Novel insights into the relationships between dendritic cell subsets in human and mouse revealed by genome-wide expression profiling

Genome-wide expression profiling of mouse and human leukocytes reveal conserved transcriptional programs of plasmacytoid or conventional dendritic cell subsets

Cell-specific proteome analyses of human bone marrow reveal molecular features of age-dependent functional decline

Diminishing potential to replace damaged tissues is a hallmark for ageing of somatic stem cells, but the mechanisms remain elusive. Here, we present proteome-wide atlases of age-associated alterations in human haematopoietic stem and progenitor cells (HPCs) and five other cell populations that constitute the bone marrow niche. For each, the abundance of a large fraction of the ~12,000 proteins identified is assessed in 59 human subjects from different ages. As the HPCs become older, pathways in central carbon metabolism exhibit features reminiscent of the Warburg effect, where glycolytic intermediates are rerouted towards anabolism. Simultaneously, altered abundance of early regulators of HPC differentiation reveals a reduced functionality and a bias towards myeloid differentiation. Ageing causes alterations in the bone marrow niche too, and diminishes the functionality of the pathways involved in HPC homing. The data represent a valuable resource for further analyses, and for validation of knowledge gained from animal models

De-identifying a public use microdata file from the Canadian national discharge abstract database

<p>Abstract</p> <p>Background</p> <p>The Canadian Institute for Health Information (CIHI) collects hospital discharge abstract data (DAD) from Canadian provinces and territories. There are many demands for the disclosure of this data for research and analysis to inform policy making. To expedite the disclosure of data for some of these purposes, the construction of a DAD public use microdata file (PUMF) was considered. Such purposes include: confirming some published results, providing broader feedback to CIHI to improve data quality, training students and fellows, providing an easily accessible data set for researchers to prepare for analyses on the full DAD data set, and serve as a large health data set for computer scientists and statisticians to evaluate analysis and data mining techniques. The objective of this study was to measure the probability of re-identification for records in a PUMF, and to de-identify a national DAD PUMF consisting of 10% of records.</p> <p>Methods</p> <p>Plausible attacks on a PUMF were evaluated. Based on these attacks, the 2008-2009 national DAD was de-identified. A new algorithm was developed to minimize the amount of suppression while maximizing the precision of the data. The acceptable threshold for the probability of correct re-identification of a record was set at between 0.04 and 0.05. Information loss was measured in terms of the extent of suppression and entropy.</p> <p>Results</p> <p>Two different PUMF files were produced, one with geographic information, and one with no geographic information but more clinical information. At a threshold of 0.05, the maximum proportion of records with the diagnosis code suppressed was 20%, but these suppressions represented only 8-9% of all values in the DAD. Our suppression algorithm has less information loss than a more traditional approach to suppression. Smaller regions, patients with longer stays, and age groups that are infrequently admitted to hospitals tend to be the ones with the highest rates of suppression.</p> <p>Conclusions</p> <p>The strategies we used to maximize data utility and minimize information loss can result in a PUMF that would be useful for the specific purposes noted earlier. However, to create a more detailed file with less information loss suitable for more complex health services research, the risk would need to be mitigated by requiring the data recipient to commit to a data sharing agreement.</p

Single cell dissection of plasma cell heterogeneity in symptomatic and asymptomatic myeloma

Multiple myeloma, a plasma cell malignancy, is the second most common blood cancer. Despite extensive research, disease heterogeneity is poorly characterized, hampering efforts for early diagnosis and improved treatments. Here, we apply single cell RNA sequencing to study the heterogeneity of 40 individuals along the multiple myeloma progression spectrum, including 11 healthy controls, demonstrating high interindividual variability that can be explained by expression of known multiple myeloma drivers and additional putative factors. We identify extensive subclonal structures for 10 of 29 individuals with multiple myeloma. In asymptomatic individuals with early disease and in those with minimal residual disease post-treatment, we detect rare tumor plasma cells with molecular characteristics similar to those of active myeloma, with possible implications for personalized therapies. Single cell analysis of rare circulating tumor cells allows for accurate liquid biopsy and detection of malignant plasma cells, which reflect bone marrow disease. Our work establishes single cell RNA sequencing for dissecting blood malignancies and devising detailed molecular characterization of tumor cells in symptomatic and asymptomatic patients

Towards Analysing Cooperative Intelligent Transport System Security Data

International audienc

Use of WinEpiFn© to assess the quality and the usable proportion of belgian small douglas fir timbers for glulam squares production: preliminary results

info:eu-repo/semantics/publishe