5 resultados para biological variability

em University of Queensland eSpace - Australia


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Purpose: PI-88 is a mixture of highly sulfated oligosaccharides that inhibits heparanase, an extracellular matrix endoglycosidase, and the binding of angiogenic growth factors to heparan sulfate. This agent showed potent inhibition of placental blood vessel angiogenesis as well as growth inhibition in multiple xenograft models, thus forming the basis for this study. Experimental Design: This study evaluated the toxicity and pharmacokinetics of PI-88 (80-315 mg) when administered s.c. daily for 4 consecutive days bimonthly (part 1) or weekly (part 2). Results: Forty-two patients [median age, 53 years (range, 19-78 years); median performance status, 1] with a range of advanced solid tumors received a total of 232 courses. The maximum tolerated dose was 250 mg/d. Dose-limiting toxicity consisted of thrombocytopenia and pulmonary embolism. Other toxicity was generally mild and included prolongation of the activated partial thromboplastin time and injection site echymosis. The pharmacokinetics were linear with dose. Intrapatient variability was low and interpatient variability was moderate. Both AUC and C-max correlated with the percent increase in activated partial thromboplastin time, showing that this pharmacodynamic end point can be used as a surrogate for drug exposure, No association between PI-88 administration and vascular endothelial growth factor or basic fibroblast growth factor levels was observed. One patient with melanoma had a partial response, which was maintained for >50 months, and 9 patients had stable disease for >= 6 months. Conclusion: The recommended dose of PI-88 administered for 4 consecutive days bimonthly or weekly is 250 mg/d. PI-88 was generally well tolerated. Evidence of efficacy in melanoma supports further evaluation of PI-88 in phase II trials.

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Various factors can influence the population dynamics of phytophages post introduction, of which climate is fundamental. Here we present an approach, using a mechanistic modelling package (CLIMEX), that at least enables one to make predictions of likely dynamics based on climate alone. As biological control programs will have minimal funding for basic work (particularly on population dynamics), we show how predictions can be made using a species geographical distribution, relative abundance across its range, seasonal phenology and laboratory rearing data. Many of these data sets are more likely to be available than long-term population data, and some can be incorporated into the exploratory phase of a biocontrol program. Although models are likely to be more robust the more information is available, useful models can be developed using information on species distribution alone. The fitted model estimates a species average response to climate, and can be used to predict likely geographical distribution if introduced, where the agent is likely to be more abundant (i.e. good locations) and more importantly for interpretation of release success, the likely variation in abundance over time due to intra- and inter-year climate variability. The latter will be useful in predicting both the seasonal and long-term impacts of the potential biocontrol agent on the target weed. We believe this tool may not only aid in the agent selection process, but also in the design of release strategies, and for interpretation of post-introduction dynamics and impacts. More importantly we are making testable predictions. If biological control is to become more of a science making and testing such hypothesis will be a key component.

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In cats with underlying low insulin sensitivity, obesity is a major risk factor for type 2 diabetes. Strategies to prevent the onset of type 2 diabetes could be implemented if these cats could be identified. Currently, two labour-intensive and complex methods have been used to measure insulin sensitivity in research studies: the hyperinsulinemic euglycemic clamp (Clamp) and the minimal model analysis (MINMOD) of a frequentlysampled intravenous glucose tolerance test. However, simpler measures are required in practice. Validation of simple measures requires a wellestablished method with minimal inter-day variability. The aims of this study were to determine the inter-day variability of the current methods of measuring insulin sensitivity in cats, and to assess the relationship between these tests and simpler measures of insulin sensitivity.

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Variability is fundamental to biological systems and is important in posturomotor learning and control. Pain induces a protective postural strategy, although variability is normally preserved. If variability is lost, does the normal postural strategy return when pain stops? Sixteen subjects performed arm movements during control trials, when the movement evoked back pain and then when it did not. Variability in the postural strategy of the abdominal muscles and pain-related cognitions were evaluated. Only those subjects for whom pain induced a reduction in variability of the postural strategy failed to return to a normal strategy when pain stopped. They were also characterized by their pain-related cognitions. Ongoing perception of threat to the back may exert tighter evaluative control over variability of the postural strategy.