[Pollution Level, Distribution Characteristic, and Ecological Risk Assessment of Environmentally Persistent Pharmaceutical Pollutants in Surface Water of Jiangsu Province].

Because Jiangsu is an important economic province of China, it is necessary to examine the pollution characteristics and assess the ecological risk of environmentally persistent pharmaceutical pollutants (EPPPs) in this region. In this study, surface water samples were obtained from grade 1-4 rivers and lakes (with an area of 50 km2 or more) in Jiangsu Province, and then analyzed to determine the pollution level of EPPPs. In total, 35 EPPPs were detected in the surface water of Jiangsu Province, with total concentrations in the samples ranging from 66.74 to 2189.83 ng·L-1. The 17 EPPPs with a detection rate of more than 25% are discussed in this study. The total concentrations of 35 EPPPs were 72.48-1142.79 ng·L-1, and the mean concentration was 345.20 ng·L-1. The total concentration of EPPPs was higher in the north and south than in the central part of Jiangsu. Yangzhou city had the highest concentration of EPPPs in the whole province, and the main sources of this pollution were domestic sewage, shipping sewage discharge, and drug use in fishery breeding. The total concentration of EPPPs decreased on both sides of the region, with the Beijing-Hangzhou Canal and waste from the Yellow River forming the middle line. An ecological risk assessment of 17 EPPPs showed that single target drugs posed a low risk to water ecology in Jiangsu Province. The combined risk quotient of 17 EPPPs in water of Jiangsu Province was 0.03-0.52, indicating that EPPPs posed a low to moderate risk.

Treatment of particle/gas partitioning using level III fugacity models in a six-compartment system.

In this paper, two level III fugacity models are developed and applied using an environmental system containing six compartments, including air, aerosols, soil, water, suspended particulate matters (SPMs), and sediments, as a "unit world". The first model, assumes equilibrium between air and aerosols and between water and SPMs. These assumptions lead to a four-fugacity model. The second model removes these two assumptions leading to a six-fugacity model. The two models, compared using four PBDE congeners, BDE-28, -99, -153, and -209, with a steady flux of gaseous congeners entering the air, lead to the following conclusions. 1. When the octanol-air partition coefficient (KOA) is less than 1011.4, the two models produce similar results; when KOA > 1011.4, and especially when KOA > 1012.5, the model results diverge significantly. 2. Chemicals are in an imposed equilibrium in the four-fugacity model, but in a steady state and not necessary an equilibrium in the six-fugacity model, between air and aerosols. 3. The results from the six-fugacity model indicate an internally consistent system with chemicals in steady state in all six compartments, whereas the four-fugacity model presents an internally inconsistent system where chemicals are in equilibrium but not a steady state between air and aerosols. 4. Chemicals are mass balanced in air and aerosols predicted by the six-fugacity model but not by the four-fugacity model. If the mass balance in air and aerosols is achieved in the four-fugacity model, the condition of equilibrium between air and aerosols will be no longer valid.

Integrated fate assessment of aromatic amines in aerobic sewage treatment plants.

The fate and exposure of chemicals in sewage treatment plants (STPs) are major considerations in risk assessment and environmental regulation. The biodegradability and removal of seven aromatic amines were systematically evaluated using a three-tiered integrated method: a standard ready biodegradability test, an aerobic sewage treatment simulation method, and model prediction. In tier 1, the seven aromatic amines were not readily biodegraded after 28 days. In adapted aerobic active sludge, 4-isopropyl aniline, 2,4-diaminotoluene, and 4-nitroaniline among them exhibited the degradation half-life time less than 20 h, the other four aromatic amines exhibited persistent with degradation half-life of > 60 h. In tier 2 of the aerobic sewage treatment simulation testing, 2,4-diaminotoluene, 4-nitroaniline, and 4-isopropylaniline demonstrated moderately to high overall removal. Hydraulic retention time (HRT) affects the removal with the optimum HRT was determined to be 12 h to 24. 2,6-Dimethyl aniline, 2-chloro-4-nitroaniline, 2,6-diethylaniline, and 3,4-dichloroaniline were not removed during the test, indicting these four aromatic amines will enter surface water and hence pose a potential risk to aquatic ecology. Considering the lack of an STP model in China for regulation purposes, in tier 3, we developed a Chinese STP (aerobic) (abbreviated as C-STP(O)) model that reflects a universal scenario for China to predict the fate. The predicted degradation, volatilization, and absorption showed a close relationship to the physicochemical properties of the chemicals, and had same tendency with tier 2 simulation test. The prediction showed that biodegradation rather than absorption or volatilization was the main removal process of aromatic amines in aerobic STP. With the combination of modified kinetics test with C-STP (O) model, the chemical fate can be more accurately predicted than using only the readily biodegradation result.

Computational methods for recognition of cancer protein markers in saliva.

In recent years, many studies have supported that cancer tissues can make disease-specific changes in some salivary proteins through some mediators in the pathogenesis of systemic diseases. These salivary proteins have the potential to become cancer-specific biomarkers in the early diagnosis stage. How to effectively identify these potential markers is one of the challenging issues. In this paper, we propose novel machine learning methods for recognition cancer biomarkers in saliva by two stages. In the first stage, salivary secreted proteins are recognized which are considered as candidate biomarkers of cancers. We picked up 557 salivary secretory proteins from 20379 human proteins by public databases and published literatures. Then, we present a training set construction strategy to solve the imbalance problem in order to make the classification methods get better accuracy. From all human protein set, the proteins belonging to the same families as salivary secretory proteins are removed. After that, we use SVC-KM method to cluster the remaining proteins, and select negative samples from each cluster in proportion. Next, the features of proteins are calculated by tools. We collect 24 protein properties such as sequence, structure and physicochemical properties, a total of 1087 features. An innovative procedure based on the local samples is proposed for selecting the appropriate features, in order to further improve the performance of SVM classifier. Experimental results show that the average sensitivity, specificity and accuracy of salivary secretory protein recognition using selected 32 features in training set are 97.09%, 98.10%, 97.61%, respectively. The use of these methods can improve the accuracy of recognition by solving the problems of unbalanced sample size and uneven distribution in training set. In the second stage, we apply the best model to dig out the salivary secreted proteins from 58 reported cancer markers, and get a total of 42 proteins which are considered to be used for salivary diagnosis. We analyze the gene expression data of three types of cancer, and predict that 33 genes will appear in saliva after they are translated into proteins. This study provides an important computational tool to help biologists and researchers reduce the number of candidate proteins and the cost of research. So as to further accelerate the discovery of cancer biomarkers in saliva and promote the development of saliva diagnosis.

Development of an integral strategy for non-target and target analysis of site-specific potential contaminants in surface water: A case study of Dianshan Lake, China.

Surface water contains a large number of potential pollutants and their transformation products, which cannot be discovered by normal target analysis alone. To detect site-specific and unknown contaminants in the environment, we established an integral analytical strategy based on liquid chromatography-high resolution mass spectrometry (LC-HRMS) combined with data processing using specific software (Compound Discoverer 3.0). In this case study of Dianshan Lake, 95 potential contaminants were tentatively identified and ranked by the scoring system. Then, the 95 compounds were categorized into 4 subgroups: pesticides, drugs, plastic additives and surfactants. To determine the sources and distribution of those pollutants, 4 heat maps were developed based on the sum of peak areas of respective categories. In addition, 19 substances with high exposure risk among the 95 compounds tentatively identified were confirmed and quantified. In the present study, the analytical strategy with non-target screening followed by target analysis demonstrated that pesticides and plastic additives are the two dominant types of contaminants in Dianshan Lake. High accuracy and high-resolution data combined with integrated software provided abundant information for the identification of a wide range of potential contaminants in the environment. This approach can be a useful tool for the simple and rapid screening and tentative detection of site-specific contaminants.

[Pollution Level, Distribution Characteristics and Risk Assessment of 32 PPCPs in Surface Water of Luomahu Lake].

A total of 22 water samples collected from Luomahu Lake were determined using high performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) to evaluate the pollution level,spatial distribution and ecological risk of 32 PPCPs.23 PPCPs were detected in surface water of Luomahu Lake and the total concentrations of 22 samples were 892-1536 ng·L-1.The concentration of norfloxacin (256-707 ng·L-1) was the highest among the detected PPCPs,followed by ketoprofen (85-438 ng·L-1),acesulfame (101-290 ng·L-1) and naproxen (1.9-112 ng·L-1).Spatial differences were found in concentrations of PPCPs in various sampling sites.Concentrations of PPCPs in northeast of Luomahu Lake were higher than those of southwest.Concentration of PPCPs in Fangtinghe River was high and that of Zhangshanzha River was relatively low.The risk assessment of 13 pharmaceutical PPCPs showed that risk quotients (RQs) of norfloxacin were 0.26-0.72,posing medial risk to aquatic ecosystem.Gemifibrozil posed low ecological risks with RQs>0.01 in most sampling sites.RQs of other 11 PPCPs were less than 0.01,posing no ecological risks.The combined risk quotients of 12 PPCPs in water of Luomahu Lake were 0.29-0.75,indicating that those compounds posed an medial risk to aquatic ecosystem.Human health risk assessment showed that the RQs were less than one for 6 selected PPCPs,indicating that these compounds did not appear to pose an appreciable risk to human health by potential environmental exposure from drinking water.

[Fate of Eleven Phthalic Acid Esters in Aerobic Sewage Treatment System].

Phthalic acid esters have potential environmental risk due to their endocrine disrupting effect. The biodegradable and removal characteristics of 11 phthalicacidesters were studied. The results showed that dimethyl phthalate(DMP), dimethoxyethyl phthalate (BMEP), diethyl phthalate(DEP), dibutyl phthalate (DBP), diisobutyl phthalate(DIBP), dinamyl phthalate (DNPP), di-n-hexyl phthalate(DNHP)and bis (2-ethylhexyl) phthalate (DEHP) had ready biodegradability, dinonyl phthalate (DNP)and dicyclohexyl phthalate (DHP)could be biodegraded but did not pass the 10 d window-period, and only 43.5% of diphenyl phthalate (DPP) was biodegraded on 28d. The degradation curves of 11 PAEs all obeyed typical first-order kinetics in aerobic sludge kinetics test, with the correlation coefficient r2>0.96, the degradation rate constant was between 0.021-1.11 h-1, and the degradation half-life was between 0.625-32.7 h. In aerobic sludge simulation test, the removal rates of 10 PAEs were>80% at hydraulic detention time of 12h, except that DNPP was only 55%-70%. The removal rates of all PAEs reached 90% at hydraulic detention time of 24h. The relative high exposure in effluent for DMP, DEP, DIBP, DBP and DEHP was found by using GC/MS, with the residue concentrations of ND-44.0, ND-12.0, 60.4-594, 88.0-823 and 130-728 ng·L-1, respectively. The results from STP model prediction showed that the removal in STP was mainly contributed by biodegradation, but for DPP, DNP and DEHP, the absorption removal was also an important removal way.

[Development of Chemical Exposure Prediction Model for Aerobic Sewage Treatment Plant for Biochemical Wastewaters].

Sewage treatment plant (STP) is a key transfer station for chemicals distributed into different environment compartment, and hence models of exposure prediction play a crucial role in the environmental risk assessment and pollution prevention of chemicals. A mass balance model namely Chinese Sewage treatment plant (C-STP(O)) was developed to predict the fate and exposure of chemicals in a conventional sewage treatment plant. The model was expressed as 9 mixed boxes by compartment of air, water, suspended solids, and settled solids. It was based on the minimum input data required on the notification in new chemicals, such as molecular weight, absorption coefficient, vapor pressure, water solubility, ready or inherent biodegradability. The environment conditions ( Temperature = 283 K, wind speed = 2 m x s(-1)) and the classic STP scenario parameters of China, especially the scenario parameters of water quality and sludge properties were adopted in C-STP( 0) model to reflect Chinese characteristics, these parameters were sewage flow of 35 000 m3 x d(-1), influent BOD5 of 0.15 g x L(-1), influent SS of 0.2 kg x m(-3), effluent SS of 0.02 kg x m(-3), BOD5 removal in aerator of 90% sludge density of 1.6 kg x L(3) and organic carbon content of 0.18-0.19. It adopted the fugacity express for mechanism of linear absorption, first-order degradation, Whitman two resistances. An overall interphase transfer constant which was the sum of surface volatilization and stripping was used to assess the volatilization in aerator. The most important and uncertain input value was the biodegradation rate constant, and determination of which required a tier test strategy from ready or inherent biodegradability data to simulate test in STP. An extrapolated criterion of US EPA to derive biodegradation rate constant using the results of ready and inherent biodegradability was compared with that of EU and was recommended. C-STP ( 0 ) was valid to predict the relative emission of volatilization, absorption, degradation and effluent, on ground of both successful simulation of the removal of 26 chemicals from references with an accuracy rate of 81% and consistency of prediction and test with absolute difference of 2.5%-6.3% for 5 phenols. In cases of prediction of three chemicals with different properties, 1,1, 2-trichloroethane, Naphthalene and DEHP, the predicted fate well satisfied the monitor data. The model is therefore believed to be a simple, robust and useful tool in fate study and exposure assessment of chemicals.

[Degradation Characteristics of Three Aniline Compounds in Simulated Aerobic Sewage Treat System].

The removal rates of 4-nitroaniline, 4-isopropyl aniline and 2-chloro-4-nitroaniline under different hydraulic retention time (HRT) were tested by employing a simulation method of aerobic biochemical sewage treatment technology in this study. The results showed that when HRT was 6 h, 12 h, and 24 h, the removal rates of dissolved organic carbon (DOC) were 70.2%, 80.3% and 88.3%, the removal rates of 4-nitroaniline were 48%, 64.7% and 75%; and the removal rates of 4-isopropyl aniline were 66%, 76% and 91%, respectively. It was concluded that increasing HRT could promote the removal rates of DOC and aniline chemicals. In contrast, 2-chloro-4-nitroaniline was difficult to be removed. The removal rates were less than 20% under all tested conditions. The kinetics analysis showed that the biodegradation of 4-nitroaniline, 4-isopropyl aniline and 2-chloro-4-nitroaniline in aerobic activated sewage (3 g x L(-1)) accorded with the first order kinetics and the regression coefficients were > 0.95. The half-life time of biodegradation was 6.01 h, 16.16 h, 123.75 h, respectively. In general, functional groups such as isopropyl had a positive effect on the biodegradation of aniline chemicals, whereas substituents such as nitro group and chlorine atom had an inhibitory effect.

[Bulky DNA adducts in human sperm correlate with semen parameters and sperm apoptosis].

OBJECTIVE: To explore the correlation of sperm polycyclic aromatic hydrocarbons (PAH)-DNA adducts with semen quality and sperm apoptosis. METHODS: We collected semen samples from 433 infertile Chinese men, detected sperm PAH-DNA adducts using immunofluorescence staining and flow cytometry, and determined the rate of sperm apoptosis by TUNEL. RESULTS: Multiple linear regression analysis showed that the level of sperm PAH-DNA adducts was correlated negatively with sperm concentration (beta = -0.632), total sperm count (beta = -0.830) and sperm motility (beta = -9.647), but positively with the rate of sperm apoptosis (beta = 0.130). CONCLUSION: Sperm PAH-DNA adducts are evidently correlated with semen quality and sperm apoptosis, and play an important role in the evaluation of male productivity.

[Effects of changes in conformation and configuration of N-containing compounds on NMR spactra].

AIM: To find the cause of abnormal NMR spectra of lomerizine dihydrochloride, cetirizine dihydrochloride and flenfluramine camphoramide. METHODS: Hypothesizing, in given conditions, there are changes of stereoisomeric conformation and configuration in structure of N-containing compounds, it results in abnormality of NMR spectra. By using the method of NMR, it is confirmed credibily. RESULTS AND CONCLUSION: The moving balance exists between two chair conformations in lomerizine dihydrochloride and cetirizine dihydrochloride. It causes that spin-nuclei of whole molecule are placed in two chemical circumstance. In solution of DMSO-d6, the speed of conformation reversal equals to the NMR time scale, so that chemical shift of spin-nuclei can not be definitely determined, peaks are broadened and even collapsed. After dropping D2O or increasing the temperature, the viscosity of the solution is decreased, the speed of reversal is quicker than NMR time scale, then normal spectra are obtained. Owing to the reversal of the three bonds of nitrogen in flenfluramine camphoramide is limited, other pair of diastereoisomer resulted from the asymmetric nitrogen can be detected by NMR. Multiplication of the peaks of 13CNMR is reasonably explained.

[Discussion of the application of three-point interaction principle to the phenylglycine racemic compound in IR spectrometry and its enantiomers separation in HPLC].

AIM: To discuss the relationship between the three-point interaction principle in the stereoselective separation of chromatography and applying this principle to survey the infrared spectrometry of racemate. METHODS: In proving the applicability of the three-point interaction principal in IR spectrometry, a special case was found that phenylglycine did not obtain enantioselective separation on the chiral column but its IR spectrometry still obey this principle and explained such special case by experiment. RESULTS: After an equal quantity of solid crystal of d-phenylglycine and l-phenylglycine were mixed and ground for several minutes, they transformed to racemic compound. X-powder diffraction also confirmed this fact. CONCLUSION: The three-point principle was relatively reliable when it was used in the enantioselective chromatography separation and the IR spectrometric analysis. The reason of the fact that phenylglycine was not separated by chiral column can be explained by the fact that the acting force between the three polarity groups in the enantiomers is so strong that they can not form the instantaneous diastereoisomer with the chiral column, it was agreeable with the phenomenon that racemic mixture easily became racemic compound only by simply grinding the mixture in IR spectrometric experiment.