEC). The combination of 4-chloroaniline, dicofol and 4-chlorophenol (without 2,4-D) at subtoxic concentrations also showed synergistic effects. The great differences in the lipophilicity of the combined substances might be the cause of the synergistic action.     

2,4-二硝基甲苯与共存化合物对发光菌的联合毒性

对2,4-二硝基甲苯与共存化合物对发光菌联合毒性的测定结果表明:2,4-二硝基甲苯与邻二硝基苯共存时,对发光菌的联合毒性为协同作用:分别与三种苯的氨基衍生物共存时.联合毒性为拮抗作用,这种拮抗作用与取代基数目、空间位阻等因素有关     

Combined toxic effect of airborne heavy metals on human lung cell line A549

Many studies have demonstrated that heavy metals existing as a mixture in the atmospheric environment cause adverse effects on human health and are important key factors of cytotoxicity; however, little investigation has been conducted on a toxicological study of a metal mixture from atmospheric fine particulate matter. The objective of this study was to predict the combined effects of heavy metals in aerosol by using in vitro human cells and obtain a suitable mixture toxicity model. Arsenic, nickel, and lead were selected for mixtures exposed to A549 human lung cancer cells. Cell proliferation (WST-1), glutathione (GSH), and interleukin (IL)-8 inhibition were observed and applied to the prediction models of mixture toxicity, concentration addition (CA) and independent action (IA). The total mixture concentrations were set by an IC₁₀-fixed ratio of individual toxicity to be more realistic for mortality and enzyme inhibition tests. The results showed that the IA model was statistically closer to the observed results than the CA model in mortality, indicating dissimilar modes of action. For the GSH inhibition, the results predicted by the IA and CA models were highly overestimated relative to mortality. Meanwhile, the IL-8 results were stable with no significant change in immune reaction related to inflammation. In conclusion, the IA model is a rapid prediction model in heavy metals mixtures; mortality, as a total outcome of cell response, is a good tool for demonstrating the combined toxicity rather than other biochemical responses.