Down syndrome (DS) is due to the presence of an extra full or partial chromosome 21 (Hsa21). The identification of genes contributing to DS pathogenesis could be the key to any rational therapy of the associated intellectual disability. We aim at generating quantitative transcriptome maps in DS integrating all gene expression profile datasets available for any cell type or tissue, to obtain a complete model of the transcriptome in terms of both expression values for each gene and segmental trend of gene expression along each chromosome. We used the TRAM (Transcriptome Mapper) software for this meta-analysis, comparing transcript expression levels and profiles between DS and normal brain, lymphoblastoid cell lines, blood cells, fibroblasts, thymus and induced pluripotent stem cells, respectively. TRAM combined, normalized, and integrated datasets from different sources and across diverse experimental platforms. The main output was a linear expression value that may be used as a reference for each of up to 37,181 mapped transcripts analyzed, related to both known genes and expression sequence tag (EST) clusters. An independent example in vitro validation of fibroblast transcriptome map data was performed through “Real-Time” reverse transcription polymerase chain reaction showing an excellent correlation coefficient (r = 0.93, p < 0.0001) with data obtained in silico. The availability of linear expression values for each gene allowed the testing of the gene dosage hypothesis of the expected 3:2 DS/normal ratio for Hsa21 as well as other human genes in DS, in addition to listing genes differentially expressed with statistical significance. Although a fraction of Hsa21 genes escapes dosage effects, Hsa21 genes are selectively over-expressed in DS samples compared to genes from other chromosomes, reflecting a decisive role in the pathogenesis of the syndrome. Finally, the analysis of chromosomal segments reveals a high prevalence of Hsa21 over-expressed segments over the other genomic regions, suggesting, in particular, a specific region on Hsa21 that appears to be frequently over-expressed (21q22). Our complete datasets are released as a new framework to investigate transcription in DS for individual genes as well as chromosomal segments in different cell types and tissues.

Background: A factory-calibrated flash glucose monitoring system (FGMS; FreeStyle Libre) recently was evaluated in dogs with uncomplicated diabetes mellitus. It is not known if this system is reliable during diabetic ketoacidosis (DKA). Objectives: To assess the performance of the FGMS in dogs with DKA and to determine the effect of severity of ketosis and acidosis, lactate concentration, body condition score (BCS), and time wearing the sensor on the accuracy of the device. Animals: Fourteen client-owned dogs with DKA. Methods: The interstitial glucose (IG) measurements were compared with blood glucose (BG) measurements obtained using a validated portable glucometer. The influence of changes in metabolic variables (β-hydroxybutyrate, pH, bicarbonate, and lactate) and the effect of BCS and time wearing on sensor performance were evaluated. Accuracy was determined by fulfillment of ISO15197:2013 criteria. Results: Metabolic variables, BCS, and time wearing were not associated with the accuracy of the sensor. Good agreement between IG measurements and BG was obtained both before and after DKA resolution (r = .88 and r = .93, respectively). Analytical accuracy was not achieved, whereas clinical accuracy was demonstrated with 100% and 99.6% of results in zones A + B of the Parkes consensus error grid analysis before and after DKA resolution, respectively. Conclusions and Clinical Importance: Changes in metabolic variables, BCS, and time wearing do not seem to affect agreement between IG and BG. Despite not fulfilling the ISO requirements, the FGMS provides clinically accurate estimates of BG in dogs with DKA.

The cytogenetic and molecular assessment of deletions, amplifications and rearrangements are key aspects in the diagnosis and therapy of cancer. Not only the initial evaluation and classification of the disease, but also the follow-up of the tumor rely on these laboratory approaches. The therapeutic choice can be guided by the results of the laboratory testing. Genetic deletions and/or amplifications directly affect the susceptibility or the resistance to specific therapies. In an era of personalized medicine, the correct and reliable molecular characterization of the disease, also during the therapeutic path, acquires a pivotal role. Molecular assays like multiplex ligation-dependent probe amplification and droplet digital PCR represent exceptional tools for a sensitive and reliable detection of genetic alterations and deserve a role in molecular oncology. In this manuscript we provide a technical comparison of these two approaches with the golden standard represented by fluorescence in situ hybridization. We also describe some relevant targets currently evaluated with these techniques in solid and hematologic tumors.

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