[Distribution Characteristics and Risk Assessment of Antimony in Typical Urban Soil].

In order to study the distribution characteristics and potential risk of antimony (Sb) in urban soil, the concentrations of soil Sb in four different land use types were analyzed based on the data of 1670 soil samples with different vertical profiles in 102 plots in Shanghai. The risks were evaluated using the potential ecological risk index method and health risk assessment model. The results showed that the average ω(Sb) in the study area was 0.52 mg·kg-1, and the content of soil Sb gradually declined with the rise in soil profile depth. Sb was enriched in surface soil, which indicated that human activities had caused disturbance to the distribution of Sb in the soil. The content of Sb in the surface soil of industrial land was higher than that of residential land and commercial land, and the content of Sb in agricultural land was the lowest. The single-factor pollution index of industrial land was the highest, reaching a slight pollution level, whereas the residential land, commercial land, and agricultural land were at even-clean or clean levels, respectively. The whole region showed slight ecological risk, with the potential ecological risk index ranging from 4.23 to 7.61. The potential ecological risk level of industrial land was moderate, which needs to be addressed. The results of health risk assessment showed that the non-carcinogenic risk of Sb in the soil was low; however, it is of great concern to residents, especially children, when on residential land.

Assessment for prognostic value of differentially expressed genes in immune microenvironment of clear cell renal cell carcinoma.

Tumor-infiltrating immune cells have been recognized to be associated with prognosis and response to immunotherapy; however, genes related to immune microenvironment of clear cell renal cell carcinoma (ccRCC) remains unclear. To better understand the effects of genes involved in immune and stromal cells on prognosis, we used Cancer Genome Atlas Kidney Renal Clear Cell Carcinoma (TCGA-KIRC), DAVID database and ESTMATE algorithm, and divided the patients into low and high groups according to immune (median: 1038.45) and stromal scores (median: 667.945), respectively. We found the immune scores were significantly correlated with clinicopathological parameters and overall survival (OS). Based on immune scores, 890 DEGs were significantly associated with OS among the 1433 up-regulated genes. Based on top 10 DEGs (IL10RA, FCER1G, SASH3, TIGIT, RHOH, IL12RB1, AIF1, LPXN, LAPTM5 and SP140), cases with number of up-regulated genes ≥ 5 were associated poor OS (P = 0.002). In addition, the mean differences of percentages of CD8 T cells (11.32%), CD4 memory resting T cells (-4.52%) and mast resting cells (-3.55%) between low and high immune scores were the most significant. Thus, combination of these genes might use to predict the efficacy of immunotherapy. Further analyses of these genes were warrant to explore their potential association with the prognosis of ccRCC.

Development of a method for efficient cost-effective screening of Aspergillus niger mutants having increased production of glucoamylase.

OBJECTIVES: To develop an efficient cost-effective screening process to improve production of glucoamylase in Aspergillus niger. RESULTS: The cultivation of A. niger was achieved with well-dispersed morphology in 48-deep-well microtiter plates, which increased the throughput of the samples compared to traditional flask cultivation. There was a close negative correlation between glucoamylase and its pH of the fermentation broth. A novel high-throughput analysis method using Methyl Orange was developed. When compared to the conventional analysis method using 4-nitrophenyl α-D-glucopyranoside as substrate, a correlation coefficient of 0.96 by statistical analysis was obtained. CONCLUSION: Using this novel screening method, we acquired a strain with an activity of 2.2 × 103 U ml-1, a 70% higher yield of glucoamylase than its parent strain.

Physiologically based pharmacokinetic model for quinocetone in pigs and extrapolation to mequindox.

Physiologically based pharmacokinetic (PBPK) models are scientific methods used to predict veterinary drug residues that may occur in food-producing animals, and which have powerful extrapolation ability. Quinocetone (QCT) and mequindox (MEQ) are widely used in China for the prevention of bacterial infections and promoting animal growth, but their abuse causes a potential threat to human health. In this study, a flow-limited PBPK model was developed to simulate simultaneously residue depletion of QCT and its marker residue dideoxyquinocetone (DQCT) in pigs. The model included compartments for blood, liver, kidney, muscle and fat and an extra compartment representing the other tissues. Physiological parameters were obtained from the literature. Plasma protein binding rates, renal clearances and tissue/plasma partition coefficients were determined by in vitro and in vivo experiments. The model was calibrated and validated with several pharmacokinetic and residue-depletion datasets from the literature. Sensitivity analysis and Monte Carlo simulations were incorporated into the PBPK model to estimate individual variation of residual concentrations. The PBPK model for MEQ, the congener compound of QCT, was built through cross-compound extrapolation based on the model for QCT. The QCT model accurately predicted the concentrations of QCT and DQCT in various tissues at most time points, especially the later time points. Correlation coefficients between predicted and measured values for all tissues were greater than 0.9. Monte Carlo simulations showed excellent consistency between estimated concentration distributions and measured data points. The extrapolation model also showed good predictive power. The present models contribute to improve the residue monitoring systems of QCT and MEQ, and provide evidence of the usefulness of PBPK model extrapolation for the same kinds of compounds.

Carbon consequences and agricultural implications of growing biofuel crops on marginal agricultural lands in China.

Using marginal agricultural lands to grow energy crops for biofuel feedstocks is a promising option to meet the biofuel needs in populous China without causing further food shortages or environmental problems. Here we quantify the effects of growing switchgrass and Miscanthus on Chinese marginal agricultural lands on biomass production and carbon emissions with a global-scale biogeochemical model. We find that the national net primary production (NPP) of these two biofuel crops are 622 and 1546 g C m(-2) yr(-1), respectively, whereas the NPP of food crops is about 600 g C m(-2) yr(-1) in China. The net carbon sink over the 47 Mha of marginal agricultural lands across China is 2.1 Tg C yr(-1) for switchgrass and 5.0 Tg C yr(-1) for Miscanthus. Soil organic carbon is estimated to be 10 kg C m(-2) in both biofuel ecosystems, which is equal to the soil carbon levels of grasslands in China. In order to reach the goal of 12.5 billion liters of bioethanol in 2020 using crop biomass as biofuel feedstocks, 7.9-8.0 Mha corn grain, 4.3-6.1 Mha switchgrass, or 1.4-2.0 Mha Miscanthus will be needed. Miscanthus has tremendous potential to meet future biofuel needs, and to benefit CO(2) mitigation in China.