Pay-as-you-go data integration for bio-informatics

Scientific research in bio-informatics is often data-driven and supported by numerous biological databases. A biological database contains factual information collected from scientific experiments and computational analyses about areas including genomics, proteomics, metabolomics, microarray gene expression and phylogenetics. Information contained in biological databases includes gene function, structure, localization (both cellular and chromosomal), clinical effects of mutations as well as similarities of biological sequences and structures. In a growing number of research projects, bio-informatics researchers like to ask combined ques- tions, i.e., questions that require the combination of information from more than one database. We have observed that most bio-informatics papers do not go into detail on the integration of different databases. It has been observed that roughly 30% of all tasks in bio-informatics workflows are data transformation tasks, a lot of time is used to integrate these databases (shown by [1]). As data sources are created and evolve, many design decisions made by their creators. Not all of these choices are documented. Some of such choices are made implicitly based on experience or preference of the creator. Other choices are mandated by the purpose of the data source, as well as inherent data quality issues such as imprecision in measurements, or ongoing scientific debates. Integrating multiple data sources can be difficult. We propose to approach the time-consuming problem of integrating multiple biological databases through the principles of ‘pay-as-you-go’ and ‘good-is-good-enough’. By assisting the user in defin- ing a knowledge base of data mapping rules, schema alignment, trust information and other evidence we allow the user to focus on the work, and put in as little effort as is necessary for the integration to serve the purposes of the user. By using user feedback on query results and trust assessments, the integration can be improved upon over time. The research will be guided by a set of use cases. As the research is in its early stages, we have determined three use cases: Homologues, the representation and integration of groupings. Homology is the relationship between two characteristics that have descended, usually with divergence, from a common ancestral characteristic. A characteristic can be any genic, structural or behavioural feature of an organism Metabolomics integration, with a focus on the TCA cycle. The TCA cycle (also known as the citric acid cycle, or Krebs cycle) is used by aerobic organism to generate energy from the oxidation of carbohydrates, fats and proteins. Bibliography integration and improvement, the correction and expansion of citation databases. [1] I. Wassink. Work flows in life science. PhD thesis, University of Twente, Enschede, January 2010

Revisiting the formal foundation of Probabilistic Databases

One of the core problems in soft computing is dealing with uncertainty in data. In this paper, we revisit the formal foundation of a class of probabilistic databases with the purpose to (1) obtain data model independence, (2) separate metadata on uncertainty and probabilities from the raw data, (3) better understand aggregation, and (4) create more opportunities for optimization. The paper presents the formal framework and validates data model independence by showing how to a obtain probabilistic Datalog as well as a probabilistic relational algebra by applying the framework to their non-probabilistic counterparts. We conclude with a discussion on the latter three goals

Issues, Concepts and Methods Relating to the Identification of the Ethics of Emerging ICTs

Ethical issues of information and communication technologies (ICTs) are important because they can have significant effects on human liberty, happiness, their ability to lead a good life. They are also of functional interest because they can determine whether technologies are used and whether their positives potential can unfold

Incremental data uncertainty handling using evidence combination: a case study on maritime data reasoning

Semantic incompatibility is a conflict that occurs in the meanings of data. In this paper, we propose an approach for data cleaning by resolving semantic incompatibility. Our approach applies a dynamic and incremental enhancement of data quality. It checks the coherency/conflict of the newly recorded facts/relations against the existing ones. It reasons over the existing information and comes up with new discovered facts/relations. We choose maritime data cleaning as a validation scenario

LMO2 and IL2RG synergize in thymocytes to mimic the evolution of SCID-X1 gene therapy-associated T-cell leukaemia

The SCID-X1 disease occurs in males that lack a functional X-linked gene encoding the interleukin 2 receptor subunit gamma (IL2RG) and thus are immuno-deficient (reviewed in Rochman et al.). Gene therapy has been a success in curing SCID-X1 in patients receiving autologous CD34+-bone marrow cells infected with retroviruses expressing IL2RG. This treatment protocol has, however, produced adverse T-cell effects where clonal T-cell leukaemias arose, and four have insertional mutagenesis of the T-cell oncogene LMO2. LMO2 is a T-cell oncogene first discovered via chromosomal translocations in T-cell acute leukaemia (T-ALL) (reviewed in Chambers and Rabbitts). It is unclear if the T-cell neoplasias in the SCID-X1 patients are simply due to insertional activation of the LMO2 gene or reflect synergy between LMO2 and IL2RG. Further, the recurrent involvement of LMO2 in SCID-X1 leukaemias is puzzling as other T-cell oncogenes (for example, TAL1/SCL, HOX11 and LYL1) might equally have been targets. This suggests that specific properties of LMO2 per se are required in these adverse events. The oncogenic potential of IL2RG itself also remains controversial. Although it causes T-cell lymphomas in mice transplanted with virally transduced haematopoetic stem cells, other studies have indicated that IL2RG is not an oncogene. Here we provide evidence that synergy is required between LMO2 and IL2RG proteins specifically in the T-cell lineage to elicit neoplasias and that additional mutations are required such as Notch1 mutations like those in human T-ALL

Alveolar ridge augmentation and preservation

In this thesis, we address the effectiveness of barrier membranes in alveolar ridge augmentation and the effects of alveolar ridge preservation in early implant placement.<br/

RAD51 Is a Selective DNA Repair Target to Radiosensitize Glioma Stem Cells.

Patients with glioblastoma die from local relapse despite surgery and high-dose radiotherapy. Resistance to radiotherapy is thought to be due to efficient DNA double-strand break (DSB) repair in stem-like cells able to survive DNA damage and repopulate the tumor. We used clinical samples and patient-derived glioblastoma stem cells (GSCs) to confirm that the DSB repair protein RAD51 is highly expressed in GSCs, which are reliant on RAD51-dependent DSB repair after radiation. RAD51 expression and RAD51 foci numbers fall when these cells move toward astrocytic differentiation. In GSCs, the small-molecule RAD51 inhibitors RI-1 and B02 prevent RAD51 focus formation, reduce DNA DSB repair, and cause significant radiosensitization. We further demonstrate that treatment with these agents combined with radiation promotes loss of stem cells defined by SOX2 expression. This indicates that RAD51-dependent repair represents an effective and specific target in GSCs

HO-3867, a STAT3 inhibitor induces apoptosis by inactivation of STAT3 activity in BRCA1-mutated ovarian cancer cells

BRCA1 plays an important role in DNA damage and repair, homologous recombination, cell-cycle regulation and apoptosis. BRCA-mutated ovarian cancer often presents at an advanced stage, however, tend to have better response to platinum-based chemotherapy as compared with sporadic cases of epithelial ovarian cancer (EOC). In spite of this, most patients will develop a recurrence and eventually succumb to the disease. Preclinical studies are currently investigating natural compounds and their analogs for tumor-directed targets in ovarian cancer. The aim of this study is to investigate whether the STAT3 inhibitor HO-3867, a novel curcumin analog, has a therapeutic effect on BRCA1-mutated ovarian cancer. Our novel agent, HO-3867 and a commercial STAT3 inhibitor, STATTIC, significantly inhibited BRCA-mutated ovarian cancer cells in vitro in a dose- and time-dependent manner. BRCA-mutated ovarian cancer cells treated with HO-3867 exhibited a significant degree of apoptosis with elevated levels of cleaved caspase-3, caspase-7 and PARP. HO-3867 treatment induced more reactive oxygen species (ROS) in BRCA-mutated cells compared with wild-type cells, however, there was no increased ROS when benign ovarian surface epithelial cells were treated with HO-3867. BRCA1-mutated cancer cells had higher expression of Tyrosine-phosphorylated STAT3 (pTyr705) as compared with other STAT proteins. Furthermore, treatment of these cells with HO-3867 resulted in decreased expression of pTyr705 and its downstream targets cyclin D1, Bcl-2 and survivin. In addition, overexpression of STAT3 cDNA provided resistance to HO-3867-induced apoptosis. Our results show that HO-3867, a potent STAT3 inhibitor, may have a role as a biologically targeted agent for BRCA1-mutated cancers either as an adjunct to cytotoxic chemotherapy or as a single agent