11种农药对淡水发光细菌青海弧菌Q67的毒性研究

以淡水发光细菌青海弧菌Q67作为测试菌剂,利用水质毒性分析仪对11种农药进行了毒性研究,获得11种农药与青海弧菌的剂量-效应关系.结果表明,作用时间为15 min时,5种可溶农药对青海弧菌Q67的毒性大小为敌敌畏＞敌百虫＞杀虫单＞乐果＞乙酰甲胺磷,6种难溶于水农药的毒性大小为甲氨基阿维菌素＞甲胺磷＞莎稗磷＞高效氯氰菊酯...     

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。     

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。     

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。     

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.     

铜、镉对水螅的急性和联合毒性作用

试验研究重金属铜(Cu2 )、镉(Cd2 )对水螅的急性毒性和联合毒性作用,探索水螅(Hydra sp.)对Cu2 、Cd2 以及两者混合的毒性效应,为水产动物病害的防治中合理使用消毒、杀虫剂以及水体污染评价提供一些参考信息.结果表明,Cu2 对水螅的24 h半致死浓度(LC50)、48 hLC50、72 hLC50、96 hLC50分别为0.072、0.054、0.042、0.037 mg/L;Cd2 对水螅的24 hLC50、48hLC50、72 hLC50、96 hLC50分别为0.001 70、0.000 63、0.000 36、0.000 36 mg/L;Cu2 、Cd2 对水螅的安全浓度分别为3.7×10-4、3.6×10-6mg/L.水螅对两种重金属的毒性反应既快速又敏感,其中Cu2 对水螅的毒性较Cd2 快,但Cd2 的毒性比Cu2 的强.等毒性配比的两种重金属混合液对水螅的毒性大于单一毒性,为协同作用.两种重金属对水螅的LC50随试验时间的延长而减小,它们对水螅的安全浓度远低于渔业水质标准.     

除草剂阿特拉津与丁草胺对麦穗鱼的联合毒性研究

以除草剂阿特拉津和丁草胺为供试毒物,研究了它们对麦穗鱼的单一及联合毒性.结果表明,阿特拉津与丁草胺对麦穗鱼的96 h半致死浓度(LC50 )分别为41.64、0.33 mg/L,安全浓度(SC)分别为4.164、0.033 mg/L.因此,阿特拉津对鱼类是一种低毒除草剂,丁草胺则对鱼类具有较高的毒性.在阿特拉津与丁草胺的联合毒性试验中,24、48、96 h的相加指数分别为0.056、 0.053 、0.084,表明阿特拉津与丁草胺对麦穗鱼的联合毒性存在协同效应.     

几种农药对鲤鱼脑AchE的联合毒性效应

采用体内染毒的方法,以鲤鱼脑乙酰胆碱酯酶(AchE)活力为指标,研究了有机磷农药对硫磷与氯乐果、甲胺磷涕灭威之间的联合毒性效应.结果表明,这些农药之间均产生较强的协同作用,但是两种农药以不同比例加入,其产生的毒性效应有明显差别,涕灭威/对硫磷之间的协同作用要强于同类农药间的作用.     

几种农药对发光菌毒性的测定和构效关系研究

测定了10种农药对发光菌的毒性数据(-lgEC50);采用密度泛涵理论(DFT)中的B3LYP方法,在B3LYP/6-31G*水平上全优化计算了17种农药的结构参数和热力学参数,将这些参数作为理论描述符,依据修正的线性溶解能理论,利用半致死浓度(EC50)实验数据,建立了用于预测农药毒性的模型,其相关方程(相关系数r=0.945 5)包含2个变量,即分子的最正氢原子电荷(qH )和熵(Sθ),并用留一交叉验证法对模型的稳定性进行了验证.此外,还利用该模型预测了17种农药对发光菌的一IgEC50.     

用SOS/Umu生物测试评价北方某自来水厂对遗传毒性物质的去除效果

大量研究表明,饮用水中存在着能导致遗传毒性的物质,在我国许多水厂水质检测能力有限的前提下,生物毒性指标作为反映有毒物质综合指标具有重要的现实意义.本研究应用SOS/Umu生物毒性测试评价了北方某市一自来水厂的A、B、C、D 4套试验工艺在不同的季节(冬春两季)各工艺段出水的遗传毒性效应.结果显示,冬春两季地表水加氯后遗传毒性效应均显著增加,冬季间接遗传毒性效应高于春季;活性炭吸附对去除遗传毒性物质效果显著,但后期加氯使遗传毒性效应增加;冬春两季比较,以及地下水和地表水比较,各工艺出水的遗传毒性效应差别很大.通过研究表明,本研究所应用的生物毒性测试SOS/Umu能够快速、准确地对水厂工艺过程中致突变物质的处理效果进行评价,能对工艺改进提出指导,是自来水质安全性评价的重要补充手段.     

发光细菌法在水质综合毒性在线检测中的应用

以海洋发光细菌费氏弧菌（Vibriofischeri）作为检测生物,采用冻干菌粉快速复苏技术,研究费氏弧菌在水质检测中的最佳测试温度和有效性测试条件,并对硫酸锌等多种毒物和几种实际水样进行发光抑制作用分析。研究表明,费氏弧菌冻干粉复苏菌液保存在2～5℃条件下能有效测试7d,最佳测试温度为15℃,最佳测试时间为15min。氯化汞、硫酸锌、硫酸镉等重金属和苯胺、多菌灵、甲醛等有机毒物对费氏弧菌均具有较强的光抑制作用,也即费氏弧菌对以上毒物较为敏感,并能够连续7d保持对同一浓度硫酸锌的敏感性较为一致。对几种实际水样的测试和分析表明,以费氏弧菌为指示生物的发光细菌法能够应用于水质环境安全的综合毒性在线监测预警中。     

)]发光细菌法在水质综合毒性在线检测中的应用

以海洋发光细菌费氏弧菌(Vibrio fischeri)作为检测生物,采用冻干菌粉快速复苏技术,研究费氏弧菌在水质检测中的最佳测试温度和有效性测试条件,并对硫酸锌等多种毒物和几种实际水样进行发光抑制作用分析。研究表明,费氏弧菌冻干粉复苏菌液保存在2~5℃条件下能有效测试7 d,最佳测试温度为15℃,最佳测试时间为15 min。氯化汞、硫酸锌、硫酸镉等重金属和苯胺、多菌灵、甲醛等有机毒物对费氏弧菌均具有较强的光抑制作用,也即费氏弧菌对以上毒物较为敏感,并能够连续7 d保持对同一浓度硫酸锌的敏感性较为一致。对几种实际水样的测试和分析表明,以费氏弧菌为指示生物的发光细菌法能够应用于水质环境安全的综合毒性在线监测预警中。     

Statistical evaluation of chronic toxicity data on aquatic organisms for the hazard identification: the chemicals toxicity distribution approach

Presently, in the Globally Harmonised System of Classification and Labelling of Chemicals the classification of substances for long-term effects to aquatic life is based on acute toxicity in combination with degradation and/or bioaccumulation potential. Recently an OECD Working Group was created to develop the classification scheme to accommodate chronic toxicity data related to aquatic organisms for assigning a chronic hazard category. This study focuses on a new approach for setting chronic toxicity cut-off values based on Chemicals Toxicity Distributions (CTDs). A CTD is obtained through statistical fitting of the data used by regulatory bodies for setting hazard-based classifications. The CTDs were made using the lowest aquatic NOEC value of each chemical. A review of different toxicological sources reporting acute aquatic toxicities was carried out. Initially, the data were arranged according to the specific source and distributions for key taxonomic groups (i.e. fishes, crustaceans and algae) were evaluated separately. In most cases, no significant departures from normality were observed. Thereafter, a compiled database containing >900 values was developed and the CTDs were constructed for each taxonomic group. Significant deviation from normality (P < 0.05) was observed in the fishes and crustaceans' CTDs. However, this deviation was apparently produced by the presence of only seven values with NOECs <1 x 10(-5) mg l(-1), while high correlation between the data and the normal scores (r-values>or= 0.989) indicated that the data were samples from normal distributions. From these observations, potential cut-off values would allow quantitative estimations of the percentage of chemicals falling into each specific category. This approach results in a simple classification hazard scheme where most chemicals are covered in one of the categories, allowing a clear distribution of the chemicals among three categories for chronic toxicity.     

Data ranges in aquatic toxicity of chemicals

A significant problem for effect assessment of aquatic ecosystems arises from the large ranges of toxicity data, which can be found in different databases and literature. Here, ranges are given for the aquatic toxicity of 27 high production volume chemicals. Based on these illustrative examples and on the current literature on uncertainty in aquatic effect assessment, toxicity ranges are discussed for their possible causes (variation in experimental condition, species, endpoint, time) and ways to handle them (safety factors). Implications and recommendations on the procedure of risk analysis of chemical substances are drawn. Two main requirements for a comprehensive risk assessment are identified, which often play a minor role in current practice (as they are often neglected) as well as in scientific discussion (as they are meant to be trivial). First, data quality must be checked critically before applying any result of a toxicity test. Secondly, experimental data should take into account different species and acute as well as chronic data. If these aspects are considered in risk analysis, which is common practice in ecotoxicology but not always in the context of practical applications in risk engineering, a more comprehensive picture of the environmental toxicity of a chemical substance can be obtained.     

Comparison of test procedures for sediment toxicity evaluation with Vibrio fischeri bacteria

The use of bacterial luminescence assays is particularly effective in the contaminated sediment evaluation. In the present study, a comparison was made of different baterial luminescence assays including acute toxicity of elutriates with Microtox® and LUMIStox®; chronic toxicity of elutriates with LUMIStox®; and, acute toxicity of solvent extracts with both the tests and the Solid Phase test with Microtox. The toxicity assay procedures were utilised for the Po River sediment toxicity evaluation, testing samples with different physical and chemical characteristics. The results evidentiated that each sediment test procedures provided indipendent and complementary ecotoxicological responces usefull for a sediment classification of the most polluted samples.     

Mechanism of concentration addition toxicity: they are different for nonpolar narcotic chemicals, polar narcotic chemicals and reactive chemicals

According to the toxicity mechanism of the individual chemicals, the concentration addition toxicity mechanism is revealed for nonpolar-narcotic-chemical mixtures, polar-narcotic-chemical mixtures and reactive-chemical mixtures, respectively. For nonpolar-narcotic-chemical mixtures, the partitioning of individual chemicals from water to biophase was determined, and the result shows that their concentration additive effect results from no competitive partitioning among individual chemicals. For polar-narcotic-chemical mixtures, their toxicity are contributed by two factors (the total baseline toxicity and the hydrogen bond donor activity of individual chemicals), and it is the concentration additive effect for either of these two factors that leads to their concentration addition toxicity. In addition, the interactions between the reactive chemicals and the biological macromolecules are discussed thoroughly. The results suggest that the net effect of these interactions is zero, and it is this zero net effect that leads to the concentration addition toxicity mechanism for reactive-chemical mixtures.     

Assessing joint toxicity of chemicals in Enchytraeus albidus (Enchytraeidae) and Porcellionides pruinosus (Isopoda) using avoidance behaviour as an endpoint

Contamination problems are often characterized by complex mixtures of chemicals. There are two conceptual models usually used to evaluate patterns of mixture toxicity: Concentration Addition (CA) and Independent Action (IA). Deviations from these models as synergism, antagonism and dose dependency also occur. In the present study, single and mixture toxicity of atrazine, dimethoate, lindane, zinc and cadmium were tested in Porcellionides pruinosus and Enchytraeus albidus, using avoidance as test parameter. For both species patterns of antagonism were found when exposed to dimethoate and atrazine, synergism for lindane and dimethoate exposures (with the exception of lower doses in the isopod case study) and concentration addition for cadmium and zinc occurred, while the exposure to cadmium and dimethoate showed dissimilar patterns.This study highlights the importance of dose dependencies when testing chemical mixtures and that avoidance tests can also be used to asses the effects of mixture toxicity.     

Classification of chemicals according to mechanism of aquatic toxicity: an evaluation of the implementation of the Verhaar scheme in Toxtree

A number of mechanisms have been identified that can lead to (acute) aquatic toxicity. The assignment of compounds to a particular mechanism of action is important in the development and utilisation of (quantitative) structure-activity relationships ((Q)SARs) for ecotoxicity. Assignment to a mechanism can be difficult; however in 1992 Verhaar et al. published a series of structural rules which aimed to classify compounds according to mechanism of action. Recent interest has seen the Verhaar rules coded into freely available software such as Toxtree available from the European Chemicals Bureau. To date, a complete critical evaluation of these rules has been lacking. Therefore, the aim of this study was to evaluate the Toxtree implementation of the Verhaar rules using two well characterised aquatic toxicity datasets (Pimephales promelas and Tetrahymena pyriformis phenol databases) for which mechanisms of toxic action are well established. The present study highlights rule, and possible coding, errors that may lead to misclassifications. Improvements to both the rules and prediction architecture are suggested. In particular further rules to improve predictions for polar narcosis (class 2) are suggested.     

2,6-二硝基甲苯与4-硝基甲苯对虹鳉鱼的联合毒性

以虹锵鱼(Poecilia reticulata)为试验材料,进行了2．6-二硝基甲苯(2,6-DNT)与4-硝基甲苯(4-NT)的急性毒性和联合毒性研究。采用Marking相加指数法(AI)及相似性参数(λ)对联合毒性做出评价。两种评价方法得出一致的结论：在等毒性配比的条件下,两者为协同作用。