335 resultados para Growth models


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This project investigated the calcium distributions of the skin, and the growth patterns of skin substitutes grown in the laboratory, using mathematical models. The research found that the calcium distribution in the upper layer of the skin is controlled by three different mechanisms, not one as previously thought. The research also suggests that tight junctions, which are adhesions between neighbouring skin cells, cannot be solely responsible for the differences in the growth patterns of skin substitutes and normal skin.

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Traditional sensitivity and elasticity analyses of matrix population models have been used to inform management decisions, but they ignore the economic costs of manipulating vital rates. For example, the growth rate of a population is often most sensitive to changes in adult survival rate, but this does not mean that increasing that rate is the best option for managing the population because it may be much more expensive than other options. To explore how managers should optimize their manipulation of vital rates, we incorporated the cost of changing those rates into matrix population models. We derived analytic expressions for locations in parameter space where managers should shift between management of fecundity and survival, for the balance between fecundity and survival management at those boundaries, and for the allocation of management resources to sustain that optimal balance. For simple matrices, the optimal budget allocation can often be expressed as simple functions of vital rates and the relative costs of changing them. We applied our method to management of the Helmeted Honeyeater (Lichenostomus melanops cassidix; an endangered Australian bird) and the koala (Phascolarctos cinereus) as examples. Our method showed that cost-efficient management of the Helmeted Honeyeater should focus on increasing fecundity via nest protection, whereas optimal koala management should focus on manipulating both fecundity and survival simultaneously. These findings are contrary to the cost-negligent recommendations of elasticity analysis, which would suggest focusing on managing survival in both cases. A further investigation of Helmeted Honeyeater management options, based on an individual-based model incorporating density dependence, spatial structure, and environmental stochasticity, confirmed that fecundity management was the most cost-effective strategy. Our results demonstrate that decisions that ignore economic factors will reduce management efficiency. ©2006 Society for Conservation Biology.

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The quality of environmental decisions should be gauged according to managers' objectives. Management objectives generally seek to maximize quantifiable measures of system benefit, for instance population growth rate. Reaching these goals often requires a certain degree of learning about the system. Learning can occur by using management action in combination with a monitoring system. Furthermore, actions can be chosen strategically to obtain specific kinds of information. Formal decision making tools can choose actions to favor such learning in two ways: implicitly via the optimization algorithm that is used when there is a management objective (for instance, when using adaptive management), or explicitly by quantifying knowledge and using it as the fundamental project objective, an approach new to conservation.This paper outlines three conservation project objectives - a pure management objective, a pure learning objective, and an objective that is a weighted mixture of these two. We use eight optimization algorithms to choose actions that meet project objectives and illustrate them in a simulated conservation project. The algorithms provide a taxonomy of decision making tools in conservation management when there is uncertainty surrounding competing models of system function. The algorithms build upon each other such that their differences are highlighted and practitioners may see where their decision making tools can be improved. © 2010 Elsevier Ltd.

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Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

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Background Ephrin-B2 is the sole physiologically-relevant ligand of the receptor tyrosine kinase EphB4, which is over-expressed in many epithelial cancers, including 66% of prostate cancers, and contributes to cancer cell survival, invasion and migration. Crucially, however, the cancer-promoting EphB4 signalling pathways are independent of interaction with its ligand ephrin-B2, as activation of ligand-dependent signalling causes tumour suppression. Ephrin-B2, however, is often found on the surface of endothelial cells of the tumour vasculature, where it can regulate angiogenesis to support tumour growth. Proteolytic cleavage of endothelial cell ephrin-B2 has previously been suggested as one mechanism whereby the interaction between tumour cell-expressed EphB4 and endothelial cell ephrin-B2 is regulated to support both cancer promotion and angiogenesis. Methods An in silico approach was used to search accessible surfaces of 3D protein models for cleavage sites for the key prostate cancer serine protease, KLK4, and this identified murine ephrin-B2 as a potential KLK4 substrate. Mouse ephrin-B2 was then confirmed as a KLK4 substrate by in vitro incubation of recombinant mouse ephrin-B2 with active recombinant human KLK4. Cleavage products were visualised by SDS-PAGE, silver staining and Western blot and confirmed by N-terminal sequencing. Results At low molar ratios, KLK4 cleaved murine ephrin-B2 but other prostate-specific KLK family members (KLK2 and KLK3/PSA) were less efficient, suggesting cleavage was KLK4-selective. The primary KLK4 cleavage site in murine ephrin-B2 was verified and shown to correspond to one of the in silico predicted sites between extracellular domain residues arginine 178 and asparagine 179. Surprisingly, the highly homologous human ephrin-B2 was poorly cleaved by KLK4 at these low molar ratios, likely due to the 3 amino acid differences at this primary cleavage site. Conclusion These data suggest that in in vivo mouse xenograft models, endogenous mouse ephrin-B2, but not human tumour ephrin-B2, may be a downstream target of cancer cell secreted human KLK4. This is a critical consideration when interpreting data from murine explants of human EphB4+/KLK4+ cancer cells, such as prostate cancer cells, where differential effects may be seen in mouse models as opposed to human clinical situations.

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Introduction & Aims Optimising fracture treatments requires a sound understanding of relationships between stability, callus development and healing outcomes. This has been the goal of computational modelling, but discrepancies remain between simulations and experimental results. We compared healing patterns vs fixation stiffness between a novel computational callus growth model and corresponding experimental data. Hypothesis We hypothesised that callus growth is stimulated by diffusible signals, whose production is in turn regulated by mechanical conditions at the fracture site. We proposed that introducing this scheme into computational models would better replicate the observed tissue patterns and the inverse relationship between callus size and fixation stiffness. Method Finite element models of bone healing under stiff and flexible fixation were constructed, based on the parameters of a parallel rat femoral osteotomy study. An iterative procedure was implemented, to simulate the development of callus and its mechanical regulation. Tissue changes were regulated according to published mechano-biological criteria. Predictions of healing patterns were compared between standard models, with a pre-defined domain for callus development, and a novel approach, in which periosteal callus growth is driven by a diffusible signal. Production of this signal was driven by local mechanical conditions. Finally, each model’s predictions were compared to the corresponding histological data. Results Models in which healing progressed within a prescribed callus domain predicted that greater interfragmentary movements would displace early periosteal bone formation further from the fracture. This results from artificially large distortional strains predicted near the fracture edge. While experiments showed increased hard callus size under flexible fixation, this was not reflected in the standard models. Allowing the callus to grow from a thin soft tissue layer, in response to a mechanically stimulated diffusible signal, results in a callus shape and tissue distribution closer to those observed histologically. Importantly, the callus volume increased with increasing interfragmentary movement. Conclusions A novel method to incorporate callus growth into computational models of fracture healing allowed us to successfully capture the relationship between callus size and fixation stability observed in our rat experiments. This approach expands our toolkit for understanding the influence of different fixation strategies on healing outcomes.

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Ectopic calcification (EC), which is the pathological deposition of calcium and phosphate in extra-skeletal tissues, may be associated with hypercalcaemic and hyperphosphataemic disorders, or it may occur in the absence of metabolic abnormalities. In addition, EC may be inherited as part of several monogenic disorders and studies of these have provided valuable insights into the metabolic pathways regulating mineral metabolism. For example, studies of tumoural calcinosis, a disorder characterised by hyperphosphataemia and progressive EC, have revealed mutations of fibroblast growth factor 23 (FGF23), polypeptide N-acetyl galactosaminyltransferase 3 (GALNT3) and klotho (KL), which are all part of a phosphate-regulating pathway. However, such studies in humans are limited by the lack of available large families with EC, and to facilitate such studies we assessed the progeny of mice treated with the chemical mutagen N-ethyl-N-nitrosourea (ENU) for EC. This identified two mutants with autosomal recessive forms of EC, and reduced lifespan, designated Ecalc1 and Ecalc2. Genetic mapping localized the Ecalc1 and Ecalc2 loci to a 11.0 Mb region on chromosome 5 that contained the klotho gene (Kl), and DNA sequence analysis identified nonsense (Gln203Stop) and missense (Ile604Asn) Kl mutations in Ecalc1 and Ecalc2 mice, respectively. The Gln203Stop mutation, located in KL1 domain, was severely hypomorphic and led to a 17-fold reduction of renal Kl expression. The Ile604Asn mutation, located in KL2 domain, was predicted to impair klotho protein stability and in vitro expression studies in COS-7 cells revealed endoplasmic reticulum retention of the Ile604Asn mutant. Further phenotype studies undertaken in Ecalc1 (kl203X/203X) mice demonstrated elevations in plasma concentrations of phosphate, FGF23 and 1,25-dihydroxyvitamin D. Thus, two allelic variants of Kl that develop EC and represent mouse models for tumoural calcinosis have been established. © 2015 Esapa et al.

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Australian providers of aged care are facing a rapidly ageing population and growth in demand for services. Beyond a sheer increase in consumers and major regulatory changes from Federal Government, many customers are becoming progressively discontented with a medically dominated model of care provision. This period of turbulence presents an opportunity for new entrants and forward-thinking organisations to disrupt the market by designing a more compelling value offering. Under this line of inquiry, the researchers conducted a qualitative content analysis study of over 37 Australian aged care organisations, clustering providers into six business model typologies. The study revealed that providers of aged care are becoming increasingly aware of emerging customer needs, and, in addressing these needs, are seeking to establish innovative models of care provision. This paper therefore presents a future model of care, along with implications for practice and policy.

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Objective: To compare the differences in the hemodynamic parameters of abdominal aortic aneurysm (AAA) between fluid-structure interaction model (FSIM) and fluid-only model (FM), so as to discuss their application in the research of AAA. Methods: An idealized AAA model was created based on patient-specific AAA data. In FM, the flow, pressure and wall shear stress (WSS) were computed using finite volume method. In FSIM, an Arbitrary Lagrangian-Eulerian algorithm was used to solve the flow in a continuously deforming geometry. The hemodynamic parameters of both models were obtained for discussion. Results: Under the same inlet velocity, there were only two symmetrical vortexes in the AAA dilation area for FSIM. In contrast, four recirculation areas existed in FM; two were main vortexes and the other two were secondary flow, which were located between the main recirculation area and the arterial wall. Six local pressure concentrations occurred in the distal end of AAA and the recirculation area for FM. However, there were only two local pressure concentrations in FSIM. The vortex center of the recirculation area in FSIM was much more close to the distal end of AAA and the area was much larger because of AAA expansion. Four extreme values of WSS existed at the proximal of AAA, the point of boundary layer separation, the point of flow reattachment and the distal end of AAA, respectively, in both FM and FSIM. The maximum wall stress and the largest wall deformation were both located at the proximal and distal end of AAA. Conclusions: The number and center of the recirculation area for both models are different, while the change of vortex is closely associated with the AAA growth. The largest WSS of FSIM is 36% smaller than that of FM. Both the maximum wall stress and largest wall displacement shall increase with the outlet pressure increasing. FSIM needs to be considered for studying the relationship between AAA growth and shear stress.

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Growth rate of abdominal aortic aneurysm (AAA) is thought to be an important indicator of the potential risk of rupture. Wall stress is also thought to be a trigger for its rupture. However, stress change during the expansion of an AAA is unclear. Forty-four patients with AAAs were included in this longitudinal follow-up study. They were assessed by serial abdominal ultrasonography and computerized tomography (CT) scans if a critical size was reached or a rapid expansion occurred. Patient-specific 3-dimensional AAA geometries were reconstructed from the follow-up CT images. Structural analysis was performed to calculate the wall stresses of the AAA models at both baseline and final visit. A non-linear large-strain finite element method was used to compute the wall stress distribution. The average growth rate was 0.66cm/year (range 0-1.32 cm/year). A significantly positive correlation between shoulder tress at baseline and growth rate was found (r=0.342; p=0.02). A higher shoulder stress is associated with a rapidly expanding AAA. Therefore, it may be useful for estimating the growth expansion of AAAs and further risk stratification of patients with AAAs.

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The growth of the Australian eastern king prawn (Melicertus plebejus) is understood in greater detail by quantifying the latitudinal effect. The latitudinal effect is the change in the species' growth rate during migration. Mark-recapture data (N = 1635, latitude 22.21 degrees S-34.00 degrees S) presents northerly movement of the eastern king prawn, with New South Wales prawns showing substantial average movement of 140 km (standard deviation: 176 km) north. A generalized von Bertalanffy growth model framework is used to incorporate the latitudinal effect together with the canonical seasonal effect. Applying this method to eastern king prawn mark-recapture data guarantees consistent estimates for the latitudinal and seasonal effects. For M. plebejus, it was found that growth rate peaks on 25 and 29 January for males and females, respectively; is at a minimum on 27 and 31 July, respectively; and that the shape parameter, k (per year), changes by -0.0236 and -0.0556 every 1 degree of latitude south increase for males and females, respectively.

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Previous studies have shown that the external growth records of the posterior adductor muscle scar (PAMS) of the bivalve Pinna nobilis are incomplete and do not produce accurate age estimations. We have developed a new methodology to study age and growth using the inner record of the PAMS, which avoids the necessity of costly in situ shell measurements or isotopic studies. Using the inner record we identified the positions of PAMS previously obscured by nacre and estimated the number of missing records in adult specimens with strong abrasion of the calcite layer in the anterior portion of the shell. The study of the PAMS and inner record of two shells that were 6 years old when collected showed that only 2 and 3 PAMS were observed, while 6 inner records could be counted, thus confirming our working methodology. Growth parameters of a P. nobilis population located in Moraira, Spain (western Mediterranean) were estimated with the new methodology and compared to those obtained using PAMS data and in situ measurements. For the comparisons, we applied different models considering the data alternatively as length-at-age (LA) and tag-recapture (TR). Among every method we tested to fit the Von Bertalanffy growth model, we observed that LA data from inner record fitted to the model using non-linear mixed effects and the estimation of missing records using the calcite width was the most appropriate. The equation obtained with this method, L = 573*(1 - e(-0.16(t-0.02))), is very similar to that calculated previously from in situ measurements for the same population.

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This article develops a method for analysis of growth data with multiple recaptures when the initial ages for all individuals are unknown. The existing approaches either impute the initial ages or model them as random effects. Assumptions about the initial age are not verifiable because all the initial ages are unknown. We present an alternative approach that treats all the lengths including the length at first capture as correlated repeated measures for each individual. Optimal estimating equations are developed using the generalized estimating equations approach that only requires the first two moment assumptions. Explicit expressions for estimation of both mean growth parameters and variance components are given to minimize the computational complexity. Simulation studies indicate that the proposed method works well. Two real data sets are analyzed for illustration, one from whelks (Dicathais aegaota) and the other from southern rock lobster (Jasus edwardsii) in South Australia.

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The von Bertalanffy growth model is extended to incorporate explanatory variables. The generalized model includes the switched growth model and the seasonal growth model as special cases, and can also be used to assess the tagging effect on growth. Distribution-free and consistent estimating functions are constructed for estimation of growth parameters from tag-recapture data in which age at release is unknown. This generalizes the work of James (1991, Biometrics 47 1519-1530) who considered the classical model and allowed for individual variability in growth. A real dataset from barramundi (Lates calcarifer) is analysed to estimate the growth parameters and possible effect of tagging on growth.

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This project investigated the calcium distributions of the skin, and the growth patterns of skin substitutes grown in the laboratory, using mathematical models. The research found that the calcium distribution in the upper layer of the skin is controlled by three different mechanisms, not one as previously thought. The research also suggests that tight junctions, which are adhesions between neighbouring skin cells, cannot be solely responsible for the differences in the growth patterns of skin substitutes and normal skin.