The NF-{kappa}B negative regulator TNFAIP3 (A20) is inactivated by somatic mutations and genomic deletions in marginal zone lymphomas

Unique and shared cytogenetic abnormalities have been documented for marginal zone lymphomas (MZLs) arising at different sites. Recently, homozygous deletions of the chromosomal band 6q23, involving the tumor necrosis factor alpha-induced protein 3 (TNFAIP3, A20) gene, a negative regulator of NF-kappaB, were described in ocular adnexal MZL, suggesting a role for A20 as a tumor suppressor in this disease. Here, we investigated inactivation of A20 by DNA mutations or deletions in a panel of extranodal MZL (EMZL), nodal MZL (NMZL), and splenic MZL (SMZL). Inactivating mutations encoding truncated A20 proteins were identified in 6 (19%) of 32 MZLs, including 2 (18%) of 11 EMZLs, 3 (33%) of 9 NMZLs, and 1 (8%) of 12 SMZLs. Two additional unmutated nonsplenic MZLs also showed monoallelic or biallelic A20 deletions by fluorescent in situ hybridization (FISH) and/or SNP-arrays. Thus, A20 inactivation by either somatic mutation and/or deletion represents a common genetic aberration across all MZL subtypes, which may contribute to lymphomagenesis by inducing constitutive NF-kappaB activation.

A comparison of pixel and object-based land cover classification. A case study of the Asmara region, Eritrea

In this paper we compare the performance of two image classification paradigms (object- and pixel-based) for creating a land cover map of Asmara, the capital of Eritrea and its surrounding areas using a Landsat ETM+ imagery acquired in January 2000. The image classification methods used were maximum likelihood for the pixel-based approach and Bhattacharyya distance for the object-oriented approach available in, respectively, ArcGIS and SPRING software packages. Advantages and limitations of both approaches are presented and discussed. Classifications outputs were assessed using overall accuracy and Kappa indices. Pixel- and object-based classification methods result in an overall accuracy of 78% and 85%, respectively. The Kappa coefficient for pixel- and object-based approaches was 0.74 and 0.82, respectively. Although pixel-based approach is the most commonly used method, assessment and visual interpretation of the results clearly reveal that the object-oriented approach has advantages for this specific case-study.