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1.
J Appl Stat ; 48(7): 1154-1179, 2021.
Artículo en Inglés | MEDLINE | ID: mdl-35706888

RESUMEN

Grouped data are frequently used in several fields of study. In this work, we use the expectation-maximization (EM) algorithm for fitting the skew-normal (SN) mixture model to the grouped data. Implementing the EM algorithm requires computing the one-dimensional integrals for each group or class. Our simulation study and real data analyses reveal that the EM algorithm not only always converges but also can be implemented in just a few seconds even when the number of components is large, contrary to the Bayesian paradigm that is computationally expensive. The accuracy of the EM algorithm and superiority of the SN mixture model over the traditional normal mixture model in modelling grouped data are demonstrated through the simulation and three real data illustrations. For implementing the EM algorithm, we use the package called ForestFit developed for R environment available at https://cran.r-project.org/web/packages/ForestFit/index.html.

2.
Fish Physiol Biochem ; 45(3): 977-986, 2019 Jun.
Artículo en Inglés | MEDLINE | ID: mdl-30648194

RESUMEN

The study was conducted to investigate the effect of diets containing 0, 2.5, 5, 7.5, and 10% S. platensis meal on total antioxidant capacity (TAC) and lipid peroxidation, as well as the expression of two antioxidant enzyme genes (SOD and CAT) in rainbow trout (Oncorhynchus mykiss). One hundred and eighty fish, with an average initial weight of 101 ± 8 g, were cultured for 10 weeks. At the end of experiment, lipid peroxidation significantly decreased in serum of fish fed with S. platensis and fish fed with 5, 7.5, and 10% microalgae showed a significantly lower value compared to control and 2.5%. Inclusion of 7.5 and 10% S. platensis in diet also decreased lipid peroxidation in liver. TAC significantly increased with increasing level of S. platensis. Expression level of superoxide dismutase (SOD) and catalase (CAT) genes significantly increased in the fish liver after administration of microalgae and fish fed with 10% S. platensis in diet showed the highest level compared to the other treatments. The present study reveals that inclusion of 10% S. platensis in diet can decrease oxidative stress in rainbow trout. Therefore, S. platensis can be used as potential antioxidant for fish farming.


Asunto(s)
Antioxidantes/metabolismo , Suplementos Dietéticos , Peroxidación de Lípido/efectos de los fármacos , Oncorhynchus mykiss/metabolismo , Spirulina , Alimentación Animal/análisis , Fenómenos Fisiológicos Nutricionales de los Animales , Animales , Dieta/veterinaria , Proteínas de Peces/genética , Proteínas de Peces/metabolismo , Regulación de la Expresión Génica/efectos de los fármacos , Estrés Oxidativo
3.
Res Vet Sci ; 101: 84-8, 2015 Aug.
Artículo en Inglés | MEDLINE | ID: mdl-26267095

RESUMEN

This study evaluated the effects of diets containing 0, 2.5, 5, 7.5 and 10% of Spirulina platensis on hematological and serum biochemical parameters of rainbow trout (Oncorhynchus mykiss). Fish (n=180; 101±8 g) were randomly divided into fifteen 300 L fiberglass tanks in triplicates for a period of ten weeks. The RBC, WBC, hemoglobin, total protein and albumin levels increased significantly in the groups supplemented with S. platensis. Dietary inclusion of S. platensis had no significant effects on hematocrit, cholesterol, triglyceride and lactate of the blood. HDL-cholesterol was larger in rainbow trout fed 10% S. platensis in comparison with the other diets, whereas LDL-cholesterol significantly decreased with increasing of S. platensis inclusion. Cortisol and glucose significantly decreased with increasing of S. platensis inclusion. The present results demonstrate that inclusion of 10% S. platensis can be introduced as an immunostimulant in rainbow trout diets.


Asunto(s)
Suplementos Dietéticos/normas , Oncorhynchus mykiss/sangre , Spirulina/química , Animales , Recuento de Células Sanguíneas , Colesterol/sangre , HDL-Colesterol/sangre , Relación Dosis-Respuesta a Droga , Triglicéridos/sangre
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