Potential Disrupting Effects of Wastewater-Derived Disinfection Byproducts on Chinese Rare Minnow (Gobiocypris rarus) Transthyretin: An In Vitro and In Silico Study.

The available information about whether wastewater-derived disinfection byproducts (DBPs) could elicit potential endocrine-related detrimental effects on aquatic organisms was scarce. Herein, the potential disrupting effects and underlying binding mechanism of 14 wastewater-derived aliphatic and aromatic DBPs and 12 other substances on Chinese rare minnow (Gobiocypris rarus) transthyretin (CrmTTR) were tested and revealed by in vitro and in silico methods. The amino acid sequences of CrmTTR were determined, and the recombinant CrmTTR with a molecular mass of 66.3 kDa was expressed and purified. In vitro assay results indicated that eight selected aromatic DBPs exhibited detectable CrmTTR disrupting ability. Meanwhile, six aliphatic DBPs were not CrmTTR binders. Molecular modeling results implied that hydrophobic hydrogen bonds and/or ionic pair interactions were non-negligible. Four binary classification models with high classification performance were constructed. A significant positive linear relationship was observed for the binding affinity data from CrmTTR and human TTR (n = 18, r = 0.922, p < 0.0001). However, the binding affinity for 13 out of 18 tested compounds with CrmTTR was higher than that with human TTR. All the results highlighted that some wastewater-derived DBPs may be potential disruptors on the aquatic organism endocrine system, and interspecies variation should not be neglected in future determination of the potential endocrine disrupting effects of wastewater-derived DBPs.

Effect of Hydrogel Contact Angle on Wall Thickness of Artificial Blood Vessel.

Vascular replacement is one of the most effective tools to solve cardiovascular diseases, but due to the limitations of autologous transplantation, size mismatch, etc., the blood vessels for replacement are often in short supply. The emergence of artificial blood vessels with 3D bioprinting has been expected to solve this problem. Blood vessel prosthesis plays an important role in the field of cardiovascular medical materials. However, a small-diameter blood vessel prosthesis (diameter < 6 mm) is still unable to achieve wide clinical application. In this paper, a response surface analysis was firstly utilized to obtain the relationship between the contact angle and the gelatin/sodium alginate mixed hydrogel solution at different temperatures and mass percentages. Then, the self-developed 3D bioprinter was used to obtain the optimal printing spacing under different conditions through row spacing, printing, and verifying the relationship between the contact angle and the printing thickness. Finally, the relationship between the blood vessel wall thickness and the contact angle was obtained by biofabrication with 3D bioprinting, which can also confirm the controllability of the vascular membrane thickness molding. It lays a foundation for the following study of the small caliber blood vessel printing molding experiment.

Emerging Polar Phenolic Disinfection Byproducts Are High-Affinity Human Transthyretin Disruptors: An in Vitro and in Silico Study.

Phenolic disinfection byproducts (phenolic-DBPs) have been identified in recent years. However, the toxicity data for phenolic-DBPs are scarce, hampering their risk assessment and the development of regulations on the acceptable concentration of phenolic-DBPs in water. In this study, the binding potency and underlying interaction mechanism between human transthyretin (hTTR) and five groups of representative phenolic-DBPs (2,4,6-trihalo-phenols, 2,6-dihalo-4-nitrophenols, 3,5-dihalo-4-hydroxybenzaldehydes, 3,5-dihalo-4-hydroxybenzoic acids, halo-salicylic acids) were determined and probed by competitive fluorescence displacement assay integrated with in silico methods. Experimental results implied that 2,4,6-trihalo-phenols, 2,6-dihalo-4-nitrophenols, and 3,5-dihalo-4-hydroxybenzaldehydes have a high binding affinity with hTTR. The hTTR binding potency of the chemicals with electron-withdrawing groups on their molecular structures were higher than that with electron-donor groups. Molecular modeling methods were used to decipher the binding mechanism between model compounds and hTTR. The results documented that ionic pair, hydrogen bonding and hydrophobic interactions were dominant interactions. Finally, a mechanism-based model for predicting the hTTR binding affinity was developed. The determination coefficient ( R2), leave-one-out cross validation Q2 ( QLOO2), bootstrapping coefficient ( QBOOT2), external validation coefficient ( QEXT2) and concordance correlation coefficient ( CCC) of the developed model met the acceptable criteria ( Q2 > 0.600, R2 > 0.700, CCC > 0.850), implying that the model had good goodness-of-fit, robustness, and external prediction performances. All the results indicated that the phenolic-DBPs have the hTTR disrupting effects, and further studies are needed to investigate their other mechanism of endocrine disruption.

Development of liposome/water partition coefficients predictive models for neutral and ionogenic organic chemicals.

Membrane/water partition coefficient (Km/w) is a vital parameter used to characterize the membrane permeability of compounds. Considering the Km/w value is difficult to observe experimentally for real biological membranes, liposome/water partition coefficient (Klip/w) is employed to approximate Km/w. Here, quantitative structure property relationship (QSPR) models for logKlip/w of the neutral organic chemicals and the neutral form of ionogenic organic chemicals (IOCs) (logKlip/w-neutral), ionic form of IOCs (logKlip/w-ionic), the speciation-corrected liposome-water distribution ratios at a pH = 7.40 (logDlip/w-(pH=7.40)) were developed. In the modeling, two modeling methods (multiple linear regressions (MLR) and k-nearest neighbor (kNN)) were used. The predictive variables employed here could be calculated from the molecular structure directly. For logKlip/w-neutral and logDlip/w-(pH=7.40), the logKOW and logDOW-based, non-logKOW and non-logDOW-based kNN-QSPR and MLR-QSPR models were developed, respectively. The evaluation results implied that the predictive performance of kNN-QSPR models is better than that of MLR-QSPR models. For logKlip/w-ionic, only one acceptable MLR-QSPR model was developed for cation and anion, respectively. The model quality of the derived models was evaluated following the OECD QSPR models validation guideline. The determination coefficient (R2), leave-one-out cross validation Q2 (Q2LOO) and bootstrapping coefficient (Q2BOOT), the external validation coefficient (Q2EXT) of all the models met the acceptable criteria (Q2 > 0.600, R2 > 0.700); while the root-mean-square error (RMSE) range from 0.351 to 0.857. All the results implied that the models had good goodness-of-fit, robustness and predictive ability. Therefore, the developed models could be used to fill the data gap for substances within the applicability domain on their missing logKlip/w-neutral, logKlip/w-ionic, logDlip/w-(pH=7.40) values.

Development of QSAR models for predicting the binding affinity of endocrine disrupting chemicals to eight fish estrogen receptor.

Endocrine disrupting effect has become a central point of concern, and various biological mechanisms involve in the disruption of endocrine system. Recently, we have explored the mechanism of disrupting hormonal transport protein, through the binding affinity of sex hormone-binding globulin in different fish species. This study, serving as a companion article, focused on the mechanism of activating/inhibiting hormone receptor, by investigating the binding interaction of chemicals with the estrogen receptor (ER) of different fish species. We collected the relative binding affinity (RBA) of chemicals with 17ß-estradiol binding to the ER of eight fish species. With this parameter as the endpoints, quantitative structure-activity relationship (QSAR) models were established using DRAGON descriptors. Statistical results indicated that the developed models had satisfactory goodness of fit, robustness and predictive ability. The Euclidean distance and Williams plot verified that these models had wide application domains, which covered a large number of structurally diverse chemicals. Based on the screened descriptors, we proposed an appropriate mechanism interpretation for the binding potency. Additionally, even though the same chemical had different affinities for ER from different fish species, the affinity of ER exhibited a high correlation for fish species within the same Order (i.e., Salmoniformes, Cypriniformes, Perciformes), which consistent with that in our previous study. Hence, when performing the endocrine disrupting effect assessment, the species diversity should be taken into account, but maybe the fish species in the same Order can be grouped together.

Development of chicken and fish muscle protein - Water partition coefficients predictive models for ionogenic and neutral organic chemicals.

Muscle protein was one of critical accumulation protein for anthropogenic chemicals. However, few predictive models were constructed for muscle protein up to now. In addition, some ionizable chemicals classes e.g. sulfonates were not successfully modeled in previously models, indicating considerable work would be needed. The major objective of this study was to develop quantitative structure-activity relationship (QSAR) models for predicting the muscle protein-water partition coefficient (logKMP/w) of chicken and fish. In the modeling, the n-octanol/water distribution coefficient (logD), functional groups, atom-centred fragments and chemical form adjusted descriptors were used to construct the models. The application domain of the derived models was defined by the Euclidean distance-based method and Williams plot. The modeling results indicated that the determination coefficient (R2), leave-one out cross validation Q2 (Q2LOO) and bootstrapping coefficient (Q2BOOT) of the QSAR models for chicken and fish were 0.882 and 0.929, 0.844 and 0.906, 0.779 and 0.792, respectively, implying the models had good goodness-of-fit and robustness. The coefficient determination (R2EXT) and external validation coefficient (Q2EXT) of the validation set for the two models were 0.874 and 0.937, 0.869 and 0.915, respectively, indicating the models had good predictive ability. The predictor variables selected to construct the logKMP/w models of chicken and fish included logD, the function groups, and the fraction of the ionized species (δI). Considering the molecular descriptors used here can be calculated from their molecular structures directly, the developed models could be easily used to fill the logKMP/w data gap for other chemicals within the applicability domain.

Development of predictive models for predicting binding affinity of endocrine disrupting chemicals to fish sex hormone-binding globulin.

Disturbing the transport process is a crucial pathway for endocrine disrupting chemicals (EDCs) exerting disrupting endocrine function. However, this mechanism has not received enough attention compared with that of hormones receptors and synthetase. Recently, we have explored the interaction between EDCs and sex hormone-binding globulin of human (hSHBG). In this study, interactions between EDCs and sex hormone-binding globulin of eight fish species (fSHBG) were investigated by employing classification methods and quantitative structure-activity relationships (QSAR). In the modeling, the relative binding affinity (RBA) of a chemical with 17ß-estradiol binding to fSHBG was selected as the endpoint. Classification models were developed for two fish species, while QSAR models were established for the other six fish species. Statistical results indicated that the models had satisfactory goodness of fit, robustness and predictive ability, and that application domain covered a large number of endogenous and exogenous steroidal and non-steroidal chemicals. Additionally, by comparing the log RBA values, it was found that the same chemical may have different affinities for fSHBG from different fish species, thus species diversity should be taken into account. However, the affinity of fSHBG showed a high correlation for fishes within the same Order (i.e., Salmoniformes, Cypriniformes, Perciformes and Siluriformes), thus the fSHBG binding data for one fish species could be used to extrapolate other fish species in the same Order.

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

The partition coefficients between bovine serum albumin (BSA) and water (KBSA/w) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logKBSA/w. However, it was found that the conventional descriptors are inappropriate for modeling logKBSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for KBSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logKBSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (Vs-adj-), the chemical form adjusted molecular dipole moment (dipolemomentadj), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logKBSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs.

Rational Selection of the 3D Structure of Biomacromolecules for Molecular Docking Studies on the Mechanism of Endocrine Disruptor Action.

Molecular modeling has become an essential tool in predicting and simulating endocrine disrupting effects of chemicals. A key prerequisite for successful application of molecular modeling lies in the correctness of 3D structure for biomacromolecules to be simulated. To date, there are several databases that can provide the experimentally-determined 3D structures. However, commonly, there are many challenges or disadvantageous factors, e.g., (a) lots of 3D structures for a given biomacromolecular target in the protein database; (b) the quality variability for those structures; (c) belonging to different species; (d) mutant amino acid residue in key positions, and so on. Once an inappropriate 3D structure of a target biomacromolecule was selected in molecular modeling, the accuracy and scientific nature of the modeling results could be inevitably affected. In this article, based on literature survey and an analysis of the 3D structure characterization of biomacromolecular targets belonging to the endocrine system in protein databases, six principles were proposed to guide the selection of the appropriate 3D structure of biomacromolecules. The principles include considering the species diversity, the mechanism of action, whether there are mutant amino acid residues, whether the number of protein chains is correct, the degree of structural similarity between the ligand in 3D structure and the target compounds, and other factors, e.g., the experimental pH conditions of the structure determined process and resolution.

Development of Quantitative Structure-Activity Relationship Models for Predicting Chronic Toxicity of Substituted Benzenes to Daphnia Magna.

The chronic toxicity of anthropogenic molecules such as substituted benzenes to Daphnia magna is a basic eco-toxicity parameter employed to assess their environmental risk. As the experimental methods are laborious, costly, and time-consuming, development in silico models for predicting the chronic toxicity is vitally important. In this study, on the basis of five molecular descriptors and 48 compounds, a quantitative structure-property relationship model that can predict the chronic toxicity of substituted benzenes were developed by employing multiple linear regressions. The correlation coefficient (R (2)) and root-mean square error (RMSE) for the training set were 0.836 and 0.390, respectively. The developed model was validated by employing 10 compounds tested in our lab. The R EXT (2) and RMSE EXT for the validation set were 0.736 and 0.490, respectively. To further characterizing the toxicity mechanism of anthropogenic molecules to Daphnia, comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA) models were developed.

Toward rational design of amines for CO2 capture: Substituent effect on kinetic process for the reaction of monoethanolamine with CO2.

Amines have been considered as promising candidates for post-combustion CO2 capture. A mechanistic understanding for the chemical processes involved in the capture and release of CO2 is important for the rational design of amines. In this study, the structural effects of amines on the kinetic competition among three typical products (carbamates, carbamic acids and bicarbonate) from amines+CO2 were investigated, in contrast to previous thermodynamic studies to tune the reaction of amines with CO2 based on desirable reaction enthalpy and reaction stoichiometry. We used a quantum chemical method to calculate the activation energies (Ea) for the reactions of a range of substituted monoethanolamines with CO2 covering three pathways to the three products. The results indicate that the formation of carbamates is the most favorable, among the three considered products. In addition, we found that the Ea values for all pathways linearly correlate with pKa of amines, and more importantly, the kinetic competition between carbamate and bicarbonate absorption pathways varies with pKa of the amines, i.e. stronger basicity results in less difference in Ea. These results highlight the importance of the consideration of kinetic competition among different reaction pathways in amine design.

Determination and prediction of the binding interaction between organophosphate flame retardants and p53.

Organophosphate flame retardants (OPFRs) have caused widespread concern because of the harm to the environment. In this study, to better explain the mechanism for the binding of OPFRs with the tumor suppressor gene p53, an integrated experimental and in silico approach was used. The binding constants of 10 OPFRs were measured by surface plasmon resonance technology (SPR). The effect of OPFRs on p53 gene and protein expression in ZF4 cells was determined by quantitative real-time PCR and Western blotting. Molecular docking and dynamics simulation were explored to find that the H-bonds and hydrophobic interactions were the dominant interaction between OPFRs and p53. On the basis of the observed interactions, proper molecular structural descriptors were used to build the quantitative structure-activity relationship (QSAR) model. The current QSAR model provided robustness, predictive ability, and mechanism interpretability. The applicability domain of the QSAR was discussed by the Williams plot. The results showed that H-bonds and electrostatic interaction governed the binding affinities between OPFRs and p53.

Predicting gaseous reaction rates of short chain chlorinated paraffins with ·OH: overcoming the difficulty in experimental determination.

Short chain chlorinated paraffins (SCCPs) are under evaluation for inclusion in the Stockholm Convention on persistent organic pollutants. However, information on their reaction rate constants with gaseous ·OH (kOH) is unavailable, limiting the evaluation of their persistence in the atmosphere. Experimental determination of kOH is confined by the unavailability of authentic chemical standards for some SCCP congeners. In this study, we evaluated and selected density functional theory (DFT) methods to predict kOH of SCCPs, by comparing the experimental kOH values of six polychlorinated alkanes (PCAs) with those calculated by the different theoretical methods. We found that the M06-2X/6-311+G(3df,2pd)//B3LYP/6-311 +G(d,p) method is time-effective and can be used to predict kOH of PCAs. Moreover, based on the calculated kOH of nine SCCPs and available experimental kOH values of 22 PCAs with low carbon chain, a quantitative structure-activity relationship (QSAR) model was developed. The molecular structural characteristics determining the ·OH reaction rate were discussed. logkOH was found to negatively correlate with the percentage of chlorine substitutions (Cl%). The DFT calculation method and the QSAR model are important alternatives to the conventional experimental determination of kOH for SCCPs, and are prospective in predicting their persistence in the atmosphere.

Recognizing high-priority disinfection byproducts based on experimental and predicted endocrine disrupting data: Virtual screening and in vitro study.

So far, about 130 disinfection by-products (DBPs) and several DBPs-groups have had their potential endocrine-disrupting effects tested on some endocrine endpoints. However, it is still not clear which specific DBPs, DBPs-groups/subgroups may be the most toxic substances or groups/subgroups for any given endocrine endpoint. In this study, we attempt to address this issue. First, a list of relevant DBPs was updated, and 1187 DBPs belonging to 4 main-groups (aliphatic, aromatic, alicyclic, heterocyclic) and 84 subgroups were described. Then, the high-priority endocrine endpoints, DBPs-groups/subgroups, and specific DBPs were determined from 18 endpoints, 4 main-groups, 84 subgroups, and 1187 specific DBPs by a virtual-screening method. The results demonstrate that most of DBPs could not disturb the endocrine endpoints in question because the proportion of active compounds associated with the endocrine endpoints ranged from 0 (human thyroid receptor beta) to 32% (human transthyretin (hTTR)). All the endpoints with a proportion of active compounds greater than 10% belonged to the thyroid system, highlighting that the potential disrupting effects of DBPs on the thyroid system should be given more attention. The aromatic and alicyclic DBPs may have higher priority than that of aliphatic and heterocyclic DBPs by considering the activity rate and potential for disrupting effects. There were 2 (halophenols and estrogen DBPs), 12, and 24 subgroups that belonged to high, moderate, and low priority classes, respectively. For individual DBPs, there were 23 (2%), 193 (16%), and 971 (82%) DBPs belonging to the high, moderate, and low priority groups, respectively. Lastly, the hTTR binding affinity of 4 DBPs was determined by an in vitro assay and all the tested DBPs exhibited dose-dependent binding potency with hTTR, which was consistent with the predicted result. Thus, more efforts should be performed to reveal the potential endocrine disruption of those high research-priority main-groups, subgroups, and individual DBPs.

Determining high priority disinfection byproducts based on experimental aquatic toxicity data and predictive models: Virtual screening and in vivo study.

Only about 100 disinfection byproducts (DBPs) have been tested for their potential aquatic toxicity. It is not known which specific DBPs, DBP main groups, and DBP subgroups are more toxic due to the lack of experimental toxicity data. Herein, high priority specific DBPs, DBP main groups, DBP subgroups, most sensitive model aquatic species, potential PBT and PMT (persistent, bioaccumulative/mobile, and toxic) DBPs were virtually screened for 1187 updated DBPs inventory. Priority setting based on experimental and predicted acute and chronic aquatic toxicity data found that the aromatic and alicyclic DBPs in four DBPs main groups showed high priority because larger proportions of aromatic and alicyclic DBPs are in high hazard categories (i.e. Acute and/or Chronic Toxic-1 or Toxic-2) according to the criteria in GHS system compared to the aliphatic and heterocyclic DBPs. The halophenols, estrogen-DBPs, nonhalogenated esters, and nonhalogenated aldehydes were recognized as high priority DBPs subgroups. For specific DBPs, 19 and 31 DBPs should be highly concerned in the future study because both acute and chronic toxicity of those DBPs to all of the three aquatic life (algae, Daphnia magna, fish) were classified as Toxic-1 and Toxic-2, respectively. The Daphnia magna and algae were sensitive to the acute toxicity of DBPs, while the fish and Daphnia magna were sensitive to the chronic toxicity of DBPs. One potential PBT (Tetrachlorobisphenol A) and four potential PMT DBPs were identified. For verification, the acute toxicity of four DBPs on three aquatic organism were performed, and their tested acute toxicity data to three aquatic organisms were consistent with the predictions. Our results could be beneficial to government regulators to adopt effective measures to limit the discharge of high priority DBPs and help the scientific community to develop or improve disinfection processes to reduce the production of high priority DBPs.

Draft genome sequence of Monascus ruber strain FM39-7.

In China, certain Monascus ruber strains are traditionally used as edible fungi. We sequenced the genome of M. ruber FM39-7 strain, an isolate from fermented rice. The genome is 25.89 Mb with a G + C content of 48.86%, containing 8485 annotated genes.

Anionic phenolic compounds bind stronger with transthyretin than their neutral forms: nonnegligible mechanisms in virtual screening of endocrine disrupting chemicals.

The molecular structures of many endocrine-disrupting chemicals (EDCs) contain groups that ionize under physiological pH conditions. It is unclear whether the neutral and ionic forms have different binding mechanisms with the macromolecular targets. We selected phenolic compounds and human transthyretin (hTTR) as a model system and employed molecular docking with quantum mechanics/molecular mechanics optimizations to probe the mechanisms. The binding patterns of ionizable ligands in hTTR crystal structures were also analyzed. We found that the anionic forms of the phenolic compounds bind stronger than the corresponding neutral forms with hTTR. Electrostatic and van de Waals interactions are the dominant forces for most of the anionic and neutral forms, respectively. Because of the dominant and orientational electrostatic interactions, the -O(-) groups point toward the entry port of the binding site. The aromatic rings of the compounds also form cation-π interactions with the -NH3(+) group of Lys 15 residues in hTTR. Molecular descriptors were selected to characterize the interactions and construct a quantitative structure-activity relationship model on the relative competing potency of chemicals with T4 binding to hTTR. It is concluded that the effects of ionization should not be neglected when constructing in silico models for screening of potential EDCs.

Disinfection byproducts of iopamidol, iohexol, diatrizoate and their distinct acute toxicity on Scenedesmus sp., Daphnia magna and Danio rerio.

The COVID-19 pandemic resulted in increasing the usage of iodinated contrast media (ICM), and thus an increase in the prevalence of ICM-contaminated wastewater. While ICM is generally safe, this has the potential to be problematic because as medical wastewater is treated and disinfected, various ICM-derived disinfection byproducts (DBPs) may be generated and released into the environment. However, little information was available about whether ICM-derived DBPs are toxic to aquatic organisms. In this study, the degradation of three typical ICM (iopamidol, iohexol, diatrizoate) at initial concentration of 10 µM and 100 µM in chlorination and peracetic acid without or with NH4+ was investigated, and the potential acute toxicity of treated disinfected water containing potential ICM-derived DBPs on Daphnia magna, Scenedesmus sp. and Danio rerio was tested. The degradation results suggested that only iopamidol was significantly degraded (level of degradation >98%) by chlorination, and the degradation rate of iohexol and diatrizoate were significantly increased in chlorination with NH4+. All three ICM were not degraded in peracetic acid. The toxicity analysis results indicate that only the disinfected water of iopamidol and iohexol by chlorination with NH4+ were toxic to at least one aquatic organism. These results highlighted that the potential ecological risk of ICM-contained medical wastewater by chlorination with NH4+ should not be neglected, and peracetic acid may be an environment-friendly alternative for the disinfection of wastewater containing ICM.

Endocrine disrupting effect and reproductive toxicity of the separate exposure and co-exposure of nano-polystyrene and diethylstilbestrol to zebrafish.

The co-occurrence of nanoplastics and other pollutants in the environment has gotten a lot of attention, but information on the biological toxicity of their co-exposure was limited. This study aims to reveal the endocrine disrupting effect and reproductive toxicity of nano-polystyrene (NPS) and diethylstilbestrol (DES) to zebrafish under separate and combined exposure. Results indicated that NPS and DES exposure in isolation reduced the hepatosomatic index and gonadosomatic index, and altered the cell maturity in gonads in both cases. Even worse, the co-exposure of NPS and DES exacerbated the damage to the liver and gonads of fish. The two pollutants individually inhibited the secretion of sex hormones and vitellogenin. The inhibition effect of DES was especially dose-dependent, while NPS had weaker effect than DES. Their combined action on the secretion of sex hormones and vitellogenin exhibited additive effect. However, NPS did not affect the content of thyroid hormones in fish, and also had no significant effect on the reduction of thyroid hormone caused by DES exposure. Furthermore, their co-exposure decreased the cumulative eggs from 1031 to 306, and the spawning number from 12 to 8. The fertilization rate and hatchability rete of eggs were reduced by 30.9% and 40.4%, respectively. The abnormality rate of embryos was 65.0%, significantly higher than in separate DES and NPS groups (55.7% and 30.8% respectively). The abnormal development of offspring was mainly pericardial cyst, spinal curvature, and growth retardation.

Research Progress of the Endocrine-Disrupting Effects of Disinfection Byproducts.

Since 1974, more than 800 disinfection byproducts (DBPs) have been identified from disinfected drinking water, swimming pool water, wastewaters, etc. Some DBPs are recognized as contaminants of high environmental concern because they may induce many detrimental health (e.g., cancer, cytotoxicity, and genotoxicity) and/or ecological (e.g., acute toxicity and development toxicity on alga, crustacean, and fish) effects. However, the information on whether DBPs may elicit potential endocrine-disrupting effects in human and wildlife is scarce. It is the major objective of this paper to summarize the reported potential endocrine-disrupting effects of the identified DBPs in the view of adverse outcome pathways (AOPs). In this regard, we introduce the potential molecular initiating events (MIEs), key events (KEs), and adverse outcomes (AOs) associated with exposure to specific DBPs. The present evidence indicates that the endocrine system of organism can be perturbed by certain DBPs through some MIEs, including hormone receptor-mediated mechanisms and non-receptor-mediated mechanisms (e.g., hormone transport protein). Lastly, the gaps in our knowledge of the endocrine-disrupting effects of DBPs are highlighted, and critical directions for future studies are proposed.