[Effect of Wnt signaling suppression on gefitinib in non small cell lung cancer cell lines].

OBJECTIVE: To explore the effect of Wnt signaling suppression on proliferation of non small cell lung cancer to gefitinib, and its related mechanisms. METHODS: PC9 and PC9/AB2 cells of both gefitinib sensitive and resistant were treated with different concentrations of gefitinib, and the proliferation index was measured using CCK8 kit. The members of Wnt signaling pathway were detected by Western blot. Dual luciferase reportor gene assay (TOP Flash) was used to document the transcriptional level of ß-catenin. ß-catenin siRNA was transfected into PC9/AB2 cells to suppress the Wnt signaling transcription, followed by treatment with different concentrations of gefitinib. Western blot was then used to detect the expression of EGFR and its downstream signaling after inhibit the expression of ß-catenin. RESULTS: Treating with different concentrations of gefitinib, the resistance of PC9/AB2 cells to gefitinib was significantly increased (P < 0.05). The members of Wnt signaling expressed at higher level in PC9/AB2 cells than in PC9 cells (t = 24.590, P = 0.000). TOP Flash examination showed that the endogenous transcriptional activity of Wnt signaling was higher in PC9/AB2 cell than that in PC9 cell (t = 4.983, P = 0.008). Compared with the negative control group, apoptotic rate and sensitivity to gefitinib significantly increased in interfered group (P < 0.05). The expression of p-ERK1/2 significantly decreased after Wnt signaling suppression, although other proteins showed no significant alterations. CONCLUSION: Suppressing the activity of Wnt signaling can partly reverse the celluar resistance to gefitinib in non small cell lung cancer.

Soil organic carbon content increase in the east and south of China is accompanied by soil acidification.

Increased soil organic carbon (OC) in China has been reported in the past two decades, suggesting the sequestration of atmospheric carbon dioxide into soil, mitigating climate change and improving soil health. On the other hand, soil pH decrease had also been reported nationwide. If the two are related, the strategy of increasing soil OC could negatively affect soil quality for food production and the environment. We investigate this thread based on large-scale soil survey data from two provinces with typical soil and cropping patterns in the east and south of China, Jiangsu (102,600 km2) and Guangdong (177,900 km2). The data include >5000 observations from soil surveys conducted over the past four decades, i.e., the 1980s, 2006-2007, and 2010-2011. Using spatiotemporal modelling, we show that across Jiangsu province, the topsoil OC on average has increased from 8.5 g kg-1 to 9.9 g kg-1 from 1980 to 2000 and a further increase to 12.6 g kg-1 in 2010. This increase was accompanied by a decrease in average pH from 7.63 to 6.90. In Guangdong, there was an overall increase in average topsoil OC content from 14.2 g kg-1, 16.5 g kg-1, and 20.2 g kg-1 with a decrease in average pH from 5.58, 4.90, and 4.98. Based on the spatiotemporal modelling results, the structural equation modelling analysis shows that OC and pH changes were significantly correlated and linked by increased soil N content. On croplands, soil N content was mainly attributed to N fertiliser application. The pH decrease was particularly significant in the east of China where the soils were neutral in pH. We recommend that more revolutionary means be taken to sequestrate atmospheric carbon into soil as the current OC increase due to increasing crop productivity via a high rate of nitrogen application may have a potential acidification effect.

Performance of median kriging with robust estimators of the variogram in outlier identification and spatial prediction for soil pollution at a field scale.

Median kriging with robust estimators of the variogram has been proposed in literature to reduce the influences of outliers in spatial data of soil pollution, because median kriging can utilize outliers in spatial prediction and robust estimators can overcome the bias caused by outliers. However, performance of the method at a field scale remains unknown. This study compared the method in two case studies of soil Pb pollution with two other commonly used methods for outlier identification, including box-plot and standardized kriging prediction error (SKPE), and with two classical geostatistical approaches for spatial prediction, including kriging with and without outliers. One case was based on data with 359 samples collected in an area of 14.5km2 in Jura, Swiss. The other was based on data with 242 samples collected in an area of 2.8km2 in Zhuzhou, China. Results showed that the method identified both global and local outliers, while the method did not identify all global outliers based on the box-plot. For the Jura data which were more seriously affected by outliers than the Zhuzhou data, the method identified 49 outliers, sharing 39 with SKPE which identified a total of 46 outliers. For the Zhuzhou data, the method found just three outliers, much fewer than the 12 outliers identified by SKPE. In the case of Jura, kriging prediction with outliers winsorized by the method was negligibly more accurate than prediction without outliers identified by SKPE, e.g., 0.15% in terms of root mean square error (RMSE). However, in the case of Zhuzhou, the former prediction was slightly less accurate than the latter, e.g., 2.39% in terms of RMSE. This study suggested that the method performed well for data which were seriously affected by outliers, but not so well for data slightly affected by outliers.

[Principal Component Analysis and Ecological Risk Assessment of Heavy Metals in Farmland Soils around a Pb-Zn Mine in Southwestern China].

The farmland soil around a Pb-Zn mine in southwestern China was studied. One hundred forty-nine surface soil samples were taken from 0-20 cm depth, and the contents of As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were tested. The correlations among these heavy metals were studied with multivariate analysis, and the potential sources of the metals were identified. The environmental risk of the metals was evaluated with the Potential Ecological Risk Index method. The results showed that the amounts of Cd, Pb, and Zn were at relatively high level, with average concentrations of 15.56, 419.4, and 933.4mg·kg-1 respectively, indicating the soil was heavily polluted. The average concentrations of Hg and As were 0.13 and 37.3mg·kg-1, suggesting moderate soil pollution. The average concentrations of Cu, Ni, and Cr were lower than Yunnan soil background values. The multivariate analysis suggested that the sources of Cd, Pb, Zn, Hg, and As were similar and came mainly from smelting activities in the mining area. The sources of Cu, Ni, and Cr were similar and can be attributed to natural sources. The comprehensive potential ecological risk index was 2294.8, which suggested a high potential ecological risk. In general, the farmland soils in the research area were polluted seriously by the mining and industrial activities.

[Distribution and migration of heavy metals in soil profiles by high-resolution sampling].

The vertical distribution of heavy metals in soils profiles is a result of heavy metals accumulation and migration under combining influence of edaphic factors and environmental conditions. It's an important basis for evaluation of heavy metals pollution and remediation of contaminated soils. By traditional sampling methods, i.e., soils were sampled according to pedogenetic horizons, only very general information about element migration can be learned. In the current study, three sites near a steel factory were selected to represent three types of land use, i.e. forest, dry land for vegetable cultivation and rice paddy field. Soils were sampled horizontally by high-resolution sampling method. In the top of 40 cm soils were sectioned in 2 cm intervals, then 5 cm intervals in next 40 cm, and 10 cm intervals in the last 20 cm of profile. Total content of Cu, Zn, Pb, Cr and Cd were determined, and the vertical distribution of Cu, Zn, Pb, Cr, Cd in every profile was analyzed. The results indicated that enrichment of heavy metals appeared in the upper most layer of the natural forest soil that without any anthropic disturbance, and this phenomenon proved that heavy metals were coming from atmospheric deposition. We found that Cu, Zn and Pb moved downward in a short distance, Cd migrated relatively faster than Cu, Zn and Pb, while Cr had no recognizable location of migration front. In the soil profiles of dry land and paddy field, there were influences of agricultural practice, the distribution and movement of metals were thus different form those of the forest soil. In cultivated layer heavy metals were evenly distributed because soils in the upper layer were mixed by cultivation, however, bellow the cultivated layer obvious migration took place again. It is concluded that different heavy metals have different mobility and there is such a relative order: Cd>Cu>Zn>Pb. The study shows that the distribution pattern can be obtained with the currently adopted high-resolution sampling method, than traditional horizon sampling, and more precise migration distance and rates can be estimated.