Current risk assessment in many countries, including European Union, is still placing focus on single substances rather than their mixtures, although mixtures are commonly found in the environment. ...To overcome this problem and gain new insights, six pharmaceuticals, namely: azithromycin (AZM), erythromycin (ERM), carbamazepine (CBA), oxytetracycline (OTC), dexamethasone (DXM), and diclofenac (DCF), were selected in order to analyze their combined toxicity in binary mixtures. Overall, 45 binary mixtures were analyzed. Single component toxicities were determined as well, for modelling purpose. Two most common mathematical models for the description of mixture toxicities were applied: concentration addition (CA) and independent action (IA) model. Comparison of the predicted and experimentally obtained toxicities provided information about the modes of toxicity action in the mixtures. OTC–DCF binary mixture indicated synergism with respect to additive behavior (CA model). All other binary combinations containing OTC or DCF were acting very similarly: the synergism with respect to additive behavior was observed for OTC–CBA and DCF-CBA combinations, while OTC–AZM, OTC–ERM, DCF–AZM and DCF–ERM exhibited antagonistic behavior with respect to CA model. All the remaining binary mixtures indicated additive behavior. The applicability of IA model as a proof of independent toxic action of the components was confirmed in cases of DCF–AZM, DCF–ERM, and OTC–AZM mixtures.
•Toxicities of six pharmaceuticals toward Vibrio fischeri were determined.•Toxicities of related binary mixtures toward Vibrio fischeri were determined.•Concentration Addition and Independent Action models were applied to predict toxicities of the mixtures.•Combined toxicity actions were discussed by comparing predicted and experimentally determined toxicities of the mixtures.
Pollutants in real aquatic systems commonly occur as chemical mixtures. Yet, the corresponding risk assessment is still mostly based on information on single-pollutant toxicity, accepting the ...assumption that pollutant mixtures exhibit additive toxicity effect which is often not the case. Therefore, it is still better to use the experimental approach. Unfortunately, experimental determination of toxicity for each mixture is practically unfeasible. In this study, quantitative structure-activity relationship (QSAR) models for the prediction of toxicity of binary mixtures towards bioluminescent bacteria Vibrio fischeri were developed at three toxicity levels (EC10, EC30 and EC50). For model development, experimentally determined toxicity values of 14 pollutants (pharmaceuticals and pesticides) were correlated with their structural features, applying multiple linear regression together with genetic algorithm. Statistical analysis, internal validation and external validation of the models were carried out. The toxicity is accurately predicted by all three models. EC30 and EC50 values are mostly influenced by geometrical distances between nitrogen and sulfur atoms. Furthermore, the simultaneous presence of oxygen and chlorine atoms in mixture can induce the increase in toxicity. At lower effect levels (EC10), nitrogen atom bonded to different groups has the highest impact on mixture toxicity. Thus, the analysis of the descriptors involved in the developed models can give insight into toxic mechanisms of the binary systems.
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•Toxicities of binary mixtures of 14 pollutants on Vibrio fischeri were determined.•QSAR toxicity models were developed at three toxicity levels: EC10, EC30, and EC50.•EC50 was related to G(N..S), SM05_EA(dm), Mor14s, and HATS4m descriptors.•EC30 was linked with F080-Cl, G(N..S), and Mor11p descriptors.•EC10 proved its connection with SpMax_EA(dm), SM11_EA(dm), and N-073 descriptors.
A capsule that summarizes the main finding of the work: QSAR models for toxicity of binary mixtures of water pollutants on three toxicity levels were developed. The results indicate that different descriptors can play major role at different toxicity levels.
Pesticides are the chemicals of increased concern regarding their adverse environmental effects. In particular, the reports on their joint toxicity effects are scarce in the literature. Therefore, ...this paper describes the experiments on toxicities of four pesticides: alachlor, chlorfenvinphos, diuron, and isoproturon, toward Vibrio fischeri. In particular, the joint toxicity effects for all possible binary combinations of the pesticides were analyzed. The analysis included the application of concentration addition and independent action models at two toxicity levels: EC10 and EC50. The analysis revealed additive behavior between all pesticide pairs. The only exception was isoproturon and chlorfenvinphos whose combination resulted in synergistic toxic activity. The original form of the logistic function was given preference over the linearized form in describing the response–dose relationships of investigated pesticides.
•Toxicities were determined toward Vibrio fischeri.•Alachlor, chlorfenvinphos, diuron, and isoproturon were examined.•Joint toxicity effects in binary pesticide-mixtures were analyzed.•Isoproturon and chlorfenvinphos indicated synergistic toxic activity.•Other binary combinations indicated additive behavior.
The occurrence of contaminants in natural waters is a potential threat to the environment. Since contaminants are commonly present as mixtures, numerous interactions may occur, resulting in lower or, ...more dangerously, higher toxicity, by comparison with single substances. The toxicity of multicomponent systems can be determined experimentally, but toxicity prediction by suitable models is faster, environmentally friendly and less expensive. Here we review approaches and models, which can be utilized in assessing toxicity of chemical mixtures. In the first part, the assessment of toxicity of chemical mixtures and possible interactions between mixture constituents are discussed. The second part covers conventional modeling, including the simplest, and most common toxicity models, namely concentration addition and independent action models, and derived integrated models. The third part presents advanced toxicity modeling. We review the quantitative structure–activity relationship (QSAR) approach and its elements: calculation of molecular descriptors and their selection with principal component analysis and genetic algorithm. Modeling with artificial neural networks is also discussed. We present hybrid models which combine the fuzzy set theory approach with the conventional concentration addition and independent action models. We conclude that conventional models: concentration addition and independent action model, are still most commonly used; integrated models are more accurate compared to conventional ones, even though their application requires more data; advanced numerical methods such as genetic algorithm, neural networks, and fuzzy set theory give a new perspective on toxicity prediction, and no universal tool for toxicity assessment has been developed so far.
Samples of cretaceous limestone have been treated with three application methods (poultice, immersion and brushing) using different concentrations of ammonium oxalate solution (AmOx) and varying ...treatment time in order to test the efficiency of surface and in-depth formation of a protective layer of calcium oxalate (CaOx). Synchrotron-based microanalytical techniques (SR-μXRD with 12.5 μm×7.5 μm (
H
×
V
) probe size, SR-μFTIR with 10 μm×10 μm and 8 μm×20 μm probe sizes) and laboratory μFTIR, XRD and SEM have been employed for analysis of the treated samples. Synchrotron-based techniques showed variations in the CaOx distribution along the surface on a micrometer scale. All treatments resulted in the development of a CaOx layer with a maximum thickness of approximately 40 μm. Application by the brushing method with 10 1-min applications with 5-min breaks during one hour showed a development of the calcium oxalate layer equivalent to the poultice treatment taking 10 h. This treatment could be preferred for large marble or limestone surfaces where poultice usage is economically not feasible.
This recommendation defines just three terms, viz., (1) molar-mass dispersity, relative-molecu- lar-mass dispersity, or molecular-weight dispersity; (2) degree-of-polymerization dispersity; and (3) ...dispersity. “Dispersity” is a new word, coined to replace the misleading, but widely used term “polydispersity index” for Mw / Mn and Xw/ Xn. The document, although brief, also has a broader significance in that it seeks to put the terminology describing dispersions of distributions of properties of polymeric (and non-polymeric) materials on an unambiguous and justifiable footing.
Liquid-liquid equilibria were experimentally investigated in systems in which the first component was aliphatic (n-hexane, n-heptane or i-octane) or aromatic hydrocarbon (toluene), the second ...component was pyridine or thiophene, and the third quasi-component was DES consisting of choline chloride and glycerol or choline chloride and ethylene glycol, at 25 °C and atmospheric pressure. The equilibria were successfully described by the NRTL and UNIQUAC models. The same models were successfully applied to describe the liquid-liquid equilibria in quasi-seven-component systems that comprised all the mentioned low molecular weight components and one DES. The restrictions of the models were discussed; it seems that the preference can be given to the UNIQUAC model.
Velika skupina industrijski važnih polimerizacijskih procesa provodi se u disperznim sustavima. Ti se procesi razlikuju prema svojoj fizičkoj prirodi, mehanizmu nastanka čestica, morfologiji čestice, ...njezinoj veličini, naboju, vrstamačestičnih me?udjelovanja i na mnoge druge načine. Polimerne disperzije i polimeri dobiveni polimerizacijom u disperznom sredstvu rabe se u različitim područjima, kao boje, adhezivi, zatim u mikroelektronici, medicini, kozmetici, biotehnologiji i drugdje. Često se ista imena upotrebljavaju za različite procese i proizvode ili se pak različita imena rabe za iste procese i proizvode. Ovaj dokument sadrži popis preporučenih naziva i definicija nužan za nedvosmislen opis procesa, proizvoda, parametara i karakterističnih svojstava povezanih s polimerima u disperznim sustavima.
The polydispersity index as a measure of the width of molecular weight distributions (MWD) is theoretically very important. However, considering MWDs of real polymers, its importance is partly lost. ...Consequently, several problems arise. The most common one is the misinterpretation of polydispersity index as a single and unique measure of the MWD width. In this work, the origin and solutions of the problem are clearly described via several theoretical distribution functions, i.e. those which are most widely applied for the description of polymer MWDs. The conclusions are confirmed by the analysis of MWDs of real samples, namely styrene-acrylonitrile copolymers. In addition, a complete procedure for the MWD data analysis is presented. Such a procedure is necessary for the correct interpretation and comparison of different, experimentally obtained, molecular weight distributions of polymers.
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