Antitumor and apoptosis induction effects of paeonol on mice bearing EMT6 breast carcinoma

Paeonol is a major phenolic micromolecular component of Moutan cortex Radicis, a traditional Chinese Medicine. It has shown antitumor effects in previous studies; however, the underlying mechanisms remain unknown. This study investigated the mechanism by giving treatments of placebo, cyclophosphamide, paeonol of 150 and 300 mg/kg to 4 groups of mice bearing EMT6 breast cancer. Apoptosis in tumor cells were confirmed by morphology analysis, including hematoxylin, eosin staining and TUNEL staining. The results showed that the weight of EMT6 breast tumor was significantly reduced in the groups treated with both 150 and 300 mg/kg of paeonol. Immunohistochemical and Western blot results showed that the expression of Bcl-2 was down-regulated while the expression of Bax, caspase 8 and caspase 3 was up-regulated respectively. These results suggest that paeonol exhibits antitumor effects and the mechanism of the inhibition is via induction of apoptosis, regulation of Bcl-2 and Bax expression, and activation of caspase 8 and caspase 3

Estimation of Forest Structural Diversity Using the Spectral and Textural Information Derived from SPOT-5 Satellite Images

Uneven-aged forest management has received increasing attention in the past few years. Compared with even-aged plantations, the complex structure of uneven-aged forests complicates the formulation of management strategies. Forest structural diversity is expected to provide considerable significant information for uneven-aged forest management planning. In the present study, we investigated the potential of using SPOT-5 satellite images for extracting forest structural diversity. Forest stand variables were calculated from the field plots, whereas spectral and textural measures were derived from the corresponding satellite images. We firstly employed Pearson’s correlation analysis to examine the relationship between the forest stand variables and the image-derived measures. Secondly, we performed all possible subsets multiple linear regression to produce models by including the image-derived measures, which showed significant correlations with the forest stand variables, used as independent variables. The produced models were evaluated with the adjusted coefficient of determination (R 2 adj) and the root mean square error (RMSE). Furthermore, a ten-fold cross-validation approach was used to validate the best-fitting models (R 2 adj \u3e 0.5). The results indicated that basal area, stand volume, the Shannon index, Simpson index, Pielou index, standard deviation of DBHs, diameter differentiation index and species intermingling index could be reliably predicted using the spectral or textural measures extracted from SPOT-5 satellite images

Mapping Forest Health Using Spectral And Textural Information Extracted From Spot-5 Satellite Images

Forest health is an important variable that we need to monitor for forest management decision making. However, forest health is difficult to assess and monitor based merely on forest field surveys. In the present study, we first derived a comprehensive forest health indicator using 15 forest stand attributes extracted from forest inventory plots. Second, Pearson’s correlation analysis was performed to investigate the relationship between the forest health indicator and the spectral and textural measures extracted from SPOT-5 images. Third, all-subsets regression was performed to build the predictive model by including the statistically significant image-derived measures as independent variables. Finally, the developed model was evaluated using the coefficient of determination (R2) and the root mean square error (RMSE). Additionally, the produced model was further validated for its performance using the leave-one-out cross-validation approach. The results indicated that our produced model could provide reliable, fast and economic means to assess and monitor forest health. A thematic map of forest health was finally produced to support forest health management

Antitumor effects of paeonol on mice bearing EMT6 breast Infiltrating ductal carcinoma

Paeonol is a micromolecular phenolic compound and it is the main component of Chinese herbal medicine that has been isolated from the root bark of Paeonia moutan. Paeonol is identified to have various physiological activities. In this study the antitumor activity and the possible mechanisms of paeonol were investigated in mice bearing EMT6 breast cancer model. The results showed that paeonol (150 mg/kg and 300 mg/kg) effectively reduced the weight of EMT6 breast tumor. Compared with the control group, paeonol significantly increased the number of tumor cells in G0/G1 phase, increased the number of cells in apoptosis and decreased the number of cells in S phase and G2/M, inhibited the expression of mutant p53, Bcl-2 and C-erbB-2 protein. The mechanisms of paeonol of antitumor effects might be associated with inhibition of tumor cells in G0/G1 phase, inducing cell apoptosis and inhibiting the expression of mutant p53, Bcl-2 and C-erbB-2 protein.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Antitumor and apoptosis induction effects of lupeol on U14 cervical carcinoma bearing mice

Lupeol is a naturally occurring pentacyclic triterpene that is present in a variety of plants throughout the world. Previous studies have demonstrated that it is a biologically active compound that exhibits various pharmacological properties. In this study, the antitumor activity and potential mechanisms of lupeol were evaluated by investigating the effects of various dosages of lupeol on the growth of U14 tumors transplanted in mice. After lupeol was administered to cervical carcinoma bearing mice, the results demonstrated that lupeol (100 mg/kg and 200 mg/kg) effectively inhibited growth of cervical carcinoma. Compared with the control group (treated with cyclophosphamide CTX), lupeol markedly increase the number of tumor cells in G0/G1 phase. The number of apoptotic cells in the tumor also exhibited an increase in the lupeol groups and the CTX group. Meanwhile, expression of bcl-2 and c-erbB-2 was downregulated, and expression of p21, bax, caspase-8 and caspase-3 was upregulated in tumor cells. These results suggest that lupeol exhibits antitumor activity and inhibits the growth of U14 cervical carcinoma via induction of apoptosis and cell cycle arrest in mice.Colegio de Farmacéuticos de la Provincia de Buenos Aire

Comparison of Coniferous Plantation Heights Using Unmanned Aerial Vehicle (UAV) Laser Scanning and Stereo Photogrammetry

Plantation forests play a critical role in forest products and ecosystems. Unmanned aerial vehicle (UAV) remote sensing has become a promising technology in forest related applications. The stand heights will reflect the growth and competition of individual trees in plantation. UAV laser scanning (ULS) and UAV stereo photogrammetry (USP) can both be used to estimate stand heights using different algorithms. Thus, this study aimed to deeply explore the variations of four kinds of stand heights including mean height, Lorey’s height, dominated height, and median height of coniferous plantations using different models based on ULS and USP data. In addition, the impacts of thinned point density of 30 pts to 10 pts, 5 pts, 1 pts, and 0.8 pts/m2 were also analyzed. Forest stand heights were estimated from ULS and USP data metrics by linear regression and the prediction accuracy was assessed by 10-fold cross validation. The results showed that the prediction accuracy of the stand heights using metrics from USP was basically as good as that of ULS. Lorey’s height had the highest prediction accuracy, followed by dominated height, mean height, and median height. The correlation between height percentiles metrics from ULS and USP increased with the increased height. Different stand heights had their corresponding best height percentiles as variables based on stand height characteristics. Furthermore, canopy height model (CHM)-based metrics performed slightly better than normalized point cloud (NPC)-based metrics. The USP was not able to extract exact terrain information in a continuous coniferous plantation for forest canopy cover (CC) over 0.49. The combination of USP and terrain from ULS can be used to estimate forest stand heights with high accuracy. In addition, the estimation accuracy of each forest stand height was slightly affected by point density, which can also be ignored