Evaluation Of The Essential Oil Of Foeniculum Vulgare Mill (Fennel) Fruits Extracted By Three Different Extraction Methods By Gc/Ms

Background: Hydrodistillation (HD) and steam-distillation, or solvent extraction methods of essential oils have some disadvantages like thermal decomposition of extracts, its contamination with solvent or solvent residues and the pollution of residual vegetal material with solvent which can be also an environmental problem. Thus, new green techniques, such as supercritical fluid extraction and microwave assisted techniques, are potential solutions to overcome these disadvantages.Materials and Methods: The aim of this study was to evaluate the essential oil of Foeniculum vulgare subsp. Piperitum fruits extracted by three different extraction methods viz. Supercritical fluid extraction (SFE) using CO2, microwave-assisted extraction (MAE) and hydro-distillation (HD) using gas chromatography-mass spectrometry (GC/MS).Results: The results revealed that both MAE and SFE enhanced the extraction efficiency of the interested components. MAE gave the highest yield of oil as well as higher percentage of Fenchone (28%), whereas SFE gave the highest percentage of anethol (72%).Conclusion: Microwave-assisted extraction (MAE) and supercritical fluid extraction (SFE) not only enhanced the essential oil extraction but also saved time, reduced the solvents use and produced, ecologically, green technologies.Keywords: Foeniculum vulgare subsp. Piperitum, microwave-assisted extraction (MAE), Supercritical fluid extraction (SFE), Essential Oils,Anethol, Fenchone, Limonene, Pinene, GC/MS

Cluster Structure on Generalized Weyl Algebras

We introduce a class of non-commutative algebras that carry a non-commutative (geometric) cluster structure which are generated by identical copies of generalized Weyl algebras. Equivalent conditions for the finiteness of the set of the cluster variables of these cluster structures are provided. Some combinatorial data, called \textit{cluster strands,} arising from the cluster structure are used to construct irreducible representations of generalized Weyl algebras.Comment: in Algebras and Representation Theory, Volume 19, No1, Feb. 201

Novel microwell-based spectrophotometric assay for determination of atorvastatin calcium in its pharmaceutical formulations

The formation of a colored charge-transfer (CT) complex between atorvastatin calcium (ATR-Ca) as a n-electron donor and 2, 3-dichloro-5,6-dicyano-1,4-benzoquinone (DDQ) as a π-electron acceptor was investigated, for the first time. The spectral characteristics of the CT complex have been described, and the reaction mechanism has been proved by computational molecular modeling. The reaction was employed in the development of a novel microwell-based spectrophotometric assay for determination of ATR-Ca in its pharmaceutical formulations. The proposed assay was carried out in 96-microwell plates. The absorbance of the colored-CT complex was measured at 460 nm by microwell-plate absorbance reader. The optimum conditions of the reaction and the analytical procedures of the assay were established. Under the optimum conditions, linear relationship with good correlation coefficient (0.9995) was found between the absorbance and the concentration of ATR-Ca in the range of 10-150 μg/well. The limits of detection and quantitation were 5.3 and 15.8 μg/well, respectively. No interference was observed from the additives that are present in the pharmaceutical formulation or from the drugs that are co-formulated with ATR-Ca in its combined formulations. The assay was successfully applied to the analysis of ATR-Ca in its pharmaceutical dosage forms with good accuracy and precision. The assay described herein has great practical value in the routine analysis of ATR-Ca in quality control laboratories, as it has high throughput property, consumes minimum volume of organic solvent thus it offers the reduction in the exposures of the analysts to the toxic effects of organic solvents, and reduction in the analysis cost by 50-fold. Although the proposed assay was validated for ATR-Ca, however, the same methodology could be used for any electron-donating analyte for which a CT reaction can be performed

Olive Oil effectively mitigates ovariectomy-induced osteoporosis in rats

<p>Abstract</p> <p>Background</p> <p>Osteoporosis, a reduction in bone mineral density, represents the most common metabolic bone disease. Postmenopausal women are particularly susceptible to osteoporosis when their production of estrogen declines. For these women, fracture is a leading cause of morbidity and mortality. This study was conducted to evaluate the protective effects of olive oil supplementation against osteoporosis in ovariectomized (OVX) rats.</p> <p>Methods</p> <p>We studied adult female Wistar rats aged 12-14 months, divided into three groups: sham-operated control (SHAM), ovariectomized (OVX), and ovariectomized rats supplemented with extravirgin olive oil (Olive-OVX) orally for 12 weeks; 4 weeks before ovariectomy and 8 weeks after. At the end of the experiment, blood samples were collected. Plasma levels of calcium, phosphorus, alkaline phosphatase (ALP), malondialdehyde (MDA), and nitrates were assayed. Specimens from both the tibia and the liver were processed for light microscopic examination. Histomorphometric analysis of the tibia was also performed.</p> <p>Results</p> <p>The OVX-rats showed a significant decrease in plasma calcium levels, and a significant increase in plasma ALP, MDA, and nitrates levels. These changes were attenuated by olive oil supplementation in the Olive-OVX rats. Light microscopic examination of the tibia of the OVX rats revealed a significant decrease in the cortical bone thickness (CBT) and the trabecular bone thickness (TBT). In addition, there was a significant increase in the osteoclast number denoting bone resorption. In the Olive-OVX rats these parameters were markedly improved as compared to the OVX group. Examination of the liver specimens revealed mononuclear cellular infiltration in the portal areas in the OVX-rats which was not detected in the Olive-OVX rats.</p> <p>Conclusions</p> <p>Olive oil effectively mitigated ovariectomy-induced osteoporosis in rats, and is a promising candidate for the treatment of postmenopausal osteoporosis.</p

Global, regional, and national comparative risk assessment of 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks, 1990-2015: a systematic analysis for the Global Burden of Disease Study 2015

SummaryBackground The Global Burden of Diseases, Injuries, and Risk Factors Study 2015 provides an up-to-date synthesis of the evidence for risk factor exposure and the attributable burden of disease. By providing national and subnational assessments spanning the past 25 years, this study can inform debates on the importance of addressing risks in context. Methods We used the comparative risk assessment framework developed for previous iterations of the Global Burden of Disease Study to estimate attributable deaths, disability-adjusted life-years (DALYs), and trends in exposure by age group, sex, year, and geography for 79 behavioural, environmental and occupational, and metabolic risks or clusters of risks from 1990 to 2015. This study included 388 risk-outcome pairs that met World Cancer Research Fund-defined criteria for convincing or probable evidence. We extracted relative risk and exposure estimates from randomised controlled trials, cohorts, pooled cohorts, household surveys, census data, satellite data, and other sources. We used statistical models to pool data, adjust for bias, and incorporate covariates. We developed a metric that allows comparisons of exposure across risk factors—the summary exposure value. Using the counterfactual scenario of theoretical minimum risk level, we estimated the portion of deaths and DALYs that could be attributed to a given risk. We decomposed trends in attributable burden into contributions from population growth, population age structure, risk exposure, and risk-deleted cause-specific DALY rates. We characterised risk exposure in relation to a Socio-demographic Index (SDI). Findings Between 1990 and 2015, global exposure to unsafe sanitation, household air pollution, childhood underweight, childhood stunting, and smoking each decreased by more than 25%. Global exposure for several occupational risks, high body-mass index (BMI), and drug use increased by more than 25% over the same period. All risks jointly evaluated in 2015 accounted for 57·8% (95% CI 56·6–58·8) of global deaths and 41·2% (39·8–42·8) of DALYs. In 2015, the ten largest contributors to global DALYs among Level 3 risks were high systolic blood pressure (211·8 million [192·7 million to 231·1 million] global DALYs), smoking (148·6 million [134·2 million to 163·1 million]), high fasting plasma glucose (143·1 million [125·1 million to 163·5 million]), high BMI (120·1 million [83·8 million to 158·4 million]), childhood undernutrition (113·3 million [103·9 million to 123·4 million]), ambient particulate matter (103·1 million [90·8 million to 115·1 million]), high total cholesterol (88·7 million [74·6 million to 105·7 million]), household air pollution (85·6 million [66·7 million to 106·1 million]), alcohol use (85·0 million [77·2 million to 93·0 million]), and diets high in sodium (83·0 million [49·3 million to 127·5 million]). From 1990 to 2015, attributable DALYs declined for micronutrient deficiencies, childhood undernutrition, unsafe sanitation and water, and household air pollution; reductions in risk-deleted DALY rates rather than reductions in exposure drove these declines. Rising exposure contributed to notable increases in attributable DALYs from high BMI, high fasting plasma glucose, occupational carcinogens, and drug use. Environmental risks and childhood undernutrition declined steadily with SDI; low physical activity, high BMI, and high fasting plasma glucose increased with SDI. In 119 countries, metabolic risks, such as high BMI and fasting plasma glucose, contributed the most attributable DALYs in 2015. Regionally, smoking still ranked among the leading five risk factors for attributable DALYs in 109 countries; childhood underweight and unsafe sex remained primary drivers of early death and disability in much of sub-Saharan Africa. Interpretation Declines in some key environmental risks have contributed to declines in critical infectious diseases. Some risks appear to be invariant to SDI. Increasing risks, including high BMI, high fasting plasma glucose, drug use, and some occupational exposures, contribute to rising burden from some conditions, but also provide opportunities for intervention. Some highly preventable risks, such as smoking, remain major causes of attributable DALYs, even as exposure is declining. Public policy makers need to pay attention to the risks that are increasingly major contributors to global burden. Funding Bill & Melinda Gates Foundation

Towards the prediction of essential genes by integration of network topology, cellular localization and biological process information

<p>Abstract</p> <p>Background</p> <p>The identification of essential genes is important for the understanding of the minimal requirements for cellular life and for practical purposes, such as drug design. However, the experimental techniques for essential genes discovery are labor-intensive and time-consuming. Considering these experimental constraints, a computational approach capable of accurately predicting essential genes would be of great value. We therefore present here a machine learning-based computational approach relying on network topological features, cellular localization and biological process information for prediction of essential genes.</p> <p>Results</p> <p>We constructed a decision tree-based meta-classifier and trained it on datasets with individual and grouped attributes-network topological features, cellular compartments and biological processes-to generate various predictors of essential genes. We showed that the predictors with better performances are those generated by datasets with integrated attributes. Using the predictor with all attributes, i.e., network topological features, cellular compartments and biological processes, we obtained the best predictor of essential genes that was then used to classify yeast genes with unknown essentiality status. Finally, we generated decision trees by training the J48 algorithm on datasets with all network topological features, cellular localization and biological process information to discover cellular rules for essentiality. We found that the number of protein physical interactions, the nuclear localization of proteins and the number of regulating transcription factors are the most important factors determining gene essentiality.</p> <p>Conclusion</p> <p>We were able to demonstrate that network topological features, cellular localization and biological process information are reliable predictors of essential genes. Moreover, by constructing decision trees based on these data, we could discover cellular rules governing essentiality.</p