Response surface methodology applied to the analysis of rice bran oil extraction process with ethanol

P>Vegetable oils can be extracted using ethanol as solvent. The main goal of this work was to evaluate the ethanol performance on the extraction process of rice bran oil. The influence of process variables, solvent hydration and temperature was evaluated using the response surface methodology, aiming to maximise the soluble substances and gamma-oryzanol transfer and minimise the free fatty acids extraction and the liquid content in the underflow solid. It can be noted that oil solubility in ethanol was highly affected by the water content. The free fatty acids extraction is improved by increasing the moisture content in the solvent. Regarding the gamma-oryzanol, it can be observed that its extraction is affected by temperature when low level of water is added to ethanol. On the other hand, the influence of temperature is minimised with high levels of water in the ethanol.

Fat-Soluble Bioactive Components in Colored Rice Varieties

Bioactive components in rice vary depending on the variety and growing condition. Fat-soluble components such as gamma-oryzanol, tocopherols, tocotrienols, carotenoids, and fatty acids were analyzed in brown, sugary brown, red, and black rice varieties using established high-performance liquid chromatography (HPLC) and GC methodologies. In addition, these colored rice varieties were further analyzed using a high-resolution liquid chromatography-mass spectrometry/mass spectrometry (LC-MS/MS) (LTQ-Orbitrap XL) to identify the [M-H](-) ions of gamma-oryzanol, ranging from m/z 573.3949 to 617.4211. The highest content of tocopherols (alpha-, 1.5; gamma-, 0.5 mg/100 g) and carotenoids (lutein 244; trans-beta carotene 25 mu g/100 g) were observed in black rice; tocotrienols (alpha-, 0.07; gamma-, 0.14 mg/100 g) in red rice, and gamma-oryzanol (115 mg/100 g) in sugary brown rice. In all colored rice varieties, the major fatty acids were palmitic (16:0), oleic (18:1n-9), and linoleic (18:2n-6) acids. When the gamma-oryzanol components were further analyzed by LC-MS/MS, 3, 10, 8, and 8 triterpene alcohols or sterol ferulates were identified in brown, sugary brown, red, and black rice varieties, respectively. Such structural identification can lead to the elucidation of biological function of each component at the molecular level. Consumption of colored rice rich in beneficial bioactive compounds may be a useful dietary strategy for achieving optimal health.

Effects of the extraction conditions on the yield and composition of rice bran oil extracted with ethanol-A response surface approach

Rice bran oil was obtained from rice bran by solvent extraction using ethanol. The influence of process variables, solvent hydration (0-24% of water, on mass basis), temperature (60-90 degrees C), solvent-to-rice bran mass ratio (2.5:1 to 4.5:1) and stirrer speed (100-250 rpm) were analysed using the response surface methodology. The extraction yield was highly affected by the solvent water content, and it varied from 8.56 to 20.05 g of oil/100 g of fresh rice bran (or 42.7-99.9% of the total oil available) depending on the experimental conditions. It was observed that oryzanol and tocols behave in different ways during the extraction process. A larger amount of tocols is extracted from the solid matrix in relation to gamma-oryzanol. It was possible to obtain values from 123 to 271 mg of tocols/kg of fresh rice bran and 1527 to 4164 mg of oryzanol/kg of fresh rice bran, indicating that it is feasible to obtain enriched oil when this renewable solvent is used. No differences in the chemical composition of the extracted oils were observed when compared to the data cited in the literature. (C) 2011 The Institution of Chemical Engineers. Published by Elsevier B.V. All rights reserved.

Liquid-liquid equilibria for systems composed of rice bran oil and alcohol-rich solvents: Application to extraction and deacidification of oil

The liquid-liquid equilibria of systems composed of rice bran oil, free fatty acids, ethanol and water were investigated at temperatures ranging from 10 to 60 degrees C. The results of the present study indicated that the mutual solubility of the compounds decreased with an increase in the water content of the solvent and a decrease in the temperature of the solution. The experimental data set was correlated by applying the UNIQUAC model. The average variance between the experimental and calculated compositions was 0.35%, indicating that the model can accurately predict behavior of the compounds at different temperatures and degrees of hydration. The adjustment of interaction parameters enables both the simulation of liquid-liquid extractors for deacidification of vegetable oil and the prediction of phase compositions for the oil and alcohol-rich phases that are generated during cooling of the stream exiting the extractor (when using ethanol as the solvent). (C) 2012 Elsevier Ltd. All rights reserved.

Evaluation of piezoelectric PVDF polymers for use in space environments. III. Comparison of the effects of vacuum UV and gamma radiation

Films of piezoelectric PVDF and P(VDF-TrFE) were exposed to vacuum UV (115-300 nm VUV) and -radiation to investigate how these two forms of radiation affect the chemical, morphological, and piezoelectric properties of the polymers. The extent of crosslinking was almost identical in both polymers after -irradiation, but surprisingly, was significantly higher for the TrFE copolymer after VUV-irradiation. Changes in the melting behavior were also more significant in the TrFE copolymer after VUV-irradiation due to both surface and bulk crosslinking, compared with only surface crosslinking for the PVDF films. The piezoelectric properties (measured using d33 piezoelectric coefficients and D-E hysteresis loops) were unchanged in the PVDF homopolymer, while the TrFE copolymer exhibited more narrow D-E loops after exposure to either - or VUV-radiation. The more severe damage to the TrFE copolymer in comparison with the PVDF homopolymer after VUV-irradiation is explained by different energy deposition characteristics. The short wavelength, highly energetic photons are undoubtedly absorbed in the surface layers of both polymers, and we propose that while the longer wavelength components of the VUV-radiation are absorbed by the bulk of the TrFE copolymer causing crosslinking, they are transmitted harmlessly in the PVDF homopolymer.

Gamma-tocotrienol as an effective agent in targeting prostate cancer stem cell-like population

Emerging evidence supports that prostate cancer originates from a rare sub-population of cells, namely prostate cancer stem cells (CSCs). Conventional therapies for prostate cancer are believed to mainly target the majority of differentiated tumor cells but spare CSCs, which may account for the subsequent disease relapse after treatment. Therefore, successful elimination of CSCs may be an effective strategy to achieve complete remission from this disease. Gamma-tocotrienols (-T3) is one of the vitamin-E constituents which have been shown to have anticancer effects against a wide-range of human cancers. Recently, we have reported that -T3 treatment not only inhibits prostate cancer cell invasion but also sensitizes the cells to docetaxel-induced apoptosis, suggesting that -T3 may be an effective therapeutic agent against advanced stage prostate cancer. Here, we demonstrate for the first time that -T3 can down-regulate the expression of prostate CSC markers (CD133/CD44) in androgen independent (AI) prostate cancer cell lines (PC-3 & DU145), as evident from western blotting analysis. Meanwhile, the spheroid formation ability of the prostate cancer cells was significantly hampered by -T3 treatment. In addition, pre-treatment of PC-3 cells with -T3 was found to suppress tumor initiation ability of the cells. More importantly, while CD133-enriched PC-3 cells were highly resistant to docetaxel treatment, these cells were as sensitive to -T3 treatment as the CD133-depleted population. Our data suggest that -T3 may be an effective agent in targeting prostate CSCs, which may account for its anticancer and chemosensitizing effects reported in previous studies.

Poisson, Poisson-gamma and zero-inflated regression models of motor vehicle crashes: balancing statistical fit and theory

There has been considerable research conducted over the last 20 years focused on predicting motor vehicle crashes on transportation facilities. The range of statistical models commonly applied includes binomial, Poisson, Poisson-gamma (or negative binomial), zero-inflated Poisson and negative binomial models (ZIP and ZINB), and multinomial probability models. Given the range of possible modeling approaches and the host of assumptions with each modeling approach, making an intelligent choice for modeling motor vehicle crash data is difficult. There is little discussion in the literature comparing different statistical modeling approaches, identifying which statistical models are most appropriate for modeling crash data, and providing a strong justification from basic crash principles. In the recent literature, it has been suggested that the motor vehicle crash process can successfully be modeled by assuming a dual-state data-generating process, which implies that entities (e.g., intersections, road segments, pedestrian crossings, etc.) exist in one of two states—perfectly safe and unsafe. As a result, the ZIP and ZINB are two models that have been applied to account for the preponderance of “excess” zeros frequently observed in crash count data. The objective of this study is to provide defensible guidance on how to appropriate model crash data. We first examine the motor vehicle crash process using theoretical principles and a basic understanding of the crash process. It is shown that the fundamental crash process follows a Bernoulli trial with unequal probability of independent events, also known as Poisson trials. We examine the evolution of statistical models as they apply to the motor vehicle crash process, and indicate how well they statistically approximate the crash process. We also present the theory behind dual-state process count models, and note why they have become popular for modeling crash data. A simulation experiment is then conducted to demonstrate how crash data give rise to “excess” zeros frequently observed in crash data. It is shown that the Poisson and other mixed probabilistic structures are approximations assumed for modeling the motor vehicle crash process. Furthermore, it is demonstrated that under certain (fairly common) circumstances excess zeros are observed—and that these circumstances arise from low exposure and/or inappropriate selection of time/space scales and not an underlying dual state process. In conclusion, carefully selecting the time/space scales for analysis, including an improved set of explanatory variables and/or unobserved heterogeneity effects in count regression models, or applying small-area statistical methods (observations with low exposure) represent the most defensible modeling approaches for datasets with a preponderance of zeros