920 resultados para growth parameters


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The GH receptor (GHR) is essential for normal postnatal growth and development, and the molecular basis of GHR action has been studied intensively. Clinical case studies and more recently mouse models have revealed the extensive phenotype of impaired GH action. We recently reported two new mouse models, possessing cytoplasmic truncations at position 569 (plus Y539/545-F) and 391, which were created to identify functional subdomains within the cytoplasmic signaling domain. In the homozygous state, these animals show progressively impaired postnatal growth coupled with complex changes in gene expression. We describe here an extended phenotype analysis encompassing the heterozygote state to identify whether single copies of these mutant receptors bring about partial or dominant-negative phenotypes. It appears that the retention of the ubiquitin-dependent endocytosis motif the N-terminal cytoplasmic domain permits turnover of these mutant receptors because no dominant-negative phenotype is seen. Nonetheless, we do observe partial impairment of postnatal growth in heterozygotes supporting limited haploinsufficiency. Reproductive function is impaired in these models in a progressive manner, in parallel with loss of signal transducer and activator of transcription-5 activation ability. In summary, we describe a more comprehensive phenotypic analysis of these mouse models, encompassing overall and longitudinal body growth, reproductive function, and hormonal status in both the heterozygote and homozygote state. Our results suggest that patients expressing single copies of similarly mutated GHRs would not display an obvious clinical phenotype.

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This preliminary compilation presents vital parameters for 22 species of freshwater fish from Lake Kariba. The majority of the growth parameters are derived from tables in Balon and Coche's "Lake Kariba: a man-made tropical ecosystem in central Africa". The rest of the parameters are compiled from more recent sources and unpublished data.

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The seasonally oscillating growth parameters and length-weight relationships for Scomber japonicus caught in the Gulf of Guayaquil, Ecuador, were determined based on length-frequency data from 1989 to 1996, using the FiSAT software package of Gayanilo et al. (1996). Estimates of growth parameters are in general agreement with previous studies on the same species. Results also imply that the growth of Scomber japonicus slows down during the cold season by approximately 50% with respect to the average growth. The mean value of the power b is significantly larger than 3, indicating that the model of allometric growth should be used for the length-weight relationship and calculation of the condition factor.

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This study investigated the effects of stocking density on the growth and fatty acid (FA) of Brycon insignis metabolism. Fingerlings (360) were distributed into eight ponds at two stocking densities (105 and 210 g/m(3)). The analysis of growth showed that the condition factor (K) and the coefficient of variation (CV) for body mass were not affected by stocking density. However, final body mass and length, specific growth rate (SGR), and weight gain (WG) were higher in the low stocking density group, which also presented a higher feed efficiency (FE) and survival (S). By contrast, muscle protein levels were higher in the high stocking density group. The plasma and muscle lipid content were not affected by stocking density, but fish reared at lower stocking density presented higher lipid concentration in the liver, with no differences in hepatosomatic index values. Even with the differences observed in metabolic and growth parameters, plasma cortisol was not affected by stocking density. The FA profile in the muscle and liver neutral fraction were not affected by stocking density, but the FA in the polar fractions differed between the two stocking densities. In the liver, total polyunsaturated fatty acids (PUFA) and PUFA n - 3 increased in higher stocking density, mainly due to an increase in docosahexaenoic acid (DHA). In addition, PUFA n - 6 were also increased in the higher stocking density group, mainly due to an increase in arachidonic acid (AA) and docosadienoic acid (22:2n - 6). In the muscle polar fraction, the saturated fatty acids (SFA) and monounsaturated fatty acids (MUFA) decreased in the animals from the higher stocking density group, and this reduction was compensated by an increase in PUFA n - 3 and PUFA n - 6, mainly the FA with 20-22 carbons (20:4n - 6: 22:4:n - 6; 22:5n - 6, 22:5n - 3, and 22:6n - 3). A different profile was observed for the C18 PUFAs, mainly 18:2n - 6 and 18:4n - 6, which were higher in the lower density stocking group. The data suggest that when living in high stocking density, B. insignis differentially utilizes the hepatic lipids as energy source and remodels the membrane fatty acids, with higher amounts of DHA in the polar muscle fraction compensated for by a decrease in MUFA. The zootechnical and physiological indices reveal that the lower stocking density group achieve overall better performance. (C) 2010 Elsevier B.V. All rights reserved.

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The objective of this study was to estimate growth parameters of carcass components (wing, thighs and drumsticks, back and breast) and organs (heart, liver, gizzard and gut) in males and females of one meat-type quail strain (Coturnix coturnix coturnix) and two laying strains (Coturnix coturnix japonica) designated either yellow or red.A total of 1350 quail from 1 to 42d old were distributed in a completely randomised design, with 5 replicates of each strain. The carcass component weights and body organs were analysed weekly and evaluated using the Gompertz function; growth rates were evaluated through derivative equations.The meat-type strain presented the highest growth rates in carcass components and organs. Across strains, females showed the highest weight of internal organs at maturity compared to males.Females had greater growth potential in breast, wings and back than males for both yellow and red laying quail.

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A numerical growth model is used to describe the catalyzed growth of carbon nanofibers in the sheath of a low-temperature plasma. Using the model, the effects of variation in the plasma sheath parameters and substrate potential on the carbon nanofiber growth characteristics, such as the growth rate, the effective carbon flux to the catalyst surface, and surface coverages, have been investigated. It is shown that variations in the parameters, which change the sheath width, mainly affect the growth parameters at the low catalyst temperatures, whereas the other parameters such as the gas pressure, ion temperature, and percentages of the hydrocarbon and etching gases, strongly affect the carbon nanofiber growth at higher temperatures. The conditions under which the carbon nanofiber growth can still proceed under low nanodevice-friendly process temperatures have been formulated and summarized. These results are consistent with the available experimental results and can also be used for catalyzed growth of other high-aspect-ratio nanostructures in low-temperature plasmas.

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A theoretical model to describe the plasma-assisted growth of carbon nanofibers (CNFs) is proposed. Using the model, the plasma-related effects on the nanofiber growth parameters, such as the growth rate due to surface and bulk diffusion, the effective carbon flux to the catalyst surface, the characteristic residence time and diffusion length of carbon atoms on the catalyst surface, and the surface coverages, have been studied. The dependence of these parameters on the catalyst surface temperature and ion and etching gas fluxes to the catalyst surface is quantified. The optimum conditions under which a low-temperature plasma environment can benefit the CNF growth are formulated. These results are in good agreement with the available experimental data on CNF growth and can be used for optimizing synthesis of related nanoassemblies in low-temperature plasma-assisted nanofabrication. © 2008 American Institute of Physics.

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This paper presents a maximum likelihood method for estimating growth parameters for an aquatic species that incorporates growth covariates, and takes into consideration multiple tag-recapture data. Individual variability in asymptotic length, age-at-tagging, and measurement error are also considered in the model structure. Using distribution theory, the log-likelihood function is derived under a generalised framework for the von Bertalanffy and Gompertz growth models. Due to the generality of the derivation, covariate effects can be included for both models with seasonality and tagging effects investigated. Method robustness is established via comparison with the Fabens, improved Fabens, James and a non-linear mixed-effects growth models, with the maximum likelihood method performing the best. The method is illustrated further with an application to blacklip abalone (Haliotis rubra) for which a strong growth-retarding tagging effect that persisted for several months was detected

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The contemporary methodology for growth models of organisms is based on continuous trajectories and thus it hinders us from modelling stepwise growth in crustacean populations. Growth models for fish are normally assumed to follow a continuous function, but a different type of model is needed for crustacean growth. Crustaceans must moult in order for them to grow. The growth of crustaceans is a discontinuous process due to the periodical shedding of the exoskeleton in moulting. The stepwise growth of crustaceans through the moulting process makes the growth estimation more complex. Stochastic approaches can be used to model discontinuous growth or what are commonly known as "jumps" (Figure 1). However, in stochastic growth model we need to ensure that the stochastic growth model results in only positive jumps. In view of this, we will introduce a subordinator that is a special case of a Levy process. A subordinator is a non-decreasing Levy process, that will assist in modelling crustacean growth for better understanding of the individual variability and stochasticity in moulting periods and increments. We develop the estimation methods for parameter estimation and illustrate them with the help of a dataset from laboratory experiments. The motivational dataset is from the ornate rock lobster, Panulirus ornatus, which can be found between Australia and Papua New Guinea. Due to the presence of sex effects on the growth (Munday et al., 2004), we estimate the growth parameters separately for each sex. Since all hard parts are shed too often, the exact age determination of a lobster can be challenging. However, the growth parameters for the aforementioned moult processes from tank data being able to estimate through: (i) inter-moult periods, and (ii) moult increment. We will attempt to derive a joint density, which is made up of two functions: one for moult increments and the other for time intervals between moults. We claim these functions are conditionally independent given pre-moult length and the inter-moult periods. The variables moult increments and inter-moult periods are said to be independent because of the Markov property or conditional probability. Hence, the parameters in each function can be estimated separately. Subsequently, we integrate both of the functions through a Monte Carlo method. We can therefore obtain a population mean for crustacean growth (e. g. red curve in Figure 1). [GRAPHICS]

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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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The Fabens method is commonly used to estimate growth parameters k and l infinity in the von Bertalanffy model from tag-recapture data. However, the Fabens method of estimation has an inherent bias when individual growth is variable. This paper presents an asymptotically unbiassed method using a maximum likelihood approach that takes account of individual variability in both maximum length and age-at-tagging. It is assumed that each individual's growth follows a von Bertalanffy curve with its own maximum length and age-at-tagging. The parameter k is assumed to be a constant to ensure that the mean growth follows a von Bertalanffy curve and to avoid overparameterization. Our method also makes more efficient use nf thp measurements at tno and recapture and includes diagnostic techniques for checking distributional assumptions. The method is reasonably robust and performs better than the Fabens method when individual growth differs from the von Bertalanffy relationship. When measurement error is negligible, the estimation involves maximizing the profile likelihood of one parameter only. The method is applied to tag-recapture data for the grooved tiger prawn (Penaeus semisulcatus) from the Gulf of Carpentaria, Australia.

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Estimation of von Bertalanffy growth parameters has received considerable attention in fisheries research. Since Sainsbury (1980, Can. J. Fish. Aquat. Sci. 37: 241-247) much of this research effort has centered on accounting for individual variability in the growth parameters. In this paper we demonstrate that, in analysis of tagging data, Sainsbury's method and its derivatives do not, in general, satisfactorily account for individual variability in growth, leading to inconsistent parameter estimates (the bias does not tend to zero as sample size increases to infinity). The bias arises because these methods do not use appropriate conditional expectations as a basis for estimation. This bias is found to be similar to that of the Fabens method. Such methods would be appropriate only under the assumption that the individual growth parameters that generate the growth increment were independent of the growth parameters that generated the initial length. However, such an assumption would be unrealistic. The results are derived analytically, and illustrated with a simulation study. Until techniques that take full account of the appropriate conditioning have been developed, the effect of individual variability on growth has yet to be fully understood.

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We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock and derive the underlying length distribution of the population and the catch when there is individual variability in the von Bertalanffy growth parameter L-infinity. The model is flexible enough to accommodate 1) any recruitment pattern as a function of both time and length, 2) length-specific selectivity, and 3) varying fishing effort over time. The maximum likelihood method gives consistent estimates, provided the underlying distribution for individual variation in growth is correctly specified. Simulation results indicate that our method is reasonably robust to violations in the assumptions. The method is applied to tiger prawn data (Penaeus semisulcatus) to obtain estimates of natural and fishing mortality.

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We consider estimation of mortality rates and growth parameters from length-frequency data of a fish stock when there is individual variability in the von Bertalanffy growth parameter L-infinity and investigate the possible bias in the estimates when the individual variability is ignored. Three methods are examined: (i) the regression method based on the Beverton and Holt's (1956, Rapp. P.V. Reun. Cons. Int. Explor. Mer, 140: 67-83) equation; (ii) the moment method of Powell (1979, Rapp. PV. Reun. Int. Explor. Mer, 175: 167-169); and (iii) a generalization of Powell's method that estimates the individual variability to be incorporated into the estimation. It is found that the biases in the estimates from the existing methods are, in general, substantial, even when individual variability in growth is small and recruitment is uniform, and the generalized method performs better in terms of bias but is subject to a larger variation. There is a need to develop robust and flexible methods to deal with individual variability in the analysis of length-frequency data.

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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.