Application of a developed triple-classification machine learning model for carcinogenic prediction of hazardous organic chemicals to the US, EU, and WHO based on Chinese database.

Cancer, the second largest human disease, has become a major public health problem. The prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven machine learning algorithms (i.e., Random Forest (RF), Logistic Regression (LR), Support Vector Machines (SVM), Complement Naive Bayes (CNB), K-Nearest Neighbor (KNN), XGBoost, and Multilayer Perceptron (MLP)) were used to construct the carcinogenicity triple classification prediction (TCP) model (i.e., 1A, 1B, Category 2). A total of 1444 descriptors of 118 hazardous organic chemicals were calculated by Discovery Studio 2020, Sybyl X-2.0 and PaDEL-Descriptor software. The constructed carcinogenicity TCP model was evaluated through five model evaluation indicators (i.e., Accuracy, Precision, Recall, F1 Score and AUC). The model evaluation results show that Accuracy, Precision, Recall, F1 Score and AUC evaluation indicators meet requirements (greater than 0.6). The accuracy of RF, LR, XGBoost, and MLP models for predicting carcinogenicity of Category 2 is 91.67%, 79.17%, 100%, and 100%, respectively. In addition, the constructed machine learning model in this study has potential for error correction. Taking XGBoost model as an example, the predicted carcinogenicity level of 1,2,3-Trichloropropane (96-18-4) is Category 2, but the actual carcinogenicity level is 1B. But the difference between Category 2 and 1B is only 0.004, indicating that the XGBoost is one optimum model of the seven constructed machine learning models. Besides, results showed that functional groups like chlorine and benzene ring might influence the prediction of carcinogenic classification. Therefore, considering functional group characteristics of chemicals before constructing the carcinogenicity prediction model of organic chemicals is recommended. The predicted carcinogenicity of the organic chemicals using the optimum machine leaning model (i.e., XGBoost) was also evaluated and verified by the toxicokinetics. The RF and XGBoost TCP models constructed in this paper can be used for carcinogenicity detection before synthesizing new organic substances. It also provides technical support for the subsequent management of organic chemicals.

Derivation of thresholds for inhaled chemically reactive irritants: Searching for substance-specific common denominators for read-across prediction.

Emergency response planning guideline values are used to protect the public when there has been a short-term chemical release. These values serve the purpose of identifying areas where a hazard exists if the concentration of hazardous chemicals is exceeded for the specified exposure duration. This paper focuses on carbonyl chlorides, a class of highly irritant/corrosive chemical intermediates characterized by the reactive moiety R-COCl. Despite their unifying property of reacting with nucleophilic biopolymers/peptides lining the airways of the respiratory tract, their adverse outcome pathway (AOP), in addition to surface area dose, appears to be dominated by their site(s) of major deposition (liquid) or retention (gas) within the respiratory tract. Thus, the physicochemical properties "phase" and "lipophilicity" become more decisive for the AOP than the chemical structure. This complicates the grouping of portal-of-entry irritant chemicals for the read-across prediction of chemicals, especially those with semivolatile properties. Phosgene (COCl2) served as a template to predict emergency response planning levels 2 (non-incapacitating, reversible injury) and 3 (nonlethal) for related chemicals such as SOCl2, formates, and acid chlorides. A rationale and guide to the systematic characterization of uncertainties associated with the lung region, water solubility of the vapor phase, and chemical specificity is given. The approach described in this paper highlights the regional differences and outcomes that are phenotypically described as irritation of the respiratory tract. Especially for such a data-lean group of chemicals, reliable read-across predictions could reduce the uncertainty associated with the derivation of values used for emergency-related risk assessment and management. Likewise, the approach suggested could improve the grouping and categorization of such chemicals, providing a means to reduce animal testing with potentially corrosive chemicals. Overall, the course taken for read-across predictions provided valid estimates as long as emphasis was directed to the physicochemical properties determining the most critical regional injury within the respiratory tract.

Malachite Green, the hazardous materials that can bind to Apo-transferrin and change the iron transfer.

Different groups of synthetic dyes might lead to environmental pollution. The binding affinity among hazardous materials with biomolecules necessitates a detailed understanding of their binding properties. Malachite Green might induce a change in the iron transfer by Apo-transferrin. Spectroscopic studies showed malachite green oxalate (MGO) could form the apo-transferrin-MGO complex and change the Accessible Surface Area (ASA) of the key amino acids for iron transfer. According to the ASA results the accessible surface area of Tyrosine, Aspartate, and Histidine of apo-transferrin significantly were changed, which can be considered as a convincing reason for changing the iron transfer. Moreover, based on the fluorescence data MGO could quench the fluorescence intensity of apo-transferrin in a static quenching mechanism. The experimental and Molecular Dynamic simulation results represented that the binding process led to micro environmental changes, around tryptophan residues and altered the tertiary structure of apo-transferrin. The Circular Dichroism (CD) spectra result represented a decrease in the amount of the α-Helix, as well as, increase in the ß-sheet volumes of the apo-transferrin structure. Moreover, FTIR spectroscopy results showed a hypochromic shift in the peaks of amide I and II. Molecular docking and MD simulation confirmed all the computational findings.

Evaluating chemical similarity as a measure to identify potential substances of very high concern.

Due to the large amount of chemical substances on the market, fast and reproducible screening is essential to prioritize chemicals for further evaluation according to highest concern. We here evaluate the performance of structural similarity models that are developed to identify potential substances of very high concern (SVHC) based on structural similarity to known SVHCs. These models were developed following a systematic analysis of the performance of 112 different similarity measures for varying SVHC-subgroups. The final models consist of the best combinations of fingerprint, similarity coefficient and similarity threshold, and suggested a high predictive performance (≥80%) on an internal dataset consisting of SVHC and non-SVHC substances. However, the application performance on an external dataset was not evaluated. Here, we evaluated the application performance of the developed similarity models with a 'pseudo-external assessment' on a set of substances (n = 60-100 for the varying SVHC-subgroups) that were putatively assessed as SVHC or non-SVHC based upon consensus scoring using expert elicitations (n = 30 experts). Expert scores were direct evaluations based on structural similarity to the most similar SVHCs according to the similarity models, and did not consider an extensive evaluation of available data. The use of expert opinions is particularly suitable as this is exactly the intended purpose of the chemical similarity models: a quick, reproducible and automated screening tool that mimics the expert judgement that is frequently applied in various screening applications. In addition, model predictions were analyzed via qualitative approaches and discussed via specific examples, to identify the model's strengths and limitations. The results indicate a good statistical performance for carcinogenic, mutagenic or reprotoxic (CMR) and endocrine disrupting (ED) substances, whereas a moderate performance was observed for (very) persistent, (very) bioaccumulative and toxic (PBT/vPvB) substances when compared to expert opinions. For the PBT/vPvB model, particularly false positive substances were identified, indicating the necessity of outcome interpretation. The developed similarity models are made available as a freely-accessible online tool. In general, the structural similarity models showed great potential for screening and prioritization purposes. The models proved to be effective in identifying groups of substances of potential concern, and could be used to identify follow-up directions for substances of potential concern.

Design and evaluation of bi-functional iron chelators for protection of dopaminergic neurons from toxicants.

While the etiology of non-familial Parkinson's disease (PD) remains unclear, there is evidence that increased levels of tissue iron may be a contributing factor. Moreover, exposure to some environmental toxicants is considered an additional risk factor. Therefore, brain-targeted iron chelators are of interest as antidotes for poisoning with dopaminergic toxicants, and as potential treatment of PD. We, therefore, designed a series of small molecules with high affinity for ferric iron and containing structural elements to allow their transport to the brain via the neutral amino acid transporter, LAT1 (SLC7A5). Five candidate molecules were synthesized and initially characterized for protection from ferroptosis in human neurons. The promising hydroxypyridinone SK4 was characterized further. Selective iron chelation within the physiological range of pH values and uptake by LAT1 were confirmed. Concentrations of 10-20 µM blocked neurite loss and cell demise triggered by the parkinsonian neurotoxicants, methyl-phenyl-pyridinium (MPP+) and 6-hydroxydopamine (6-OHDA) in human dopaminergic neuronal cultures (LUHMES cells). Rescue was also observed when chelators were given after the toxicant. SK4 derivatives that either lacked LAT1 affinity or had reduced iron chelation potency showed altered activity in our assay panel, as expected. Thus, an iron chelator was developed that revealed neuroprotective properties, as assessed in several models. The data strongly support the role of iron in dopaminergic neurotoxicity and suggests further exploration of the proposed design strategy for improving brain iron chelation.

Physicochemical characteristics of oil-based cuttings from pretreatment in shale gas well sites.

Understanding the physicochemical characteristics of oil-based cuttings (OBCs) is an important foundation for subsequent treatment and management. The macro- and microscopic properties of white oil-based cuttings (WOBCs) and diesel-based cuttings (DBCs) after the different pretreatment steps have been assessed using scanning electron microscopy. The organic and inorganic compositions of OBCs have been analyzed using X-ray diffraction, Fourier-transform infrared spectrometry, and gas chromatography-mass spectrometry. Inorganic matter (SiO2, BaSO4, and CaCO3), alkanes, aromatic compounds, and water were the main components of OBCs. The organic content (26.14%) and alkane content of the WOBCs were higher than that of the DBCs, whereas for the inorganic content (70.87%), the reverse was true. The macro- and micromorphologies of OBCs were quite different because their oil and water contents were different. The oil contents of OBCs decreased in the order A1 (14.64%) > A3 (12.67%) > A2 (11.06%) and B1 (9.19%) > B3 (8.94%) > B2 (4.66%); the water contents decreased in the order A1 (2.99%) > A3 (2.19%) > A2 (1.09%) and B1 (2.30%) > B3 (1.87%) > B2 (1.09%). Moreover, a skid-mounted treatment technology for OBCs was proposed. The results can be a scientific guidance for the treatment and management of OBCs.

Quality Control: Personal Protective Equipment for Use When Handling Hazardous Drugs.

United States Pharmacopeia Chapter <800>, concerned with the handling of hazardous drugs in healthcare settings, requires that any entity handling such drugs maintain a hazardous drug list. While this list must include any drug found on the latest NIOSH List of Antineoplastic and Other Hazardous Drugs in Health Settings, entities are expected to include other drugs and substances of concern. The intent of this article is to provide concrete information concerning articles of personal protective equipment, as well as guidance as to where and how they should be donned, used, and removed. This information will cover every aspect of handling hazardous drugs from receipt to disposal, most certainly including both sterile and nonsterile compounding.

Direct Prediction of the Toxic Gas Diffusion Rule in a Real Environment Based on LSTM.

Predicting the diffusion rule of toxic gas plays a distinctly important role in emergency capability assessment and rescue work. Among diffusion prediction models, the traditional artificial neural network has exhibited excellent performance not only in prediction accuracy but also in calculation time. Nevertheless, with the continuous development of deep learning and data science, some new prediction models based on deep learning algorithms have been shown to be more advantageous because their structure can better discover internal laws and external connections between input data and output data. The long short-term memory (LSTM) network is a kind of deep learning neural network that has demonstrated outstanding achievements in many prediction fields. This paper applies the LSTM network directly to the prediction of toxic gas diffusion and uses the Project Prairie Grass dataset to conduct experiments. Compared with the Gaussian diffusion model, support vector machine (SVM) model, and back propagation (BP) network model, the LSTM model of deep learning has higher prediction accuracy (especially for the prediction at the point of high concentration values) while avoiding the occurrence of negative concentration values and overfitting problems found in traditional artificial neural network models.

Highly potent radical scavenging-anti-oxidant activity of biologically reduced graphene oxide using Nettle extract as a green bio-genic amines-based reductants source instead of hazardous hydrazine hydrate.

Reduced graphene oxide (rGO) is relied upon to be the most promising candidate for high-proficiency. Hydrazine is the most conventional efficient reducing agent that has been frequently used for reduction of graphene oxide, however, it is not environmentally safe due to its toxic nature, causing unsatisfactory defects on the basal plan of GO. Therefore, employing green and efficient reducing agents from natural sources like plant extracts has become the research interest for obtaining high quality reduced graphene oxide sheets in recent years. Here a one-step, easy, cost-effective and green synthesis method based on Nettle leaves' extract has been introduced as an effective reduction method of graphene oxide compared with the toxic and harmful Hydrazine hydrate substance. In this study, GO and rGO were obtained from various methods and characterized by Raman spectroscopy, field emission scanning electron microscope, high-resolution transmission electron microscope (HR-TEM), X-ray diffraction analysis (XRD) and X-ray photon spectroscopy (XPS) analysis. Results of different analytical techniques revealed that the Nettle leaves' extract could successfully reduce GO sheets to high performance reduced graphene oxide with 79% efficiency in comparison with conventional Hydrazine hydrate. On the other side the rGO obtained by Nettle solution could scavenge the free radicals with 70% inhibition capacity at least concentration. Existence of Histamine and Serotonin and many other polyphenols as a part of Nettle leaves composition by following anti-oxidants mechanisms (H donation or electron transfer) promote the anti-oxidant functionality of Nettle leaves. So the highlighted achievement of this paper is to obtain a highly anti-oxidant green reduced graphene oxide with a wide applications i.e medical and polymer composite with UV-shielding activity.

Emission level of seven mainstream smoke toxicants from cigarette with variable tobacco leaf constituents.

[Introduction] Seven smoke constituents, including hydrogen cyanide (HCN), ammonia (NH3), phenol, benzo[α]pyrene (B[a]P), carbon monoxide (CO)¸ crotonaldehyde, and 4-(methylnitrosamino)-1- (3-pyridyl)-1-butanone (NNK), are proposed be the most relevant constituents for smoking-related diseases. [Methods] Different combinations of leaf stalk positions, varieties and locations were used to create variable chemistry of cigarette filler and smoke. Experimental cigarettes were measured for emission level of seven smoke toxicants and content of seventy-three filler components. [Results] The ranges of coefficient of variation (CV) for seven smoke toxicants were 15.43%-43.15%. The emission pattern of NNK and crotonaldehyde were different from that of other five smoke toxicants. Most of the seven smoke toxicants were influenced in following order: stalk position > location > variety. The leaf constitutes closely correlated with seven smoke toxicants were analyzed. [Conclusions] The results showed that seven toxicants were significantly influenced by leaf position and location, and closely correlated with leaf components, such as potassium, malate and alkaloid contents. The results provide useful and comprehensive information on the affecting factors and correlating leaf constituents for the variations of seven smoke toxicants.

The hazards and risks of inhaled poorly soluble particles - where do we stand after 30 years of research?

BACKGROUND: In 2006, titanium dioxide and carbon black were classified by IARC as "possibly carcinogenic to humans" and in 2017 the European Chemicals Agency's (ECHA) Committee for Risk Assessment concluded titanium dioxide meets the criteria to be classified as suspected of causing cancer (category 2, through the inhalation route). These classifications were based primarily on the occurrence of lung cancer in rats exposed chronically to high concentrations of these materials, as no such responses have been observed in other animal species similarly exposed. After the EU classification of titanium dioxide, it was suggested that Poorly Soluble particles of Low Toxicity (PSLTs) can be evaluated as a group. MAIN BODY: To better understand the current state of scientific opinion, we sought perspective from several international experts on topics relevant to the classification of carbon black; titanium dioxide; and, the potential future classification of PSLTs. Areas discussed included: grouping of PSLTs; the relevance of rat lung cancer responses to high concentrations of PSLTs; and, clearance overload and implications for interpretation of inhalation toxicology studies. We found there were several areas where a large majority of experts, including ourselves, agreed. These included concerns on the grouping of PSLT and the definition of clearance overload. Regarding the extrapolation of PSLT associated lung cancer in rats there were some strongly held differences, although most experts questioned the relevance when excessive exposures which overwhelm lung clearance were required. SHORT CONCLUSION: Given the ongoing discussion on PSLT classification and safety, we believe it is important to re-activate the public debate including experts and stakeholders. Such an open discussion would serve to formally document where scientific consensus and differences exist. This could form the basis for design of future safety programs and safety assessments.

Forgotten partners and function regulators of inducible metallothioneins.

Metallothioneins are peculiar cysteine rich, heat resistant, small cellular plasma proteins expressed through almost all life forms. The currently established biological functions of metallothioneins are the homeostasis of essential metals and protection against toxic transitional metals (TM) alongside defence from oxidative stress by direct scavenging of reactive oxygen and nitrogen species (ROS and RNS). In mammals, among the four main evolutionary conserved forms, only the ubiquitously expressed metallothionein 1 and 2 (here abbreviated as MT) are inducible by TM, oxidative stress, glucocorticoids and starvation among various other stimuli. However, more than sixty years after being discovered, metallothioneins still bear unresolved issues about their possible physiological function and regulation. The biological function of MTs has still not been associated with the in vitro-demonstrated capacity of MT interaction with cellular molecules glutathione (GSH) or adenosine triphosphate (ATP), or with the possibility of direct iron-MT binding in the reducing intracellular environment of some organelles, e.g. lysosomes. Iron as the most abundant cellular TM is also one of the main physiological sources of ROS. Moreover, iron exhibits strain, sex and age differences that reflected ROS generation and MT induction in (patho)physiology and toxicology studies. A recent study showed that iron sex differences follows expression of both ferritin and MT leading to wide implications from essential TM interconnectivity to aging. This review places emphasis on biochemically proven but physiologically ignored interactions of MT with iron to stimulate advanced research for establishing a wide frame of the biological roles of MTs important for health and longevity.

Gas/Particle Partitioning Constants of Nicotine, Selected Toxicants, and Flavor Chemicals in Solutions of 50/50 Propylene Glycol/Glycerol As Used in Electronic Cigarettes.

For an electronic cigarette (e-cigarette) aerosol with known total particulate matter concentration (TPM, µg/m3), predictions of the fractions of some compound i in the gas and particle phases ( fg, i and fp, i) at equilibrium can be made based on Kp, i (m3/µg), the compound-dependent gas/particle partitioning equilibrium constant. fg, i and fp, i affect the modes and locations of deposition in the respiratory tract. Kp, i depends inversely on (1) the pure compound liquid vapor pressure ( pL, io), (2) mole fraction activity coefficient (ζ i) in the absorbing liquid, and (3) mean molecular weight of the absorbing liquid (MW). Kp, i values were measured at 20 °C for 32 compounds as spiked into simulated e-cigarette liquids prepared as 50/50 mixtures (by weight) of propylene glycol (PG) and glycerol (GL). Kp, i values at 37 °C were estimated. The 32 compounds were nicotine (in free-base form), seven toxicants (propanal, acetone, hydroxyacetone, benzene, toluene, p-xylene, and ethylbenzene), and 24 flavor chemicals (2,3-pentanedione ("acetyl propionyl"), isobutyl acetate, ethyl butyrate, butyl butyrate, isoamyl acetate, 2,3-dimethylpyrazine, 3-methyl-1-butanol, limonene, 2,3,5-trimethylpyrazine, p-cymene, benzaldehyde, ( Z)-3-hexen-1-ol, menthol, 2-acetylpyrrole, benzyl alcohol, methyl salicylate, cinnamaldehyde, methyl anthranilate, (+)-aromadendrene, cinnamyl alcohol, methyl cinnamate, maltol, ethyl maltol, and coumarin). The measured log Kp, i values were found to be generally correlated with literature values of log pL, io; the scatter is caused by variation in ζ i between ∼1 and ∼1000. Kp measurements were attempted, but values were not reported for acetaldehyde, 2,3-butanedione (diacetyl), vanillin, and ethyl vanillin. Acetaldehyde was found to form significant amounts of its cyclic trimer and cyclic tetramer; for diacetyl, the evidence suggested significant amounts of reaction products, possibly hemiketals and ketals with PG/GL, and for vanillin and ethyl vanillin, the Kp values are large and accordingly more difficult to measure. fg values are calculated using a range of Kp and TPM values.

Safe handling of monoclonal antibodies: Too large to be hazardous?

It has been argued that the larger molecular weight of hazardous monoclonal antibodies may prevent their dermal absorption via occupational exposure. However, this assertion does not seem to be supported by direct evidence. Although the larger molecular weight may render monoclonal antibodies less probable to achieve therapeutic systemic level through dermal absorption, the concern in occupational health is whether these drugs can possibly attain a detectable level through repeated dermal exposure. Currently, there is no direct evidence to support a particular molecular weight above which a drug cannot achieve a detectable level following repeated occupational exposure. Therefore, the precautionary principle would dictate that repeated exposure of healthcare workers to hazardous monoclonal antibodies should be kept to a minimum.

Flow evaluation of the leaching hazardous materials from spent nickel-cadmium batteries discarded in different water surroundings.

The leaching characteristics of hazardous materials from Ni-Cd batteries immersed in four typical water samples, i.e., water with NaCl, river water, tap water, and deionized water, were investigated to evaluate the potential environmental harm of spent Ni-Cd batteries in the water surroundings. It is shown that four water surroundings all could leach hazardous materials from the Ni-Cd batteries. The water with NaCl concentration of 66.7 mg L-1 had the highest leaching ability, the hazardous materials were leached after only approximately 50 days (average time, with a standard deviation of 4.1), while less than 100 days were needed in the others. An electrochemical corrosion is considered to be the main leaching mechanism leading to battery breakage, while the dissolution-deposition process and the powder route result in the leakage and transference of nickel and cadmium materials from the electrodes. The anions, i.e., SO42- and Cl-, and dissolved oxygen in water were demonstrated to be the vital factors that influence the leaching processes. Thus, it is proposed that spent Ni-Cd batteries must be treated properly to avoid potential danger to the environment.

Assessment of novel tobacco heating product THP1.0. Part 3: Comprehensive chemical characterisation of harmful and potentially harmful aerosol emissions.

For a tobacco heating product (THP), which heats rather than burns tobacco, the emissions of toxicants in the aerosol were compared with those in cigarette smoke under a machine-puffing regimen of puff volume 55 ml, puff duration 2 s and puff interval 30 s. The list of toxicants included those proposed by Health Canada, the World Health Organization Study Group on Tobacco Product Regulation (TobReg), the US Food and Drug Administration and possible thermal breakdown products. In comparison to the University of Kentucky 3R4F reference cigarette the toxicant levels in the THP1.0 emissions were significantly reduced across all chemical classes. For the nine toxicants proposed by TobReg for mandated reduction in cigarette emissions, the mean reductions in THP1.0 aerosol were 90.6-99.9% per consumable with an overall average reduction of 97.1%. For the abbreviated list of harmful and potentially harmful constituents of smoke specified by the US Food and Drug Administration Tobacco Products Scientific Advisory Committee for reporting in cigarette smoke (excluding nicotine), reductions in the aerosol of THP1.0 were 84.6-99.9% per consumable with an overall average reduction of 97.5%.

Cytotoxicity screening and cytokine profiling of nineteen nanomaterials enables hazard ranking and grouping based on inflammogenic potential.

Engineered nanomaterials (ENMs) are being produced for an increasing number of applications. Therefore, it is important to assess and categorize ENMs on the basis of their hazard potential. The immune system is the foremost defence against foreign bodies. Here we performed cytokine profiling of a panel of nineteen representative ENMs procured from the Joint Research Centre (JRC) and commercial sources. Physicochemical characterization was performed using dynamic light scattering. The ENMs were all shown to be endotoxin content free. The human macrophage-differentiated THP.1 cell line was employed for cytotoxicity screening and based on the calculated IC50 values, the multi-walled carbon nanotubes (MWCNTs), ZnO, Ag and SiO2 NMs were found to be the most cytotoxic while single-walled carbon nanotubes (SWCNTs), TiO2, BaSO4 and CeO2 NMs, as well as the nanocellulose materials, were non-cytotoxic (at doses up to 100 µg/mL). Multiplex profiling of cytokine and chemokine secretion indicated that the TiO2, SiO2, BaSO4, CeO2 and nanocellulose materials induced potent inflammatory responses at sub-cytotoxic doses. Hierarchical clustering of cytokine responses coupled with pathway analysis demonstrated that the panel of ENMs could be segregated into two distinct groups characterized by activation and deactivation, respectively, of PPAR (peroxisome proliferator-activated receptor)/LXR (liver X receptor/retinoid X receptor) nuclear receptor pathways (NRPs). Furthermore, using rosiglitazone, a selective PPAR-γ agonist, we could show that PPAR-γ played an important role in the activation of inflammatory responses in cells exposed to TiO2 and SiO2 NMs. These studies show that ENMs of diverse chemical compositions can be grouped according to their inflammatory potential.

General baseline toxicity QSAR for nonpolar, polar and ionisable chemicals and their mixtures in the bioluminescence inhibition assay with Aliivibrio fischeri.

The Microtox assay, a bioluminescence inhibition assay with the marine bacterium Aliivibrio fischeri, is one of the most popular bioassays for assessing the cytotoxicity of organic chemicals, mixtures and environmental samples. Most environmental chemicals act as baseline toxicants in this short-term screening assay, which is typically run with only 30 min of exposure duration. Numerous Quantitative Structure-Activity Relationships (QSARs) exist for the Microtox assay for nonpolar and polar narcosis. However, typical water pollutants, which have highly diverse structures covering a wide range of hydrophobicity and speciation from neutral to anionic and cationic, are often outside the applicability domain of these QSARs. To include all types of environmentally relevant organic pollutants we developed a general baseline toxicity QSAR using liposome-water distribution ratios as descriptors. Previous limitations in availability of experimental liposome-water partition constants were overcome by reliable prediction models based on polyparameter linear free energy relationships for neutral chemicals and the COSMOmic model for charged chemicals. With this QSAR and targeted mixture experiments we could demonstrate that ionisable chemicals fall in the applicability domain. Most investigated water pollutants acted as baseline toxicants in this bioassay, with the few outliers identified as uncouplers or reactive toxicants. The main limitation of the Microtox assay is that chemicals with a high melting point and/or high hydrophobicity were outside of the applicability domain because of their low water solubility. We quantitatively derived a solubility cut-off but also demonstrated with mixture experiments that chemicals inactive on their own can contribute to mixture toxicity, which is highly relevant for complex environmental mixtures, where these chemicals may be present at concentrations below the solubility cut-off.

Toward the Design of Less Hazardous Chemicals: Exploring Comparative Oxidative Stress in Two Common Animal Models.

Sustainable molecular design of less hazardous chemicals presents a potentially transformative approach to protect public health and the environment. Relationships between molecular descriptors and toxicity thresholds previously identified the octanol-water distribution coefficient, log D, and the HOMO-LUMO energy gap, ΔE, as two useful properties in the identification of reduced aquatic toxicity. To determine whether these two property-based guidelines are applicable to sublethal oxidative stress (OS) responses, two common aquatic in vivo models, the fathead minnow (Pimephales promelas) and zebrafish (Danio rerio), were employed to examine traditional biochemical biomarkers (lipid peroxidation, DNA damage, and total glutathione) and antioxidant gene activation following exposure to eight structurally diverse industrial chemicals (bisphenol A, cumene hydroperoxide, dinoseb, hydroquinone, indene, perfluorooctanoic acid, R-(-)-carvone, and tert-butyl hydroperoxide). Bisphenol A, cumene hydroperoxide, dinoseb, and hydroquinone were consistent inducers of OS. Glutathione was the most consistently affected biomarker, suggesting its utility as a sensitivity response to support the design of less hazardous chemicals. Antioxidant gene expression (changes in nrf2, gclc, gst, and sod) was most significantly (p < 0.05) altered by R-(-)-carvone, cumene hydroperoxide, and bisphenol A. Results from the present study indicate that metabolism of parent chemicals and the role of their metabolites in molecular initiating events should be considered during the design of less hazardous chemicals. Current empirical and computational findings identify the need for future derivation of sustainable molecular design guidelines for electrophilic reactive chemicals (e.g., SN2 nucleophilic substitution and Michael addition reactivity) to reduce OS related adverse outcomes in vivo.