117 resultados para native medicine


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Information and Communication Technologies are dramatically transforming Allopathic medicine. Technological developments including Tele-medicine, Electronic health records, Standards to ensure computer systems inter-operate, Data mining, Simulation, Decision Support and easy access to medical information each contribute to empowering patients in new ways and change the practice of medicine. To date, informatics has had little impact on Ayurvedic medicine. This tutorial provides an introduction to key informatics initiatives in Allopothic medicine using real examples and suggests how applications can be applied to Ayurvedic medicine.

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BACKGROUND: Adherence to medicines is important in subjects with diabetes, as nonadherence is associated with an increased risk of morbidity and mortality. However, it is not clear whether there is an association between adherence to medicines and glycaemic control, as not all studies have shown this. One of the reasons for this discrepancy may be that, although there is a standard measure of glycaemic control i.e. HbA1c, there is no standard measure of adherence to medicines. Adherence to medicines can be measured either qualitatively by Morisky or non-Morisky methods or quantitatively using the medicines possession ratio (MPR). AIMS OF THE REVIEW: The aims of this literature review are (1) to determine whether there is an association between adherence to anti-diabetes medicines and glycaemic control, and (2) whether any such association is dependent on how adherence is measured. Methods A literature search of Medline, CINAHL and the Internet (Google) was undertaken with search terms; 'diabetes' with 'adherence' (or compliance, concordance, persistence, continuation) with 'HbA1c' (or glycaemic control). RESULTS: Twenty-three studies were included; 10 qualitative and 12 quantitative studies, and one study using both methods. For the qualitative methods measurements of adherence to anti-diabetes medicines (non-Morisky and Morisky), eight out of ten studies show an association with HbA1c. Nine of ten studies using the quantitative MPR, and two studies using MPR for insulin only, have also shown an association between adherence to anti-diabetes medicines and HbA1c. However, the one study that used both Morisky and MPR did not show an association. Three of the four studies that did not show a relationship, did not use a range of HbA1c values in their regression analysis. The other study that did not show a relationship was specifically in a low income population. CONCLUSIONS: Most studies show an association between adherence to anti-diabetes medicines and HbA1c levels, and this seems to be independent of method used to measure adherence. However, to show an association it is necessary to have a range of HbA1c values. Also, the association is not always apparent in low income populations.

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We describe an investigation into how Massey University’s Pollen Classifynder can accelerate the understanding of pollen and its role in nature. The Classifynder is an imaging microscopy system that can locate, image and classify slide based pollen samples. Given the laboriousness of purely manual image acquisition and identification it is vital to exploit assistive technologies like the Classifynder to enable acquisition and analysis of pollen samples. It is also vital that we understand the strengths and limitations of automated systems so that they can be used (and improved) to compliment the strengths and weaknesses of human analysts to the greatest extent possible. This article reviews some of our experiences with the Classifynder system and our exploration of alternative classifier models to enhance both accuracy and interpretability. Our experiments in the pollen analysis problem domain have been based on samples from the Australian National University’s pollen reference collection (2,890 grains, 15 species) and images bundled with the Classifynder system (400 grains, 4 species). These samples have been represented using the Classifynder image feature set.We additionally work through a real world case study where we assess the ability of the system to determine the pollen make-up of samples of New Zealand honey. In addition to the Classifynder’s native neural network classifier, we have evaluated linear discriminant, support vector machine, decision tree and random forest classifiers on these data with encouraging results. Our hope is that our findings will help enhance the performance of future releases of the Classifynder and other systems for accelerating the acquisition and analysis of pollen samples.

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Samples of Forsythia suspensa from raw (Laoqiao) and ripe (Qingqiao) fruit were analyzed with the use of HPLC-DAD and the EIS-MS techniques. Seventeen peaks were detected, and of these, twelve were identified. Most were related to the glucopyranoside molecular fragment. Samples collected from three geographical areas (Shanxi, Henan and Shandong Provinces), were discriminated with the use of hierarchical clustering analysis (HCA), discriminant analysis (DA), and principal component analysis (PCA) models, but only PCA was able to provide further information about the relationships between objects and loadings; eight peaks were related to the provinces of sample origin. The supervised classification models-K-nearest neighbor (KNN), least squares support vector machines (LS-SVM), and counter propagation artificial neural network (CP-ANN) methods, indicated successful classification but KNN produced 100% classification rate. Thus, the fruit were discriminated on the basis of their places of origin.

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The Sydney rock oyster (Saccostrea glomerata) (SRO) is an oyster species that only occurs in estuaries along Australia's east coast. The SRO industry evolved from commercial gathering of oyster in the 1790s to a high production volume aquaculture industry in the 1970s. However, since the late 1970s the SRO industry has experienced a significant and continuous decline in production quantities and the industry's future commercial viably appears to be uncertain. The aim of this study was to review the history and the status of the SRO industry and to discuss the potential future prospects of this industry. This study summarised findings of the existing literature about the industry and defined development stages of the industry. Particular focus was put on the more recent development within the industry (1980s-present) which has not been covered adequately in the existing literature. The finding from this study revealed that major issues of the industry are linked to the management of prevailing diseases, the handling of water quality impairments from increasing coastal development, increasing competition from Australia's Pacific oyster (Crassostrea gigas) industry and the current socio-economic profile of the industry. The study also found that policy makers are currently confronted by the dilemma of saving a "dying art". Findings from this industry review may be vital for current and future fisheries managers and stakeholders as a basis for reviewing industry management and development strategies. This review may also be of interest for other aquaculture industries and fisheries who are dealing with similar challenges as the SRO industry.

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In the health care industry, Job Satisfaction (JS) is linked with work performance, psychological well-being and employee turnover. Although research into JS among health professionals has a long history worldwide, there has been very little analysis in Vietnam. No study has addressed JS of preventive medicine workers in Vietnam, and there is no reliable and valid instrument in Vietnamese language and context for evaluation of JS in this group. This project was conducted to fill these gaps. The findings contribute evidence regarding factors that influence JS in this sector of the health industry that should be applied to personnel management policies and practices in Vietnam.

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Biomedical systems involve a large number of entities and intricate interactions between these. Their direct analysis is, therefore, difficult, and it is often necessary to rely on computational models. These models require significant resources and parallel computing solutions. These approaches are particularly suited, given parallel aspects in the nature of biomedical systems. Model hybridisation also permits the integration and simultaneous study of multiple aspects and scales of these systems, thus providing an efficient platform for multidisciplinary research.

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This work explores the potential of Australian native plants as a source of second-generation biodiesel for internal combustion engines application. Biodiesels were evaluated from a number of non-edible oil seeds which are grow naturally in Queensland, Australia. The quality of the produced biodiesels has been investigated by several experimental and numerical methods. The research methodology and numerical model developed in this study can be used for a broad range of biodiesel feedstocks and for the future development of renewable native biodiesel in Australia.

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Introduction Chronic wounds are an area of major concern. The on-going and in-direct costs are substantial, reaching far beyond the costs of the hospitalization and associated care. As a result, pharmacological therapies have been developed to address treatment insufficiencies, however, the availability of drugs capable of promoting the wound repair process still remain limited. The wound healing properties of various herbal plants is well recognised amongst indigenous Australians. Hence, based on traditional accounts, we evaluated the wound healing potential of two Australian native plants. Methods Bioactive compounds were methanol extracted from dried plant leaves that were commercially sourced. Primary keratinocyte (Kc) and fibroblast (Fib) cells (denoted as Kc269, Kc274, Kc275, Kc276 and Fib274) obtained from surgical discarded tissue were cultured in 48-well plates and incubated (37⁰C, 5% CO2) overnight. The growth media was discarded and replaced with fresh growth media plus various concentrations (15.12 µg/mL, 31.25 µg/mL, 62.5 µg/mL, 125 µg/mL, 250 µg/mL and 500 µg/mL) of the plant extracts. Cellular responses were measured using the alamarBlue® assay and the CyQUANT® assay. Plant extracts in the aqueous phase were prepared by boiling whole leaves in water and taking aqueous phase samples at various (1, 2 , 5 minutes boiling) time points. Plant leaves were either added before the water was boiled (cold boiled) or after the water was boiled (hot boiled). The final concentrations of the aqueous plant extracts were 3.3 ng/mL (± 0.3 ng/mL) per sample. The antimicrobial properties of the plant extracts were tested using the well diffusion assay method against Staphylococcus aureus, Klebsiella pnuemoniae and methicillin resistant S. aureus and Bacillus cereus. Results Assay results from the almarBlue® and CYQUANT® assays indicated that extracts from both native plants at various time points (0, 24 and 48 hours) and concentrations (31.25 mg/mL, 62.5 mg/mL, and 125 mg/mL) were significantly higher (n=3, p=0.03 for Kc269, p=0.04 for Kc274, p=0.02 for Fib274, p=0.04 for Kc275 and p=0.001 for Kc276) compared with the untreated controls. Neither plant extract demonstrated cytotoxic effects. Significant antimicrobial activity against methicillin resistant Staphylococcus aureus (p=0.0009 for hot boiled plant A, n=2, p=0.034 for cold boiled plant A, n=2) K. pnuemoniae (p=0.0009 for hot boiled plant A, n=2, p=0.002 for cold boiled plant A, n=2) and B. cereus (p=0.0009 for hot boiled plant A, n=2, p=0.003 for cold boiled plant A, n=2) was observed at concentrations of 3.2 ng/mL for plant A and 3.4 ng/mL for plant B. Conclusion Both native plants contain bioactive compounds that increase cellular metabolic rates and total nucleic acid content. Neither plant was shown to be cytotoxic. Furthermore, both exhibited significant antimicrobial activity.

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Invasive non-native plants have negatively impacted on biodiversity and ecosystem functions world-wide. Because of the large number of species, their wide distributions and varying degrees of impact, we need a more effective method for prioritizing control strategies for cost-effective investment across heterogeneous landscapes. Here, we develop a prioritization framework that synthesizes scientific data, elicits knowledge from experts and stakeholders to identify control strategies, and appraises the cost-effectiveness of strategies. Our objective was to identify the most cost-effective strategies for reducing the total area dominated by high-impact non-native plants in the Lake Eyre Basin (LEB). We use a case study of the ˜120 million ha Lake Eyre Basin that comprises some of the most distinctive Australian landscapes, including Uluru-Kata Tjuta National Park. More than 240 non-native plant species are recorded in the Lake Eyre Basin, with many predicted to spread, but there are insufficient resources to control all species. Lake Eyre Basin experts identified 12 strategies to control, contain or eradicate non-native species over the next 50 years. The total cost of the proposed Lake Eyre Basin strategies was estimated at AU$1·7 billion, an average of AU$34 million annually. Implementation of these strategies is estimated to reduce non-native plant dominance by 17 million ha – there would be a 32% reduction in the likely area dominated by non-native plants within 50 years if these strategies were implemented. The three most cost-effective strategies were controlling Parkinsonia aculeata, Ziziphus mauritiana and Prosopis spp. These three strategies combined were estimated to cost only 0·01% of total cost of all the strategies, but would provide 20% of the total benefits. Over 50 years, cost-effective spending of AU$2·3 million could eradicate all non-native plant species from the only threatened ecological community within the Lake Eyre Basin, the Great Artesian Basin discharge springs. Synthesis and applications. Our framework, based on a case study of the ˜120 million ha Lake Eyre Basin in Australia, provides a rationale for financially efficient investment in non-native plant management and reveals combinations of strategies that are optimal for different budgets. It also highlights knowledge gaps and incidental findings that could improve effective management of non-native plants, for example addressing the reliability of species distribution data and prevalence of information sharing across states and regions.

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This article examines the legal responses to protect traditional knowledge of biodiversity in the wake of the Rio Convention on Biological Diversity. It considers the relative merits of the inter-locking regimes of contract law, environmental law, intellectual property law, and native title law. Part 1 considers the natural drug discovery industry in Australia. In particular, it looks at the operations of Amrad, Astra Zeneca R & D, and the Australian Institute of Marine Science. This section examines the key features of the draft regulations proposed under the Environment Protection and Biodiversity Conservation Act 1999 (Cth) - model contracts, informed consent, benefit-sharing, and ministerial discretion. The use of Indigenous Land Use Agreements in the context of access to genetic resources is also explored. Part 2 considers the role played by native title law in dealing with tangible and intangible property interests. The High Court decision in Western Australia v Ward considers the relationship between native title rights and cultural knowledge. The Federal Court case of Neowarra v Western Australia provides an intriguing gloss on this High Court decision. Part 3 looks at whether traditional knowledge of biodiversity can be protected under intellectual property law. It focuses upon reforms such as Senator Aden Ridgeway's proposed amendments to the Plant Breeder's Rights Act 1994 (Cth), and the push to make disclosure of origin a requirement of patent law.

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In order to progress beyond currently available medical devices and implants, the concept of tissue engineering has moved into the centre of biomedical research worldwide. The aim of this approach is not to replace damaged tissue with an implant or device but rather to prompt the patient's own tissue to enact a regenerative response by using a tissue-engineered construct to assemble new functional and healthy tissue. More recently, it has been suggested that the combination of Synthetic Biology and translational tissue-engineering techniques could enhance the field of personalized medicine, not only from a regenerative medicine perspective, but also to provide frontier technologies for building and transforming the research landscape in the field of in vitro and in vivo disease models.

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This project investigates for the first time the biological mechanisms underlying the anecdotal use of Shikonin, an active component extracted from the Chinese herbal medicine "Zi Cao", as a treatment for hypertrophic scars. Compelling molecular and cellular evidence was generated supporting the therapeutic value of Shikonin as a scar treatment, suggesting that further development of this agent is warranted.

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The explosive growth in the development of Traditional Chinese Medicine (TCM) has resulted in the continued increase in clinical and research data. The lack of standardised terminology, flaws in data quality planning and management of TCM informatics are preventing clinical decision-making, drug discovery and education. This paper argues that the introduction of data warehousing technologies to enhance the effectiveness and durability in TCM is paramount. To showcase the role of data warehousing in the improvement of TCM, this paper presents a practical model for data warehousing with detailed explanation, which is based on the structured electronic records, for TCM clinical researches and medical knowledge discovery.