943 resultados para Share knowledge
Resumo:
Background: Internationally, the use of dietary supplements has been growing rapidly. Patient support for pharmacist sales of nutritional and dietary supplements is also strong. The increase in demand for nutritional and dietary supplements and subsequent advice about these products, however, makes it necessary that pharmacists maintain a contemporary knowledge of the area. Aim of review: This systematic review was conducted to examine the current evidence regarding the level of the nutritional and dietary supplement knowledge of community pharmacists and their understanding of their therapeutic effects. Method: Electronic databases including Medline, Scopus, Embase, CINAHL, Scifinder and the Cochrane Controlled Trials Register were searched. Studies assessing nutritional knowledge of pharmacists in community pharmacies were eligible for inclusion. All languages and study designs were considered. Study results were analysed and pharmacist knowledge scores were given out of 100Â . Results: From 5594 studies identified, nine met the inclusion criteria. Each study tested pharmacist knowledge with predetermined questions calculating results as the number of questions answered correctly. These knowledge scores were converted to a percentage score for the purpose of this paper. The median knowledge score across all papers was 64%. A lack of studies assessing community pharmacist's knowledge of commonly sold vitamins and minerals was observed. Conclusions Global community pharmacist knowledge of dietary supplements appears to be poor. Community pharmacists have an professional responsibility to provide accurate health information about dietary supplements as they do for any other therapies they provide to patients. Further research including that which assesses pharmacist's therapeutic knowledge of commonly sold vitamins and minerals is suggested.
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There are many potential bioremediation approaches that may be suitable for prawn farms in Queensland. Although most share generally accepted bioremediation principles, advocacy for different methods tends to vary widely. This diversity of approach is particularly driven by the availability and knowledge of functional species at different localities around the world. In Australia, little is known about the abilities of many native species in this regard, and translocation and biosecurity issues prevent the use of exotic species that have shown potential in other countries. Species selected must be tolerant of eutrophic conditions and ecological shifts, because prawn pond nutrient levels and pathways can vary with different assemblages of autotrophic and heterotrophic organisms. Generally, they would be included in a constructed ecosystem because of their functional contributions to nutrient cycling and uptake, and to create nutrient sinks in forms of harvestable biomass. Wide salinity, temperature and water quality tolerances are also valuable attributes for selected species due to the sometimes-pronounced effects of environmental extremes, and to provide over-wintering options and adequate safety margins in avoiding mass mortalities. To practically achieve these bioremediation polycultures on a large scale, and in concert with the operations of a prawn farm, methods involving seed production, stock management, and a range of other farm engineering and product handling systems need to be reliably achievable and economically viable. Research funding provided by the Queensland Government through the Aquaculture Industry Development Initiative (AIDI) 2002-04 has enabled a number of technical studies into biological systems to treat prawn farm effluent for recirculation and improved environmental sustainability. AIDI bioremediation research in southern Queensland was based at the Bribie Island Aquaculture Research Centre (BIARC), and was conducted in conjunction with AIDI genetics and selection research, and a Natural Heritage Trust (NHT) funded program (Coast and Clean Seas Project No.717757). This report compilation provides a summary of some of the work conducted within these programs.
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The quality of species distribution models (SDMs) relies to a large degree on the quality of the input data, from bioclimatic indices to environmental and habitat descriptors (Austin, 2002). Recent reviews of SDM techniques, have sought to optimize predictive performance e.g. Elith et al., 2006. In general SDMs employ one of three approaches to variable selection. The simplest approach relies on the expert to select the variables, as in environmental niche models Nix, 1986 or a generalized linear model without variable selection (Miller and Franklin, 2002). A second approach explicitly incorporates variable selection into model fitting, which allows examination of particular combinations of variables. Examples include generalized linear or additive models with variable selection (Hastie et al. 2002); or classification trees with complexity or model based pruning (Breiman et al., 1984, Zeileis, 2008). A third approach uses model averaging, to summarize the overall contribution of a variable, without considering particular combinations. Examples include neural networks, boosted or bagged regression trees and Maximum Entropy as compared in Elith et al. 2006. Typically, users of SDMs will either consider a small number of variable sets, via the first approach, or else supply all of the candidate variables (often numbering more than a hundred) to the second or third approaches. Bayesian SDMs exist, with several methods for eliciting and encoding priors on model parameters (see review in Low Choy et al. 2010). However few methods have been published for informative variable selection; one example is Bayesian trees (O’Leary 2008). Here we report an elicitation protocol that helps makes explicit a priori expert judgements on the quality of candidate variables. This protocol can be flexibly applied to any of the three approaches to variable selection, described above, Bayesian or otherwise. We demonstrate how this information can be obtained then used to guide variable selection in classical or machine learning SDMs, or to define priors within Bayesian SDMs.
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The kidney filtration barrier consists of fenestrated endothelial cell layer, glomerular basement membrane and slit diaphragm (SD), the specialized junction between glomerular viscelar epithelial cells (podocytes). Podocyte injury is associated with the development of proteinuria, and if not reversed the injury will lead to permanent deterioration of the glomerular filter. The early events are characterized by disruption of the integrity of the SD, but the molecular pathways involved are not fully understood. Congenital nephrotic syndrome of the Finnish type (CNF) is caused by mutations in NPHS1, the gene encoding the SD protein nephrin. Lack of nephrin results in loss of the SD and massive proteinuria beginning before birth. Furthermore, nephrin expression is decreased in acquired human kidney diseases including diabetic nephropathy. This highlights the importance of nephrin and consequently SD in regulating the kidney filtration function. However, the precise molecular mechanism of how nephrin is involved in the formation of the SD is unknown. This thesis work aimed at clarifying the role of nephrin and its interaction partners in the formation of the SD. The purpose was to identify novel proteins that associate with nephrin in order to define the essential molecular complex required for the establishment of the SD. The aim was also to decipher the role of novel nephrin interacting proteins in podocytes. Nephrin binds to nephrin-like proteins Neph1 and Neph2, and to adherens junction protein P-cadherin. These interactions have been suggested to play a role in the formation of the SD. In this thesis work, we identified densin as a novel interaction partner for nephrin. Densin was localized to the SD and it was shown to bind to adherens junction protein beta-catenin. Furthermore, densin was shown to behave in a similar fashion as adherens junction proteins in cell-cell contacts. These results indicate that densin may play a role in cell adhesion and, therefore, may contribute to the formation of the SD together with nephrin and adherens junction proteins. Nephrin was also shown to bind to Neph3, which has been previously localized to the SD. Neph3 and Neph1 were shown to induce cell adhesion alone, whereas nephrin needed to trans-interact with Neph1 or Neph3 from the opposite cell surface in order to make cell-cell contacts. This was associated with the decreased tyrosine phosphorylation of nephrin. These data extend the current knowledge of the molecular composition of the nephrin protein complex at the SD and also provide novel insights of how the SD may be formed. This thesis work also showed that densin was up-regulated in the podocytes of CNF patients. Neph3 was up-regulated in nephrin deficient mouse kidneys, which share similar podocyte alterations and lack of the SD as observed in CNF patients podocytes. These data suggest that densin and Neph3 may have a role in the formation of morphological alterations in podocytes detected in CNF patients. Furthermore, this thesis work showed that deletion of beta-catenin specifically from adult mouse podocytes protected the mice from the development of adriamycin-induced podocyte injury and proteinuria compared to wild-type mice. These results show that beta-catenin play a role in the adriamycin induced podocyte injury. Podocyte injury is a hallmark in many kidney diseases and the changes observed in the podocytes of CNF patient share characteristics with injured podocytes observed in chronic kidney diseases. Therefore, the results obtained in this thesis work suggest that densin, Neph3 and beta-catenin participate in the molecular pathways which result in morphological alterations commonly detected in injured podocytes in kidney diseases.
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In preparation for the introduction of human papillomavirus (HPV) vaccine, we investigated awareness and knowledge of HPV/HPV vaccine and potential acceptability to HPV vaccine among mothers with a teenage daughter in Weihai, Shandong, China. A cross-sectional survey was conducted in 2013 with a sample of 1850 mothers who had a daughter (aged 9–17 years) attending primary, junior and senior high schools. In the final sample (N = 1578, response rate 85.30%), awareness of HPV was reported by 305 (19.32%) mothers. Awareness varied significantly by daughter’s age (P<0.01), mother’s education level (P<0.01), mother’s occupation (P<0.01), household income (P<0.01) and residence type (P<0.01). Knowledge about HPV/HPV vaccine was poor with a mean total score of 3.56 (SD = 2.40) out of a possible score of 13. Mothers with a higher education level reported higher levels of knowledge (P = 0.02). Slightly more than one-fourth (26.49%) of mothers expressed their potential acceptability of HPV vaccine for their daughters. Acceptability increased along with increased daughters’ age (P<0.01), household income (P<0.01) and knowledge level (P<0.01). House wives and unemployed mothers had the highest acceptability (P<0.01). The most common reasons for not accepting HPV vaccination were “My daughter is too young to have risk of cervical cancer (30.95%)”, “The vaccine has not been widely used, and the decision will be made after it is widely used (24.91%)”, “Worry about the safety of the vaccine (22.85%)”. Awareness and knowledge of HPV/HPV vaccines are poor and HPV vaccine acceptability is low among these Chinese mothers. These results may help inform appropriate health education programs in this population.
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This research is a step forward in discovering knowledge from databases of complex structure like tree or graph. Several data mining algorithms are developed based on a novel representation called Balanced Optimal Search for extracting implicit, unknown and potentially useful information like patterns, similarities and various relationships from tree data, which are also proved to be advantageous in analysing big data. This thesis focuses on analysing unordered tree data, which is robust to data inconsistency, irregularity and swift information changes, hence, in the era of big data it becomes a popular and widely used data model.
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Australian preschool teachers’ use of Web-searching in their classroom practice was examined (N = 131). Availability of Internet-enabled digital technology and the contribution of teacher demographic characteristics, comfort with digital technologies and beliefs about their use were assessed. Internet-enabled technologies were available in 53% (n = 69) of classrooms. Within these classrooms, teacher age and beliefs predicted Web-searching practice. Although comfortable with digital access of knowledge in their everyday life, teachers reported less comfort with Web-searching in the context of their classroom practice. The findings identify the provision of Internet-enabled technologies and professional development as actions to support effective and confident inclusion of Web-searching in classrooms. Such actions are necessary to align with national policy documents that define acquisition of digital literacies as a goal and assert digital access to knowledge as an issue of equity.
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In this thesis the use of the Bayesian approach to statistical inference in fisheries stock assessment is studied. The work was conducted in collaboration of the Finnish Game and Fisheries Research Institute by using the problem of monitoring and prediction of the juvenile salmon population in the River Tornionjoki as an example application. The River Tornionjoki is the largest salmon river flowing into the Baltic Sea. This thesis tackles the issues of model formulation and model checking as well as computational problems related to Bayesian modelling in the context of fisheries stock assessment. Each article of the thesis provides a novel method either for extracting information from data obtained via a particular type of sampling system or for integrating the information about the fish stock from multiple sources in terms of a population dynamics model. Mark-recapture and removal sampling schemes and a random catch sampling method are covered for the estimation of the population size. In addition, a method for estimating the stock composition of a salmon catch based on DNA samples is also presented. For most of the articles, Markov chain Monte Carlo (MCMC) simulation has been used as a tool to approximate the posterior distribution. Problems arising from the sampling method are also briefly discussed and potential solutions for these problems are proposed. Special emphasis in the discussion is given to the philosophical foundation of the Bayesian approach in the context of fisheries stock assessment. It is argued that the role of subjective prior knowledge needed in practically all parts of a Bayesian model should be recognized and consequently fully utilised in the process of model formulation.
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A teacher network was formed at an Australian university in order to better promote interdisciplinary student learning on the complex social-environmental problem of climate change. Rather than leaving it to students to piece together disciplinary responses, eight teaching academics collaborated on the task of exposing students to different types of knowledge in a way that was more than the summing of disciplinary parts. With a part-time network facilitator providing cohesion, network members were able to teach into each other’s classes, and share material and student activities across a range of units that included business, zoology, marine science, geography and education. Participants reported that the most positive aspects of the project were the collegiality and support for teaching innovation provided by peers. However, participants also reported being time-poor and overworked. Maintaining the collaboration beyond the initial one year project proved difficult because without funding for the network facilitator, participants were unable to dedicate the time required to meet and collaborate on shared activities. In order to strengthen teacher collaboration in a university whose administrative structures are predominantly discipline-based, there is need for recognition of the benefits of interdisciplinary learning to be matched by recognition of the need for financial and other resources to support collaborative teaching initiatives.
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At present, the rate of small firm adoption of the Internet's ubiquitous World Wide Web (the web) far exceeds the actual exploitation its commercial potential. An inability to strategically acquire, comprehend and use external knowledge is proposed as a major barrier to optimal exploitation of the Internet. This paper discusses the limitations of applying market orientation theory to explain and guide small firm exploitation of the web. Absorptive capacity is introduced as an alternative theory that when viewed from an evolutionary perspective provides potentially more insightful discussion. An inability to detect emerging business model dominant designs is suggested to be a mixture of the nature of the technology that supports the Internet and underdeveloped small firm knowledge processing capabilities. We conclude with consideration of the practical and theoretical implications that arise from the paper.
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This study examines the impact of corporate practice on schooling and on teachers' professional development at the end of the millennium. It is argued that the production of new forms of knowledge is creating new sites of struggle over who owns educational knowledge, and this has profound implications for professional identity formation in all areas of social and economic endeavour, including education. As schools are re-shaped into corporations, school administrators and teachers are under increasing pressure to improve their productivity and to develop themselves as enterprising leaders and managers. To do so they are drawing more and more heavily on the growing non-academic literature of selfimprovement and self-development. Concern is expressed that such literature tends to value mindless optimism over radical doubt.
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Head motion (HM) is a well known confound in analyses of functional MRI (fMRI) data. Neuroimaging researchers therefore typically treat HM as a nuisance covariate in their analyses. Even so, it is possible that HM shares a common genetic influence with the trait of interest. Here we investigate the extent to which this relationship is due to shared genetic factors, using HM extracted from resting-state fMRI and maternal and self report measures of Inattention and Hyperactivity-Impulsivity from the Strengths and Weaknesses of ADHD Symptoms and Normal Behaviour (SWAN) scales. Our sample consisted of healthy young adult twins (N = 627 (63% females) including 95 MZ and 144 DZ twin pairs, mean age 22, who had mother-reported SWAN; N = 725 (58% females) including 101 MZ and 156 DZ pairs, mean age 25, with self reported SWAN). This design enabled us to distinguish genetic from environmental factors in the association between head movement and ADHD scales. HM was moderately correlated with maternal reports of Inattention (r = 0.17, p-value = 7.4E-5) and Hyperactivity-Impulsivity (r = 0.16, p-value = 2.9E-4), and these associations were mainly due to pleiotropic genetic factors with genetic correlations [95% CIs] of rg = 0.24 [0.02, 0.43] and rg = 0.23 [0.07, 0.39]. Correlations between self-reports and HM were not significant, due largely to increased measurement error. These results indicate that treating HM as a nuisance covariate in neuroimaging studies of ADHD will likely reduce power to detect between-group effects, as the implicit assumption of independence between HM and Inattention or Hyperactivity-Impulsivity is not warranted. The implications of this finding are problematic for fMRI studies of ADHD, as failing to apply HM correction is known to increase the likelihood of false positives. We discuss two ways to circumvent this problem: censoring the motion contaminated frames of the RS-fMRI scan or explicitly modeling the relationship between HM and Inattention or Hyperactivity-Impulsivity