Xuewen Li

Investigation of residual fluoroquinolones in a soil-vegetable system in an intensive vegetable cultivation area in Northern China.

One of the largest vegetable cultivation field sites in Northeast China was selected to investigate the occurrence and distribution pattern of fluoroquinolones (FQs) in the soil-vegetable system. A total of 100 surface soil samples and 68 vegetable samples were collected from this study area. The antibiotic concentration was analyzed using high-performance liquid chromatography tandem mass spectrometry. Results indicated the presence of FQs in all soil samples. Ciprofloxacin (CIP) had the highest mean concentration, at 104.4 μg · kg(-1) in the soil, a level that represents a relatively high risk to the environment and to human health. However, in the vegetable samples, norfloxacin (NOR) was significantly higher than CIP and enrofloxacin (ENR), ranging from 18.2 to 658.3 μg · kg(-1). The transfer ability of NOR in soil-vegetables is greater than that of CIP and ENR. Moreover, we found that the solanaceous fruits had a higher antibiotic accumulation ability than the leafy vegetables. Taken together, these data indicate that greater attention should be paid to the region in which vegetables with higher accumulation ability are grown.

Spatial estimation of antibiotic residues in surface soils in a typical intensive vegetable cultivation area in China

Antibiotic residues in surface soils can lead to serious health risks and ecological hazards. Spatial mean concentration of antibiotic residues in the soil is the most important indicator of a regions environmental risk to antibiotic residues. Considerable estimation error would lead to an inefficient strategy of pollution control that happens when sample size is small and the estimation model does not match the spatial features of the object to be surveyed. On the basis of the available datasets, it was found that the distribution of antibiotics residue in soil follows a spatial stratification pattern. Accordingly, we used a new spatial estimation method called Mean of Surface with Non-homogeneity (MSN) to estimate antibiotic concentrations in surface soil of the Shandong Province, an important vegetable growing region in China. The standard error of the mean estimates obtained by MSN was significantly smaller (by about 1.02-6.82 μg/kg) than the estimation errors produced by three mainstream methods, simple arithmetic estimation (2.9-11.8 μg/kg), stratified estimation (2.5-10.6 μg/kg) and ordinary kriging estimation (2.2-8.2 μg/kg).

Surface modeling of soil antibiotics

Large numbers of livestock and poultry feces are continuously applied into soils in intensive vegetable cultivation areas, and then some veterinary antibiotics are persistent existed in soils and cause health risk. For the spatial heterogeneity of antibiotic residues, developing a suitable technique to interpolate soil antibiotic residues is still a challenge. In this study, we developed an effective interpolator, high accuracy surface modeling (HASM) combined vegetable types, to predict the spatial patterns of soil antibiotics, using 100 surface soil samples collected from an intensive vegetable cultivation area located in east of China, and the fluoroquinolones (FQs), including ciprofloxacin (CFX), enrofloxacin (EFX) and norfloxacin (NFX), were analyzed as the target antibiotics. The results show that vegetable type is an effective factor to be combined to improve the interpolator performance. HASM achieves less mean absolute errors (MAEs) and root mean square errors (RMSEs) for total FQs (NFX+CFX+EFX), NFX, CFX and EFX than kriging with external drift (KED), stratified kriging (StK), ordinary kriging (OK) and inverse distance weighting (IDW). The MAE of HASM for FQs is 55.1 μg/kg, and the MAEs of KED, StK, OK and IDW are 99.0 μg/kg, 102.8 μg/kg, 106.3 μg/kg and 108.7 μg/kg, respectively. Further, RMSE simulated by HASM for FQs (CFX, EFX and NFX) are 106.2 μg/kg (88.6 μg/kg, 20.4 μg/kg and 39.2 μg/kg), and less 30% (27%, 22% and 36%), 33% (27%, 27% and 43%), 38% (34%, 23% and 41%) and 42% (32%, 35% and 51%) than the ones by KED, StK, OK and IDW, respectively. HASM also provides better maps with more details and more consistent maximum and minimum values of soil antibiotics compared with the measured data. The better performance can be concluded that HASM takes the vegetable type information as global approximate information, and takes local sampling data as its optimum control constraints.

Accumulation of steroid hormones in soil and its adjacent aquatic environment from a typical intensive vegetable cultivation of North China

Steroid hormones released from manure agricultural application are a matter of global concern. The residual levels of steroid hormones were studied in a typical intensive vegetable cultivation area in northeast China, with a long history of heavy manure application. Seven steroids (estrone, 17α-estradiol, 17β-estradiol, estriol, testosterone, androstendione and progesterone) were analyzed from soil sampled from vegetable greenhouses, from sediments and water from the adjacent drainage ditch and from the groundwater. The results showed that target steroids were detected in the soil samples, with detection frequencies varying from 3.13 to 100%. The steroid concentrations varied substantially in soils, ranging from below the detection limit to 109.7μg·kg(-1). Three steroids-progesterone, androstendione and estrone-were found to have relatively high residue concentrations in soil, with maximum concentrations of 109.7, 9.83 and 13.30μg·kg(-1), respectively. In adjacent groundwater, all the steroids, with the exception of estrone, were detected in one or more of the 13 groundwater samples. The concentrations of steroids in groundwater ranged from below the method detection limit to 2.38ng·L(-1). Six of the seven (excluding androstendione) were detected in drainage ditch water samples, with concentrations ranging from below the detection limit to 14ng·L(-1). Progesterone, androstendione and estrone accumulated relatively easily in soils; their concentrations in groundwater were lower than those of other steroids. The concentrations of testosterone and estriol were relatively low in soil, while in groundwater were higher than those of other steroids. The residual levels of steroids in soil and groundwater showed a clear spatial variation in the study area. The residual levels of steroid hormones in soil varied substantially between differently planted greenhouses.

Perinatal exposure to low doses of tributyltin chloride reduces sperm count and quality in mice

Exposure to endocrine disruptors (EDs) during early development might lead to adverse health outcomes later in life. Tributyltin (TBT), a proven ED, is widely used in consumer goods and industrial products. Herein we demonstrate the effects of low doses of tributyltin chloride (TBTCl) on reproduction of male KM mice. Pregnant mice were administered by gavage with 0, 1, 10, or 100 μg TBTCl/kg body weight/day from day 6 of pregnancy through the period of lactation. TBTCl dramatically decreased sperm counts and motility on postnatal days (PNDs) 49 and 152. Meanwhile, a significant increase in sperm abnormality was observed in exposed mice on PND 49, but comparable to that in the control on PND 152. The histopathological analysis of testes of treated animals showed a dose‐dependent increase in sloughing of germ cells in seminiferous tubules. Mice treated with 10 μg TBTCl/kg exhibited decreased intratesticular 17β‐estradiol (E2) levels on PND 49, and then followed by an obvious recovery on PND 152. While, no significant differences in serum E2, testosterone (T) levels and intratesticular T levels were detectable between control and TBTCl‐exposed offspring at the sacrifice. These results suggest that perinatal TBTCl exposure is implicated in causing long lasting alterations in male reproductive system and these changes may persist far into adulthood.

Using robust Bayesian network to estimate the residuals of fluoroquinolone antibiotic in soil

Prediction of antibiotic pollution and its consequences is difficult, due to the uncertainties and complexities associated with multiple related factors. This article employed domain knowledge and spatial data to construct a Bayesian network (BN) model to assess fluoroquinolone antibiotic (FQs) pollution in the soil of an intensive vegetable cultivation area. The results show: (1) The relationships between FQs pollution and contributory factors: Three factors (cultivation methods, crop rotations, and chicken manure types) were consistently identified as predictors in the topological structures of three FQs, indicating their importance in FQs pollution; deduced with domain knowledge, the cultivation methods are determined by the crop rotations, which require different nutrients (derived from the manure) according to different plant biomass. (2) The performance of BN model: The integrative robust Bayesian network model achieved the highest detection probability (pd) of high-risk and receiver operating characteristic (ROC) area, since it incorporates domain knowledge and model uncertainty. Our encouraging findings have implications for the use of BN as a robust approach to assessment of FQs pollution and for informing decisions on appropriate remedial measures.

Spatial Prediction of Soil Antibiotics Based on High-Accuracy Surface Modeling

The spatial prediction of soil antibiotic is more difficult than other normal soil properties due to the diverse sources of soil antibiotics. Few studies have attempted to predict soil antibiotic residues in intensive vegetable cultivation areas. High-accuracy surface modeling (HASM) is regarded as an important new technique in the pedometrics and digital soil mapping fields. A total of 100 surface soil samples were collected from the north-central part of the Shandong Province of China. The antibiotic concentrations, including ciprofloxacin (CF), enrofloxacin (EF), norfloxacin (NF), and fluoroquinolones (FQs), were analyzed using high-performance liquid chromatography–tandem mass spectrometry. We employed splines to compare its performance with that of HASM method. The errors of HASM for NF, CF, EF, and FQ were less compared to splines. HASM has less mean absolute error (MAE) and root mean square error (RMSE) than splines. The RMSEs of splines for FQ, CF, EF, and NF were 3.02, 2.34, 3.46, and 2.64 times lager than those of HASM, respectively. Therefore, HASM can be considered as an alternative and accurate method for interpolating soil antibiotics. It can also make the map more consistent with the true spatial distributions.

Potential of Pteris vittata to Remove Tetracycline Antibiotics from Aquatic Media.

The role of combined arsenic and antibiotics pollution in the environment has recently gained more attention. In this study, a new approach to eliminate tetracycline antibiotics (TCs) from water, via the fern species Pteris vittata (L.), an arsenic hyperaccumulator, was investigated. The encouraging results showed that more than half of the TCs could be removed from the water solution (with the starting concentration of TCs about 1.0 mg kg−1 respectively) after one day of treatment. No TCs (less than 0.01 mg kg−1) were detected in the solution after five days of treatment. The results showed that Pteris vittata has high ability to eliminate TCs, which makes it suitable for practical application. Further research found that TCs concentrations were very low in both the roots and the pinnae of Pteris vittata, which indicates that accumulation in the fronds is not the main removal mechanism and that degradation in the fronds might be the main cause. Present results provide a feasible method for simultaneous removal of arsenic and TCs from livestock-polluted wastewater. However, more research work should be done before any real-world application is made.