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Autosomal dominant polycystic kidney disease (ADPKD) is a common monogenic kidney disease. Emerging research indicates that the Notch signaling pathway plays an indispensable role in the pathogenesis of numerous kidney diseases, including ADPKD. Herein, we identified that Notch3 but not other Notch receptors was overexpressed in renal tissues from mice with ADPKD and ADPKD patients. Inhibiting Notch3 with γ-secretase inhibitors, which block a proteolytic cleavage required for Notch3 activation, or shRNA knockdown of Notch3 significantly delayed renal cyst growth in vitro and in vivo. Subsequent mechanistic study elucidated that the cleaved intracellular domain of Notch3 (N3ICD) and Hes1 could bind to the PTEN promoter, leading to transcriptional inhibition of PTEN. This further activated the downstream PI3K-AKT-mTOR pathway and promoted renal epithelial cell proliferation. Overall, Notch3 was identified as a novel contributor to renal epithelial cell proliferation and cystogenesis in ADPKD. We envision that Notch3 represents a promising target for ADPKD treatment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Inc. All rights reserved.)

Insecticides are widely used in crop protection against insects and frequently detected in aquatic environment. Photolysis kinetics are directly related with exposure assessment and risk assessment. However, the photolysis mechanism of neonicotinoid insecticides with different structures has not been studied and compared systematically in the literature. In this paper, the photolysis rate constants in water were determined for eleven insecticides under irradiation of simulated sunlight. At the same time, the photolysis mechanism and effect of dissolved organic matter (DOM) on their photolysis were studied. The results showed that photolysis rates of eleven insecticides vary in a large range. The photolysis rates of nitro-substituted neonicotinoids and butenolide insecticide are much faster than that of cyanoimino-substituted neonicotinoids and sulfoximine insecticide. The ROS scavenging activity assays reveal that direct photolysis dominates the degradation of seven insecticides and, on the other hand, self-sensitized photolysis dominates four insecticides. The shading-effect from DOM can reduce the direct photolysis rates, on the other hand, ROSs generated by triplet-state DOM ( 3 DOM*) can also accelerate photolysis of insecticides. According to the photolytic products identified from HPLC-MS, these eleven insecticides have different photolysis pathways. Six insecticides are degraded from the removal of nitro group from their parent compounds and four insecticides are degraded through ·OH reaction or singlet oxygen ( 1 O 2 ) reaction. QSAR (quantitative structure-activity relationship) analysis showed that photolysis rate was directly related to the energy gap between the highest occupied molecular orbital to the lowest unfilled molecular orbital (E gap  = E LUMO -E HOMO ) and dipole moment (δ). These two descriptors reflect the chemical stability and reactivity of insecticides. The pathways developed from identified products and the molecular descriptors of QSAR models can well verify the photolysis mechanisms of eleven insecticides., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Elsevier Ltd. All rights reserved.)

For the first time, a global regression quantitative structure-toxicity/activity relationship (QSTR/QSAR) model was developed for the toxicity of a large data set including 1236 chemicals towards Vibrio fischeri, by using random forest (RF) regression algorithm. The optimal RF model with RF parameters of mtry = 3, ntree = 150 and nodesize = 5 was based on 13 molecular descriptors. It can achieve accurate prediction for the toxicity of 99.1% of 1236 chemicals, and yield coefficients of determination R 2 of 0.893 for 930 log(Mw/IBC50) in the training set, 0.723 for 306 log(Mw/IBC50) in the test se, and 0.865 for 1236 toxicity log(Mw/IBC50) in the total set. The optimal RF global model proposed in this work is comparable to other published local QSTR models on small datasets of the toxicity to Vibrio fischeri., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

The photochemical behaviors of chiral pollutants in aqueous solutions are rarely studied using chiral monomers, which may hamper their precise risk assessment and lead to suspicious conclusions. In this study, we systematically investigated the phototransformation behavior and toxicity evolution of two widely used chiral pesticides (triadimefon (TF) and triadimenol (TN)) at enantiomer and diastereomer levels, and proposed a calculation method of total photolysis rate constants of chiral mixture. Results show that TF and TN could be photodegraded faster in pure water than in natural waters, and the observed photolysis rate constants (k obs ) of TN with two chiral centers exhibit enantioselectivity, i.e., k obs (TN-RS) = k obs (TN-SR) > k obs (TN-RR) = k obs (TN-SS). The photolysis of TF and TN mainly occurs through their excited singlet and triplet states, respectively. Their photodegradation pathways mainly include dechlorination and elimination of triazole ring. TF could also undergo ether bond cleavage. It is also found that, both TF and TN exhibit photo-induced toxicity to V. fischeri, due to the generation of more toxic products than parent compounds. Furthermore, TN exhibits enantioselective photo-induced toxicity after 240-min irradiation, which could be ascribed to the formation of chiral products. These results could benefit the understanding of enantioselective environmental behavior of chiral pollutants., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 Northeast Normal University. Published by Elsevier Ltd.. All rights reserved.)

Vasopressin V 2 receptors (V 2 R) are a promising drug target for autosomal dominant polycystic kidney disease (ADPKD). As previous research demonstrated that the residence time of V 2 R antagonists is critical to their efficacy in both ex vivo and in vivo models of ADPKD, we performed extensive structure-kinetic relationship (SKR) analyses on a series of benzodiazepine derivatives. We found that subtle structural modifications of the benzodiazepine derivatives dramatically changed their binding kinetics but not their affinity. Compound 18 exhibited a residence time of 77 min, which was 7.7-fold longer than that of the reference compound tolvaptan (TVP). Accordingly, compound 18 exhibited higher efficacy compared to TVP in an in vivo model of ADPKD. Overall, our study exemplifies a kinetics-directed medicinal chemistry effort for the development of efficacious V 2 R antagonists. We envision that this strategy may also have general applicability in other therapeutic areas.

Renal cyst development and expansion in autosomal dominant polycystic kidney disease (ADPKD) involves over-proliferation of cyst-lining epithelial cells and excessive cystic fluid secretion. While metformin effectively inhibits renal cyst growth in mouse models of ADPKD it exhibits low potency, and thus an adenosine monophosphate-activated protein kinase (AMPK) activator with higher potency is required. Herein, we adopted a drug repurposing strategy to explore the potential of PF-06409577, an AMPK activator for diabetic nephropathy, in cellular, ex vivo and in vivo models of ADPKD. Our results demonstrated that PF-06409577 effectively down-regulated mammalian target of rapamycin pathway-mediated proliferation of cyst-lining epithelial cells and reduced cystic fibrosis transmembrane conductance regulator-regulated cystic fluid secretion. Overall, our data suggest that PF-06409577 holds therapeutic potential for ADPKD treatment., (© 2022 The Authors. FEBS Open Bio published by John Wiley & Sons Ltd on behalf of Federation of European Biochemical Societies.)

With the promotion of carbon neutrality, it is also important to synchronously promote the assessment and sustainable management of chemicals so as to protect public health. Humans and animals are possibly exposed to endocrine disruptors that have inhibitory effects on thyroid stimulating hormone receptor (TSHR). As such, it is important to identify chemicals that inhibit TSHR and to develop models to predict their inhibitory activity. In this study, 5952 compounds derived from a cyclic adenosine monophosphate (cAMP) analysis, a key signaling pathway in thyrocytes, were used to establish a binary classification model comparing methods that included random forest (RF), extreme gradient boosting (XGB), and logistic regression (LR). The prediction model based on RF showed the highest identification accuracy for revealing chemicals that may inhibit TSHR. For the RF model, recall was calculated at 0.89, balance accuracy was 0.85, and its receiver operating characteristic (ROC) curve-area under (AUC) was 0.92, indicating that the model had very high predictive capacity. The lowest CDocker energy (CE) and CDocker interaction energy (CIE) for chemicals and TSHR were determined and were subsequently introduced into the predictive model as descriptors. A regression model, extreme gradient boosting-Regression (XGBR), was successfully established yielding an R 2  = 0.65 to predict inhibitory activity for active compounds. Parameters that included dissociation characteristics, molecular structure, and binding energy were all key factors in the predictive model. We demonstrate that QSAR models are useful approaches, not only for identifying chemicals that inhibit TSHR, but for predicting inhibitory activity of active compounds., (Copyright © 2022 Elsevier Inc. All rights reserved.)

Cyst formation and enlargement in autosomal dominant kidney disease (ADPKD) is mainly driven by aberrantly increased cytosolic cAMP in renal tubule epithelial cells. Because the vasopressin V 2 receptor (V 2 R) regulates intracellular cAMP levels in kidneys, a series of benzodiazepine derivatives were developed targeting the V 2 R. Among these derivatives, compound 25 exhibited potent binding affinity to the V 2 R ( K i = 9.0 ± 1.5 nM) and efficacious cAMP inhibition (IC 50 = 9.2 ± 3.0 nM). This led to the suppression of cyst formation and growth in both an MDCK cell model and an embryonic kidney cyst model. Further advancing compound 25 in a murine model of ADPKD demonstrated a significantly improved in vivo efficacy compared with the reference compound tolvaptan. Overall, compound 25 holds therapeutic potential for the treatment of ADPKD.

Prevailing strategies directing early-phase drug discovery heavily rely on equilibrium-based metrics such as affinity, which overlooks the kinetic process of a drug molecule interacting with its target. Herein, we developed a number of vasopressin V 2 receptor (V 2 R) antagonists with divergent binding affinities and kinetics for autosomal dominant polycystic kidney disease (ADPKD). Surprisingly, the residence time of the V 2 R antagonists, but not their affinity, was correlated with the efficacy in both ex vivo and in vivo models of ADPKD. We envision that the kinetics-directed drug candidate selection and development may have general applicability for ADPKD and other therapeutic areas as well.

Exposure of cells to xenobiotic human-made products can lead to genotoxicity and cause DNA damage. It is an urgent need to quickly identify the chemicals that cause DNA damage, and their toxicity should be predicted. In this study, recursive partitioning (RP), binary logistic regression, and one machine learning approach, namely, random forest (RF) classifier, were used to predict the active and inactive compounds of a total 5036 data based on the assay conducted by a β-lactamase reporter gene under control of the p53 response element (p53RE) from Tox21 library. Results show that the binary logistic regression model with a threshold of 0.5 has a high accuracy rate (83%) to distinguish active and inactive compounds. The RF classifier method has satisfactory results, with an accuracy rate (84.38%) approximately higher than that of binary logistic regression. The models established can identify compounds that induce DNA damage and activate p53, and provide a scientific basis for the risk assessment of organic chemicals in the environment., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Insecticides, fungicides, dinitrobenzenes, resorcinols, phenols and anilines are widely used in agricultural and industrial productions. However, their modes of toxic action are unclear in some nontarget organisms, such as worms and tadpoles. In this study, acute toxicity data was experimentally collected for Limnodrilus hoffmeisteri worms and Rana chensinensis tadpoles, respectively. Interspecies correlation and excess toxicity were calculated to determine modes of action (MOAs) between the two species for class-based compounds. The result showed that, although the interspecies correlation of toxicity between the tadpoles and worms is significant with a coefficient of determination (R 2 ) of 0.83, tadpoles are more sensitive than the worms and toxicity values between these two species are not identical with an overall 0.43 log unit difference. Regression analysis revealed that the toxicity of nonpolar narcotics or baseline compounds is linearly related to hydrophobicity for both the tadpoles and worms and the two baseline models are parallel, suggesting that these nonpolar narcotics share the same MOA between the two species. The difference of baseline toxicities between the two species is attributed to differences in bioconcentration factors. Analysis of the excess toxicity calculated from the toxicity ratio (TR) suggested that phenols and anilines can be classified as polar narcotics, not only to fish, but also to the tadpoles and worms. These compounds are more toxic than the baseline compounds and quantitative structure-activity relationship (QSAR) models show that their toxicity is linearly related to chemical hydrophobicity and polarity. Analysis of the excess toxicity reveals that aminophenols and resorcinols can be classified as reactive compounds, and insecticides and fungicides can be classified as specifically-acting compounds for both species. These compounds exhibited significantly greater toxic effect to both the tadpoles and worms. QSAR models have been developed to describe the toxic mechanisms for nonpolar narcotics, polar narcotics, reactive chemicals and specifically-acting compounds, and a theoretical equation has been derived to explain the effect of bio-uptake and interaction of the chemical with target receptors for both tadpole and worm toxicity. Our study reveals that tadpole toxicity can be estimated from worm toxicity data and the two species can serve as surrogates for each other in the safety evaluation of organic pollutants., (Copyright © 2022. Published by Elsevier B.V.)

Mitochondria are significant targets in cells for many environmental chemicals. Mitochondrial damage and dysfunction can lead to apoptosis and death of fish. The objectives of this study were to compare the modes of action (MOAs) between fish, cell and mitochondrial toxicity. To achieve the goal, toxicity correlation, excess toxicity and quantitative structure-activity relationship (QSAR) were investigated between these three toxicity endpoints for a wide range of compounds. Results showed that fish toxicity is well correlated to cytotoxicity, but overall fish toxicity is relatively greater than the cytotoxicity. On the other hand, fish or cell toxicity is poorly related to mitochondrial toxicity, suggesting some compounds share same toxic mechanism but some not. The excess toxicity calculated from toxicity ratio (TR) shows that specifically-acting compounds in cytotoxicity, such as insecticides, fungicides, herbicides, dyes and medications used to treat cancer, depression, heart failure and blood pressure, are active compounds in mitochondrial toxicity. However, the less inert compounds identified in fish and cell toxicity exhibit greatly mitochondrial toxicity. QSAR models reveal that fish or cell toxicity is closely related to the chemical hydrophobicity, ionization, energy of lowest unoccupied molecular orbital, hydrogen bonding potential and stability. These descriptors reflect chemical bio-uptake, reactivity and interaction with target receptors. On the other hand, binomial model reveals that mitochondrial toxicity is closely related to the chemical hydrophobicity and polarizability/dipolarity, indicating bio-uptake and Van der Waals interaction play key roles in mitochondrial toxicity. Theoretical equations have been used to explain the toxicity correlation, excess toxicity and QSAR for fish, cell and mitochondrial toxicity. Above results suggest that cytotoxicity can serve as a surrogate for fish toxicity and be used in the safety evaluation of organic pollutants in aqueous environment, but not mitochondrial toxicity, although some compounds share same modes of action between fish or cell toxicity and mitochondrial toxicity., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Neonicotinoids have been often detected in aquatic environment with high concentrations; however, little is known about their risk and fate to/in fish. This study systematically investigated the bio-uptake, tissue distribution and metabolism of neonicotinoids in zebrafish, taking clothianidin (CLO) as an example. The results revealed the uptake and elimination kinetics of CLO in whole fish and different tissues was very similar, and its bioconcentration factor (<1) indicates the low bioaccumulation potential in zebrafish. The highest accumulative tissues for CLO were found to be intestine and liver. Eight biotransformation products were identified in intestine and liver, and the metabolic pathways were found to be N-demethylation and nitro-reduction. The metabolic kinetics of two products (desmethyl clothianidin and clothianidin urea) revealed the metabolism of CLO mainly occurred in liver and intestine. This suggested that the hepatobiliary system played an important role in the metabolism and elimination of CLO. This study provides a comprehensive evaluation of the toxicokinetics of CLO in zebrafish, and these results can contribute to its ecological risk assessment., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Neonicotinoids are widely used pesticides all over the world and pose severe water pollution. Although they can be degraded via absorbing sunlight, few attentions have been paid to the environmental risks of their photolysis products. In this paper, the photo-toxicity was investigated for four neonicotinoids (dinotefuran, nitenpyram, thiamethoxam and clothianidin) based on a series of experiments (i.e., photolysis kinetics, radical scavenging, bioluminescent inhibition test to Vibrio Fischeri and intermediate identification) and in-silico calculation of photolysis pathway. The results show that direct photolysis dominates the photolysis of the four neonicotinoids under simulated sunlight radiation. The bioluminescent inhibition kinetics shows that all four neonicotinoids have photo-induced toxicity to V. fischeri, but with different light-induced responses. Scavenging radicals (·OH and 1 O 2 ) will decrease the photo-induced toxicity of all the four neonicotinoids, indicating radicals play important roles to the photo-chemical reactions of intermediates. Dissolved organic matters exhibit slightly shading effect to the photolysis rates of four parent compounds. However, the ROSs generated by DOM can accelerate the photo-chemical reactions of intermediates, leading to different photo-induced toxicity in present of DOM. According to the detected intermediates and Gaussian calculations, there are different photolysis pathways and mechanisms for the four neonicotinoids. The calculation for photo-sensitization reactions with 3 O 2 indicates that both energy transfer reactions and electron transfer reactions can be produced under simulated sunlight radiation, which further consolidate that reactive oxygen species are involved in the photolysis process. A theoretical model has been developed to explain the toxicity variations of four neonicotinoids in different aqueous conditions., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Deep domain adaptation methods have achieved appealing performance by learning transferable representations from a well-labeled source domain to a different but related unlabeled target domain. Most existing works assume source and target data share the identical label space, which is often difficult to be satisfied in many real-world applications. With the emergence of big data, there is a more practical scenario called partial domain adaptation, where we are always accessible to a more large-scale source domain while working on a relative small-scale target domain. In this case, the conventional domain adaptation assumption should be relaxed, and the target label space tends to be a subset of the source label space. Intuitively, reinforcing the positive effects of the most relevant source subclasses and reducing the negative impacts of irrelevant source subclasses are of vital importance to address partial domain adaptation challenge. This paper proposes an efficiently-implemented Deep Residual Correction Network (DRCN) by plugging one residual block into the source network along with the task-specific feature layer, which effectively enhances the adaptation from source to target and explicitly weakens the influence from the irrelevant source classes. Specifically, the plugged residual block, which consists of several fully-connected layers, could deepen basic network and boost its feature representation capability correspondingly. Moreover, we design a weighted class-wise domain alignment loss to couple two domains by matching the feature distributions of shared classes between source and target. Comprehensive experiments on partial, traditional and fine-grained cross-domain visual recognition demonstrate that DRCN is superior to the competitive deep domain adaptation approaches.

Microplastics (MPs), a growing class of emerging pollutants in the environment, have attracted widespread attention due to their adsorption properties. Recent research on MPs has mainly concentrated on seawater, and little work has been conducted on freshwater. Investigating and predicting the adsorption behavior of organic pollutants by MPs are necessary in freshwater. In this study, the adsorption behavior of 13 organic chemicals by polyethylene (PE) and chlorinated polyethylene (CPE) MPs was determined under freshwater conditions. Results shows the majority of the organic chemicals exhibit no distinctive differences in their adsorption on two MPs. However, the adsorption of polycyclic aromatic hydrocarbons and chlorobenzene on CPE is obviously stronger than that on PE, and the result is a counter for two pesticides. Quantitative structure activity relationship (QSAR) analysis was performed for the prediction of adsorption capacity. A QSAR model with acceptable performance (R 2  = 0.8586) was built to predict the adsorptive affinity (expressed as logK d ) of organic compounds on the PE MPs via multivariable linear regression (MLR) on forty-nine determined and collected data. The octanol/water partition coefficient (logK ow ) and excess molar refractive index (E) play dominant roles in the model. A QSAR model with satisfactory performance (R 2  = 0.9302) was also established for logK d values from CPE MPs in freshwater by using 13 adsorption data determined. The logK ow and most negative charge on Cl atom (Q - max,cl ) play decisive roles in the adsorption. The findings can provide a scientific basis for the risk assessment of waters contaminated by MPs and organic pollutants., (Copyright © 2021 Elsevier Inc. All rights reserved.)

To estimate spatial distribution, source analysis and uncertainty of heavy metals (Pb, Cd, Cr, Hg, As, Cu, Zn, and Ni) based on geographic information system (GIS), positive matrix factorization model (PMF) and bootstrap (BS) using 382 soil samples collected from cultivated soils in Lanzhou. The mean contents of Cd, Hg, Cu, Zn and Ni were high as 1.7,1.7, 2.1, 1.5 and 1.3 times local background values, mean contents of Pb, Cr and As were lower than local background values. However, the mean contents of eight heavy metals were lower environmental quality risk control standard for soil contamination of agricultural soil. Proportions of four sources were identified: Cr was predominantly contributed by natural sources (29.14%), Cu, Zn and Ni was primarily from industrial sources (25.26%), Hg and As were mainly of agricultural sources (27.49%), Pb and Cd mainly came from traffic source and smelting-related activities (18.09%). Uncertainties analysis contained three aspects: bootstrap runs, factor contributions in the PMF solution, and coefficient of variation (CV) values. By combining the four pollution source factors with bootstrap runs, the accuracy of the four pollution source factors were reliable based on PMF model. The median values in the BS runs was considered the most true factor contribution, and the 5th-95th quartile interval represents the variability of each factor, Factor 4 (traffic source) R 2 was 0.70 and lower variability. The highest CV value usually means a significantly deviation degree. In this study, the CV values of Cr in Factor 1, Cu, Zn, and Ni in Factor 2, Hg, and As in Factor 3, Pb, and Cd in Factor 4 were lower, indicates a lower deviation degree. and with the lowest content among heavy metals usually was also with the greatest uncertainties. In this study improves understanding of the reduction of heavy metal pollution in cultivated soil, and also serves as reference for pollution source apportionment in other regions., (Copyright © 2021. Published by Elsevier Inc.)

Visual domain adaptation aims to seek an effective transferable model for unlabeled target images by benefiting from the well-labeled source images following different distributions. Many recent efforts focus on extracting domain-invariant image representations via exploring target pseudo labels, predicted by the source classifier, to further mitigate the conditional distribution shift across domains. However, two essential factors are overlooked by most existing methods: 1) the learned transferable features should be not only domain invariant but also category discriminative; and 2) the target pseudo label is a two-edged sword to cross-domain alignment. In other words, the wrongly predicted target labels may hinder the class-wise domain matching. In this article, to address these two issues simultaneously, we propose a discriminative transfer feature and label consistency (DTLC) approach for visual domain adaptation problems, which can naturally unify cross-domain alignment with discriminative information preserved and label consistency of source and target data into one framework. To be specific, DTLC first incorporates class discriminative information by penalizing the maximum distance of data pair in the same class and the minimum distance of data pair sharing the different labels for each data into the distribution alignment of both domains. The target pseudo labels are then refined based on the label consistency within the domains. Thus, the transfer feature learning and coarse-to-fine target labels would be coupled to benefit each other in an iterative way. Comprehensive experiments on several visual cross-domain benchmarks verify that DTLC can gain remarkable margins over state-of-the-art (SOTA) nondeep visual domain adaptation methods and even be comparable to competitive deep domain adaptation ones.

Cellular exposure to xenobiotic human-made products will lead to oxidative stress that gives rise to DNA damage, as well as chemical or mechanical damage. Distinguishing the chemicals that will induce oxidative stress and predicting their toxicity is necessary. In the present study, 4270 compounds in the ARE-bla assay were investigated to predict active and inactive compounds by using simple algorithms, namely, recursive partitioning (RP) and binomial logistic regression, and to develop the quantitative structure-activity relationship (QSAR) models of chemicals that activate the ARE pathway to induce oxidative stress and exert toxic effects on cells. A decision tree based on scaffold-based fragments obtained through RP analysis showed the best identification accuracy. However, the overall identification accuracy of this model for active compounds was unsatisfactory due to limited fragments. Furthermore, a binomial logistic regression model was developed from 638 active compounds and 3632 inactive chemicals. The model with a cutoff of 0.15 could predict chemicals that were active or inactive with the prediction accuracy of 69.1%. Its area under the receiver operating characteristic (ROC) curve metric (AUROC) was 0.762, which indicated the acceptable predictive ability of this model. The parameters nBM (number of multiple bonds) and H% (percentage of H atom) played dominant roles in the prediction of the activity (inactive or active) of chemicals. A global QSAR model was developed to predict the toxicity of active chemicals. However, the model displayed an unsatisfactory result with R 2  = 0.316 and R 2 ext  = 0.090. Active chemicals were then classified on the basis of structure. A total of 79 compounds with carbon chains could be predicted with acceptable performance by using a QSAR model with six descriptors (R 2  = 0.722, R 2 ext  = 0.798, Q 2 Loo  = 0.654, Q 2 Boot  = 0.755, Q 2 ext  = 0.721). The simple models established here contribute to efforts on identification compounds inducing oxidative stress and provide the scientific basis for risk assessment to organisms in the environment., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Inc. All rights reserved.)

The ozonation-based advanced oxidation process is a promising treatment technology for wastewater with micropollutants. The second-order reaction rate constant (k O3 ) of ozone (O 3 ) with organic compounds is an important index for estimating removal efficiency of organic pollutants in engineered treatment; however, the experimental k O3 values are currently only available for hundreds of chemicals. In this study, two quantitative-structure activity relationship (QSAR) models were developed to predict k O3 of various organic chemicals with multiple linear regression (MLR) and support vector machine (SVM) methods. The built QSAR models cover a large dataset (136 chemicals) and more structurally diverse chemicals as compared to the existing models. The MLR model possesses satisfactory goodness-of-fit (R 2 tr  = 0.734), robustness (Q 2 LOO  = 0.700, Q 2 BOOT  = 0.772) and predictive ability (R 2 ext  = 0.797, Q 2 ext  = 0.794), and the SVM model also has good fitness (R 2 tr  = 0.862) and predictability (R 2 ext  = 0.782, Q 2 ext  = 0.775). The applicability domain of the models has been extended and includes chemicals (especially some emerging pollutants) that are rarely covered in many previous models. The underlying molecular structural factors influencing ozonation are revealed. The energy of the highest occupied molecular orbital (E HOMO ) and the phenol/enol/carboxyl OH group (O-057) are the two most important molecular structural factors governing the reactivity of organic compounds with ozone. The developed models can serve as a prescreening tool for the removal prediction of organic pollutants by ozone., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Risk assessment of pollutants to humans and ecosystems requires much toxicological data. However, experimental testing of compounds expends a large number of animals and is criticized for ethical reasons. The in silico method is playing an important role in filling the data gap. In this paper, the acute toxicity data of 1221 chemicals to Vibrio fischeri were collected. The global models obtained showed that there was a poor relationship between the toxicity data and the descriptors calculated based on linear and nonlinear regression analysis. This is due to the fact that the studied compounds contain not only non-reactive compounds but also reactive and specifically acting compounds with different modes of action (MOAs). MOAs are fundamental for the development of mechanistically based QSAR models and toxicity prediction. To investigate MOAs and develop MOA-based prediction models, the compounds were classified into baseline, less inert, reactive, and specifically acting compounds based on the modified Verhaar's classification scheme. Satisfactory models were established by multivariate linear regression (MLR) and support vector machine (SVM) analysis not only for baseline and less inert chemicals, but also for reactive and specifically acting compounds. Compared with linear models obtained by the MLR method, the nonlinear models obtained by the SVM method had better performance. The cross validation proved that all of the models were robust except for those for reactive chemicals with nN (number of nitrogen atoms) = 0 and n(C=O) (number of carbonyl groups) > 0 (Q 2 ext < 0.5). The application domains and outliers are discussed for those MOA-based models. The models developed in this paper are significantly helpful not only because the application domains for baseline and less inert compounds have been expended, but also the toxicity of reactive and specifically acting compounds can be successfully predicted. This work will promote understanding of toxic mechanisms and toxicity prediction for the chemicals with structural diversity, especially for reactive and specifically acting compounds.

Ganoderma lucidum (G. lucidum, Lingzhi) is a well-known Chinese traditional medicine to improve health and to treat numerous diseases for over 2000 years in Asian countries. G. lucidum has the abundant chemical components such as triterpenes and polysaccharides, which have various biological activities including anti-oxidation, anti-inflammation, anti-liver disorders, anti-tumor growth and metastasis, etc. Recently, many lines of studies have elucidated the therapeutic effects of G. lucidum and its extractions on various acute kidney injury (AKI) and chronic kidney disease (CKD) pathogenesis, including autosomal dominant polycystic kidney disease, diabetic nephropathy, renal proximal tubular cell oxidative damage and fibrotic process, renal ischemia reperfusion injury, cisplatin-induced renal injury, adriamycin-induced nephropathy, chronic proteinuric renal diseases, etc. Clinical researches also showed potent anti-renal disease bioactivities of G. lucidum. In this chapter, we review experimental and clinical researches and provide comprehensive insights into the renoprotective effects of G. lucidum. In recent years, renal diseases have gradually aroused attention on account of their booming prevalence worldwide and lack of effective therapies. Although the complicated pathogenesis of kidney diseases, such as acute kidney injury (AKI) and chronic kidney diseases (CKD) have been intensively studied. The morbidity and mortality of AKI and CKD still rise continuously. Thanks to the conventional experience and the multi-target characteristics, natural products have been increasingly recognized as an alternative source for treating renal diseases., Competing Interests: Conflict of interest The authors have no conflicts of interest to declare., (© 2020 Elsevier Inc. All rights reserved.)

Wilms' tumour (WT) is a frequent primary malignant tumour of urinary system in children. LncRNAs small nucleolar RNA host gene 6 (SNHG6) modulates kinds of biological procedures of cancer cells. Our research is to explore the effect and associated regulatory mechanism of SNHG6 in WT. CCK8 assays and bromodeoxyuridine were used to determine cell viability and cell proliferation, respectively. Flow cytometric analysis was performed to measure cell apoptosis rate. Cell mobility was tested through transwell and migration assays. Western blotting was employed to test the expression of proteins related to cell proliferation, cell apoptosis and signal pathways. In the results, overexpression of SNHG6 was found in WT tissues. The knockdown of SNHG6 suppressed cell proliferation, migration and incursion, but promoted apoptosis. Further study found that the knockdown of SNHG6 elevated the expression of miR-15a. Then, the combination of miR-15a inhibitor abolished the inhibiting effect of si-SNHG6 on WT progression. We also found that the TAK1/JNK and Wnt/β-catenin signal pathways were inactivated by the knockdown of SNHG6 through elevating the expression of miR-15a. In summary, SNHG6 is an oncogene of WT development by targeting miR-15a.

The rapid development of the economy in China resulted in increasingly serious water pollution problem. A lot of water pollution treatment projects have been launched to improve the water environment quality. Water pollution treatment is a complex and long-term task. Considering the concept of water pollution with fuzziness and the factors affecting the effect of water pollution treatment (EWPT), this study constructs a multi-dimensional dynamic fuzzy comprehensive monitoring model. The model considers the vague boundaries in the representation of water pollution and various factors affecting the treatment effect, such as monitoring time, monitoring index, and monitoring location. In detail, firstly, existing methods for evaluating the EWPT are analyzed and reviewed. Then a multi-dimensional dynamic model is developed for monitoring the EWPT. Finally, the Yueya Lake of Henan Province in China is taken as an example to demonstrate the effectiveness and practicability of the proposed method. From the analysis of the results, to maintain the cleanliness of the water, efforts should still be made to eliminate and completely block the pollutants on the shore in order to fundamentally solve the problem.

The single toxicity (IC 50 ) of zinc (Zn) and 11 nitro-substituted benzenes to Photobacterium phosphoreum were determined, respectively. On basis of single toxicity, the joint toxicity of binary mixtures of Zn and 11 nitro-substituted benzenes at different Zn concentrations of 0.2 IC 50 , 0.5 IC 50 , and 0.8 IC 50 were measured. The joint toxicity was evaluated by toxic unit (TU) and additive index (AI) methods. The results indicated that the joint toxicity was not only depending on the Zn concentrations but also on the substituted groups of nitro-substituted benzenes. The quantitative structure-activity relation (QSAR) equations were developed and the results showed that the toxicity of nitro-substituted benzenes has different joint effect at the different Zn concentrations. At the Zn concentration of 0.2 IC 50 , the binary joint effects were mainly antagonism and the joint toxicity was negatively related to descriptors called VE2&#95;B(p) and TIC3. At the Zn concentration of 0.5 IC 50 and 0.8 IC 50 , the binary joint effects were mainly antagonism and simple addition, and the joint toxicity was related to the same descriptor Eig06&#95; AEA(dm). It indicated that the joint toxic actions were similar when combined at the medium and high concentrations of Zn.

The hydrated electron (e aq - )-based reduction processes are promising for removing organic pollutants in water engineering systems. The reductive kinetics, especially the second order rate constants ( [Formula: see text] ) of e aq - with organic compounds, is important for evaluating and modeling the advanced reduction processes. In this study, the [Formula: see text] values for aliphatic compounds and phenyl-based compounds are, for the first time, modeled by the quantitative structure-activity relationship (QSAR) method. The structural features governing the reactivity of two classes of organic compounds toward e aq - were revealed, and the energy of the lowest unoccupied molecular orbital (E LUMO ), one-electron reduction potential (E RED ) and polarizability (α) were found to be the important molecular parameters in both two models. The built QSAR models provide robust predictive tools for estimating the removal of emerging pollutants using e aq - during wastewater treatment processes. Additionally, quantum chemical calculations were employed to probe into the mechanism and feasibility of the single electron transfer (SET) pathway in the e aq - -based reduction process. The thermodynamic investigation suggests that the compounds with electron-withdrawing groups tend to possess higher [Formula: see text] and lower Gibbs free energy (ΔG SET ) and Gibbs free energies of activation (∆ ‡ G SET ∘ ) than the ones with electron-donating groups, indicating the SET process occurs more readily. It is also found that the refractory halogenated compounds can achieve dehalogenation via the SET pathway., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

The mechanisms of kidney diseases, such as acute kidney injury (AKI) and chronic kidney disease (CKD), have been intensively studied. Nonetheless, the morbidity and mortality of AKI and CKD increased in recent years. Recently, natural products have been increasingly recognized as an alternative source for treating renal diseases on account of the conventional experience and the multi-target characteristics. Ganoderma lucidum (G. lucidum, Lingzhi) has been used for centuries as nutraceuticals and alternative medicine to improve health and to treat numerous diseases. Benefiting from various biological activities, such as anti-oxidation, anti-inflammation, anti-tumor growth and metastasis, etc., G. lucidum has been proved to exhibit significant role in preventing and treating various kidney diseases. In this chapter, we review certain researches and provide comprehensive insights into the renoprotective effects of G. lucidum.

Aqueous ·OH reaction rate constants ( k OH ) for organophosphate esters (OPEs) are essential for assessing their environmental fate and removal potential in advanced oxidation processes (AOPs). Herein experimental and in silico approaches were adopted to obtain k OH values for a variety of OPEs. The determined k OH for 18 OPEs varies from 4.0 × 10 8 M -1 s -1 to 1.6 × 10 10 M -1 s -1 . Based on the experimental k OH values, a quantitative structure-activity relationship model that involves molecular structural information on the number of heavy atoms, content index, and the most negative charge of C atoms was developed for predicting k OH of other OPEs. Furthermore, appropriate density functional theory (DFT) and solvation models were selected, which together with transition state theory were employed to predict k OH of three representative OPEs. The deviation between the DFT calculated and the experimental k OH values ( k cal / k exp ) is within 2. Half-lives of the OPEs were estimated to be 0.5-22791.3 days in natural waters and 0.044-19.7 s in AOPs, indicating the OPEs are potentially persistent in natural waters and can be quickly eliminated by AOPs. The determined k OH values and the in silico methods offer a scientific base for assessing OPEs fate in aquatic environments.

The acute toxicity of organic pollutants to fish, Daphnia magna, Tetrahymena pyriformis, and Vibrio fischeri was investigated. The results indicated that the Toxicity Ratio (TR) threshold of log TR =1, which has been based on the distribution of toxicity data to fish, can also be used to discriminate reactive or specifically acting compounds from baseline narcotics for Daphnia magna and Vibrio fischeri. A log TR=0.84 is proposed for Tetrahymena pyriformis following investigation of the relationships between the species sensitivity and the absolute averaged residuals (AAR) between the predicted baseline toxicity and the experimental toxicity. Less inert compounds exhibit relatively higher toxicity to the lower species (Tetrahymena pyriformis and Vibrio fischeri) than the higher species (fish and Daphnia magna). A greater number of less inert compounds with log TR greater than the thresholds was observed for Tetrahymena pyriformis and Vibrio fischeri. This may be attributed to the hydrophilic compounds which may pass more easily through cell membranes than the skin or exoskeleton of organisms and have higher bioconcentration factors in the lower species, leading to higher toxicity. Most of classes of chemical associated with excess toxicity to one species also exhibited excess toxicity to other species, however, a few classes with excess toxicity to one species exhibiting narcotic toxicity to other species and thus may have different MOAs between species. Some ionizable compounds have log TR much lower than one because of the over-estimated log K OW . The factors that influence the toxicity ratio calculated from baseline level are discussed in this paper., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Aquaporin-2 (AQP2) is a water channel protein expressed in principal cells (PCs) of the kidney collecting ducts (CDs) and plays a critical role in mediating water reabsorption and urine concentration. AQP2 undergoes both regulated trafficking mediated by vasopressin (VP) and constitutive recycling, which is independent of VP. For both pathways, actin cytoskeletal dynamics is a key determinant of AQP2 trafficking. We report here that manganese chloride (MnCl 2 ) is a novel and potent regulator of AQP2 trafficking in cultured cells and in the kidney. MnCl 2 treatment promoted internalization and intracellular accumulation of AQP2. The effect of MnCl 2 on the intracellular accumulation of AQP2 was associated with activation of RhoA and actin polymerization without modification of AQP2 phosphorylation. Although the level of total and phosphorylated AQP2 did not change, MnCl 2 treatment impeded VP-induced phosphorylation of AQP2 at its serine-256, -264, and -269 residues and dephosphorylation at serine 261. In addition, MnCl 2 significantly promoted F-actin polymerization along with downregulation of RhoA activity and prevented VP-induced membrane accumulation of AQP2. Finally, MnCl 2 treatment in mice resulted in significant polyuria and reduced urinary concentration, likely due to intracellular relocation of AQP2 in the PCs of kidney CDs. More importantly, the reduced urinary concentration caused by MnCl 2 treatment in animals was not corrected by VP. In summary, our study identified a novel effect of MnCl 2 on AQP2 trafficking through modifying RhoA activity and actin polymerization and uncovered its potent impact on water diuresis in vivo.

Background/aims: A sodium-glucose co-transporter-2 inhibitor dapagliflozin is widely used for lowering blood glucose and its usage is limited in type 2 diabetes mellitus patients with moderate renal impairment. As its effect on kidney function is discrepant and complicated, the aim of this study is to determine the effect of dapagliflozin on the progression of diabetic nephropathy and related mechanisms., Methods: Twelve-week-old male C57BL/6 wild-type and db/db mice were treated with vehicle or 1 mg/kg dapagliflozin for 12 weeks. Body weight, blood glucose, insulin tolerance, glucose tolerance, pyruvate tolerance and 24-hour urine were measured every 4 weeks. At 24 weeks of age, renal function was evaluated by blood urea nitrogen level, creatinine clearance, urine output, urinary albumin excretion, Periodic Acid-Schiff staining, Masson's trichrome staining and electron microscopy. Changes in insulin signaling and gluconeogenic key regulatory enzymes were detected using Western blot analysis., Results: Dapagliflozin did not alleviate but instead aggravated diabetic nephropathy manifesting as increased levels of microalbuminuria, blood urea nitrogen, and glomerular and tubular damage in db/db mice. Despite adequate glycemic control by dapagliflozin, urinary glucose excretion increased after administration before 24 weeks of age and was likely associated with renal impairment. Increased urinary glucose excretion was mainly derived from the disturbance of glucose homeostasis with elevated hepatic and renal gluconeogenesis induced by dapagliflozin. Although it had no effect on insulin sensitivity and glucose tolerance, dapagliflozin further induced the expression of gluconeogenic key rate-limiting enzymes through increasing the expression levels of FoxO1 in the kidney and liver., Conclusion: These experimental results indicate that dapagliflozin aggravates diabetes mellitus-induced kidney injury, mostly through increasing gluconeogenesis., (© 2018 The Author(s). Published by S. Karger AG, Basel.)

Autosomal dominant polycystic kidney disease (ADPKD) is a common monogenetic disease characterized by the progressive development of renal cysts with further need for effective therapy. Here our aim was to investigate the effect of Ganoderma triterpenes (GT) on the development of kidney cysts. Importantly, GT attenuated cyst development in two mouse models of ADPKD with phenotypes of severe cystic kidney disease. Assays for tubulogenesis showed that GT promoted epithelial tubule formation in MDCK cells, suggesting a possible effect on epithelial cell differentiation. The role of GT in regulating key signaling pathways involved in the pathogenesis of PKD was further investigated by immune blotting. This showed that GT specifically downregulated the activation of the Ras/MAPK signaling pathway both in vitro and in vivo without detectable effect on the mTOR pathway. This mechanism may be involved in GT downregulating intracellular cAMP levels. Screening of 15 monomers purified from GT for their effects on cyst development indicated that CBLZ-7 (ethyl ganoderate C2) had a potent inhibitory effect on cyst development in vitro. Additionally, like GT, CBLZ-7 was able to downregulate forskolin-induced activation of the Ras/MAPK pathway. Thus, GT and its purified monomer CBLZ-7 may be potential therapeutic regents for treating ADPKD., (Copyright © 2017 International Society of Nephrology. Published by Elsevier Inc. All rights reserved.)

The water channel aquaporin-2 (AQP2) is a major regulator of water homeostasis in response to vasopressin (VP). Dynamic trafficking of AQP2 relies on its close interaction with trafficking machinery proteins and the actin cytoskeleton. Here, we report the identification of ezrin, an actin-binding protein from the ezrin/radixin/moesin (ERM) family as an AQP2-interacting protein. Ezrin was first detected in a co-immunoprecipitation (co-IP) complex using an anti-AQP2 antibody in a proteomic analysis. Immunofluorescence staining revealed the co-expression of ezrin and AQP2 in collecting duct principal cells, and VP treatment caused redistribution of both proteins to the apical membrane. The ezrin-AQP2 interaction was confirmed by co-IP experiments with an anti-ezrin antibody, and by pulldown assays using purified full-length and FERM domain-containing recombinant ezrin. By using purified recombinant proteins, we showed that ezrin directly interacts with AQP2 C-terminus through its N-terminal FERM domain. Knocking down ezrin expression with shRNA resulted in increased membrane accumulation of AQP2 and reduced AQP2 endocytosis. Therefore, through direct interaction with AQP2, ezrin facilitates AQP2 endocytosis, thus linking the dynamic actin cytoskeleton network with AQP2 trafficking., Competing Interests: Competing interestsThe authors declare no competing or financial interests., (© 2017. Published by The Company of Biologists Ltd.)

Aquaporin-3 (AQP3), a transporter of water, glycerol and H 2 O 2 , is expressed in basolateral membranes of principal cells in kidney collecting duct. Here, we report that AQP3 deletion in mice affects renal function and modulates renal injury. We found collecting duct hyperplasia and cell swelling in kidneys of adult AQP3 null mice. After mild renal ischemia-reperfusion (IR), AQP3 null mice had significantly greater blood urea nitrogen (57mg/dl) and creatinine (136μM) than wild-type mice (35mg/dl and 48μM, respectively), and showed renal morphological changes, including tubular dilatation, erythrocyte diapedesis and collecting duct incompletion. MPO, MDA and SOD following IR in AQP3 null mice were significantly different from that in wild-type mice (1.7U/g vs 0.8U/g, 3.9μM/g vs 2.4μM/g, 6.4U/mg vs 11U/mg, respectively). Following IR, AQP3 deletion inhibited activation of mitogen-activated protein kinase (MAPK) signaling and produced an increase in the ratios of Bax/Bcl-2, cleaved caspase-3/caspase-3 and p-p53/p53. Studies in transfected MDCK cells showed that AQP3 expression attenuated reduced cell viability following hypoxia-reoxygenation, with reduced apoptosis and increased MAPK signaling. Our results support a novel role for AQP3 in modulating renal injury and suggest the mechanisms involved in protection against hypoxic injury., (Copyright © 2017. Published by Elsevier B.V.)

Although modes of action (MOAs) play a key role in the understanding of the toxic mechanism of chemicals, the MOAs have not been investigated for antibiotics to green algae. This paper is to discriminate excess toxicity from baseline level and investigate the MOAs of 13 different antibiotics to algae by using the determined toxicity values. Comparison of the toxicities shows that the inhibitors of protein synthesis to bacteria, such as azithromycin, doxycycline, florfenicol and oxytetracycline, exhibit significantly toxic effects to algae. On the other hand, the cell wall synthesis inhibitors, such as cefotaxime and amoxicillin, show relatively low toxic effects to the algae. The concentrations determined by HPLC indicate that quinocetone and amoxicillin can be easily photodegraded or hydrolyzed during the toxic tests. The toxic effects of quinocetone and amoxicillin to the algae are attributed to not only their parent compounds, but also their metabolites. Investigation on the mode of action shows that, except rifampicin, all the tested antibiotics exhibit excess toxicity to Pseudokirchneriella subcapitata (P. subcapitata). These antibiotics can be identified as reactive modes of action to the algae. They act as electrophilic mechanism of action to P. subcapitata. These results are valuable for the understanding of the toxic mechanism to algae., (Copyright © 2016 Elsevier Ltd. All rights reserved.)

Autosomal dominant polycystic kidney disease (ADPKD) is a monogenetic disease that still lacks effective therapy. Repulsive guidance molecule b (RGMb), a co-receptor for bone morphogenetic proteins (BMPs) and a ligand for neogenin, is expressed in renal tubular epithelial cells. Previous studies showed that RGMb plays negative roles in several types of tumors and prevents the immune system from over activation. The present study was designed to explore the effects of RGMb in ADPKD development. We found that expression of RGMb in kidney was less in PKD mice than wild-type mice. With stimulation of 8-bromo-cAMP, RGMb-null embryonic kidneys had greater cyst index, though their ureteric bud branched less than wild-type mice at E13.5. Postnatal RGMb-null kidneys showed interstitial hyperplasia and decreased tubular structures, especially in the boundary area of renal cortex and medulla. RGMb overexpression dramatically inhibited cyst development and promoted tubulogenesis in MDCK cells grown in 3D collagen gels. Biochemical analysis showed increased p-Smad1/5/8 and decreased p-ERK in RGMb-overexpressing MDCK cells, suggesting modulated BMP signaling. Specific inhibition of p-Smad1/5/8 by LDN193189 reversed the suppression of RGMb on MDCK cyst model. These results reveal RGMb as a novel regulator for ADPKD by promoting renal tubule branching and regulating BMP signaling pathway. Elevating RGMb and enhancing p-Smad1/5/8 are promising new strategies to treat ADPKD., (Copyright © 2016 Elsevier Inc. All rights reserved.)

Background: The cAMP-PKA signaling pathway and TGF-β1-dependent fibrosis pathways are of particular importance in ADPKD progression, but the cross-talk between these pathways remains unclear. Therefore, we used an MDCK-cell model and embryonic kidney-cyst model to study the regulatory role of cAMP-PKA signaling in the TGF-β1 induced fibrotic process., Method and Results: Pkd1(flox/flox); Ksp-Cre and Pkd1(+/+); Ksp-Cre mice were used as an in vivo model. Increased kidney volume, renal cysts formation and up-regulation of the fibrosis-related proteins TGF-β1, connective tissue growth factor (CTGF), and fibronectin (FN) can be observed in Pkd1(flox/flox); Ksp-Cre mice. In an embryonic kidneys-cyst model, TGF-β1, FN and collagen type I were highly expressed. Western blotting revealed the obviously up-regulation of TGF-β1, CTGF, FN and collagen type I expression following forskolin treatment in MDCK cells. Selective PKA inhibition with H89 may partially reversed the above effects. Pretreatment with the TGF-β RI kinase inhibitor VI SB431542 suppressed the increased expression of CTGF, FN and collagen type I caused by forskolin. Our data also indicate that forskolin inhibited TGF-β-induced ERK1/2 phosphorylation and FN up-regulation. ERK inhibition useing PD98059 significantly inhibited the expression of CTGF, FN and collagen type I caused by TGF-β1., Conclusions: The cAMP-PKA signaling pathway can directly promote the production of TGF-β1 and/or TGF-β1-dependent fibrogenetic molecules in MDCK cells and embryonic kidney cysts, but when TGF-β1 and its downstream pathways were highly expressed in MDCK cells, cAMP-PKA had a significantly negative effect on TGF-β1 induced p-ERK1/2 and FN expression., (© 2015 S. Karger AG, Basel.)

The discrimination of excess toxicity from narcotic effect plays a crucial role in the study of modes of toxic action for organic compounds. In this paper, the toxicity data of 758 chemicals to Daphnia magna and 993 chemicals to Tetrahymena pyriformis were used to investigate the excess toxicity. The result showed that mode of toxic action of chemicals is species dependent. The toxic ratio (TR) calculated from baseline model over the experimentally determined values showed that some classes (e.g. alkanes, alcohols, ethers, aldehydes, esters and benzenes) shared same modes of toxic action to both D. magna and T. pyriformis. However, some classes may share different modes of toxic action to T. pyriformis and D. magna (e.g. anilines and their derivatives). For the interspecies comparison, same reference threshold need to be used between species toxicity. The excess toxicity indicates that toxicity enhancement is driven by reactive or specific toxicity. However, not all the reactive compounds exhibit excess toxicity. In theory, the TR threshold should not be related with the experimental uncertainty. The experimental uncertainty only brings the difficulty for discriminating the toxic category of chemicals. The real threshold of excess toxicity which is used to identify baseline from reactive chemicals should be based on the critical concentration difference inside body, rather than critical concentration outside body (i.e. EC50 or IGC50). The experimental bioconcentration factors can be greatly different from predicted bioconcentration factors, resulting in different toxic ratios and leading to mis-classification of toxic category and outliers., (Copyright © 2013 Elsevier Ltd. All rights reserved.)

Prediction of the biodegradability of organic pollutants is an ecologically desirable and economically feasible tool for estimating the environmental fate of chemicals. In this paper, linear and nonlinear relationships between biological oxygen demand (BOD) and molecular descriptors/fragments have been investigated for 1130 organic chemicals. Significant relationships have been observed between the simple molecular descriptors and %BOD for some homologous compounds, but not for the whole set of compounds. Electronic parameters, such as E(HOMO) and E(LUMO), are the dominant factors affecting the biodegradability for some homologous chemicals. However, other descriptors, such as molecular weight, acid dissociation constant and polarity still have a significant impact on the biodegradation. The best global model for %BOD prediction is that developed from a chain-based fragmentation scheme. At the same time, the theoretical relationship between %BOD and molecular descriptors/fragments has been investigated, based on a first-order kinetic process. The %BOD is nonlinearly, rather than linearly, related to the descriptors. The coefficients of determination can be significantly improved by using nonlinear models for the homologous compounds and the whole data set. After analysing 1130 ready and not ready biodegradable compounds using 23 simple descriptors and various fragmentation schemes, it was revealed that biodegradation could be well predicted from a chain-based fragmentation scheme, a decision tree and a %BOD model. The models were capable of separating NRB and RB with an overall accuracy of 87.2%, 83.0% and 82.5%, respectively. The best classification model developed was a chain-based model but it used 155 fragments. The simplest model was a decision tree which only used 10 structural fragments. The effect of structures on the biodegradation has been analysed and the biodegradation pathway and mechanisms have been discussed based on activating and inactivating fragments., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The individual toxicities of Cu and 11 nitroaromatic compounds to Photobacterium phosphoreum were determined. The toxicity was expressed as the concentrations causing a 50% inhibition of bioluminescence after 15 min exposure (IC(50)). To evaluate the joint effect between the metal ion and the 11 nitroaromatic compounds, the joint toxicity of Cu and 11 nitroaromatic compounds were measured at different Cu concentrations (0.2IC(50), 0.5IC(50) and 0.8IC(50)), respectively. The result shows that the binary joint effect between Cu and nitroaromatic compounds is mainly simple addition at the low Cu concentration (0.2IC(50)). However, an antagonism effect, 55% and 64%, was observed between Cu and 11 nitroaromatic compounds for Cu at medium and high concentrations (0.5IC(50) and 0.8IC(50)). Quantitative structure-activity relationship (QSAR) analysis was performed to study the joint toxicity for the 11 nitroaromatic compounds. The result shows that the toxicity of nitroaromatic compounds is related to descriptors of Connolly solvent-excluded volume (CSEV) and dipolarity/polarizability (S) at low Cu concentration. On the other hand, the toxicity is related to Connolly accessible area (CAA) at medium and high Cu concentrations. The result indicates that different QSAR models on complex mixtures need to be developed to assess the ecological risk in real environments. Using single toxic data to evaluate the toxic effect of mixtures may result in wrong conclusions., (Copyright © 2012 Elsevier B.V. All rights reserved.)

The complex biological and mechanical requirements for implant materials in the human body generally cannot be furnished by one single material. In the present study, hydroxyapatite/polymer composite coatings with different contents of hydroxyapatite were produced using a flame spray system. This processing route is intended to obtain a coating with an optimal combination of biological and mechanical properties of these two materials for skeletal implants. The composite coatings were produced from a mechanical blend of hydroxyapatite and ethylene methacrylic acid copolymer powders, which were delivered from a fluidized bed powder feeder. Characterization of the coating surface morphology, polished coating cross-sections, and fracture surface morphology was conducted by scanning electron microscopy. The dissolution behavior of the coatings was evaluated with a calcium-specific ion meter. The stress-strain behavior was investigated by tensile testing. The biological and mechanical properties were found to be related to the volume and distribution of the hydroxyapatite in the polymer matrix. This technique provides a means of preparing hydroxyapatite/polymer coatings for application as implants.