ABSTRACT
Ectodermal dysplasia is a diverse group of genetic disorders that involve defects of the ectodermally derived structures and their accessory appendages including hair, nails, teeth, skin and glands. Other parts of the body, such as the eyes or throat, may be affected as well. Oral signs and symptoms are present in most of patients. The aim of this article is to report a case of child affected by ectodermal dysplasia with partial anodontia and to summarize some of the literature on current knowledge of oral manifestations and orofacial function as dental manifestations can be crucial for differential diagnosis of this disorder.
ABSTRACT
The aim of this work was to optimize the biomass production by Bifidobacterium bifidum 255 using the response surface methodology (RSM) and artificial neural network (ANN) both coupled with GA. To develop the empirical model for the yield of probiotic bacteria, additional carbon and nitrogen content, inoculum size, age, temperature and pH were selected as the parameters. Models were developed using » fractional factorial design (FFD) of the experiments with the selected parameters. The normalized percentage mean squared error obtained from the ANN and RSM models were 0.05 and 0.1 percent, respectively. Regression coefficient (R²) of the ANN model showed higher prediction accuracy compared to that of the RSM model. The empirical yield model (for both ANN and RSM) obtained were utilized as the objective functions to be maximized with the help of genetic algorithm. The optimal conditions for the maximal biomass yield were 37.4 °C, pH 7.09, inoculum volume 1.97 ml, inoculum age 58.58 h, carbon content 41.74 percent (w/v), and nitrogen content 46.23 percent (w/v). The work reported is a novel concept of combining the statistical modeling and evolutionary optimization for an improved yield of cell mass of B. bifidum 255.