Supporting annotated Relations

Annotations and provenance data play a key role in understanding and curating scientific databases. However, current database management systems lack adequate support for managing annotations and provenance data including: (1) handling annotations at multiple granularities, i.e., at the table, tuple, column and cell levels, (2) propagating annotations along with query answers, (3) querying data based on their annotations, and (4) providing declarative ways to add, archive, and restore annotations. In this paper, we propose to treat multi-granular annotations and provenance as first class objects inside the database. We introduce the concept of "Annotated Relations " along with new operators and extended semantics for the standard relational oDerators in support of annotated relations. We present an expressive and declarative extension to SQL to support the processing and querying of annotated tables. We study several schemes for storing and indexing annotations based on annotation granularity and annotation size. Extensions to PostgreSQL are introduced to support annotated relations and implementation challenges are discussed. Performance analysis illustrates the potential of annotated relations as they achieve up to an order-of-magnitude reduction in storage and I/O costs.

Assessing the expression of differentiation antagonizing non-protein coding RNA (DANCR) in newly diagnosed Egyptian acute myeloid leukemia patients

Abstract Background Role of Long non-coding RNAs in cancer research in the recent years have been highlighted with evidence to their involvement in cancer disease pathogenesis and progression. One of these emerging long non-coding RNAs is differentiation antagonizing non-protein coding RNA (DANCR). DANCR distinct expression in different cancers and implication in tumor signaling pathways made it a promising therapeutic target for cancer. The purpose of this study was to evaluate DANCR expression in de novo acute myeloid leukemia (AML) patients and to assess DANCR expression in relation to cytogenetics and French American British (FAB) AML classification as well as correlate DANCR expression with patients’ response to treatment. The present study included 60 newly diagnosed AML patients and 30 healthy subjects as controls. Relative DANCR expression was done using real time qPCR method. Results DANCR was significantly downregulated in AML patients compared to controls (p = 0.038). In addition, DANCR showed significantly lower expression in M4 and M5 compared to M0, M1, and M2 groups (p < 0.001). Furthermore, DANCR expression was significantly downregulated in cytogenetically normal AML patients compared to the controls (p = 0.011). Conclusion Significant downregulation of DANCR in AML suggests a potential tumor suppressor role and variable expression of DANCR among AML subtypes suggests that DANCR action may be different among AML subtypes. Also, M1 subtype patients with higher DANCR expression were less refractory to treatment and therefore less resistant to cytarabine

Smartphones as Distributed Witnesses for Digital Forensics

Part 3: Mobile Device ForensicsInternational audienceSmartphones have become an integral part of people’s lives. Their wide range of capabilities and support of diverse applications result in a wealth of data being stored in smartphone memory. Although tools are available to extract and view the data stored in smartphones, no comprehensive process exists for event reconstruction using the extracted data. Data in smartphones is typically stored in SQLite databases and can, therefore, be easily transformed. To perform event reconstruction, multiple SQLite databases have to be integrated. This paper proposes a novel mobile event reconstruction process that allows for event reconstruction by querying the integrated SQLite databases collected from multiple smartphones. The process can create detailed accounts of the events that took place before, during and after an incident