Anticancer properties of essential oils and other natural products

Essential oils are secondary metabolites with a key-role in plants protection, consisting primarily of terpenes with a volatile nature and a diverse array of chemical structures. Essential oils exhibit a wide range of bioactivities, especially antimicrobial activity, and have long been utilized for treating various human ailments and diseases. Cancer cell prevention and cytotoxicity are exhibited through a wide range of mechanisms of action, with more recent research focusing on synergistic and antagonistic activity between specific essential oils major and minor components. Essential oils have been shown to possess cancer cell targeting activity and are able to increase the efficacy of commonly used chemotherapy drugs including paclitaxel and docetaxel, having also shown proimmune functions when administered to the cancer patient. The present review represents a state-of-the-art review of the research behind the application of EOs as anticancer agents both in vitro and in vivo. Cancer cell target specificity and the use of EOs in combination with conventional chemotherapeutic strategies are also explored

Kayfu Asrar Nazhariat Al Arjihat

253 hal.; 24 c

Limitations and Improvements of the Leaf Optical Properties Model Leaf Incorporating Biochemistry Exhibiting Reflectance and Transmittance Yields (LIBERTY)

Leaf Incorporating Biochemistry Exhibiting Reflectance and Transmittance Yields (LIBERTY) models the effects of leaf biochemical concentrations on reflectance spectra on the basis of Melamed theory, which has several limitations. These are: (1) the radiation components are not treated satisfactorily; (2) the directional changes of both particle and sublayer scattering ratios are not considered; and (3) the boundary constraint which makes needle leaves different from broadleaves is not included. Proofs of these limitations as well as theoretical improvements are given in this study. Global sensitivity analysis (SA) of three models: the original LIBERTY, our improved LIBERTY (LIBERTYim) and The optical PROperties SPECTra model (PROSPECT) suggests that compared with LIBERTY, the global reflectance and transmittance of LIBERTYim are more sensitive to diametrical absorbance α d —a parameter related to leaf biochemistry. Moreover, the global reflectance and transmittance of LIBERTYim and PROSPECT had similar sensitivity patterns to the input variables, demonstrating indirectly the validity of our improvements over LIBERTY. However, neither LIBERTY nor LIBERTYim considers boundary constraints, which limits their applications in modelling needle leaf optical properties. We introduced a particle string model, which might be used to simulate needle leaf optical properties in the future

Limited Effects of Water Absorption on Reducing the Accuracy of Leaf Nitrogen Estimation

Nitrogen is an essential nutrient in many terrestrial ecosystems because it affects vegetation’s primary production. Due to the variety of nitrogen-containing substances and the differences in their composition across species, statistical approaches are now dominant in remote sensing retrieval of leaf nitrogen content. Many studies remove spectral regions characterized by strong water absorptions before retrieving nitrogen content, because water is believed to mask the absorption features of nitrogen. The objectives of this study are to discuss the necessity of this practice and to explore how water absorption affects leaf nitrogen estimation. Spectral measurements and chemical analyses for Maize, Sawtooth Oak, and Sweetgum leaves were carried out in 2014. The leaf optical properties model PROSPECT5 was used to eliminate the influences of water on the measured reflectance spectra. The inversion accuracy of PROPECT5 for chlorophyll, carotenoid, water, and dry matter of Maize was also discussed. Measured, simulated, and water-removed spectra were used to: (1) find the optimal nitrogen-related spectral index; and (2) regress with the area-based leaf nitrogen concentration (LNC) using the partial least square regression technique (PLSR). Two types of spectral indices were selected in this study: Normalized Difference Spectral Index (NDSI) and Ratio Spectral Index (RSI). Additionally, first-order derivative forms of measured, simulated, and water-removed spectra were devised to search for the optimal spectral indices. Finally, species-specific optimal indices and cross-species optimal indices, as well as their root mean square errors (RMSE) and coefficients of determination (R2), were obtained. The Ending Top Percentile (ETP), an indicator of the performance of cross-species optimal indices, was also calculated. PLSR was combined with leave-one-out cross validation (LOOCV) for each species. The predicted root mean square errors (RMSEP) and predicted R2 were finally calculated. The results showed that chlorophyll, carotenoid, and water contents could be estimated with R2 of 0.75, 0.59, and 0.69, respectively, which were acceptable for fresh leaves. The dry matter was retrieved with a relatively lower accuracy because of the fixed absorption coefficients adopted by PROSPECT5. The performances of species-specific optimal indices using water-free spectra were comparable to or worse than the corresponding indices derived with measured or simulated spectra. Compared with measured spectra, ETP did not change much after the effects of water were removed, and the R2 between cross-species optimal spectral indices and area-based LNC for Sawtooth Oak and Sweetgum decreased while it remained almost the same for Maize, suggesting that the water-removed cross-species optimal indices were inferior to the corresponding optimal indices found without water removal. ETP was larger than 30% for all spectra, demonstrating the non-existence of common optimal NDSI or RSI for the three species. After water removal, the accuracy of PLSR for Sawtooth Oak and Sweetgum decreased and increased negligibly for Maize. The results suggest that water absorption has limited effects on reducing the accuracy of leaf nitrogen estimation. On the contrary, the accuracy may decrease due to the loss of spectral information caused by the removal of water-sensitive spectral regions