Parallel implementation of Multilevel BDDC

In application of the Balancing Domain Decomposition by Constraints (BDDC) to a case with many substructures, solving the coarse problem exactly becomes the bottleneck which spoils scalability of the solver. However, it is straightforward for BDDC to substitute the exact solution of the coarse problem by another step of BDDC method with subdomains playing the role of elements. In this way, the algorithm of three-level BDDC method is obtained. If this approach is applied recursively, multilevel BDDC method is derived. We present a detailed description of a recently developed parallel implementation of this algorithm. The implementation is applied to an engineering problem of linear elasticity and a benchmark problem of Stokes flow in a cavity. Results by the multilevel approach are compared to those by the standard (two-level) BDDC method.Comment: 9 pages, 2 figures, 3 table

Valproic acid inhibits adhesion of vincristine- and cisplatin-resistant neuroblastoma tumour cells to endothelium

Drug resistance to chemotherapy is often associated with increased malignancy in neuroblastoma (NB). In pursuit of alternative treatments for chemoresistant tumour cells, we tested the response of multidrug-resistant SKNSH and of vincristine (VCR)-, doxorubicin (DOX)-, or cisplatin (CDDP)-resistant UKF-NB-2, UKF-NB-3 or UKF-NB-6 NB tumour cell lines to valproic acid (VPA), a differentiation inducer currently in clinical trials. Drug resistance caused elevated NB adhesion (UKF-NB-2VCR, UKF-NB-2DOX, UKF-NB-2CDDP, UKF-NB-3VCR, UKF-NB-3CDDP, UKF-NB-6VCR, UKF-NB-6CDDP) to an endothelial cell monolayer, accompanied by downregulation of the adhesion receptor neural cell adhesion molecule (NCAM). Based on the UKF-NB-3 model, N-myc proteins were enhanced in UKF-NB-3VCR and UKF-NB-3CDDP, compared to the drug naïve controls. p73 was diminished, whereas the p73 isoform deltaNp73 was upregulated in UKF-NB-3VCR and UKF-NB-3CDDP. Valproic acid blocked adhesion of UKF-NB-3VCR and UKF-NB-3CDDP, but not of UKF-NB-3DOX, and induced the upregulation of NCAM surface expression, NCAM protein content and NCAM coding mRNA. Valproic acid diminished N-myc and enhanced p73 protein level, coupled with downregulation of deltaNp73 in UKF-NB-3VCR and UKF-NB-3CDDP. Valproic acid also reverted enhanced adhesion properties of drug-resistant UKF-NB-2, UKF-NB-6 and SKNSH cells, and therefore may provide an alternative approach to the treatment of drug-resistant NB by blocking invasive processes

Expression of Foxp3 in colorectal cancer but not in Treg cells correlates with disease progression in patients with colorectal cancer

Background: Regulatory T cells (Treg) expressing the transcription factor forkhead-box protein P3 (Foxp3) have been identified to counteract anti-tumor immune responses during tumor progression. Besides, Foxp3 presentation by cancer cells itself may also allow them to evade from effector T-cell responses, resulting in a survival benefit of the tumor. For colorectal cancer (CRC) the clinical relevance of Foxp3 has not been evaluated in detail. Therefore the aim of this study was to study its impact in colorectal cancer (CRC). Methods and Findings: Gene and protein analysis of tumor tissues from patients with CRC was performed to quantify the expression of Foxp3 in tumor infiltrating Treg and colon cancer cells. The results were correlated with clinicopathological parameters and patients overall survival. Serial morphological analysis demonstrated Foxp3 to be expressed in cancer cells. High Foxp3 expression of the cancer cells was associated with poor prognosis compared to patients with low Foxp3 expression. In contrast, low and high Foxp3 level in tumor infiltrating Treg cells demonstrated no significant differences in overall patient survival. Conclusions: Our findings strongly suggest that Foxp3 expression mediated by cancer cells rather than by Treg cells contribute to disease progression

Class I histone deacetylases 1, 2 and 3 are highly expressed in renal cell cancer

Background Enhanced activity of histone deacetylases (HDAC) is associated with more aggressive tumour behaviour and tumour progression in various solid tumours. The over-expression of these proteins and their known functions in malignant neoplasms has led to the development of HDAC inhibitors (HDI) as new anti-neoplastic drugs. However, little is known about HDAC expression in renal cell cancer. Methods We investigated the expression of HDAC 1, 2 and 3 in 106 renal cell carcinomas and corresponding normal renal tissue by immunohistochemistry on tissue micro arrays and correlated expression data with clinico-pathological parameters including patient survival. Results Almost 60% of renal cell carcinomas expressed the HDAC isoforms 1 and 2. In contrast, HDAC 3 was only detected in 13% of all renal tumours, with particular low expression rates in the clear cell subtype. HDAC 3 was significantly higher expressed in pT1/2 tumours in comparison to pT3/4 tumours. Expression of class I HDAC isoforms correlated with each other and with the proliferative activity of the tumours. We found no prognostic value of the expression of any of the HDAC isoforms in this tumour entity. Conclusion Class I HDAC isoforms 1 and 2 are highly expressed in renal cell cancer, while HDAC 3 shows low, histology dependent expression rates. These unexpected differences in the expression patterns suggests alternative regulatory mechanisms of class I HDACs in renal cell cancer and should be taken into account when trials with isoform selective HDI are being planned. Whether HDAC expression in renal cancers is predictive of responsiveness for HDI will have to be tested in further studies

Combining the receptor tyrosine kinase inhibitor AEE788 and the mammalian target of rapamycin (mTOR) inhibitor RAD001 strongly inhibits adhesion and growth of renal cell carcinoma cells

Background Treatment options for metastatic renal cell carcinoma (RCC) are limited due to resistance to chemo- and radiotherapy. The development of small-molecule multikinase inhibitors have now opened novel treatment options. The influence of the receptor tyrosine kinase inhibitor AEE788, applied alone or combined with the mammalian target of rapamycin (mTOR) inhibitor RAD001, on RCC cell adhesion and proliferation in vitro has been evaluated. Methods RCC cell lines Caki-1, KTC-26 or A498 were treated with various concentrations of RAD001 or AEE788 and tumor cell proliferation, tumor cell adhesion to vascular endothelial cells or to immobilized extracellular matrix proteins (laminin, collagen, fibronectin) evaluated. The anti-tumoral potential of RAD001 combined with AEE788 was also investigated. Both, asynchronous and synchronized cell cultures were used to subsequently analyze drug induced cell cycle manipulation. Analysis of cell cycle regulating proteins was done by western blotting. Results RAD001 or AEE788 reduced adhesion of RCC cell lines to vascular endothelium and diminished RCC cell binding to immobilized laminin or collagen. Both drugs blocked RCC cell growth, impaired cell cycle progression and altered the expression level of the cell cycle regulating proteins cdk2, cdk4, cyclin D1, cyclin E and p27. The combination of AEE788 and RAD001 resulted in more pronounced RCC growth inhibition, greater rates of G0/G1 cells and lower rates of S-phase cells than either agent alone. Cell cycle proteins were much more strongly altered when both drugs were used in combination than with single drug application. The synergistic effects were observed in an asynchronous cell culture model, but were more pronounced in synchronous RCC cell cultures. Conclusions Potent anti-tumoral activitites of the multikinase inhibitors AEE788 or RAD001 have been demonstrated. Most importantly, the simultaneous use of both AEE788 and RAD001 offered a distinct combinatorial benefit and thus may provide a therapeutic advantage over either agent employed as a monotherapy for RCC treatment

Effects of the histone deacetylase inhibitor valproic acid on Notch signalling in human neuroblastoma cells

Neuroblastoma (NB), a sympathetically derived childhood tumour, shows characteristics of neuronal precursor cells, suggesting a halted differentiation process. We have previously shown that the Notch signalling cascade, a key player during normal neurogenesis, also might be involved in NB differentiation. Valproic acid (VPA), a well-tolerated antiepileptic drug, has been shown to induce differentiation and cell death of NB cells, possibly associated with its recently described HDAC inhibiting activity. Stimulation of NB cells with VPA led to increased cell death and phenotypic changes associated with differentiation, that is, neurite extension and upregulation of neuronal markers. VPA treatment also led to an activated Notch signalling cascade as shown by increased levels of intracellular Notch-1 and Hes-1, mimicking the initial phase of induced differentiation. These results reinforce that VPA potentially could be used in differentiation therapy of NB and that the effects in part could be a consequence of interference with the Notch signalling cascade

Molecular targeting of prostate cancer cells by a triple drug combination down-regulates integrin driven adhesion processes, delays cell cycle progression and interferes with the cdk-cyclin axis

Background: Single drug use has not achieved satisfactory results in the treatment of prostate cancer, despite application of increasingly widespread targeted therapeutics. In the present study, the combined impact of the mammalian target of rapamycin (mTOR)-inhibitor RAD001, the dual EGFr and VGEFr tyrosine kinase inhibitor AEE788 and the histone deacetylase (HDAC)-inhibitor valproic acid (VPA) on prostate cancer growth and adhesion in vitro was investigated. Methods: PC-3, DU-145 and LNCaP cells were treated with RAD001, AEE788 or VPA or with a RAD-AEE-VPA combination. Tumor cell growth, cell cycle progression and cell cycle regulating proteins were then investigated by MTT-assay, flow cytometry and western blotting, respectively. Furthermore, tumor cell adhesion to vascular endothelium or to immobilized extracellular matrix proteins as well as migratory properties of the cells was evaluated, and integrin alpha and beta subtypes were analyzed. Finally, effects of drug treatment on cell signaling pathways were determined. Results: All drugs, separately applied, reduced tumor cell adhesion, migration and growth. A much stronger anti-cancer effect was evoked by the triple drug combination. Particularly, cdk1, 2 and 4 and cyclin B were reduced, whereas p27 was elevated. In addition, simultaneous application of RAD001, AEE788 and VPA altered the membranous, cytoplasmic and gene expression pattern of various integrin alpha and beta subtypes, reduced integrin-linked kinase (ILK) and deactivated focal adhesion kinase (FAK). Signaling analysis revealed that EGFr and the downstream target Akt, as well as p70S6k was distinctly modified in the presence of the drug combination. Conclusions: Simultaneous targeting of several key proteins in prostate cancer cells provides an advantage over targeting a single pathway. Since strong anti-tumor properties became evident with respect to cell growth and adhesion dynamics, the triple drug combination might provide progress in the treatment of advanced prostate cancer

Histone deacetylase inhibitors valproate and trichostatin A are toxic to neuroblastoma cells and modulate cytochrome P450 1A1, 1B1 and 3A4 expression in these cells

Histone deacetylase inhibitors such as valproic acid (VPA) and trichostatin A (TSA) were shown to exert antitumor activity. Here, the toxicity of both drugs to human neuroblastoma cell lines was investigated using MTT test, and IC50 values for both compounds were determined. Another target of this work was to evaluate the effects of both drugs on expression of cytochrome P450 (CYP) 1A1, 1B1 and 3A4 enzymes, which are known to be expressed in neuroblastoma cells. A malignant subset of neuroblastoma cells, so-called N-type cells (UKF-NB-3 cells) and the more benign S-type neuroblastoma cells (UKF-NB-4 and SK-N-AS cell lines) were studied from both two points of view. VPA and TSA inhibited the growth of neuroblastoma cells in a dose-dependent manner. The IC50 values ranging from 1.0 to 2.8 mM and from 69.8 to 129.4 nM were found for VPA and TSA, respectively. Of the neuroblastoma tested here, the N-type UKF-NB-3 cell line was the most sensitive to both drugs. The different effects of VPA and TSA were found on expression of CYP1A1, 1B1 and 3A4 enzymes in individual neuroblastoma cells tested in the study. Protein expression of all these CYP enzymes in the S-type SK-N-AS cell line was not influenced by either of studied drugs. On the contrary, in another S-type cell line, UKF-NB-4, VPA and TSA induced expression of CYP1A1, depressed levels of CYP1B1 and had no effect on expression levels of CYP3A4 enzyme. In the N-type UKF-NB-3 cell line, the expression of CYP1A1 was strongly induced, while that of CYP1B1 depressed by VPA and TSA. VPA also induced the expression of CYP3A4 in this neuroblastoma cell line

Benchmarking natural-language parsers for biological applications using dependency graphs

BACKGROUND: Interest is growing in the application of syntactic parsers to natural language processing problems in biology, but assessing their performance is difficult because differences in linguistic convention can falsely appear to be errors. We present a method for evaluating their accuracy using an intermediate representation based on dependency graphs, in which the semantic relationships important in most information extraction tasks are closer to the surface. We also demonstrate how this method can be easily tailored to various application-driven criteria. RESULTS: Using the GENIA corpus as a gold standard, we tested four open-source parsers which have been used in bioinformatics projects. We first present overall performance measures, and test the two leading tools, the Charniak-Lease and Bikel parsers, on subtasks tailored to reflect the requirements of a system for extracting gene expression relationships. These two tools clearly outperform the other parsers in the evaluation, and achieve accuracy levels comparable to or exceeding native dependency parsers on similar tasks in previous biological evaluations. CONCLUSION: Evaluating using dependency graphs allows parsers to be tested easily on criteria chosen according to the semantics of particular biological applications, drawing attention to important mistakes and soaking up many insignificant differences that would otherwise be reported as errors. Generating high-accuracy dependency graphs from the output of phrase-structure parsers also provides access to the more detailed syntax trees that are used in several natural-language processing techniques