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We used a class of stochastic differential equations (SDE) to model the evolution of cattle weight that, by an appropriate transformation of the weight, resulted in a variant of the Ornstein-Uhlenbeck model. In previous works, we have dealt with estimation, prediction, and optimization issues for this class of models. However, to incorporate individual characteristics of the animals, the average transformed size at maturity parameter α and/or the growth parameter β may vary randomly from animal to animal, which results in SDE mixed models. Obtaining a closed-form expression for the likelihood function to apply the maximum likelihood estimation method is a difficult, sometimes impossible, task. We compared the known Laplace approximation method with the delta method to approximate the integrals involved in the likelihood function. These approaches were adapted to allow the estimation of the parameters even when the requirement of most existing methods, namely having the same age vector of observations for all trajectories, fails, as it did in our real data example. Simulation studies were also performed to assess the performance of these approximation methods. The results show that the approximation methods under study are a very good alternative for the estimation of SDE mixed models. [ABSTRACT FROM AUTHOR]

In early work we have studied a class of stochastic differential equation (SDE) models, for which the Gompertz and the Bertalanffy-Richards stochastic models are particular cases, to describe individual growth in random environments, and applied it to model cattle weight evolution using real data. We have started to work on these type of models considering that the model parameters are fixed, i.e. the same for all the animals. Aiming to incorporate variability among individuals, we consider that the model parameters can be random variables, resulting in SDE mixed models. In additon, here we consider SDE mixed models, allowing the parameters to be random and propose to incorporate each animal's genetic characteristics considering the transformed animal's weight at maturity to be a function of its genetic values. The main objective is to extend the SDE mixed model to the more realistic case where the individual's genetic value becomes an important component in the estimated growth curve. For the estimation of the model parameters we have used maximum likelihood estimation theory. Estimates and asymptotic confidence intervals of the parameters are presented. A comparison with SDE non-mixed model and SDE mixed model without the inclusion of genetic characteristics is shown with the conclusion that the incorporation of some genetic characteristics in the model parameters improves the estimation of the animal's growth curve. [ABSTRACT FROM AUTHOR]

A class of stochastic differential equation models was applied to describe the evolution of the weight of Mertolengo cattle. We have determined the optimal mean profit obtained by selling an animal at the cattle market, using two approaches. One consists in determining the optimal selling age (independently of the weight) and the other consists in selling the animal when a fixed optimal weight is achieved for the first time (independently of the age). The profit probability distribution can be computed for such optimal age/weight. For typical market values, we observed that the second approach achieves a higher optimal mean profit compared with the first one, and, in most cases, even provides a lower standard deviation. [ABSTRACT FROM AUTHOR]

Stochastic differential equations (SDE) appropriately describe a variety of phenomena occurring in random environments, such as the growth dynamics of individual animals. Using appropriate weight transformations and a variant of the Ornstein–Uhlenbeck model, one obtains a general model for the evolution of cattle weight. The model parameters are α , the average transformed weight at maturity, β , a growth parameter, and σ , a measure of environmental fluctuations intensity. We briefly review our previous work on estimation and prediction issues for this model and some generalizations, considering fixed parameters. In order to incorporate individual characteristics of the animals, we now consider that the parameters α and β are Gaussian random variables varying from animal to animal, which results in SDE mixed models. We estimate parameters by maximum likelihood, but, since a closed-form expression for the likelihood function is usually not possible, we approximate it using our proposed delta approximation method. Using simulated data, we estimate the model parameters and compare them with existing methodologies, showing that the proposed method is a good alternative. It also overcomes the existing methodologies requirement of having all animals weighed at the same ages; thus, we apply it to real data, where such a requirement fails. [ABSTRACT FROM AUTHOR]

The human epidermis has a characteristic lipidic composition in the stratum corneum, where ceramides play a crucial role in the skin barrier homeostasis and in water-holding capacity. Several skin diseases, such as atopic dermatitis and psoriasis, exhibit a dysfunction in the lipid barrier with altered ceramide levels and increased loss of transepidermal water. Glucocorticoids are normally employed in the therapeutical management of these pathologies. However, they have shown a poor safety profile and reduced treatment efficiency. The main objective of this review is to, within the framework of the limitations of the currently available therapeutical approaches, establish the relevance of nanocarriers as a safe and efficient delivery strategy for glucocorticoids and ceramides in the topical treatment of skin disorders with barrier impairment. [ABSTRACT FROM AUTHOR]

Wound care has been clinically demanding due to inefficacious treatment that represents an economic burden for healthcare systems. In Europe, approximately 7 million people are diagnosed with untreated wounds, leading to a cost between 6.000€ and 10.000€ per patient/year. In the United States of America, 1.5 million people over 65 years old suffer from chronic wounds. A promising therapeutic strategy is the use of exogenous growth factors because they are decreased at the wound site, limiting the recovery of the skin. Insulin is one of the cheapest growth factors in the market able to accelerate the re-epithelialization and stimulate angiogenesis and cell migration. However, the effectiveness of topical insulin in wound healing is hampered by the proteases in the wound bed. The encapsulation into nanoparticles improves its stability in the wound, providing adhesion to the mucosal surface and allowing its sustained release. The aim of this review is to perform a standing point about a promising strategy to treat different types of wounds by the topical delivery of insulin-loaded nanocarriers. [ABSTRACT FROM AUTHOR]

Diabetes mellitus greatly affects the quality of life of patients and has a worldwide prevalence. Insulin is the most commonly used drug to treat diabetic patients and is usually administered through the subcutaneous route. However, this route of administration is ineffective due to the low concentration of insulin at the site of action. This route of administration causes discomfort to the patient and increases the risk of infection due to skin barrier disturbance caused by the needle. The oral administration of insulin has been proposed to surpass the disadvantages of subcutaneous administration. In this review, we give an overview of the strategies to deliver insulin by the oral route, from insulin conjugation to encapsulation into nanoparticles. These strategies are still under development to attain efficacy and effectiveness that are expected to be achieved in the near future., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)