10 resultados para natural health products

em Digital Commons at Florida International University


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Insulin signaling is one of the main initiators of adipogenesis, the conversion from pre-adipocyte to adipocyte or lipid droplet. Rab proteins are the master regulator of intracellular trafficking and endosome fusion in endocytosis, making them potential regulators of insulin signaling in adipogenesis. Pre-adipocytes 3T3-Ll cells expressing several Rab5 constructs were used to examine the effect of dehydroleucodine (DhL ), a sesquiterpene lactone isolated from aerial parts of Artemisia douglasiana Besser. The results obtained identify Rab5 deactivation as a key step for adipogenesis by forming signaling endosomes. The addition of DhL significantly inhibited the lipid droplet accumulation in a dose-dependent manner and dramatically attenuated the synthesis of adipogenic transcriptional factors, C/EBPa and PPARy. Activation of AMPKa, Erk and Akt during adipocytic differentiation was not inhibited by treatment with DhL. This data suggest that DhL has an important role in Rab5 dependent adipogenesis by regulating several transcriptional factors including PP ARy expression, which is known to play an essential role during fat formation.

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According to the 1999 U.S. Census, there were approximately thirty-three million African Americans and approximately 1.8 million non-Hispanic black immigrants in the United States. The 1997 U.S. Census estimated that there were as many as 554,000 foreign-born Haitians and 505,000 foreign-born Jamaicans living in the United States, mainly residing in Florida and New York. The U.S. Census claims that blacks are one of the largest emerging ethnic groups in America constituting at least twelve percent of this country's population. Because of this increase, their specific health beliefs and health care options are increasingly nationally significant. ^ In the present intra-black and inter-ethnic study, two hundred seventy African Americans, Haitian immigrants, and Jamaican immigrants residing in South Florida were quantitatively and qualitatively surveyed in order to investigate their health beliefs and health care options. According to the reviewed literature, the three black ethnic groups researched in this study have not been compared or contrasted before in relation to these beliefs and health care choices. ^ As was discovered by the present research, differing health beliefs and health care options were the cultural products of the ethnic differences of the researched communities. It was expected that differing health beliefs among the researched black groups might indicate disparate patterns of health care utilization of either western or non-western models. Additionally, it was projected that by investigating the health beliefs and the health care options of these emerging black ethnic groups, western health care providers in the United States could become better versed in medically servicing growing ethnically-disparate black populations. The study yielded results about the researched groups that supported major findings in the reviewed literature. The data were reported and examined, and theoretical generalizations from the data were discussed. The most important of these findings was that, within a race, health beliefs and health care options were determined by specific ethno-cultural variables dependent on national origins. ^

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The United States Census Bureau (2006) reported that in 2005 more than 46 million Americans lacked health insurance, and that by 2019 national spending for health care would exceed $4.5 trillion (Centers for Medicare & Medicaid Services, 2010). Because those numbers are expected to increase, health tourists are seeking better opportunities for low-cost, high-quality treatment in other countries, plus the added benefit of experiencing foreign cultures. Health tourism is a rapidly growing market in both advanced and developing countries. The purpose of this study was to develop an applicable model of health tourism, the Jeju-Style Health Tourism Model, for Jeju Special Self-Governing Province, in the Republic of Korea (South Korea) and to provide other cities and countries with its implications. This study employed a focus group, indepth interviews, and content analysis to discover important factors in developing the model. The results suggested that four major sources must be executed together to maximize the benefits of health tourism development. On a foundation of natural resources, knowledge-based resources were most important (54.5%), followed by artificial resources (25.7%), and expenses-based resources (19.8%).

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One-third of botanical remedies from southern Italy are used to treat skin and soft tissue infections (SST's). Methicillin-resistant Staphylococcus aureus (MRSA), a common cause of SSTIs, is responsible for increased morbidity and mortality from infections. Therapeutic options are limited by antibiotic resistance. Many plants possess potent antimicrobial compounds for these disorders. Validation of traditional medical practices is important for the people who rely on medicinal plants. Moreover, identification of novel antibiotics and anti-pathogenic agents for MRSA is important to global healthcare.^ I took an ethnopharmacological approach to understand how Italian medicinal plants used for the treatment of SSTIs affect MRSA growth and virulence. My hypothesis was that plants used in folk remedies for SSTI would exhibit lower cytotoxicity and greater inhibition of bacterial growth, biofilm formation and toxin production in MRSA than plants used for remedies unrelated to the skin or for plants with no ethnomedical application. The field portion of my research was conducted in the Vulture-Alto Bradano area of southern Italy. I collected 104 plant species and created 168 crude extracts. In the lab, I screened samples for activity against MRSA in a battery of bioassays. Growth inhibition was analyzed using broth microtiter assays for determination of the minimum inhibitory concentration. Interference with quorum-sensing (QS) processes, which mediate pathogenicity, was quantified through RP-HPLC of δ-toxin production. Interference with biofilm formation and adherence was assessed using staining methods. The mammalian cytotoxicity of natural products was analyzed using MTT cell proliferation assay techniques.^ Although bacteriostatic activity was limited, extracts from six plants used in Italian folk medicine (Arundo donax, Ballota nigra, Juglans regia, Leopoldia comosa, Marrubium vulgare, and Rubus ulmifolius ) significantly inhibited biofilm formation and adherence. Moreover, plants used to treat SSTI demonstrated significantly greater anti-biofilm activity when compared to plants with no ethnomedical application. QSI activity was evident in 90% of the extracts tested and extracts from four plants ( Ballota nigra, Castanea saliva, Rosmarinus officinalis, and Sambucus ebulus) exhibited a significant dose-dependent response. Some of the plant remedies for SSTI identified in this study can be validated due to anti-MRSA activity.^

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Hydrophobicity as measured by Log P is an important molecular property related to toxicity and carcinogenicity. With increasing public health concerns for the effects of Disinfection By-Products (DBPs), there are considerable benefits in developing Quantitative Structure and Activity Relationship (QSAR) models capable of accurately predicting Log P. In this research, Log P values of 173 DBP compounds in 6 functional classes were used to develop QSAR models, by applying 3 molecular descriptors, namely, Energy of the Lowest Unoccupied Molecular Orbital (ELUMO), Number of Chlorine (NCl) and Number of Carbon (NC) by Multiple Linear Regression (MLR) analysis. The QSAR models developed were validated based on the Organization for Economic Co-operation and Development (OECD) principles. The model Applicability Domain (AD) and mechanistic interpretation were explored. Considering the very complex nature of DBPs, the established QSAR models performed very well with respect to goodness-of-fit, robustness and predictability. The predicted values of Log P of DBPs by the QSAR models were found to be significant with a correlation coefficient R2 from 81% to 98%. The Leverage Approach by Williams Plot was applied to detect and remove outliers, consequently increasing R 2 by approximately 2% to 13% for different DBP classes. The developed QSAR models were statistically validated for their predictive power by the Leave-One-Out (LOO) and Leave-Many-Out (LMO) cross validation methods. Finally, Monte Carlo simulation was used to assess the variations and inherent uncertainties in the QSAR models of Log P and determine the most influential parameters in connection with Log P prediction. The developed QSAR models in this dissertation will have a broad applicability domain because the research data set covered six out of eight common DBP classes, including halogenated alkane, halogenated alkene, halogenated aromatic, halogenated aldehyde, halogenated ketone, and halogenated carboxylic acid, which have been brought to the attention of regulatory agencies in recent years. Furthermore, the QSAR models are suitable to be used for prediction of similar DBP compounds within the same applicability domain. The selection and integration of various methodologies developed in this research may also benefit future research in similar fields.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: (1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (E LUMO) via QSAR modelling and analysis; (2) to validate the models by using internal and external cross-validation techniques; (3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl ) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: (1) Linear or Multi-linear Regression (MLR); (2) Partial Least Squares (PLS); and (3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: (1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; (2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; (3) E LUMO are shown to correlate highly with the NCl for several classes of DBPs; and (4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.

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Background Sucralose has gained popularity as a low calorie artificial sweetener worldwide. Due to its high stability and persistence, sucralose has shown widespread occurrence in environmental waters, at concentrations that could reach up to several μg/L. Previous studies have used time consuming sample preparation methods (offline solid phase extraction/derivatization) or methods with rather high detection limits (direct injection) for sucralose analysis. This study described a faster and sensitive analytical method for the determination of sucralose in environmental samples. Results An online SPE-LC–MS/MS method was developed, being capable to quantify sucralose in 12 minutes using only 10 mL of sample, with method detection limits (MDLs) of 4.5 ng/L, 8.5 ng/L and 45 ng/L for deionized water, drinking and reclaimed waters (1:10 diluted with deionized water), respectively. Sucralose was detected in 82% of the reclaimed water samples at concentrations reaching up to 18 μg/L. The monthly average for a period of one year was 9.1 ± 2.9 μg/L. The calculated mass loads per capita of sucralose discharged through WWTP effluents based on the concentrations detected in wastewaters in the U. S. is 5.0 mg/day/person. As expected, the concentrations observed in drinking water were much lower but still relevant reaching as high as 465 ng/L. In order to evaluate the stability of sucralose, photodegradation experiments were performed in natural waters. Significant photodegradation of sucralose was observed only in freshwater at 254 nm. Minimal degradation (<20%) was observed for all matrices under more natural conditions (350 nm or solar simulator). The only photolysis product of sucralose identified by high resolution mass spectrometry was a de-chlorinated molecule at m/z 362.0535, with molecular formula C12H20Cl2O8. Conclusions Online SPE LC-APCI/MS/MS developed in the study was applied to more than 100 environmental samples. Sucralose was frequently detected (>80%) indicating that the conventional treatment process employed in the sewage treatment plants is not efficient for its removal. Detection of sucralose in drinking waters suggests potential contamination of surface and ground waters sources with anthropogenic wastewater streams. Its high resistance to photodegradation, minimal sorption and high solubility indicate that sucralose could be a good tracer of anthropogenic wastewater intrusion into the environment.

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The non-timber forest products (NTFPs) sector in Nepal is being promoted with the concept of sustainable management as articulated by the Convention on Biological Diversity. To promote and regulate this sector, Nepal adopted the Herbs and NTFP Development Policy in 2004. The goal of this thesis was to assess the effectiveness of this policy along with other forestry and natural resource policies in Nepal concerning the conservation and sustainable use of NTFPs. I conducted open-ended semi-structured interviews with 28 key informants in summer 2006 in Nepal where I also collected relevant documents and publications. I did qualitative analysis of data obtained from interviews and document review. The research found many important issues that need to be addressed to promote the NTFP sector as envisioned by the Government of Nepal. The findings of this research will help to further implement the policy and promote the NTFP sector through sustainable management practices.

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The objective of this thesis was to investigate the effects of the built environment on the outcome of young patients. This investigation included recent innovations in children's hospitals that integrated both medical and architectural case studies as part of their design issues. In addition, the intervention responded to man-made conditions and natural elements of the site. The thesis project, a Children's Rehabilitation Hospital, is located at 1500 N.W. River Drive in Miami, Florida. The thesis intervention emerged from a site analysis that focused on the shifting of the urban grid, the variation in scale of the immediate context and the visual-physical connection to the river's edge. Furthermore, it addressed the issues of overnight accommodation for patient's families, as well as sound control through the use of specific materials in space enclosures and open courtyards. The key to the success of this intervention lies in the special attention given to the integration between nature and the built environment. Issues such as the incorporation of nature within a building through the use of vistas and the exploitation of natural light through windows and skylights, were pivotal in the creation of a pleasant environment for visitors, employees and young patients.

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Quantitative Structure-Activity Relationship (QSAR) has been applied extensively in predicting toxicity of Disinfection By-Products (DBPs) in drinking water. Among many toxicological properties, acute and chronic toxicities of DBPs have been widely used in health risk assessment of DBPs. These toxicities are correlated with molecular properties, which are usually correlated with molecular descriptors. The primary goals of this thesis are: 1) to investigate the effects of molecular descriptors (e.g., chlorine number) on molecular properties such as energy of the lowest unoccupied molecular orbital (ELUMO) via QSAR modelling and analysis; 2) to validate the models by using internal and external cross-validation techniques; 3) to quantify the model uncertainties through Taylor and Monte Carlo Simulation. One of the very important ways to predict molecular properties such as ELUMO is using QSAR analysis. In this study, number of chlorine (NCl) and number of carbon (NC) as well as energy of the highest occupied molecular orbital (EHOMO) are used as molecular descriptors. There are typically three approaches used in QSAR model development: 1) Linear or Multi-linear Regression (MLR); 2) Partial Least Squares (PLS); and 3) Principle Component Regression (PCR). In QSAR analysis, a very critical step is model validation after QSAR models are established and before applying them to toxicity prediction. The DBPs to be studied include five chemical classes: chlorinated alkanes, alkenes, and aromatics. In addition, validated QSARs are developed to describe the toxicity of selected groups (i.e., chloro-alkane and aromatic compounds with a nitro- or cyano group) of DBP chemicals to three types of organisms (e.g., Fish, T. pyriformis, and P.pyosphoreum) based on experimental toxicity data from the literature. The results show that: 1) QSAR models to predict molecular property built by MLR, PLS or PCR can be used either to select valid data points or to eliminate outliers; 2) The Leave-One-Out Cross-Validation procedure by itself is not enough to give a reliable representation of the predictive ability of the QSAR models, however, Leave-Many-Out/K-fold cross-validation and external validation can be applied together to achieve more reliable results; 3) ELUMO are shown to correlate highly with the NCl for several classes of DBPs; and 4) According to uncertainty analysis using Taylor method, the uncertainty of QSAR models is contributed mostly from NCl for all DBP classes.