RESUMEN
Resumen Objetivo: Genotipificar muestras de Giardia aisladas de pacientes de tres regiones geográficas de Colombia. Materiales y métodos: Se examinaron 22 aislados de G. intestinalis, los primeros descritos cultivados axénicamente de origen colombiano por medio del análisis del polimorfismo de longitud de fragmentos de restricción (RFLP) del gen glutamato deshidrogenasa (gdh). Resultados y conclusión: El patrón del RFLP mostró que todos los aislados pertenecían al ensamblaje A, específicamente al AI; resultado confirmado por secuenciación. Con este estudio se pretende contribuir al conocimiento de los genotipos circulantes de Giardia intestinalis en Colombia.
Abstract Objective: To genotype samples of G. intestinalis isolated from patients of three Colombian regions. Materials and methods: 22 isolates of Giardia (all of them established as axenic cultures) were examined by analyzing restriction fragment length polymorphism (RFLP) of the glutamate dehydrogenase gene (gdh). Results and conclusion: The RFLP patterns showed that all of the Giardia isolates belonged to the assembly A, specifically to AI. This result was confirmed by sequencing. This study aims to contribute to the knowledge of circulating genotypes of Giardia intestinalis in Colombia.
RESUMEN
An extended dynamical model for growth and sporulation of Bacillus thuringiensis subsp. kurstaki in an intermittent fed-batch culture with total cell retention is proposed. This model differs from reported models, by including dynamics for natural death of cells and substrate consumption for cell maintenance. The proposed model uses sigmoid functions to describe these kinetic parameters. Equations for time evolution of substrate, vegetative, sporulated and total cell concentration were taken from previous works. Model parameters were determined from batch experimental data obtained in pilot plant. Parameter identification was developed in two stages: (1) coarse identification using a multivariable optimization with constraints algorithm, (2) fine identification by heuristic fit of model parameters looking for a minimal model error. The proposed model estimates adequate time evolution of the process variables with a mean error of 2.6% on substrate concentration and 6.7% on biomass concentration.