Constitutional Haploinsufficiency of Tumor Suppressor Genes in Mentally Retarded Patients With Microdeletions in 17p13.1

Chromosome microdeletions or duplications are detected in 10-20% of patients with mental impairment and normal karyotypes. A few cases have been reported of mental impairment with microdeletions comprising tumor suppressor genes. By array-CGH we detected 4 mentally impaired individuals carrying de novo microdeletions sharing an overlapping segment of similar to 180 kb in 17p13.1. This segment encompasses 18 genes, including 3 involved in cancer, namely KCTD11/REN, DLG4/PSD95, and GPS2. Furthermore, in 2 of the patients, the deletions also included TP53, the most frequently inactivated gene in human cancers. The 3 tumor suppressor genes KCTD11, DLG4, and GPS2, in addition to the GABARAP gene, have a known or suspected function in neuronal development and are candidates for causing mental impairment in our patients. Among our 4 patients with deletions in 17p13.1, 3 were part of a Brazilian cohort of 300 mentally retarded individuals, suggesting that this segment may be particularly prone to rearrangements and appears to be an important cause (similar to 1%) of mental retardation. Further, the constitutive deletion of tumor suppressor genes in these patients, particularly TP53, probably confers a significantly increased lifetime risk for cancer and warrants careful oncological surveillance of these patients. Constitutional chromosome deletions containing tumor suppressor genes in patients with mental impairment or congenital abnormalities may represent an important mechanism linking abnormal phenotypes with increased risks of cancer. Copyright (C) 2009 S. Karger AG, Basel

Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms

J.A. Ferreira Neto, E.C. Santos Junior, U. Fra Paleo, D. Miranda Barros, and M.C.O. Moreira. 2011. Optimal subdivision of land in agrarian reform projects: an analysis using genetic algorithms. Cien. Inv. Agr. 38(2): 169-178. The objective of this manuscript is to develop a new procedure to achieve optimal land subdivision using genetic algorithms (GA). The genetic algorithm was tested in the rural settlement of Veredas, located in Minas Gerais, Brazil. This implementation was based on the land aptitude and its productivity index. The sequence of tests in the study was carried out in two areas with eight different agricultural aptitude classes, including one area of 391.88 ha subdivided into 12 lots and another of 404.1763 ha subdivided into 14 lots. The effectiveness of the method was measured using the shunting line standard value of a parceled area lot`s productivity index. To evaluate each parameter, a sequence of 15 calculations was performed to record the best individual fitness average (MMI) found for each parameter variation. The best parameter combination found in testing and used to generate the new parceling with the GA was the following: 320 as the generation number, a population of 40 individuals, 0.8 mutation tax, and a 0.3 renewal tax. The solution generated rather homogeneous lots in terms of productive capacity.