4 resultados para Mixed-species flocks

em Aston University Research Archive


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1. Adrenomedullin (AM) has two known receptors formed by the calcitonin receptor-like receptor (CL) and receptor activity-modifying protein (RAMP) 2 or 3: We report the effects of the antagonist fragments of human AM and CGRP (AM 22-52 and CGRP 8-37) in inhibiting AM at human (h), rat (r) and mixed species CL/RAMP2 and CL/RAMP3 receptors transiently expressed in Cos 7 cells or endogenously expressed as rCL/rRAMP2 complexes by Rat 2 and L6 cells. 2. AM 22-52 (10 μM) antagonised AM at all CL/RAMP2 complexes (apparent pA 2 values: 7.34±0.14 (hCL/hRAMP2), 7.28±0.06 (Rat2), 7.00±0.05 (L6), 6.25±0.17(rCL/hRAMP2)). CGRP 8-37 (10 μM) resembled AM 22-52 except on the rCL/hRAMP2 complex, where it did not antagonise AM (apparent PA 2 values: 7.04±0.13 (hCL/hRAMP2), 6.72±0.06 (Rat2), 7.03±0. 12 (L6)). 3. On CL/RAMP3 receptors, 10 μM CGRP 8-37 was an effective antagonist at all combinations (apparent pA 2 values: 6.96±0.08 (hCL/hRAMP3), 6.18±0.18 (rCL/rRAMP3), 6.48±0.20 (rCL/ hRAMP3)). However, 10 μm AM 22-52 only antagonised AM at the hCL/hRAMP3 receptor (apparent PA 2 6.73±0.14). 4. BIBN4096BS (10 μM) did not antagonise AM at any of the receptors. 5. Where investigated (all-rat and rat/human combinations), the agonist potency order on the CL/ RAMP3 receptor was AM∼βCGRP>αCGRP. 6. rRAMP3 showed three apparent polymorphisms, none of which altered its coding sequence. 7. This study shows that on CL/RAMP complexes, AM 22-52 has significant selectivity for the CL/ RAMP2 combination over the CL/RAMP3 combination. On the mixed species receptor, CGRP 8-37 showed the opposite selectivity. Thus, depending on the species, it is possible to discriminate pharmacologically between CL/RAMP2 and CL/RAMP3 AM receptors.

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Objective: Reduced insulin sensitivity associated with fasting hyperproinsulinaemia is common in type 2 diabetes. Proinsulinaemia is an established independent cardiovascular risk factor. The objective was to investigate fasting and postprandial release of insulin, proinsulin (PI) and 32-33 split proinsulin (SPI) before and after sensitization to insulin with pioglitazone compared to a group treated with glibenclamide. Design and patients: A randomized double-blind placebo-controlled trial. Twenty-two type 2 diabetic patients were recruited along with 10 normal subjects. After 4 weeks washout, patients received a mixed meal and were assigned to receive pioglitazone or glibenclamide for 20 weeks, after which patients received another identical test meal. The treatment regimes were designed to maintain glycaemic control (HbA1c) at pretreatment levels so that ß-cells received an equivalent glycaemic stimulus for both test meals. Measurements: Plasma insulin, PI, SPI and glucose concentrations were measured over an 8-h postprandial period. The output of PI and SPI was measured as the integrated postprandial response (area under the curve, AUC). Results: Pioglitazone treatment resulted in a significant reduction in fasting levels of PI and SPI compared to those of the controls. Postprandially, pioglitazone treatment had no effect on the insulin AUC response to the meal but significantly reduced the PI and SPI AUCs. Glibenclamide increased fasting insulin and the postprandial insulin AUC but had no effect on the PI and SPI AUCs. Conclusions: Sensitization to insulin with pioglitazone reduces the amount of insulin precursor species present in fasting and postprandially and may reduce cardiovascular risk. © 2007 The Authors.

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We investigate a mixed problem with variable lateral conditions for the heat equation that arises in modelling exocytosis, i.e. the opening of a cell boundary in specific biological species for the release of certain molecules to the exterior of the cell. The Dirichlet condition is imposed on a surface patch of the boundary and this patch is occupying a larger part of the boundary as time increases modelling where the cell is opening (the fusion pore), and on the remaining part, a zero Neumann condition is imposed (no molecules can cross this boundary). Uniform concentration is assumed at the initial time. We introduce a weak formulation of this problem and show that there is a unique weak solution. Moreover, we give an asymptotic expansion for the behaviour of the solution near the opening point and for small values in time. We also give an integral equation for the numerical construction of the leading term in this expansion.

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The spray zone is an important region to control nucleation of granules in a high shear granulator. In this study, a spray zone with cross flow is quantified as a well-mixed compartment in a high shear granulator. Granulation kinetics is quantitatively derived at both particle-scale and spray zone-scale. Two spatial decay rates, DGSDR (droplet-granule spatial decay rate) ζDG and DPSDR (droplet-primary particle spatial decay rate) ζDP, which are functions of volume fraction and diameter of particulate species within the powder bed, are defined to simplify the deduction. It is concluded that in cross flow, explicit analytical results show that the droplet concentration is subject to exponential decay with depth which produces a numerically infinite depth of spray zone in a real penetration process. In a well-mixed spray zone, the depth of the spray zone is 4/(ζDG + ζDP) and π2/3(ζDG + ζDP) in cuboid and cylinder shape, respectively. The first-order droplet-based collision rates of, nucleation rate B0 and rewetting rate RW0 are uncorrelated with the flow pattern and shape of the spray zone. The second-order droplet-based collision rate, nucleated granule-granule collision rate RGG, is correlated with the mixing pattern. Finally, a real formulation case of a high shear granulation process is used to estimate the size of the spray zone. The results show that the spray zone is a thin layer at the powder bed surface. We present, for the first time, the spray zone as a well-mixed compartment. The granulation kinetics of a well-mixed spray zone could be integrated into a Population Balance Model (PBM), particularly to aid development of a distributed model for product quality prediction.