The aim of this study was to explore the correlation between the expression levels of Gli1 and p53 in pancreatic ductal adenocarcinoma (PDAC) and its pathological significance. Immunohistochemistry (IHC) was employed to measure the expression level of Gli1 and p53 in 85 sets of paraffin-embedded PDAC and corresponding para-carcinoma tissue specimens. The relationship between these results and the respective patients’ clinicopathologic parameters was analyzed.
The correct classification of individuals is extremely important for the preservation of genetic variability and for maximization of yield in breeding programs using phenotypic traits and genetic markers. The Fisher and Anderson discriminant functions are commonly used multivariate statistical techniques for these situations, which allow for the allocation of an initially unknown individual to predefined groups. However, for higher levels of similarity, such as those found in backcrossed populations, these methods have proven to be inefficient.
The aim of this study was to evaluate different methods used in genomic selection, and to verify those that select a higher proportion of individuals with superior genotypes. Thus, F2 populations of different sizes were simulated (100, 200, 500, and 1000 individuals) with 10 replications each. These consisted of 10 linkage groups (LG) of 100 cM each, containing 100 equally spaced markers per linkage group, of which 200 controlled the characteristics, defined as the 20 initials of each LG.