An artificial intelligence-based model for predicting reproductive toxicity of bisphenol analogues mixtures to the rotifer Brachionus calyciflorus.

The joint toxicity effects of mixtures, particularly reproductive toxicity, one of the main causes of aquatic ecosystem degradation, are often overlooked as it is impractical to test all mixtures. This study developed and evaluated the following models to predict the concentration response curve concerning the joint reproductive toxicity of mixtures of three bisphenol analogues (BPA, BPF, BPAF) on the rotifer Brachionus calyciflorus: concentration addition (CA), independent action (IA), and two deep neural network (DNN) models. One applied mixture molecular descriptors as input variables (DNN-QSAR), while the other applied the ratios of chemicals in the mixtures (DNN-Ratio). Descriptors related to molecular mass were found to be of greater importance and exhibited a proportional relationship with toxic effects. The results indicate that the range of correlation coefficients (R2) between predicted and measured values for various mixture rays by CA and IA models is 0.372 to 0.974 and - 0.970 to 0.586, respectively. The R2 values for DNN-Ratio and DNN-QSAR were 0.841 to 0.984 and 0.834 to 0.991, respectively, demonstrating that models developed by DNN significantly outperform traditional models in predicting the joint toxicity of mixtures. Furthermore, DNN-QSAR not only predicts mixture toxicity but also provides accurate toxicity predictions for BPA, BPF, and BPAF, with R2 values of 0.990, 0.616, and 0.887, respectively, while DNN-Ratio yields values of 0.920, 0.355, and - 0.495. The study also found that the joint effects of mixtures are primarily influenced by the total concentration of the mixtures, and an increase in total concentration shifts the joint effects towards addition. This study introduces a novel approach to predict joint toxicity and analyze the influencing factors of joint effects, providing a more comprehensive assessment of the ecological risk posed by mixtures.

Estimating the temporal and spatial distribution and threats of bisphenol A in temperate lakes using machine learning models.

Bisphenol A (BPA) is easily enriched in many human-disturbed watersheds, particularly lakes with poor water mobility, which is posing a threat to aquatic biota. While previous studies have focused on the concentration of BPA in water and its toxicity to aquatic organisms, a small amount of measured data is not enough to reveal the temporal and spatial distribution and threats of BPA, and estimate the ecological risk in watersheds. Therefore, we collected 164 measured BPA data points from Taihu Lake to develop machine learning models using random forest (RF), support vector machine (SVM) and least square regression (LSR) and created month-by-month watershed prediction maps in temperate lakes to estimate the spatiotemporal distribution and threats of BPA. Due to RF's superior robustness to noisy data, the RF model exhibits the best performance among the three algorithms. The RF model showed acceptable predictive performance on the modeling dataset (coefficients of determination and root-mean-square error for the training set were 0.927 and 17.499, respectively, and 0.607, 39.645 for the validation set, respectively). The maps indicated that areas susceptible to anthropogenic activities were more severely polluted by BPA, and rainy climate may favor the migration of BPA to aquatic ecosystems. The model was also applied to predict 42 data points of BPA collected from Dianchi Lake, and the results showed that most predicted data were within a factor of 10 of the measured data, but the prediction accuracy of the model has declined. The ecological risks in the two lakes were evaluated and attention should be paid to the regions with higher risks. Our study provided a novel idea for comprehensive monitoring of an unconventional trace pollutant with endocrine disrupting effects in aquatic ecosystems and analyzing their spatiotemporal distribution, which will contribute to the scientific assessment of the ecological risk of BPA.

Assessing the impact of river connectivity on fish biodiversity in the Yangtze River Basin using a multi-index evaluation framework.

The Yangtze River Basin, the world's third-largest river basin and a hot spot for global biodiversity conservation, is facing biodiversity crisis caused by reduced river connectivity. The deterioration arises from four dimensions: longitudinal, lateral, vertical and temporal. However, limited research has quantified the spatiotemporal connectivity of the Yangtze River Basin and further evaluated the consequent impact on fish biodiversity. In our study, a multi-index evaluation framework was developed to assess the variations in the four-dimensional connectivity of the Yangtze River Basin from 1980 to 2020, and fish biodiversity affected by reduced connectivity was detected by environmental DNA metabarcoding. Our results showed that the Yangtze River Basin suffers from a pronounced connectivity reduction, with 67% of assessed rivers experiencing deteriorated connectivity in recent years. The lost fish biodiversity along the river reaches with the worst connectivity was likely attributed to the construction of hydropower plants. The headwaters and the downstreams of most hydropower plants had a higher fish biodiversity compared with reservoirs. The free-flowing reaches in the downstream of the lowest hydropower station, had higher lotic fish abundance compared with that in the upstream. As for the entire Yangtze River Basin, 67% of threatened fish species, with 70% endemic species, were threatened by reduced river connectivity. Our result indicates that the massive loss of river connectivity changes the spatiotemporal patterns of fish community and threatens protected fish. More effective measures to restore the populations of affected fish in rivers with reduced river connectivity are required.

Environmental DNA unveiling the fish community structure and diversity features in the Yangtze River basin.

Fish, as top predators in aquatic ecosystems, play an important role in maintaining the structure and functioning of these ecosystems, making their diversity a topic of great interest. This study focused on the Yangtze River Basin to investigate the fish community structure and diversity using environmental DNA (eDNA) technology. The results showed that a total of 71616 fish operational taxonomic units (OTUs) and 90 fish belonging to 23 families were detected, with the Cyprinidae family being the dominant group, followed by the Cobitidae, Amblycipitidae, etc. Compared to historical traditional morphological fish surveys, the quantity of fish detected using eDNA was relatively low, but the overall distribution pattern of fish communities was generally consistent. The highest fish Shannon-Wiener diversity index in the Yangtze River Basin sites reaches 2.60 with an average value of 1.25. The fish diversity index was higher in the downstream compared to the middle and upstream regions, and there were significant differences among different sampling sites. Significant environmental factors influencing α-diversity included chlorophyll-a, chemical oxygen demand, dissolved oxygen, total nitrogen, and elevation. Non-metric multidimensional scaling (NMDS) analysis revealed significant differences in fish community composition between the upstream and middle/lower reaches of the Yangtze River, while the composition of fish communities in the middle and lower reaches was more similar. Redundancy analysis (RDA) indicated that total organic carbon (TOC) was positively correlated with fish community distribution in the upstream, while water temperature and NO3-N were negatively correlated with fish distribution in the upstream. NH3-N and CODMn were negatively correlated with fish distribution in the middle and downstream regions, indicating a relatively severe water pollution in these areas. Additionally, fish communities in the Yangtze River displayed a typical distance decay pattern.

Glycolic acid-based deep eutectic solvents boosting co-production of xylo-oligomers and fermentable sugars from corncob and the related kinetic mechanism.

BACKGROUND: Xylo-oligomers are a kind of high value-added products in biomass fractionation. Although there are several chemical methods to obtain xylo-oligomers from biomass, the reports about the deep eutectic solvents (DESs)-mediated co-production of xylo-oligomers and fermentable sugars and the related kinetic mechanism are limited. RESULTS: In this work, glycolic acid-based DESs were used to obtain xylo-oligomers from corncob. The highest xylo-oligomers yield of 65.9% was achieved at 120 °C for 20 min, of which the functional xylo-oligosaccharides (XOSs, DP 2-5) accounted for up to 31.8%. Meanwhile, the enzymatic digestion of cellulose and xylan in residues reached 81.0% and 95.5%, respectively. Moreover, the addition of metal inorganic salts significantly accelerated the hydrolysis of xylan and even the degradation of xylo-oligomers in DES, thus resulting in higher selectivity of xylan removal. AlCl3 showed the strongest synergistic effect with DES on accelerating the processes, while FeCl2 is best one for xylo-oligomers accumulation, affording the highest xylo-oligomers yield of 66.1% for only 10 min. Furthermore, the kinetic study indicates that the 'potential hydrolysis degree' model could well describe the xylan hydrolysis processes and glycolic acid/lactic acid (3:1) is a promising solvent for xylo-oligomers production, in particular, it worked well with FeCl2 for the excellent accumulation of xylo-oligomers. CONCLUSIONS: Glycolic acid-based deep eutectic solvents can be successfully applied in corncob fractionation with excellent xylo-oligomers and fermentable sugars yields on mild conditions, and the large amount of xylo-oligosaccharides accumulation could be achieved by specific process controlling. The strategies established here can be useful for developing high-valued products from biomass.

Acute Toxicity Assessment and Prediction Models of Four Heavy Metals.

Water quality criteria (WQC) are developed to protect aquatic organisms. Toxicity data of local fish are essential to improve the applicability of WQC derivatives. However, the paucity of local cold-water fish toxicity data limits the development of WQC in China. Brachymystax lenok is a representative Chinese-endemic cold-water fish, which plays an important role in the characterization of metal toxicity in the water environment. Whereas, the ecotoxicological effects of copper, zinc, lead and cadmium, as well as its potential as a test species for the metal WQC, remain to be investigated. In our study, acute toxicity tests of copper, zinc, lead and cadmium were performed on this fish according to the OECD method and 96 h-LC50 values were calculated. The results showed that the 96 h-LC50 values of Cu2+, Zn2+, Pb2+ and Cd2+ for B. lenok were 134, 222, 514 and 734 µg/L, respectively. Toxicity data for freshwater species and Chinese-native species were collected and screened, and the mean acute values of each metal for each species were ranked. The results showed that the accumulation probability of zinc by B. lenok was the lowest and less than 15%. Thus, B. lenok was sensitive to Zn and can be considered as the test cold-water fish for derivation of Zn WQC. In addition, B. lenok in comparison with warm-water fish, we found that cold-water fish are not always more sensitive to heavy metals than warm-water fish. Finally, the models for toxic effects prediction of different heavy metals on the same species were constructed and evaluated the reliability of the model. We suggest that the alternative toxicity data provided by the simulations can be used to derive WQC for metals.

New insights into the mechanism of ammonia toxicity: Focus on Cactus.

The NF-κB signaling pathway is the most critical pathway in innate immunity. IκB (Cactus) is the primary cytoplasmic inhibitor of NF-κB (Dorsal). In this study, we found that ammonia exposure could significantly induce the expression of Cactus, in a dose-dependent manner in different tissues, with the highest expression in the gill of Corbicula fluminea. The expression pattern-related elements (Tube and Dorsal) in the NF-κB signaling pathway were also analyzed, showing significant up-regulation in 48 h. There was an inhibitory effect between up-regulated Cactus and Dorsal in 72 h, which may regulate Dorsal as a negative feedback pathway function to control the expression of pro-inflammatory cytokines (IL-1ß, IL-6, and TNF-α). Besides, through molecular docking simulation, we found that the Cactus could be directly activated by NH3, complementing the regulatory mechanism of the Cactus. To further test our hypothesis, the levels of pro-inflammatory cytokines decreased after adding PDTC (the antioxidant of Cactus/IκB), suggesting that PDTC can prevent the degradation of Cactus, inhibit Dorsal translocating into the nucleus, and activate the pro-inflammatory cytokines. This revealed the inhibitory effect of Cactus on activating Dorsal/NF-κB factors in the NF-κB signaling pathway. Thus, we suggested that the Cactus is an essential regulator of ammonia-activated inflammation in C. fluminea, which was reported to be activated only by bacteria and immune stimulators. Our study provides a new perspective on the mechanism of ammonia toxicity in invertebrates.

Health risk assessment and development of human health ambient water quality criteria for PBDEs in China.

Polybrominated diphenyl ethers (PBDEs) are not only a class of highly efficient brominated flame retardants (BFRs) but also a class of typical persistent organic pollutants (POPs) that are persistent and widely distributed in various environmental media. This study examined the concentrations of PBDEs in five environmental media (water, soil, air, dust, and food) and two human body media (human milk and blood) in China from 2010 to 2020. In addition, this study conducted multi-pathway exposure health risk assessments of populations of different ages in urban, rural, key regions, and industrial factories using the Monte-Carlo simulation. Finally, the human health ambient water quality criteria (AWQC) of eight PBDEs were derived using Chinese exposure parameters and bioaccumulation factors (BAFs). The results showed that the eastern and southeastern coastal regions of China were heavily polluted by PBDEs, and the variation trends of the ΣPBDEs concentrations in the different exposure media were not consistent. PBDEs did not pose a risk to urban and rural residents in ordinary regions, but the hazard indexes (HIs) for residents in key regions and occupational workers exceeded the safety threshold. Dust exposure was the primary exposure pathway for urban and rural residents in ordinary regions, but for residents in key regions and occupational workers, dietary exposure was the primary exposure pathway. BDE-209 was found to be the most serious individual PBDE congener in China. The following human health AWQC values of the PBDEs were derived: drinking water exposure: 0.233-65.2 µg·L-1; and drinking water and aquatic products exposure: 8.51 × 10-4-1.10 µg·L-1.

Prediction of chemical reproductive toxicity to aquatic species using a machine learning model: An application in an ecological risk assessment of the Yangtze River, China.

The endocrine disrupting chemicals (EDCs) have been at the forefront of environmental issues for over 20 years and are a principle factor considered in every ecological risk assessment, but this kind of risk assessment faces difficulties. The expense, time cost of in vivo tests, and lack of toxicity data are key limiting factors for the ability to conduct ecological risk assessments of EDCs to aquatic species. In this study, a machine learning model named the support vector machine (SVM) was used to predict the reproductive toxicity of EDCs, and the performance of the models was evaluated. The results showed that the SVM model provided more accurate toxicity prediction data compared with the interspecies correlation estimation (ICE) model developed by previous study to predict the reproductive toxicity. The application of the predicted toxicity data was an important supplement to the observed data for the ecological risk assessment of EDCs in the Yangtze River, where estrogens and phenolic compounds have been found at some sampling sites in the middle and lower reaches. The results showed that the ecological risk of estrone, 17ß-estradiol, and ethinyl estradiol were significant. This study revealed the application potential of machine learning models for the prediction of reproductive toxicity effects of EDCs. This can provide reliable alternative toxicity data for the ecological risk assessments of EDCs.

Methodology of fish eDNA and its applications in ecology and environment.

Fish environmental DNA (eDNA) studies have made substantial progress during the past decade, and significant advances in monitoring fishes have been gained by taking advantage of this technology. Although a number of reviews concerning eDNA are available and some recent fish eDNA reviews focused on fisheries or standard method have been published, a systematic review of methodology of fish eDNA and its applications in ecology and environment has not yet been published. To our knowledge, this is the first review of fish eDNA for solving ecological and environmental issues. First, the most comprehensive literature analysis of fish eDNA was presented and analyzed. Then, we systematically discuss the relevant experiments and analyses of fish eDNA, and infers that standard workflow is on the way to consensus. We additionally provide reference sequence databases and the primers used to amplify the reference sequences or detecting fish eDNA. The abiotic and biotic conditions affecting fish eDNA persistence are also summarized in a schematic diagram. Subsequently, we focus on the major achievements of fish eDNA in ecology and environment. We additionally highlight the exciting new tools, including in situ autonomous monitoring devices, CRISPR nucleic acid detection technology, and meta-omics technology for fish eDNA detection in future. Ultimately, methodology of fish eDNA will provide a wholly new paradigm for conservation actions of fishes, ecological and environmental management at a global scale.

Modeling the ecological status response of rivers to multiple stressors using machine learning: A comparison of environmental DNA metabarcoding and morphological data.

Understanding the ecological status response of rivers to multiple stressors is a precondition for river restoration and management. However, this requires the collection of appropriate data, including environmental variables and the status of aquatic organisms, and analysis via a suitable model that captures the nonlinear relationships between ecological status and various stressors. The morphological approach has been the standard data collection method employed for establishing the status of aquatic organisms. However, this approach is very laborious and restricted to a specific set of organisms. Recently, an environmental DNA (eDNA) metabarcoding data approach has been developed that is far more efficient than the morphological approach and potentially applicable to an unlimited set of organisms. However, it remains unclear how well eDNA metabarcoding data reflects the impacts of environmental stressors on aquatic ecosystems compared with morphological data, which is essential for clarifying the potential applications of eDNA metabarcoding data in the ecological monitoring and management of rivers. The present work addresses this issue by modeling organism diversity based on three indices with respect to multiple environmental variables in both the catchment and reach scales. This is done by corresponding support vector machine (SVM) models constructed from eDNA metabarcoding and morphological data on 24 sampling locations in the Taizi River basin, China. According to the mean absolute percent error (MAPE) between the measured diversity index values and the index values predicted by the SVM models, the SVM models constructed from eDNA metabarcoding data (MAPE = 3.87) provide more accurate predictions than the SVM models constructed from morphological data (MAPE = 28.36), revealing that the eDNA metabarcoding data better reflects environmental conditions. In addition, the sensitivity of SVM model predictions of the ecological indices for both catchment-scale and reach-scale stressors is evaluated, and the stressors having the greatest impact on the ecological status of rivers are identified. The results demonstrate that the ecological status of rivers is more sensitive to environmental stressors at the reach scale than to stressors at the catchment scale. Therefore, our study is helpful in exploring the potential applications of eDNA metabarcoding data and SVM modeling in the ecological monitoring and management of rivers.

Comparative metagenomics reveals the microbial diversity and metabolic potentials in the sediments and surrounding seawaters of Qinhuangdao mariculture area.

Qinhuangdao coastal area is an important mariculture area in North China. Microbial communities play an important role in driving biogeochemical cycle and energy flow. It is necessary to identify the microbial communities and their functions in the coastal mariculture area of Qinhuangdao. In this study, the microbial community compositions and their metabolic potentials in the sediments and their surrounding seawaters of Qinhuangdao mariculture area were uncovered by the 16S rRNA gene amplicon sequencing and metagenomic shotgun sequencing approaches. The results of amplicon sequencing showed that Gammaproteobacteria and Alphaproteobacteria were predominant classes. Our datasets showed a clear shift in microbial taxonomic groups and the metabolic pathways in the sediments and surrounding seawaters. Metagenomic analysis showed that purine metabolism, ABC transporters, and pyrimidine metabolism were the most abundant pathways. Genes related to two-component system, TCA cycle and nitrogen metabolism exhibited higher abundance in sediments compared with those in seawaters. The presence of cadmium-resistant genes and ABC transporters suggested the ability of microorganisms to resist the toxicity of cadmium. In summary, this study provides comprehensive and significant differential signatures in the microbial community and metabolic pathways in Qinhuangdao mariculture area, and can develop effective microbial indicators to monitor mariculture area in the future.

Advances in Studies on Toxic Effects of Short-Chain Chlorinated Paraffins (SCCPs) and Characterization of Environmental Pollution in China.

Short-chain chlorinated paraffins (SCCPs) were included in the Stockholm Convention in 2017. SCCPs have persistence, bioaccumulation, long-range environmental mobility and biological toxicity, significant toxicity to aquatic organisms, and potential carcinogenicity. Little study was on the progress research on the current environmental pollution in China. We reviewed the pollution conditions of SCCPs in air, soil, and water and their accumulation in food and organisms in China, especially for the contaminations of aquatic ecosystem. Meanwhile, we summarize the recent studies on the toxic effects and toxicological mechanisms of SCCPs on aquatic organisms and mammals. Finally, the further direction and trends for SCCP research were proposed. More efforts are necessary to conduct a comprehensive risk assessment and evaluate the relative importance of the various exposure routes.

China national water quality criteria for the protection of freshwater life: Ammonia.

Ammonia is one of the two mandatory indexes for China's water environment pollution control. The current China ammonia water quality standard does not reflect the effect of water quality parameters on ammonia toxicity. The Ministry of Ecology and Environment of China just released the China National Aquatic Life Criteria Report for ammonia. This paper discusses the technical route, formulation process and results of the national ammonia criteria. Based on China's own technical guidelines, a total of 259 acceptable acute and 44 acceptable chronic data for ammonia were adopted. The temperature of the water body corresponding to the ammonia criteria was divided into 6 grades, and the pH was divided into 12 grades, which constitutes 72 groups of water quality conditions. Based on the empirical formulas recommended by USEPA, the ammonia toxicity data was adjusted, and the optimal fitting model was used to derive the 72 short-term criteria and the 72 long-term criteria for ammonia. In terms of criteria derivation, the method used by the USEPA to extrapolate at the criteria level has been improved and replaced with extrapolation at the species level, making the final criteria value more accurate.

Effects of acute ammonia toxicity on oxidative stress, DNA damage and apoptosis in digestive gland and gill of Asian clam (Corbicula fluminea).

Ammonia is one of the major pollutants associated with the main river basins due to ammonification of uneaten food and animal excretion, which usually brings detrimental health effects to aquatic invertebrate. However, the mechanisms of ammonia toxicity in aquatic invertebrate have rarely been reported. In this study, C. fluminea was exposed to different levels of ammonia (control group, 10 mg/L, and 25 mg/L) for 24 h and 48 h, and digestive gland and gill were collected to explore toxic effects on oxidative stress, DNA damage and apoptosis under ammonia stress. The results showed that ammonia poisoning could increase the activity of oxidative stress enzyme (SOD and CAT), inducing differentially expressed genes (DRAM2, GADD45, P53, BAX, BCL2, CASP8, CASP9, CASP3, HSP70 and HSP90) and different cytokines (IL-1 beta, IL-8, IL-17 and TNF-alpha) of DNA damage and apoptosis. The difference of toxic effects induced by ammonia among digestive gland and gill were also observed by real-time PCR and TUNEL staining. Our results will be helpful to understand the mechanism of aquatic toxicology induced by ammonia in C. fluminea.

Environmental DNA: An Emerging Tool in Ecological Assessment.

Environmental DNA (eDNA), as a recent research hotspot in environmental science, the use of eDNA in biological monitoring has the advantages of sensitivity and time/labor saving. The eDNA technology combined with scientific advancement has been applied in investigations of target species (such as invasive species, endangered species and other rare species), biomass, and biodiversity. In addition, ecotoxicology studies and environmental pollution impact assessments based on the development of eDNA technology have gradually emerged in recent years. In this article, we summarizes the application of eDNA in ecological assessment, include species diversity assessment and chemical contamination impacts assessment, provide guiding questions for study design. We additionally discuss current challenges associated with eDNA. Finally, looking to the future, we discuss the opportunities of eDNA technology in environmental protein, environmental sample processor and ecogenomic sensors.

Transcriptome analysis of response mechanism to ammonia stress in Asian clam (Corbicula fluminea).

Corbicula fluminea is highly sensitive to ammonia, and its response mechanism to ammonia stress is unclear. In this study, C. fluminea was exposed to different levels of ammonia (control group, 10 mg/L, and 25 mg/L) for 24 h and 48 h. A comparative analysis of transcriptome sequencing (RNA-seq) of C. fluminea digestive gland showed that the expression of 6742 genes (11.54%) was significantly affected by ammonia stress. The TLR, NF-κB, FOXO, and apoptotic signaling pathways were involved in the regulation. The differential expression of 14 genes was confirmed by real-time PCR. In summary, the response mechanism of C. fluminea digestive gland under ammonia stress may be different from that of oxidative stress in marine vertebrates. Also, the NMDAR-mediated pathway may not be the main mechanism in the response to ammonia stress in C. fluminea. The present study is a preliminary study for further investigation into ammonia toxicity in shellfish.

Archaeal community variation in the Qinhuangdao coastal aquaculture zone revealed by high-throughput sequencing.

The differences in archaeal diversity and community composition in the sediments and waters of the Qinhuangdao coastal aquaculture zone were investigated. Furthermore, the associations between dominant archaeal taxa with geographic and environmental variables were evaluated. High-throughput sequencing of archaeal 16S rRNA genes yielded a total of 176,211 quality-filtered reads and 1,178 operational taxonomic units (OTUs) overall. The most abundant phylum and class among all communities were Thaumarchaeota and Nitrososphaeria, respectively. Beta diversity analysis indicated that community composition was divided into two groups according to the habitat type (i.e., sediments or waters). Only 9.8% OTUs were shared by communities from the two habitats, while 73.9% and 16.3% of the OTUs were unique to sediment or water communities, respectively. Furthermore, the relative abundances of the dominant OTUs differed with habitat type. Investigations of relationships between dominant OTUs and environmental variables indicated that some dominant OTUs were more sensitive to variation in environmental factors, which could be due to individual taxonomic differences in lifestyles and biological processes. Overall, the investigation of archaeal community variation within the Qinhuangdao coastal aquaculture zone provides an important baseline understanding of the microbial ecology in this important ecosystem.

Research Progress on Toxic Effects and Water Quality Criteria of Triclosan.

Triclosan (TCS) is an effective broad-spectrum antimicrobial agent that is widely used in personal care products. It has been detected in different environmental media, and poses high potential ecological risk. In this article, we carried out a literature review of recent studies on the toxic effects of TCS from different aspects at the molecular, cell, tissue, organ, and individual level. TCS can exhibit acute toxicity to aquatic organisms, affect the normal expression and physiological function of enzymes and genes, and produce cytotoxicity. Many studies have demonstrated that TCS exerts significant endocrine-disrupting effects on organisms, interfering the normal physiological functions of the reproductive, thyroid, and nervous systems via related signaling pathways. Moreover, we reported current research on the water quality criteria of TCS and discuss possible future research directions.

Comparative analysis of freshwater species sensitivity distributions and ecotoxicity for priority pesticides: Implications for water quality criteria.

Organochlorine pesticides (OCPs) and organophosphate pesticides (OPPs) posed severe threats to the aquatic environment in China. The toxicity data of 18 priority OCPs and OPPs for Chinese and American species were collected, and their species sensitivity distributions (SSDs) and ecotoxicity were compared. Physicochemical characteristics and chemical structures were used to analyze the difference in the pesticide toxicity. Results suggested that there is no significant difference between the HC5 values (hazardous concentration protecting 95% of species) of China and America as a whole. However, the HC5 values of nearly half of these pesticides (8/18) differ dramatically between Chinese and American due to the different resident species distribution. It indicated that it is necessary to develop local water quality criteria in China. The regression analysis of pesticides toxicity differences indicated a decrease in LC50/EC50 values (for Oncorhynchus mykiss and Carassius auratu) with the increase in molecular weights of pesticides. Pesticides with larger MWs might be more toxic to aquatic species. Similar trend was also observed in the regression analysis of a decrease in both American and Chinese HC5 values for with increase of the number of containing halogen atoms. It indicated the potency of these parameters to be used to predict the ecotoxicity of pesticide.