Yan Liu

Southwest University in Chongqing, Pehpei, Chongqing Shi, China

Are you Yan Liu?

Claim your profile

Publications (5)8.66 Total impact

  • [Show abstract] [Hide abstract]
    ABSTRACT: As the main synthetic raw materials of polycarbonate, bisphenol A (BPA) and its analogues have been important issues in environmental pollution. The current studies focus mainly on BPA's estrogen effects and little on their cytotoxic effects. To assess the cytotoxicities of the five BPA analogues, we employed the MTS assay to determine the inhibition toxicity to MCF-7 (ER-), 2,4-dinitrophenylhydrazine assay to determine the release rate of lactate dehydrogenase (LDH) escaping into cell culture medium, and single cell gel electrophoresis assay (SCGE) to detect DNA damage. The dose-response curves (DRC) between the observed inhibition toxicities and concentrations of the BPA compounds in MTS assay were fitted by using the nonlinear least squares (NLS) and the results showed that all the dose-response relationships were effectively described by the Weibull or Logit function. The toxicities expressed by--lgpEC50 were BPB > BPC > TDP > BPE > BPA. LDH assay and SCGE assay showed that when the concentrations of BPA analogues were EC20, the MCF-7 cell proliferation was slightly inhibited due to its little damaged DNA, and at EC40 the cell proliferations were significantly inhibited due to the seriously damaged DNA, leading to the damage of cell membrane and release of LDH.
    Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.] 11/2012; 33(11):3935-40.
  • [Show abstract] [Hide abstract]
    ABSTRACT: The bioluminescence inhibition of six triazine herbicides including desmetryne (DES), simetryn (SIM), velpar (VEL), prometon (PRO), metribuzin (MET), and aminotriazine (AMI) on Vibrio qinghaiensis sp.-Q67 (Q67) was determined to investigate the effects of exposure duration on the ecotoxicological relevance of triazine herbicides. Based on the short-term microplate toxicity analysis (MTA), a long-term MTA was established to assess the impact of exposure time on the toxicities of the herbicides. The results show that the long-term toxicities of DES and SIM are similar to their short-term toxicities, and the long-term toxicities of VEL, PRO, and MET are higher than their short-term toxicities, while AMI without short-term toxicity has a high long-term toxicity. In addition, a parabolic relationship was found between the pEC(50) (the negative logarithm of the EC(50), log 1/EC(50)) and the logarithm of octanol-water partition coefficient (logK(ow)). To better understand their toxicity process, the time-dependent toxicities of the six herbicides on Q67 were determined over a period of 12 h during which measurements were taken every 30 min to generate an integral effect surface related to both concentration and duration.
    Water Research 02/2009; 43(6):1731-9. · 4.66 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: Using the molecular electronegativity distance vector (MEDV) descriptors derived directly from the molecular topological structures, the gas chromatographic relative retention times (RRTs) of 209 polychlorinated biphenyls (PCBs) on the SE-54 stationary phase were predicted. A five-variable regression equation with the correlation coefficient of 0.9964 and the root mean square errors of 0.0152 was developed. The descriptors included in the equation represent degree of chlorination (nCl), nonortho index (Ino), and interactions between three pairs of atom types, i.e., atom groups -C= and -C=, -C= and >C=, -C= and -Cl. It has been proved that the retention times of all 209 PCB congeners can be accurately predicted as long as there are more than 50 calibration compounds. In the same way, the MEDV descriptors are also used to develop the five- or six-variable models of RRTs of PCBs on other 18 stationary phases and the correlation coefficients in both modeling stage and LOO cross-validation step are not lower than 0.99 except two models.
    Journal of Separation Science 02/2006; 29(2):296-301. · 2.59 Impact Factor
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: The molecular holographic distance vector (MHDV) is employed to characterize the structures of 51 sub-stituted benzenes. 29 descriptors from 91 MHDV ones have nonzero values where 3 descriptors have only one nonzero sample and 1 descriptor only two nonzero samples. A genetic algorithm is used to select an optimal combination of the variables from the remaining 25 nonzero descriptors. Then the optimal descriptors are em-ployed to relate to the relative biodegradability using multiple linear regression method. The 6-variable linear model developed has high quality where the correlation coefficient of estimations and the root mean square error of estimations are 0.9604 and 0.280, respectively, and the correlation coefficient of predictions and the root mean square error of predictions for leave-one-out procedure are 0.9471 and 0.324, respectively.
    Journal- Chinese Chemical Society Taipei 01/2003; 50(2). · 0.88 Impact Factor
  • [Show abstract] [Hide abstract]
    ABSTRACT: 8wt%WO3/SiO2 metathesis (disproportionation) catalysts with different pore structures were prepared by the incipient-wetness-impregnation method. The as-synthesized catalysts were characterized by N2 adsorption-desorption, scanning electron microscopy (SEM), X-ray diffraction (XRD), UV-visible diffuse reflectance spectroscopy (DRS) and scanning transmission electron microscopy-high-angle annular dark field (STEM HAADF). The results of STEM HAADF showed that WO3 species were not uniformly distributed on the SiO2 support. The experimental results of 8wt%WO3/SiO2 performance in ethene/decene metathesis revealed that the catalytic effect of 8wt%WO3/SiO2 catalyst and coke formation over it were closely related to the support pore structure: The 8wt%WO3/SiO2 catalyst with a more complicated pore structure showed better catalytic performance but the coke deposition rate was also faster.
    Petroleum Science 10(1). · 0.53 Impact Factor