Modeling non-monotonic dose-response relationships: model evaluation and hormetic quantities exploration

Derivation of water quality criteria for paraquat, bisphenol A and carbamazepine using quantitative structure-activity relationship and species sensitivity distribution (QSAR-SSD)

The risk assessment of an expanding array of emerging contaminants in aquatic ecosystems and the establishment of water quality criteria rely on species sensitivity distribution (SSD), necessitating ample multi-trophic toxicity data. Computational methods, such as quantitative structure-activity relationship (QSAR), enable the prediction of specific toxicity data, thus mitigating the need for costly experimental testing and exposure risk assessment. In this study, robust QSAR models for four aquatic species (Rana pipiens, Crassostrea virginica, Asellus aquaticus, and Lepomis macrochirus) were developed using leave-one-out (LOO) screening variables and the partial least squares algorithm to predict toxicity data for paraquat, bisphenol A, and carbamazepine. These predicted data can be integrated with experimental data to construct SSD models and derive hazardous concentration for 5 % of species (HC5) for the criterion maximum concentration. The chronic water quality criterion for paraquat, bisphenol A, and carbamazepine were determined at 6.7, 11.1, and 3.5 μg/L, respectively. The QSAR-SSD approach presents a viable and cost-effective method for deriving water quality criteria for other emerging contaminants.

Protecting the invisible: Establishing guideline values for copper toxicity to marine microbiomes

Understanding the rapid responses of marine microbiomes to environmental disturbances is paramount for supporting early assessments of harm to high-value ecosystems, such as coral reefs. Yet, management guidelines aimed at protecting aquatic life from environmental pollution remain exclusively defined for organisms at higher trophic levels. In this study, 16S rRNA gene amplicon sequencing was applied in conjunction with propidium monoazide for cell-viability assessment as a sensitive tool to determine taxon- and community-level changes in a seawater microbial community under copper (Cu) exposure. Bayesian model averaging was used to establish concentration-response relationships to evaluate the effects of copper on microbial composition, diversity, and richness for the purpose of estimating microbiome Hazard Concentration (mHCx) values. Predicted mHC5 values at which a 5 % change in microbial composition, diversity, and richness occurred were 1.05, 0.72, and 0.38 μg Cu L-1, respectively. Threshold indicator taxa analysis was applied across the copper concentrations to identify taxon-specific change points for decreasing taxa. These change points were then used to generate a Prokaryotic Sensitivity Distribution (PSD), from which mHCxdec values were derived for copper, suitable for the protection of 99, 95, 90, and 80 % of the marine microbiome. The mHC5dec guideline value of 0.61 μg Cu L-1, protective of 95 % of the marine microbial community, was lower than the equivalent Australian water quality guideline value based on eukaryotic organisms at higher trophic levels. This suggests that marine microbial communities might be more vulnerable, highlighting potential insufficiencies in their protection against copper pollution. The mHCx values proposed here provide approaches to quantitatively assess the effects of contaminants on microbial communities towards the inclusion of prokaryotes in future water quality guidelines.

Time-dependent hormetic dose responses of skin care product mixtures to Vibrio qinghaiensis sp.-Q67: Appearance and quantification

Hormesis is a widely recognized and extensively studied phenomenon. However, few studies have described the quantitative characteristics of hormesis required for appropriate risk assessment. Although skin care product (SCP) mixtures and their active ingredients can induce the hormesis of Vibrio qinghaiensis sp.-Q67 (Q67), the quantitative characteristics of time-dependent hormetic dose responses in SCPs have not yet been investigated. In this study, 28 SCP mixtures were tested for luminescence toxicity against Q67 after five exposure durations (0.25, 3, 6, 9, and 12 h). With increasing exposure duration, the concentration response curves (CRCs) were classified as constant monotonic nonlinear (S-shaped) for four SCPs, S- to hormetic (J-shaped) for 13 SCPs, and constant J-shaped for 11 SCPs. Of 140 CRCs, 98 were J-shaped. An increased frequency of SCPs inducing hormesis was observed. The toxicity (pEC50) of the SCPs was independent of the exposure duration and product type. The maximum stimulatory effect (Emin) of the 12 SCPs increased with exposure duration. We proposed a modified parameter, the width of inhibition dose zone (WIDZ; EC50/EC10), to depict the width of inhibition dose zone. The WIDZ of S-shaped CRCs were significantly larger than that of J-shaped CRCs. In addition, the characteristic parameters reported in the general literature were analyzed. The good linear relationship between EC50 and the maximum stimulatory effective concentration (ECmin) indicated that toxicity may be transformed into stimulatory effects over exposure durations. The width of stimulation dose zone (WSDZ) and Emin of the seven SCPs had the same increasing trends with increasing exposure duration. The combination of WIDZ with other characteristic parameters (e.g., zero effective concentration point, ECmin, etc.) could better depict hormesis with low-dose stimulation and high-dose inhibition. The quantitative characteristics of the dose-responses of hormesis-inducing SCPs could provide reference basis for the risk assessment of SCP mixtures.

Polyacrylonitrile microfibers pose a significant threat to the early-stage survival of zebrafish

Microplastic pollution, especially microfibers (MFs), presents a critical global environmental challenge in natural water bodies. Yet, research on the toxic effects of MFs, particularly during early fish development, is limited. This study aimed to investigate MFs' toxic effects and mechanisms on early-stage zebrafish. Zebrafish embryos were exposed to varying concentrations of polyacrylonitrile microfibers (PanMfs) for 7 days. Results revealed PanMfs adhering to the embryos' surface, with higher concentrations accelerating heart rate and causing pericardial edema in post-hatching larvae. Larvae ingested PanMfs, leading to their accumulation in the intestines and increased levels of reactive oxygen species (ROS) and mitochondrial quantity. Notably, lipid metabolism and calcium ion related signaling pathways underwent significant changes. Low concentration MFs affected glycometabolism pathways, with potential roles for aldob and cacng1a, exhibiting pronounced increases in ROS levels. High concentration of MFs had the most profound impact on signal transduction-related pathways, and possibly triggering micromitophagy and apoptosis in zebrafish intestinal epithelial cells through the Kras/MAPK signaling pathway, with potential roles for kras and mapk9. Although ROS increase was somewhat alleviated, it resulted in decreased survival rates and restricted growth in high concentration of MFs group. These findings highlight the significant threat of MFs to the early survival of fish. MFs pollution prevention and control hold great significance in the conservation of fishery resources.

A study of long-term toxicity of multiple mixtures with hormetic effects by the characteristic parameter σ2(k∙ECx) and stepwise method

A previous study found that the characteristic parameter σ2(k∙ECx) (the concentration ECx and slope k of the concentrationresponse curve (CRC) at the effect x %) can predict the acute combined toxicity of multiple mixtures with S-shaped CRCs. In this paper, the competence of σ2(k∙ECx) to predict the long-term toxicity of multiple mixtures with J-shaped CRCs was explored using the Aliivibrio fischeri as the test organism. The combined toxicity was evaluated by the independent action (IA) model and the effect ratio (ERx) model. The stepwise method was used to divide J-shaped CRC into ML and MR (SL and SR). The results showed that the σ2(k∙ECx) and ERx of each segment was in good agreement with the exponential function. A new type of mixture was added to the original type A and type B, whose rules of interaction were opposite to those of type B (named opposite B, OB). This paper improves the understanding and analysis of the J-shaped CRCs in environmental risk assessment.

Resveratrol, Endocrine Disrupting Chemicals, Neurodegenerative Diseases and Depression: Genes, Transcription Factors, microRNAs, and Sponges Involved

We aimed to examine the molecular basis of the positive effect of resveratrol against amyotrophic lateral sclerosis (ALS), Parkinson's disease (PD), cognitive impairment (CI), and depression induced by a mixture of bisphenol A (BPA), BPS, and BPF. The CTD, GeneMania, Metascape, SwissADME, Cytoscape, MIENTURNET, miRNAsong, and Autodock Vina were the fundamental tools for analysis. Resveratrol exerts its protective effects on selected diseases induced by a mixture of BPA, BPS, and BPF through the following genes: PTGS2 and GSR for ALS; INS, IL6, BDNF, and SOD1 for PD; BDNF, CASP3, TNF, INS, IGF1, IL1B for CI; and BDNF, PTGS2, and IL6 for depression. Detoxification was noted as the most important for ALS, dopamine metabolism for PD, apoptosis for CI, and the selenium micronutrient network for depression. hsa-miR-377-3p, hsa-miR-1-3p, hsa-miR-128-3p, and hsa-miR-204-5p were highlighted. We created and tested in silico sponges that inhibited these miRNAs. NFE2L2, BACH1, PPARG, and NR4A3 were listed as the key transcription factors implicated in resveratrol's protective effect against harmful studied chemicals. Furthermore, resveratrol's physicochemical properties and pharmacokinetics are consistent with its therapeutic benefits in ALS, PD, CI, and depression, owing to its high gastrointestinal absorption, drug-likeness, non-P-glycoprotein substrate, and capacity to penetrate the blood-brain barrier.

SAHmap: Synergistic-antagonistic heatmap to evaluate the combined synergistic effect of mixtures of three pesticides on multiple endpoints of Caenorhabditis elegans

The environmental pollution caused by toxic chemicals such as pesticides has become a global problem. The mixture of dichlorvos (DIC), dimethoate (DIM), aldicarb (ALD) poses potential risks to the environment and human health. To fully explore the interaction of complex mixtures on Caenorhabditis elegans behavioral toxicity endpoint. This study created a synergistic-antagonistic heatmap (SAHmap) based on the combination index to systematically describe the toxicological interaction prospect of the mixture system. It was shown that the three pesticides and their binary as well as ternary mixture rays have significant concentration-response relationship on three behavioral endpoints of nematodes, From the perspective of synergistic-antagonistic heatmaps, all the mixture rays in the DIC-DIM mixture system showed strong synergism on the three behavioral and lethal endpoints. In the ternary mixture system, the five mixture rays showed different interaction between the behavioral endpoint and the lethal endpoint, and showed slight synergism to two behavioral endpoints as a whole. The emergence of synergism should arouse our attention to these hazardous chemicals. In addition, the use of SAHmap and the significant linear correlation among three behavioral endpoints further improved the efficiency of the study on the behavioral toxicity of pesticide mixtures to Caenorhabditis elegans.

Statistical modeling of hormesis quantities in inverted U-shaped dose-response relationships by reparameterization of a bilogistic model

Statistical procedures that allow quantitative determination of hormesis features are required for quantitative characterization of hormesis to provide information on the biphasic dose-response phenomenon and its variability. Only a direct estimate of individual effective doses in hormetic dose-response relationships is possible using prior extensions of the bilogistic model of Beckon and coworkers. This study presented further extensions of the model to determine the toxic potency and hormetic dose zone by estimating two effective doses simultaneously. In addition, the extended models allow for partitioning the hormetic dose zone through the dose of maximum stimulation. This study demonstrated a 4-step statistical modeling approach to quantify 20 hormesis quantities. The applicability and challenges of the mathematical procedures are discussed based on a few examples of hormetic dose-response relationships. The syntaxes for the analyses were provided as Appendix to demonstrate its implementation in SAS^® statistical software. Given the variability of hormetic dose-responses generated from toxicological studies in many disciplines, the proposed approach cannot apply to all dose-response patterns. However, we hope the proposed extensions could provide versatile statistical tools for quantitatively exploring a variety of biphasic dose-response curves.

Effects of heavy metals on cardiovascular diseases in pre and post-menopausal women: from big data to molecular mechanism involved

To assess the link between a mixed heavy metal (cadmium, lead, and mercury) and the 10-year risk of cardiovascular diseases (CVDs) in pre- and post-menopausal Korean women aged ≥20 years, as well as identify potential molecular mechanisms of mixed heavy metal-induced CVDs. Multivariate linear regression, weighted quantile sum (WQS) regression, quantile g-computation (gqcomp), and Bayesian kernel machine regression (BKMR) models were used to examine the effects of mixed heavy metals and the 10-year risk of CVDs. The Comparative Toxicogenomics Database, MicroRNA ENrichment TURned NETwork, and the microRNA sponge generator and tester were used as the key data-mining approaches. In our BKMR analysis, we found that the overall effect of mixed heavy metals was linked to the 10-year risk of CVDs in postmenopausal women in the upper 20^th percentiles and in premenopausal women in the upper 55^th percentiles. Mercury was identified as the key chemical for the 10-year risk of CVDs in pre- and postmenopausal women. In silico analysis revealed that a heavy metal mixture interacted with six genes associated with CVD development. Physical interactions (77.6%) were found to be the most common among CVD-related genes induced by the heavy metals studied. Several pathways have been identified as the main molecular mechanisms that could be affected by studied heavy metals and are implicated in the development of CVDs (e.g., lipid and lipoprotein metabolism, lipoprotein metabolism, cholesterol metabolism, and cardiovascular disease). ALB, APOE, ATF5, and CREB3L3 were the key genes and transcription factors related to CVDs induced by the mixture of the investigated heavy metals, respectively. The two miRNAs with the highest interaction and expression in the development of CVDs were hsa-miR-199a-5p and hsa-miR-199a-3p. We also designed and tested miRNA sponge sequences for these miRNAs. The cutoff thresholds for each heavy metal level linked with the 10-year risk of CVDs were described. A mixture of heavy metal exposures, especially mercury, was more strongly linked with the 10-year risk of CVDs in postmenopausal women than in premenopausal women. Early interventions in postmenopausal women should be considered to reduce CVD risks.

Joint action of binary mixtures based on parameter k·ECx from concentration-response curves in long-term toxicity assay

A previous acute toxicity study of binary mixtures showed that the combined toxicity can be predicted with the parameter k∙EC_x. To systematically investigate the ability of k∙EC_x to predict the chronic combined toxicity of binary mixtures, the toxicity of six contaminants and five binary mixtures was determined by long-term microplate toxicity analysis (L-MTA) using Aliivibrio fischeri as the test organism. The independent action model (IA) and the relative model deviation ratio (rMDR) were employed to determine the relationship between the Δ(k∙EC_x)% and rMDR_x. The results showed that these two factors conformed to the exponential function in long-term toxicity. Owing to the time-dependence of toxicity, the mixture type of chronic toxicity changes to the relative type of acute toxicity. If the acute toxicity of binary mixtures changes their mode of joint action throughout the concentration range, the chronic toxicity will also change their mode of joint action, and vice versa. This study clarified the change rules of the joint action of binary mixtures in acute and chronic toxicity which can promote research on chronic toxicity of binary mixtures.

Sensitivity of Ostracods to U, Cd and Cu: The Case of Cypridopsis vidua

The development of uranium mines has been necessary to obtain abundant and scarce uranium resources, but they also bring inevitable radioactive contamination to the surrounding soil, rivers and lakes. This paper explores the sensitivity of Cypridopsis vidua to the radioactive element uranium and the heavy elements cadmium and copper with single and combined acute toxicity experiments and combined toxicity model predictions. The results from the single toxicity experiments showed that the degree of toxic effects was cadmium > copper > uranium. The combined toxicity experiments showed that the compound toxicity of U-Cd and U-Cu was higher than the weakest component and lower than the strongest component, whereas the compound toxicity of Cd-Cu was higher than either of its components. When the overall proportion of a more toxic metal was increased, its mixed toxicity also increased, and vice versa. Combined toxicity predictions showed that the U-Cd combination was best described by the concentration additive (CA) model, the independent action (IA) model was more applicable to the Cd-Cu combination, and the most applicable model for the U-Cu combination changed depending on the concentration gradient. The acute toxicity data from this study provide a reference for the development of wastewater discharge standards for uranium mines, enriches the data related to the toxicity of uranium for ostracods and deepens the understanding of the threat of uranium pollution to aquatic ecosystems.

The protective effects of curcumin on metabolic syndrome and its components: In-silico analysis for genes, transcription factors, and microRNAs involved

BACKGROUND

We aimed to identify the molecular mechanisms behind curcumin's therapeutic benefits for metabolic syndrome (MetS) and its components.

METHODS

The Comparative Toxicogenomics Database, MIENTURNET, Metascape, GeneMania, and Cytoscape software were critical analytic tools.

RESULTS

Curcumin may have therapeutic effects on MetS and its components via the following genes: NOS3, IL6, INS, and ADIPOQ, particularly PPARG. Curcumin has higher docking scores than other genes with INS and PPARG (docking scores: -8.3 and -5.8, respectively). Physical interactions (56%) were found to be the most prevalent for dyslipidemia, co-expression for hypertension, obesity, T2DM, and MetS. "Galanin receptor pathway", "lipid particles composition", "IL-18 signaling pathway", "response to extracellular stimulus", and "insulin resistance" were listed in the first of the key pathways for MetS, dyslipidemia, hypertension, obesity, and diabetes, respectively. The protein-protein interaction enrichment analysis study also identified "vitamin B12 metabolism," "folate metabolism," and "selenium micronutrient network" as three major molecular pathways linked to MetS targeted by curcumin. PPARG was the key transcription factor that regulated practically all curcumin-targeted genes linked to MetS and its components. Curcumin targeted hsa-miR-155-5p, which has been linked to T2DM, hypertension, and MetS, as well as hsa-miR-130b-3p and hsa-miR-22-3p, which have been linked to dyslipidemia and obesity, respectively. In silico, sponges that regulated hsa-miR-155-5p were developed and evaluated. Curcumin, MetS, and its components have been found to target adipocytes, cardiac myocytes, smooth muscle, the liver, and pancreas. Curcumin's physicochemical properties and pharmacokinetics are closely connected with its therapeutic advantages in MetS and its components due to its high gastrointestinal absorption, drug-likeness, water solubility, and lipophilic nature. Curcumin is a CYP1A9 and CYP3A4 inhibitor. Although curcumin has a low bioavailability, it can be synthesized and administered to increase its pharmacokinetic features.

CONCLUSIONS

Curcumin needs to undergo therapeutic optimization and further study into its pharmacological structure before it can be used to treat MetS and its components.

Exposure to a mixture of heavy metals induces cognitive impairment: Genes and microRNAs involved

Converging evidence demonstrates that microRNAs (miRNAs) play an important role in the etiology of cognitive impairment. Thus, we aim to: (i) identify the molecular mechanisms of heavy metals, particularly miRNAs involved in the development of cognitive impairment; and (ii) generate miRNA sponges to prevent them from binding with their target messenger RNAs. The Comparative Toxicogenomics Database (CTD; http://ctd.mdibl.org), MicroRNA ENrichment TURned NETwork (MIENTURNET, http://userver.bio.uniroma1.it/apps/mienturnet/) and the microRNA sponge generator and tester (miRNAsong, http://www.med.muni.cz/histology/miRNAsong) were used as the core data-mining approaches in the current study. We observed that lead acetate, arsenic, gold, copper, iron, and aluminum, as well as their mixtures, had significant effects on the development of cognitive impairment. Although prevalent genes obtained from investigated heavy metals of cognitive impairment were different, the "PI3K-Akt signaling pathway", "pathways of neurodegeneration-multiple diseases", "apoptosis", "apoptosis-multiple species", "p53 signaling pathway", "NF-kappa B signaling pathway", and "Alzheimer's disease pathway" were highlighted. The mixed heavy metals altered the genes BAX, CASP3, BCL2, TNF, and IL-1B, indicating the significance of apoptosis and pro-inflammatory cytokines in the pathogenesis of cognitive impairment and the possibility of targeting these genes in future neuroprotective therapy. In addition, we used a network-based approach to identify key genes, miRNAs, pathways, and diseases related to the development of cognitive impairment. We also found 16 significant miRNAs related to cognitive impairment (hsa-miR-1-3p, hsa-let-7a-5p, hsa-miR-9-5p, hsa-miR-16-5p, hsa-miR-17-5p, hsa-miR-20a-5p, hsa-miR-26a-5p, hsa-miR-26b-5p, hsa-miR-34a-5p, hsa-miR-101-3p, hsa-miR-106a-5p, hsa-miR-128-3p, hsa-miR-144-3p, hsa-miR-199a-3p, hsa-miR-204-5p, and hsa-miR-335-5p). Finally, we created and evaluated miRNA sponge sequences for these miRNAs in silico. Further studies, including in vivo and in vitro, are needed to assess the link between these genes, miRNAs, pathways, and cognitive impairment.

New methods of top-to-down mixture toxicity prediction: A case study of eliminating of the effects of cosolvent from binary mixtures

At present, the toxicity prediction of mixtures mainly focuses on the concentration addition (CA) and independent action (IA) based on individual toxicants to predict the toxicity of multicomponent mixtures. This process of predicting the toxicity of multicomponent mixtures based on single substances or low component mixtures is called down-to-top method in this study. However, due to the particularity of some toxicants, we have to use the top-to-down idea to obtain or eliminate the toxicity of some components from mixtures. For example, the toxicity of toxicants is obtained from the toxicity of a mixture with, especially toxic, cosolvent added. In the study, two top-to-down methods, the inverse CA (ICA) and inverse IA (IIA) models, were proposed to eliminate the effects of a certain component from multicomponent mixtures. Furthermore, taking the eight binary mixtures consisting of different shapes of cosolvents (isopropyl alcohol (IPA) having hormesis and dimethyl sulfoxide (DMSO)) and toxicants (two ionic liquids and two pesticides) as an example, combined with the interaction evaluated by CA and IA model, the influence of different shapes of components on top-to-down toxicity prediction was explored. The results showed that cosolvent IPA having hormesis may cause unpredictable effects, even at low concentrations, and should be used with caution. For DMSO, most of the toxicant's toxicity obtained by ICA and IIA models were almost in accordance with those observed experimentally, which showed that ICA and IIA could effectively eliminate the effects of cosolvent, even if toxic cosolvent, from the mixture. Ultimately, a frame of cosolvent use and toxicity correction for the hydrophobic toxicant were suggested based on the top-to-down toxicity prediction method. The proposed methods improve the existing framework of mixture toxicity prediction and provide a new idea for mixture toxicity evaluation and risk assessment.

Prediction on the combined toxicities of stimulation-only and inhibition-only contaminants using improved inverse distance weighted interpolation

The evaluation of ecological risks of contaminant mixtures to organisms is very challenging due to the non-linear response of organisms to each component, especially under the co-existence of both stimulators and inhibitors. Whether the stimulatory effect can reduce or even offset the inhibitory effect would be critical to the risk assessment and the treatment measures of mixed pollutants. Here, the combined toxicity of sodium fluoride (NaF), a stimulator with stimulation rate >100%, and six compounds that cannot induce hormesis (four ionic liquids (ILs) and two pesticides) were studied. The time-dependent toxicity of each toxicant on Vibrio qinghaiensis sp.-Q67 was investigated at 0.25, 2, 4, 6, 8, 10 and 12 h. Results showed that four ILs and two pesticides failed to induce hormesis, while NaF induced hormesis from 2 to 6 h and induced stimulation only after 6 h and reached its maximum (650%) at 12 h. All mixture rays with NaF induced hormesis at different times. In the four NaF-IL mixture systems, the absolute value of maximum stimulation demonstrated an upwards and then a downwards trend with the increasing of mixture ratio of IL. In two NaF-pesticide systems, the maximum stimulation effect declined with the increasing of the mixture ratio of pesticide. The toxicities of the mixture were successfully predicted by the improved inverse distance weighted interpolation, which are not able to be predicted by the commonly used concentration addition or independent action models. This paper shed lights on evaluating the hormesis of mixtures and the ecological risk of fluoride.

A Universal Delayed Difference Model Fitting Dose-response Curves

PURPOSE

Dose-response curves, which fit a multitude of experimental data derived from toxicology, are widely used in physics, chemistry, biology, and other fields. Although there are many dose-response models for fitting dose-response curves, the application of these models is limited by many restrictions and lacks universality, so there is a need for a novel, universal dynamical model that can improve fits to various types of dose-response curves.

METHODS

We expand the hormetic Ricker model, taking the delay inherent in the dose-response into account, and develop a novel and dynamic delayed Ricker difference model (DRDM) to fit various types of dose-response curves. Furthermore, we compare the DRDM with other dose-response models to confirm that it can mimic different types of dose-response curves.

DATA ANALYSIS

By fitting various types of dose-response data sets derived from drug applications, disease treatment, pest control, and plant management, and comparing the imitative effect of the DRDM with other models, we find that the DRDM fits monotonic dose-response data well and, in most circumstances, the DRDM has a better imitative effect to non-monotonic dose-response data with hormesis than other models do.

RESULTS

The MSE of fits of the DRDM to S-shaped dose-response data (DS2-G) is not lower than those for four other models, but the MSE of fits to U-shaped (DS7) and inverted U-shaped dose-response data (DS10) were lower than for two other models. This means that the imitative effect of the DRDM is comparable to other models of monotonic dose-response data, but is a significant improvement compared to traditional models of non-monotonic dose-response data with hormesis.

CONCLUSION

We propose a novel dynamic model (DRDM) for fitting to various types of dose-response curves, which can reflect the dynamic trend of the population growth compared with traditional static dose-response models. By analyzing data, we have confirmed that the DRDM provides an ideal description of various dose-response observations and it can be used to fit a wide range of dose-response data sets, especially for hormetic data sets. Therefore, we conclude that the DRDM has a good universality for dose-response curve fitting.

Combined lethal toxicities of pesticides with similar structures to Caenorhabditis elegans are not necessarily concentration additives

Studies have shown that the mixture toxicity of compounds with similar modes of action (MOAs) is usually predicted by the concentration addition (CA) model. However, due to the lack of toxicological information on compounds, more evidence is needed to determine whether the above conclusion is generally applicable. In general, the same type of compounds with similar chemical structures have similar MOAs, so whether the toxicities of the mixture of these compounds are additive needs to be further studied. In this paper, three types of pesticides with similar chemical structures (three organophosphoruses, two carbamates and two neonicotinoids) that may have similar MOAs were selected and five binary mixture systems were constructed. For each system, five mixture rays with different concentration ratios were designed by the direct equipartition ray design (EquRay) method. The mortality of Caenorhabditis elegans was regarded as the endpoint for the toxicity exposure to single pesticides and binary mixtures. The combined toxicities were evaluated simultaneously using the CA model, isobologram and combination index. The structural similarity of the same type of pesticides was quantitatively analyzed according to the MACCS molecular fingerprint and the slope of dose-response curve at pEC₅₀. The results show that the toxicities of neonicotinoid mixtures and carbamate mixtures are almost antagonistic. The entire mixture system of dichlorvos and dimethoate produced synergism, and four of the five mixture rays of dimethoate and methamidophos induced antagonism, while among the mixture rays of dichlorvos and methamidophos, different concentrations showed different interaction types. The results of structural similarity analysis show that the size of structural similarity showed a certain quantitative relationship with the toxicity interaction of mixtures, that is, the structural similarity of the same type of pesticides may show an additive action in a certain range.

Assessing the combined toxicity of carbamate mixtures as well as organophosphorus mixtures to Caenorhabditis elegans using the locomotion behaviors as endpoints

Carbamate pesticides (CMs) and organophosphorus pesticides (OPs) have been widely used in agriculture and toxicologically affect non-target organisms. Although there are many reports about their toxicities, the combined behavioral toxicities of CM/OP mixtures on Caenorhabditis elegans have rarely been studied. In this study, body bend inhibition (BBI), head thrash inhibition (HTI), and swimming speed inhibition (SSI) by CMs and OPs were chosen as the toxicity endpoints. The locomotion behavioral toxicities of individual pesticides (carbofuran (CAR), methomyl (MET), chlorpyrifos (CPF), and triazophos (TAP)) and their binary mixtures on C. elegans were determined systematically and the toxicological interaction profiles of various CM/OP mixture rays constructed using the combination index. It was shown that four pesticides and their binary mixture rays have significant inhibitory effects on the locomotion behavior of C. elegans; that is, they produce locomotion behavioral toxicities and the toxicity of two OPs is higher than those of two CMs. The toxicological interactions in the binary CM and OP mixtures are different from each other. For example, one mixture ray (CAR-MET-R1) in the CM system on the SSI endpoint exhibits synergism at all concentration levels, another ray (CAR-MET-R3) displays low-dose synergism and high-dose additive action on BBI and HTI endpoints, and weak synergism at high-dose on SSI, and other rays perform additive action. Two rays (CPF-TAP-R1 and CPF-TAP-R2) in the OP mixture system display low-dose additive action and high-dose antagonism on the three endpoints. Another ray (CPF-TAP-R3) shows the additive action at all concentration levels. It can be concluded that it is not sufficient to evaluate the combined toxicity of binary CM/OP mixtures using only one concentration ratio ray and that it is necessary to examine multiple concentration ratios.

Elucidating the influence of environmentally relevant toxic metal mixture on molecular mechanisms involved in the development of neurodegenerative diseases: In silico toxicogenomic data-mining

This in silico toxicogenomic analysis aims to: (i) testify the hypothesis about the influence of the environmentally relevant toxic metals (lead, methylmercury (organic form of mercury), cadmium and arsenic) on molecular mechanisms involved in amyotrophic lateral sclerosis (ALS), Parkinson's Disease (PD) and Alzheimer's disease (AD) development; and (ii) demonstrate the capability of in silico toxicogenomic data-mining for distinguishing the probable mechanisms of mixture-induced toxic effects. The Comparative Toxicogenomics Database (CTD; http://ctd. mdibl.org) and Cytoscape software were used as the main data-mining tools in this analysis. The results have shown that there were 7, 13 and 14 common genes for all the metals present in the mixture for each of the selected neurodegenerative disease (ND), respectively: ALS, PD and AD. Physical interactions (68.18%) were the most prominent interactions between the genes extracted for ALS, co-expression (60.85%) for PD and interactions predicted by the server (44.30%) for AD. SOD2 gene was noted as the mutual gene for all the selected ND. Oxidative stress, folate metabolism, vitamin B12, AGE-RAGE, apoptosis were noted as the key disrupted molecular pathways that contribute to the neurodegenerative disease's development. Gene ontology analysis revealed biological processes affected by the investigated mixture (glutathione metabolic process was listed as the most important for ALS, cellular response to toxic substance for PD, and neuron death for AD). Our results emphasize the role of oxidative stress, particularly SOD2, in neurodegeneration triggered by environmental toxic metal mixture and give a new insight into common molecular mechanisms involved in ALS, PD and AD pathology.

BNNmix: A new approach for predicting the mixture toxicity of multiple components based on the back-propagation neural network

The chemical mixtures in various environmental media not only have concentration diversity but also mixture-ratio diversity. It is impossible to experimentally determine the toxicities of all mixtures; therefore, it is necessary to develop effective methods based on models to predict mixture toxicity. In this study, a new approach (BNNmix) based on the back-propagation neural network (BPNN) was developed and used to predict the toxicities of seven-component mixtures (consisting of two substituted phenols, two pesticides, two ionic liquids, and one heavy metal) on Caenorhabditis elegans. We found that the combined toxicities of various mixtures used in the experiments were neither global concentration-additive nor global response-additive, which implied that it was impossible to accurately predict the toxicities of such mixtures by using common models such as concentration addition (CA) and response addition (independent action, IA). Using the BNNmix approach to estimate or predict the toxicities of the mixtures under test, it was found that the predictive toxicities of various mixtures with different mixture ratios and concentrations were almost in accordance with those observed experimentally. Unlike the CA and IA models, the BNNmix approach can predict not only the toxicities of mixtures having toxicological interactions but also those with global concentration or response additivities.

Effects of soil acid stress on the survival, growth, reproduction, antioxidant enzyme activities, and protein contents in earthworm (Eisenia fetida)

This study focused on the study of earthworm survival, growth, reproduction, enzyme activities, and protein contents to evaluate and predict the effects of different soil pH levels and determine the optimal risk assessment indicators for the effects. Survival rate, growth rate, and cocoon number as well as four enzyme (glutathione peroxidase (GSH-PX), superoxide dismutase (SOD), peroxidase (POD), and catalase (CAT)) activities and two proteins (total protein (TP) and metallothionein (MT)) contents in earthworms were determined to characterize the responses of earthworm activity to five soil pH levels. These biological datasets (survival, growth, and reproduction) were compared with biochemical indexes (GSH-PX, SOD, POD, CAT, TP, and MT), mainly using biphasic dose-response models. The results indicated that the soil pH value had significant inhibitory effects on the survival, growth, and reproduction of earthworms beginning with 3.0, 4.0, and 5.2, respectively. The dose-response models (J-shaped and inverted U-shaped curves) statistics indicated that the critical values (ECZEP) of the GSH-PX, SOD, POD, CAT, TP, and MT inhibited by soil acid stress were 3.46, 3.76, 3.35, 3.54, 3.50, and 3.96 (average 3.60), respectively. In the present study, the fitting curve analysis showed that the responses of the CAT activities and TP and MT contents in earthworm in response to soil pH have the behavior of hormesis.

Similarities between the Yin/Yang Doctrine and Hormesis in Toxicology and Pharmacology

Hormesis is a generalizable dose-response relationship characterized by low-dose stimulation and high-dose inhibition. Despite debate over this biphasic dose-response curve, hormesis is challenging central beliefs in the evaluation of chemicals or drugs and has influenced biological model selection, concentration range, study design, and hypothesis testing. We integrate the traditional Chinese philosophy - Yin/Yang doctrine - into the representation of the Western hormetic dose-response relationship and review the Yin/Yang historical philosophy contained in the hormesis concept, aiming to promote general acceptance and wider applications of hormesis. We suggest that the Yin/Yang doctrine embodies the hormetic dose-response, including the relationship between the opposing components, curve shape, and time-dependence, and may afford insights that clarify the hormetic dose-response relationship in toxicology and pharmacology.

pH affects the hormesis profiles of personal care product components on luminescence of the bacteria Vibrio qinghaiensis sp. -Q67

Hormesis describes a specific phenomenon in a biphasic concentration-response curve: low concentrations stimulate a response, while high concentrations suppress it. Hormesis could be influenced by several environmental factors, e.g. pH. In this study, the concentration-response/bioluminescence inhibition profiles (CRPs) of six components in personal care products to Vibrio qinghaiensis sp.-Q67 were measured at five different pH levels. When the exposure lasted for 0.25 h, CRPs of the six components at various pH levels were S-shaped, except ascorbic acid 2-glucoside (AA2G) at pH 10.5. When it lasted for 12 h, the CRPs were J-shaped, except AA2G at pH 6.5, 7.5, and 9.5. To rationally explain these changes in hormesis expressed by J-shaped CRP, four characteristic parameters, the minimum effect (E_min) and its corresponding concentration (EC_min), the median effective concentration (EC₅₀), and the zero effect concentration point (ZEP, where the effect is 0 and the concentration is ZEP), were used to quantify the J-shaped CRP. The results indicated that these parameters vary with pH. Additionally, ZEP showed an excellent linear relationship with EC₁₀ (R² = 0.9994) at all pH levels, indicating that EC₁₀ could replace the no-observed effective concentration (NOEC) in ecological risk assessment. Furthermore, to elucidate the possible mechanism of hormesis, the binding of the components to the luciferase receptors was analyzed using molecular docking technology. The results showed that the components displaying hormesis bind more easily to the α subunit of luciferase than to the β subunit.

Conlecs: A novel procedure for deriving the concentration limits of chemicals outside the criteria of human drinking water using existing criteria and species sensitivity distribution based on quantitative structure-activity relationship prediction

Water quality criteria (WQC) for an increasing number of emerging chemicals need to be developed to protect human health and biological safety. Existing species sensitivity distribution (SSD) methods can only be used to help establish WQC for ecological protection, and cannot be extended to the protection of human beings from various hazards. In this study, a novel procedure called Conlecs is proposed to derive the concentration limits (ConLs) of pesticides outside the criteria for human drinking water (CHDW) using the existing criteria of pesticides and SSD integrated with the toxicity prediction achieved through robust QSAR models. Optimal SSD models of four pesticides (within the CHDW) and two pesticides (outside the CHDW) on 12 species were first constructed, and the existing ConLs of four pesticides within the CHDW were then utilized to select the most suitable species for the optimal proportions to avoid human hazards (PHH), allowing the ConLs of two pesticides outside the CHDW to be derived.

Novel Segmented Concentration Addition Method to Predict Mixture Hormesis of Chlortetracycline Hydrochloride and Oxytetracycline Hydrochloride to Aliivibrio fischeri

Hormesis is a concentration-response phenomenon characterized by low-concentration stimulation and high-concentration inhibition, which typically has a nonmonotonic J-shaped concentration-response curve (J-CRC). The concentration addition (CA) model is the gold standard for studying mixture toxicity. However, the CA model had the predictive blind zone (PBZ) for mixture J-CRC. To solve the PBZ problem, we proposed a segmented concentration addition (SCA) method to predict mixture J-CRC, which was achieved through fitting the left and right segments of component J-CRC and performing CA prediction subsequently. We selected two model compounds including chlortetracycline hydrochloride (CTCC) and oxytetracycline hydrochloride (OTCC), both of which presented J-CRC to Aliivibrio fischeri (AVF). The seven binary mixtures (M1-M7) of CTCC and OTCC were designed according to their molar ratios of 12:1, 10:3, 8:5, 1:1, 5:8, 3:10, and 1:12 referring to the direct equipartition ray design. These seven mixtures all presented J-CRC to AVF. Based on the SCA method, we obtained mixture maximum stimulatory effect concentration (ECm) and maximum stimulatory effect (Em) predicted by SCA, both of which were not available for the CA model. The toxicity interactions of these mixtures were systematically evaluated by using a comprehensive approach, including the co-toxicity coefficient integrated with confidence interval method (CTCICI), CRC, and isobole analysis. The results showed that the interaction types were additive and antagonistic action, without synergistic action. In addition, we proposed the cross point (CP) hypothesis for toxic interactive mixtures presenting J-CRC, that there was generally a CP between mixture observed J-CRC and CA predicted J-CRC; the relative positions of observed and predicted CRCs on either side of the CP would exchange, but the toxic interaction type of mixtures remained unchanged. The CP hypothesis needs to be verified by more mixtures, especially those with synergism. In conclusion, the SCA method is expected to have important theoretical and practical significance for mixture hormesis.

Polyethylene glycol 400 significantly enhances the stimulation of 2-phenoxyethanol on Vibrio qinghaiensis sp.-Q67 bioluminescence

Previous studies demonstrated long-term stimulation of some commercial personal care products (PCPs) on freshwater luminescent bacteria Vibrio qinghaiensis sp.-Q67 (Q67). However, whether a certain component can affect mixture's hormetic effect is still unknown. In this paper, two of ingredients in PCPs, 2-phenoxyethanol (PhE) and polyethylene glycol 400 (PEG400), were selected as object compounds to explore the relationship between concentration-response (CR) of mixtures and that of a single component. It was found that PEG400 has monotonic CR (MCR) on Q67 both at the short-term (0.25 h) and long-term (12 h) exposures while PhE has MCR at 0.25 h and hormetic CR (HCR) at 12 h. Here, the concentration-response curves (CRCs) of PEG400 at 0.25 and 12 h are overlapped each other and the CRCs of PEG400 are on the right of PhE. If the pEC₅₀ is taken as a toxic index, the toxicities of PEG400 at two times are basically the same, and those of PhE are the same, too, but PhE is twice as toxic as PEG400. For the mixtures of PEG400 and PhE, all rays except R1 have MCRs at 0.25 h while all rays have HCRs at 12 h where the higher the mixture ratio of PhE is, the more negative the maximum stimulation effect is. More importantly, the E_min values of all rays are more negative (1.79-3.17-fold) than that of PhE worked alone, which implies that the introduction of PEG400 significantly enhances stimulative effect of PhE. At 0.25 h, all binary mixture rays but R1 produce a low-concentration additive action and high-concentration synergism. At 12 h, all rays display additive action, antagonism, additive action, and synergism in turn when the concentration changes from low to high. The overall findings suggested toxicological interactions should be considered in the risk assessment of PCPs and their potential impacts on ecological balances.

Using an interpolation-based method (IDVequ) to predict the combined toxicities of hormetic ionic liquids

In the field of computational toxicology, predicting toxicological interaction or hormesis effect of a mixture from individuals is still a challenge. The two most frequently used model concentration addition (CA) and independent action (IA) also cannot solve these challenges perfectly. In this paper, we used IDV_equ (an interpolation method based on the Delaunay triangulation and Voronoi tessellation as well as the training set of direct equipartition ray design (EquRay) mixtures) to predict the toxicities of binary mixtures composed of hormetic ionic liquids (ILs). One of the purposes is to verify the predictive ability of IDV_equ. The other one is to improve the risk assessment of ILs mixtures especial hormetic ILs, because the toxicity reports of ILs mixtures are rarely reported in particular the toxicity of the hormetic ILs mixtures. Hence, we determined time-dependent toxicities of four ILs and their binary mixtures (designed by EquRay) to Vibrio qinghaiensis sp.-Q67 at first. Then, mixture toxicities were predicted and compared using the IDV_equ and CA. The results show that, the accuracy of IDV_equ is higher than the accuracy of CA. And, more important, to some mixtures out of the CA application, IDV_equ also can predict the mixture effects accurately. It showed that IDV_equ can be applied to predict the toxicity of any binary mixture regardless of the type of concentration-response curve of the components. These toxicity data provided useful information for researching the prediction of hormesis or toxicological interaction of the mixture and toxicities of ILs mixtures.

Combined Toxicity of 2,4-Dichlorophenoxyacetic Acid and Its Metabolites 2,4-Dichlorophenol (2,4-DCP) on Two Nontarget Organisms

2,4-Dichlorophenoxyacetic acid (2,4-D), a phenoxyalkanoic acid herbicide, is among the most widely distributed pollutants in the environment. 2,4-Dichlorophenol (2,4-DCP), as the main metabolite of 2,4-D, always accompanies 2,4-D. In this paper, we did research on the combined toxicities of 2,4-D and 2,4-DCP to Vibrio qinghaiensis sp.-Q67 (Q67) and Caenorhabditis elegans. It was found that the toxicity of 2,4-DCP is more severe than that of its parent 2,4-D at any concentration levels whether to Q67 or to C. elegans. Furthermore, 2,4-DCP to Q67 has the time-dependent toxicity. The toxicity of the mixture of 2,4-D and 2,4-DCP to Q67 is increasing with the exposure time, but that to C. elegans does not change over time. There is a good linear relationship between the pEC₅₀/pLC₅₀ value of binary mixture ray of 2,4-D and 2,4-DCP and the mixture ratio of 2,4-DCP, which implies the predictability of mixture toxicity of 2,4-D and 2,4-DCP. The toxicological interactions of the binary mixtures to Q67 are basically additive actions whether at 0.25 or at 12 h. However, most mixtures have antagonistic interactions against C. elegans.

Commercial personal care product mixtures exhibit hormetic concentration-responses to Vibrio qinghaiensis sp.-Q67

The biological effects related to personal care products (PCPs) are almost induced by some active ingredients in the PCPs rather than the PCP itself. In this study, 23 common and widely used toner, skin water, and make-up water (TSM) commodities were directly taken as mixture samples, and Vibrio qinghaiensis sp.-Q67 (Q67) was used as the test organism. The toxicities of the TSMs to Q67 were determined via microplate toxicity analysis at 0.25 h and 12 h. Each TSM commodity can be regarded as a complicated mixture (relative concentration is 1). It was shown that the concentration-response curves (CRCs) of 23 TSMs are monotonic sigmoid-shaped (S-shaped) at 0.25 h, the CRCs of six TSMs are also S-shaped but the other 17 TSMs are non-monotonic hormetic or J-shaped at 12 h. In addition, to effectively characterize the nature of the stimulation and inhibition phases, it is suggested that five parameters such as the EC_L (the median stimulation effective concentration (left)), E_min (the maximum stimulation effect), EC_min (the maximum stimulation effective concentration), ZEP (zero effect point where the effect is 0 and the concentration is ZEP), and EC₅₀ can depict the non-monotonic CRC. To the best of our knowledge, this is the first study about the hormetic CRCs of commercial PCP mixtures.

Hormetic effects of glyphosate on plants

As all herbicides act on pathways or processes crucial to plants, in an inhibitory or stimulatory way, low rates of any herbicide might be used to modulate plant growth, development, or plant composition. Glyphosate is the most used herbicide in the world, and very low rates of this herbicide can stimulate plant growth, an effect called hormesis. Several studies have shown that glyphosate applications at low rates can increase plant growth, induce shikimic acid accumulation, increase photosynthesis and stomatal opening, increase seed production, and shorten the plant life cycle. Low rates of glyphosate applied to leaves have been reported to cause one or more of these effects in an expanding group of species. Under field conditions, pesticide rates are not uniform, causing some target organisms to receive rates that are low enough to cause hormesis. Until the present, low rates of glyphosate have not been recommended as a growth stimulant for crops, because the hormetic dose can vary considerably, depending on many factors. The objective of the present review is to summarize and analyze existing information about the hormetic effects of glyphosate on plants, thus contributing to understanding how glyphosate hormesis takes place and evaluating the potential use of glyphosate to stimulate plant growth. © 2017 Society of Chemical Industry.

Modelling and simulation of biased agonism dynamics at a G protein-coupled receptor

Theoretical models of G protein-coupled receptor (GPCR) concentration-response relationships often assume an agonist producing a single functional response via a single active state of the receptor. These models have largely been analysed assuming steady-state conditions. There is now much experimental evidence to suggest that many GPCRs can exist in multiple receptor conformations and elicit numerous functional responses, with ligands having the potential to activate different signalling pathways to varying extents-a concept referred to as biased agonism, functional selectivity or pluri-dimensional efficacy. Moreover, recent experimental results indicate a clear possibility for time-dependent bias, whereby an agonist's bias with respect to different pathways may vary dynamically. Efforts towards understanding the implications of temporal bias by characterising and quantifying ligand effects on multiple pathways will clearly be aided by extending current equilibrium binding and biased activation models to include G protein activation dynamics. Here, we present a new model of time-dependent biased agonism, based on ordinary differential equations for multiple cubic ternary complex activation models with G protein cycle dynamics. This model allows simulation and analysis of multi-pathway activation bias dynamics at a single receptor for the first time, at the level of active G protein (αGTP), towards the analysis of dynamic functional responses. The model is generally applicable to systems with NG G proteins and N* active receptor states. Numerical simulations for NG=N*=2 reveal new insights into the effects of system parameters (including cooperativities, and ligand and receptor concentrations) on bias dynamics, highlighting new phenomena including the dynamic inter-conversion of bias direction. Further, we fit this model to 'wet' experimental data for two competing G proteins (Gi and Gs) that become activated upon stimulation of the adenosine A1 receptor with adenosine derivative compounds. Finally, we show that our model can qualitatively describe the temporal dynamics of this competing G protein activation.

Time-dependent and Pb-dependent antagonism and synergism towards Vibrio qinghaiensis sp.-Q67 within heavy metal mixtures

Toxicity interaction has aroused many researchers' interest in the combined toxicity of pollutants. Recently, some published studies have shown that the toxicity of some mixture pollutants is time dependent and well correlated with certain components in the mixture. Therefore, to investigate whether toxicity interaction is affected by the exposure time or certain components, synergism and antagonism within typical environmental contaminants of heavy metal mixtures were analyzed in different exposure times. Herein, three binary and one ternary mixture systems were designed by using three heavy metals: cadmium chloride, lead chloride (Pb) and manganese(ii) chloride tetrahydrate (Mn). For each mixture system, five mixture rays with different concentration ratios were arranged by direct equipartition ray design and uniform design ray methods. The toxicities of the three heavy metals and 20 mixture rays towards photobacteria Vibrio qinghaiensis sp.-Q67 (Q67) were determined by the established time-dependent microplate toxicity analysis (t-MTA) in different exposure durations of 0.25, 2, 4, 8 and 12 h. It was shown that the toxicities of three heavy metals (Cd, Pb and Mn) as well as their binary and ternary mixture rays to Q67 were also time dependent, but different metals or mixture rays showed different time characteristics. Surprisingly, some mixture rays exhibited antagonism or synergism with time dependency and the time characteristics varied in different mixture systems. Furthermore, the binary or ternary mixture systems with Pb displayed antagonism, while the Cd–Mn mixture system without Pb exhibited additive action or synergism, which indicated that Pb was probably the causative agent of antagonism produced by mixtures.

Toxicity interaction has gained much interest in the research of toxicity of mixture pollutants.

JSFit: a method for the fitting and prediction of J- and S-shaped concentration–response curves

Most monotonic S-shaped concentration–response curves (CRCs) can be satisfactorily described by a classical Hill equation. However, the Hill equation cannot effectively describe the non-monotonic J-shaped CRCs that display stimulation at low concentrations and inhibition at high concentrations. On the other hand, the physical meaning of the model parameters in current models describing the J-shaped CRCs is not very clear. It is well known that both toxicity experiments and the fitting process inevitably produce uncertainty. To effectively deal with the J-shaped concentration–response data with uncertainty and make the model parameters meaningful, we developed a method for the fitting of the J-shaped and/or S-shaped concentration–response data (simply called JSFit). The JSFit first uses one Hill equation (S-shaped) or combines with two Hill equations (J-shaped) for fitting, then nonlinear least squares fitting is performed by means of the Levenberg–Marquardt algorithm, and finally the observation-based confidence intervals of the fitting curve are constructed by the delta procedure. For the convenience of application, we wrote a computational program (JSFit) using the MATAB programming language and introduced automation of the initial parameters into the program. The JSFit was then successfully used in the fitting and prediction of the toxic data of pesticides, ionic liquids, antibiotics, and personal skin-care products on Vibrio Qinghaiensis sp.-Q67.

S- and J-shaped concentration–response curves (CRCs) can be satisfactorily described by one classical Hill equation and combines with two Hill equations respectively.

Global concentration additivity and prediction of mixture toxicities, taking nitrobenzene derivatives as an example

The toxicity of a mixture depends not only on the mixture concentration level but also on the mixture ratio. For a multiple-component mixture (MCM) system with a definite chemical composition, the mixture toxicity can be predicted only if the global concentration additivity (GCA) is validated. The so-called GCA means that the toxicity of any mixture in the MCM system is the concentration additive, regardless of what its mixture ratio and concentration level. However, many mixture toxicity reports have usually employed one mixture ratio (such as the EC₅₀ ratio), the equivalent effect concentration ratio (EECR) design, to specify several mixtures. EECR mixtures cannot simulate the concentration diversity and mixture ratio diversity of mixtures in the real environment, and it is impossible to validate the GCA. Therefore, in this paper, the uniform design ray (UD-Ray) was used to select nine mixture ratios (rays) in the mixture system of five nitrobenzene derivatives (NBDs). The representative UD-Ray mixtures can effectively and rationally describe the diversity in the NBD mixture system. The toxicities of the mixtures to Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). For each UD-Ray mixture, the concentration addition (CA) model was used to validate whether the mixture toxicity is additive. All of the UD-Ray mixtures of five NBDs are global concentration additive. Afterwards, the CA is employed to predict the toxicities of the external mixtures from three EECR mixture rays with the NOEC, EC₃₀, and EC₇₀ ratios. The predictive toxicities are in good agreement with the experimental toxicities, which testifies to the predictability of the mixture toxicity of the NBDs.

The time-dependent synergism of the six-component mixtures of substituted phenols, pesticides and ionic liquids to Caenorhabditis elegans

Traditional environmental risk assessment rarely focused on exposures to multi-component mixtures which may cause toxicological interactions and usually ignored that toxicity is a process in time, which may underestimate the environment risk of mixtures. In this paper, six chemicals belonging to three categories, two substituted phenols, two pesticides and two Ionic liquids, were picked to construct a six-component mixture system. To systematically examine the effects of various concentration compositions, the uniform design ray method was employed to design nine mixture rays with nine mixture ratios and for every mixture ray 12 concentration levels were specified by the fixed ratio ray design. The improved combination index was used to evaluate the combined toxicities of the mixtures to Caenorhabditis elegans (C. elegans) in the exposure times of 6, 12 and 24h. It was shown that the mixture rays display time-dependent synergism, i.e. the range of synergistic effect narrows and the strength of synergism runs down with exposure time, which illustrates that the mixture toxicity of some chemicals is not a sum of individual toxicities at some exposure times and it is necessary to consider the toxicological interaction in mixtures.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDV_equ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDV_equ successfully predicted the toxicities of various types of binary mixtures.

Hormesis of some organic solvents on Vibrio qinghaiensis sp.-Q67 from first binding to the β subunit of luciferase

Hormesis is a biphasic concentration–response relationship. During the luminescence inhibition test ofVibrio qinghaiensissp.-Q67 (Q67), some organic solvents display the hormesis phenomenon.

Complex toxicological interaction between ionic liquids and pesticides to Vibrio qinghaiensis sp.-Q67

Ionic liquids (ILs) and pesticides may coexist in ecosystems, because more and more people try to extract pesticides from various samples using ILs.

An automated fitting procedure and software for dose-response curves with multiphasic features

In cancer pharmacology (and many other areas), most dose-response curves are satisfactorily described by a classical Hill equation (i.e. 4 parameters logistical). Nevertheless, there are instances where the marked presence of more than one point of inflection, or the presence of combined agonist and antagonist effects, prevents straight-forward modelling of the data via a standard Hill equation. Here we propose a modified model and automated fitting procedure to describe dose-response curves with multiphasic features. The resulting general model enables interpreting each phase of the dose-response as an independent dose-dependent process. We developed an algorithm which automatically generates and ranks dose-response models with varying degrees of multiphasic features. The algorithm was implemented in new freely available Dr Fit software (sourceforge.net/projects/drfit/). We show how our approach is successful in describing dose-response curves with multiphasic features. Additionally, we analysed a large cancer cell viability screen involving 11650 dose-response curves. Based on our algorithm, we found that 28% of cases were better described by a multiphasic model than by the Hill model. We thus provide a robust approach to fit dose-response curves with various degrees of complexity, which, together with the provided software implementation, should enable a wide audience to easily process their own data.

Blocking the entrance of AMP pocket results in hormetic stimulation of imidazolium-based ionic liquids to firefly luciferase

The hormesis characterized by low-concentration stimulation and high-concentration inhibition has gained significant interest over the past decades. Some organic solvents and ionic liquids (ILs) have hormetic concentration responses (HCR) to bioluminescence such as firefly luciferase and Vibrio qinghaiensis sp.-Q67. In this study, we determine the effects of 1-alkyl-3-methylimidazolium chlorine ILs ([Cnmim]Cl, n=2, 4, 6, 8, 10 and 12) to firefly luciferase in order to verify the mechanism of hormesis. The luminescence inhibition toxicity tests show that the stimulation effects of [C8mim]Cl and [C10mim]Cl are obvious, [C6mim]Cl and [C12mim]Cl are minor, and [C2mim]Cl and [C4mim]Cl are rare. The enzyme kinetics show that [C8mim]Cl and [C10mim]Cl are the competitive inhibitors with ATP while [C2mim]Cl and [C4mim]Cl are the noncompetitive ones. Molecular dynamics simulation results reveal that imidazolium rings of [C8mim] and [C10mim] locate at the entrance of luciferin pocket which is adjacent to AMP pocket, while alkyl-chains insert into the bottom of the luciferin pocket. Combining the results from inhibition test, kinetics assay and molecular simulation, we can deduce that occupying AMP pocket by imidazolium ring is responsible for hormetic stimulation.

Predictability of the time-dependent toxicities of aminoglycoside antibiotic mixtures to Vibrio qinghaiensis sp.-Q67

The combined toxicities of all binary mixtures constructed by four aminoglycoside (AG) antibiotics are concentration additive, which has nothing to do with exposure time, mixture ratio, and concentration level.

Application of the combination index integrated with confidence intervals to study the toxicological interactions of antibiotics and pesticides in Vibrio qinghaiensis sp.-Q67

It is necessary to explore the effect of confidence intervals on the combination index (CI) so that rationally evaluate the toxicological interaction (synergism or antagonism) which is dependent on the concentration ratio, the mixture concentration and the exposure time. To effectively detect the toxicological interaction taking place in mixtures, we combined the CI with the observation-based confidence intervals (OCI) which can characterize the uncertainty in toxicity test and in data fitting. In time scale, the short-term (15min) and long-term (12h) toxicities of three chemicals (imidacloprid (IMI), pirimicarb (PIR) and streptomycin sulfate (STR)) and their binary mixtures on Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). The mixtures of IMI, PIR and STR have additive actions all but four IMI-PIR rays (R2-R5) at the effect levels above about 30-40% whose long-term toxicological interaction are synergism.