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Hemodialysis-related amyloidosis (HRA) represents one of the main dialysis-related pathologies. It occurs secondary to the deposition of beta-2-microglobulin (|32M), preferentially in the synovium and bone. Clinical features of HRA include carpal tunnel syndrome (CTS), erosive arthropathy, spondyloarthropathy, lytic bone lesions, and pathological fractures. The diagnosis can be made by X-Ray imaging, computerized tomography, magnetic resonance and more recently by β2M-Scintigraphy. HRA can be diagnosed as early as 2 years after the start of regular dialysis treatment (RDT). It was observed in a post-mortem study that over 90% of patients had developed HRA within 7 years2, albeit other authors have claimed that the incidence may be much less3. Although P2M amyloidosis almost invariably seems to be associated with RDT, it was described a patient with severe renal insufficiency who developed the syndrome without having ever been on dialysis4. Treatment-related factors (mainly, dialysis duration) are generall...

Background Several tools have been developed to perform global gene expression profile data analysis, to search for specific chromosomal regions whose features meet defined criteria as well as to study neighbouring gene expression. However, most of these tools are tailored for a specific use in a particular context (e.g. they are species-specific, or limited to a particular data format) and they typically accept only gene lists as input. Results TRAM (Transcriptome Mapper) is a new general tool that allows the simple generation and analysis of quantitative transcriptome maps, starting from any source listing gene expression values for a given gene set (e.g. expression microarrays), implemented as a relational database. It includes a parser able to assign univocal and updated gene symbols to gene identifiers from different data sources. Moreover, TRAM is able to perform intra-sample and inter-sample data normalization, including an original variant of quantile normalization (scaled quantile), useful to normalize data from platforms with highly different numbers of investigated genes. When in 'Map' mode, the software generates a quantitative representation of the transcriptome of a sample (or of a pool of samples) and identifies if segments of defined lengths are over/under-expressed compared to the desired threshold. When in 'Cluster' mode, the software searches for a set of over/under-expressed consecutive genes. Statistical significance for all results is calculated with respect to genes localized on the same chromosome or to all genome genes. Transcriptome maps, showing differential expression between two sample groups, relative to two different biological conditions, may be easily generated. We present the results of a biological model test, based on a meta-analysis comparison between a sample pool of human CD34+ hematopoietic progenitor cells and a sample pool of megakaryocytic cells. Biologically relevant chromosomal segments and gene clusters with differential expression during the differentiation toward megakaryocyte were identified. Conclusions TRAM is designed to create, and statistically analyze, quantitative transcriptome maps, based on gene expression data from multiple sources. The release includes FileMaker Pro database management runtime application and it is freely available at http://apollo11.isto.unibo.it/software/, along with preconfigured implementations for mapping of human, mouse and zebrafish transcriptomes.

Members of the bone morphogenetic protein (BMP) family and their receptors (BMPRs and activin receptors-ActRs) promote the development of bones with a fine regulation of their expression. Mutations in BMPs or BMPRs cause several diseases, as shown in knockout mice, such as skeletal defects, familial primary pulmonary hypertension and neoplasias. Osteosarcoma is the most frequent primary malignant tumor of bone. Due to their importance in bone development, BMPs, BMPRs and ActRs could also play a role in osteosarcoma growth and development. Previous data have shown that the overexpression of the BMPR-II was related to poor prognosis in malignant and metastatic bone tumors. We evaluate by reverse transcription-linked polymerase chain reaction analysis (RT-PCR) the expression pattern of BMPs, BMPRs and ActRs in five different human osteosarcoma cell lines (MG63, G292, HOS, SaOS and U2). Moreover, we performed the mutational screening of the complete BMPR-II mRNA by automated sequencing of the correspondent cDNA to evaluate the presence of point mutations in osteosarcoma cell lines. All the osteosarcoma cell lines studied simultaneously expressed the BMPs, BMPRs and ActRs investigated. No mutations were detected in the BMPR-II cDNA. Our results suggest the presence of a mechanism involving the simultaneous activation of the BMPs and their receptors in osteosarcoma cell lines.