78 resultados para Predictive medicine

em CentAUR: Central Archive University of Reading - UK


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There is controversy about whether traditional medicine can guide drug discovery, and investment in ethnobotanically led research has fluctuated. One view is that traditionally used plants are not necessarily efficacious and there are no robust methods for distinguishing the ones that are most likely to be bioactive when selecting species for further testing. Here, we reconstruct a genus-level molecular phylogeny representing the 20,000 species found in the floras of three disparate biodiversity hotspots: Nepal, New Zealand and the Cape of South Africa. Borrowing phylogenetic methods from community ecology, we reveal significant clustering of the 1,500 traditionally used species, and provide a direct measure of the relatedness of the three medicinal floras. We demonstrate shared phylogenetic patterns across the floras: related plants from these regions are used to treat medical conditions in the same therapeutic areas. This strongly suggests independent discovery of plant efficacy, an interpretation corroborated by the presence of a significantly greater proportion of known bioactive species in these plant groups than in a random sample. Phylogenetic cross-cultural comparison can focus screening efforts on a subset of traditionally used plants that are richer in bioactive compounds, and could revitalise the use of traditional knowledge in bioprospecting.

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A new dynamic model of water quality, Q(2), has recently been developed, capable of simulating large branched river systems. This paper describes the application of a generalized sensitivity analysis (GSA) to Q(2) for single reaches of the River Thames in southern England. Focusing on the simulation of dissolved oxygen (DO) (since this may be regarded as a proxy for the overall health of a river); the GSA is used to identify key parameters controlling model behavior and provide a probabilistic procedure for model calibration. It is shown that, in the River Thames at least, it is more important to obtain high quality forcing functions than to obtain improved parameter estimates once approximate values have been estimated. Furthermore, there is a need to ensure reasonable simulation of a range of water quality determinands, since a focus only on DO increases predictive uncertainty in the DO simulations. The Q(2) model has been applied here to the River Thames, but it has a broad utility for evaluating other systems in Europe and around the world.

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The need to map vegetation communities over large areas for nature conservation and to predict the impact of environmental change on vegetation distributions, has stimulated the development of techniques for predictive vegetation mapping. Predictive vegetation studies start with the development of a model relating vegetation units and mapped physical data, followed by the application of that model to a geographic database and over a wide range of spatial scales. This field is particularly important for identifying sites for rare and endangered species and locations of high biodiversity such as many areas of the Mediterranean Basin. The potential of the approach is illustrated with a mapping exercise in the alti-meditterranean zone of Lefka Ori in Crete. The study established the nature of the relationship between vegetation communities and physical data including altitude, slope and geomorphology. In this way the knowledge of community distribution was improved enabling a GIS-based model capable of predicting community distribution to be constructed. The paper describes the development of the spatial model and the methodological problems of predictive mapping for monitoring Mediterranean ecosystems. The paper concludes with a discussion of the role of predictive vegetation mapping and other spatial techniques, such as fuzzy mapping and geostatistics, for improving our understanding of the dynamics of Mediterranean ecosystems and for practical management in a region that is under increasing pressure from human impact.

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University students suffer from variable sleep patterns including insomnia;[1] furthermore, the highest incidence of herbal use appears to be among college graduates.[2] Our objective was to test the perception of safety and value of herbal against conventional medicine for the treatment of insomnia in a non-pharmacy student population. We used an experimental design and bespoke vignettes that relayed the same effectiveness information to test our hypothesis that students would give higher ratings of safety and value to herbal product compared to conventional medicine. We tested another hypothesis that the addition of side-effect information would lower people’s perception of the safety and value of the herbal product to a greater extent than it would with the conventional medicine.

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Orlistat is an effective weight-loss medicine, which will soon be available for purchase in pharmacies. We used a factorial experiment and found that informing people about the availability for purchase of this medicinal product previously only available on prescription resulted in higher ratings of perceived value and effectiveness compared to a natural health supplement even though we used the same statement about effectiveness. This positive perception of orlistat was not impaired by the provision of side-effect information. Orlistat will soon be available in pharmacies. Health professionals must act to prevent its misuse by those not overweight.

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Abstract 1.7.4

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A method was developed to evaluate crop disease predictive models for their economic and environmental benefits. Benefits were quantified as the value of a prediction measured by costs saved and fungicide dose saved. The value of prediction was defined as the net gain made by using predictions, measured as the difference between a scenario where predictions are available and used and a scenario without prediction. Comparable 'with' and 'without' scenarios were created with the use of risk levels. These risk levels were derived from a probability distribution fitted to observed disease severities. These distributions were used to calculate the probability that a certain disease induced economic loss was incurred. The method was exemplified by using it to evaluate a model developed for Mycosphaerella graminicola risk prediction. Based on the value of prediction, the tested model may have economic and environmental benefits to growers if used to guide treatment decisions on resistant cultivars. It is shown that the value of prediction measured by fungicide dose saved and costs saved is constant with the risk level. The model could also be used to evaluate similar crop disease predictive models.

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Disease-weather relationships influencing Septoria leaf blotch (SLB) preceding growth stage (GS) 31 were identified using data from 12 sites in the UK covering 8 years. Based on these relationships, an early-warning predictive model for SLB on winter wheat was formulated to predict the occurrence of a damaging epidemic (defined as disease severity of 5% or > 5% on the top three leaf layers). The final model was based on accumulated rain > 3 mm in the 80-day period preceding GS 31 (roughly from early-February to the end of April) and accumulated minimum temperature with a 0A degrees C base in the 50-day period starting from 120 days preceding GS 31 (approximately January and February). The model was validated on an independent data set on which the prediction accuracy was influenced by cultivar resistance. Over all observations, the model had a true positive proportion of 0.61, a true negative proportion of 0.73, a sensitivity of 0.83, and a specificity of 0.18. True negative proportion increased to 0.85 for resistant cultivars and decreased to 0.50 for susceptible cultivars. Potential fungicide savings are most likely to be made with resistant cultivars, but such benefits would need to be identified with an in-depth evaluation.

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Two novel benzodioxotetraaza macrocycles [2,9-dioxo-1,4,7,10-tetraazabicyclo[10.4.0]1,11-hexadeca-1(11),13,15-triene (H(2)L1) and 2,10-dioxo-1,4,8,11-tetraazabicyclo[11.4.0]1,12-heptadeca-1(12),14,16-triene (H(2)L2)] were synthesized by a [1 + 1] crablike cyclization. The protonation constants of both ligands were determined by H-1 NMR titration and by potentiometry at 25.0 degrees C in 0.10 M ionic strength in KNO3. The latter method was also used to ascertain the stability constants of their copper(II) complexes. These studies showed that the CuL1 complex has a much lower thermodynamic stability than the CuL2, and the H(2)L2 displays an excellent affinity for copper(II), due to the good fit of copper(II) into its cavity. The copper complexes of the novel ligands were characterized by electronic spectroscopy in solution and by crystal X-ray diffraction. These studies indicated that the copper center in the CuL1 complex adopts a square-pyramidal geometry with the four nitrogen atoms of the macrocycle forming the equatorial plane and a water molecule at axial position, and the copper in the CuL2 complex is square-planar. Several labeling conditions were tested, and only H(2)L2 could be labeled with Cu-67 efficiently (> 98%) in mild conditions (39 degrees C, 15 min) to provide a slightly hydrophilic radioligand (log D = -0.19 +/- 0.03 at pH 7.4). The in vitro stability was studied in the presence of different buffers or with an excess of diethylenetriamine-pentaethanoic acid. Very high stability was shown under these conditions for over 5 days. The incubation of the radiocopper complex in human serum showed 6% protein binding.