Model Order Reduction for Rotating Electrical Machines

The simulation of electric rotating machines is both computationally expensive and memory intensive. To overcome these costs, model order reduction techniques can be applied. The focus of this contribution is especially on machines that contain non-symmetric components. These are usually introduced during the mass production process and are modeled by small perturbations in the geometry (e.g., eccentricity) or the material parameters. While model order reduction for symmetric machines is clear and does not need special treatment, the non-symmetric setting adds additional challenges. An adaptive strategy based on proper orthogonal decomposition is developed to overcome these difficulties. Equipped with an a posteriori error estimator the obtained solution is certified. Numerical examples are presented to demonstrate the effectiveness of the proposed method

A simple algebraic cancer equation: calculating how cancers may arise with normal mutation rates

<p>Abstract</p> <p>Background</p> <p>The purpose of this article is to present a relatively easy to understand cancer model where transformation occurs when the first cell, among many at risk within a colon, accumulates a set of driver mutations. The analysis of this model yields a simple algebraic equation, which takes as inputs the number of stem cells, mutation and division rates, and the number of driver mutations, and makes predictions about cancer epidemiology.</p> <p>Methods</p> <p>The equation [<it>p </it>= 1 - (1 - (1 - (1 - <it>u</it>)^<it>d</it>)^<it>k</it>)^{<it>Nm </it>}] calculates the probability of cancer (<it>p</it>) and contains five parameters: the number of divisions (<it>d</it>), the number of stem cells (<it>N </it>× <it>m</it>), the number of critical rate-limiting pathway driver mutations (<it>k</it>), and the mutation rate (<it>u</it>). In this model progression to cancer "starts" at conception and mutations accumulate with cell division. Transformation occurs when a critical number of rate-limiting pathway mutations first accumulates within a single stem cell.</p> <p>Results</p> <p>When applied to several colorectal cancer data sets, parameter values consistent with crypt stem cell biology and normal mutation rates were able to match the increase in cancer with aging, and the mutation frequencies found in cancer genomes. The equation can help explain how cancer risks may vary with age, height, germline mutations, and aspirin use. APC mutations may shorten pathways to cancer by effectively increasing the numbers of stem cells at risk.</p> <p>Conclusions</p> <p>The equation illustrates that age-related increases in cancer frequencies may result from relatively normal division and mutation rates. Although this equation does not encompass all of the known complexity of cancer, it may be useful, especially in a teaching setting, to help illustrate relationships between small and large cancer features.</p

AV-65, a novel Wnt/β-catenin signal inhibitor, successfully suppresses progression of multiple myeloma in a mouse model

Multiple myeloma (MM) is a malignant neoplasm of plasma cells. Although new molecular targeting agents against MM have been developed based on the better understanding of the underlying pathogenesis, MM still remains an incurable disease. We previously demonstrated that β-catenin, a downstream effector in the Wnt pathway, is a potential target in MM using RNA interference in an in vivo experimental mouse model. In this study, we have screened a library of more than 100 000 small-molecule chemical compounds for novel Wnt/β-catenin signaling inhibitors using a high-throughput transcriptional screening technology. We identified AV-65, which diminished β-catenin protein levels and T-cell factor transcriptional activity. AV-65 then decreased c-myc, cyclin D1 and survivin expression, resulting in the inhibition of MM cell proliferation through the apoptotic pathway. AV-65 treatment prolonged the survival of MM-bearing mice. These findings indicate that this compound represents a novel and attractive therapeutic agent against MM. This study also illustrates the potential of high-throughput transcriptional screening to identify candidates for anticancer drug discovery

Use of Aspirin postdiagnosis improves survival for colon cancer patients

Background: The preventive role of non-steroid anti-inflammatory drugs (NSAIDs) and aspirin, in particular, on colorectal cancer is well established. More recently, it has been suggested that aspirin may also have a therapeutic role. Aim of the present observational population-based study was to assess the therapeutic effect on overall survival of aspirin/NSAIDs as adjuvant treatment used after the diagnosis of colorectal cancer patients. Methods: Data concerning prescriptions were obtained from PHARMO record linkage systems and all patients diagnosed with colorectal cancer (1998-2007) were selected from the Eindhoven Cancer Registry (population-based cancer registry). Aspirin/NSAID use was classified as none, prediagnosis and postdiagnosis and only postdiagnosis. Patients were defined as non-user of aspirin/NSAIDs from the date of diagnosis of the colorectal cancer to the date of first use of aspirin or NSAIDs and user from first use to the end of follow-up. Poisson regression was performed with user status as time-varying exposure.Results:In total, 1176 (26%) patients were non-users, 2086 (47%) were prediagnosis and postdiagnosis users and 1219 (27%) were only postdiagnosis users (total n=4481). Compared with non-users, a survival gain was observed for aspirin users; the adjusted rate ratio (RR) was 0.77 (95% confidence interval (CI) 0.63-0.95; P=0.015). Stratified for colon and rectal, the survival gain was only present in colon cancer (adjusted RR 0.65 (95%CI 0.50-0.84; P=0.001)). For frequent users survival gain was larger (adjusted RR 0.61 (95%CI 0.46-0.81; P=0.001). In rectal cancer, aspirin use was not associated with survival (adjusted RR 1.10 (95%CI 0.79-1.54; P=0.6). The NSAIDs use was associated with decreased survival (adjusted RR 1.93 (95%CI 1.70-2.20; P<0.001). Conclusion: Aspirin use initiated or continued after diagnosis of colon cancer is associated with a lower risk of overall mortality. These findings strongly support initiation of a placebo-controlled trial that investigates the role of aspirin as adjuvant treatment in colon cancer patients

Sulindac Sulfide Reverses Aberrant Self-Renewal of Progenitor Cells Induced by the AML-Associated Fusion Proteins PML/RARα and PLZF/RARα

Chromosomal translocations can lead to the formation of chimeric genes encoding fusion proteins such as PML/RARα, PLZF/RARα, and AML-1/ETO, which are able to induce and maintain acute myeloid leukemia (AML). One key mechanism in leukemogenesis is increased self renewal of leukemic stem cells via aberrant activation of the Wnt signaling pathway. Either X-RAR, PML/RARα and PLZF/RARα or AML-1/ETO activate Wnt signaling by upregulating γ-catenin and β-catenin. In a prospective study, a lower risk of leukemia was observed with aspirin use, which is consistent with numerous studies reporting an inverse association of aspirin with other cancers. Furthermore, a reduction in leukemia risk was associated with use of non-steroidal anti-inflammatory drug (NSAID), where the effects on AML risk was FAB subtype-specific. To better investigate whether NSAID treatment is effective, we used Sulindac Sulfide in X-RARα-positive progenitor cell models. Sulindac Sulfide (SSi) is a derivative of Sulindac, a NSAID known to inactivate Wnt signaling. We found that SSi downregulated both β-catenin and γ-catenin in X-RARα-expressing cells and reversed the leukemic phenotype by reducing stem cell capacity and increasing differentiation potential in X-RARα-positive HSCs. The data presented herein show that SSi inhibits the leukemic cell growth as well as hematopoietic progenitors cells (HPCs) expressing PML/RARα, and it indicates that Sulindac is a valid molecular therapeutic approach that should be further validated using in vivo leukemia models and in clinical settings

Absent in Melanoma 2 (AIM2) is an important mediator of interferon-dependent and -independent HLA-DRA and HLA-DRB gene expression in colorectal cancers

Absent in Melanoma 2 (AIM2) is a member of the HIN-200 family of hematopoietic, IFN-inducible, nuclear proteins, associated with both, infection defense and tumor pathology. Recently, AIM2 was found to act as a DNA sensor in innate immunity. In addition, we and others have previously demonstrated a high frequency of AIM2-alterations in microsatellite unstable (MSI-H) tumors. To further elucidate AIM2 function in colorectal tumors, we here addressed AIM2-responsive target genes by microarray based gene expression profiling of 22 244 human genes. A total of 111 transcripts were significantly upregulated, whereas 80 transcripts turned out to be significantly downregulated in HCT116 cells, constitutively expressing AIM2, compared with AIM2-negative cells. Among the upregulated genes that were validated by quantitative PCR and western blotting we recognized several interferon-stimulated genes (ISGs: IFIT1, IFIT2, IFIT3, IFI6, IRF7, ISG15, HLA-DRA, HLA-DRB, TLR3 and CIITA), as well as genes involved in intercellular adhesion and matrix remodeling. Expression of ISGs correlated with expression of AIM2 in 10 different IFN-γ treated colorectal cancer cell lines. Moreover, small interfering RNA-mediated knock-down of AIM2 resulted in reduced expression of HLA-DRA, HLA-DRB and CIITA in IFN-γ-treated cells. IFN-γ independent induction of HLA-DR genes and their encoded proteins was also demonstrated upon doxycyclin-regulated transient induction of AIM2. Luciferase reporter assays revealed induction of the HLA-DR promoter upon AIM2 transfection in different cell lines. STAT-signaling was not involved in IFN-γ independent induction of ISGs, arguing against participation of cytokines released in an autostimulating manner. Our data indicate that AIM2 mediates both IFN-γ dependent and independent induction of several ISGs, including genes encoding the major histocompatibility complex (MHC) class II antigens HLA-DR-α and -β. This suggests a novel role of the IFN/AIM2/ISG cascade likewise in cancer cells

Research of working area development parameters in conditions of deep steep deposit finalizing

Отримано формули розрахунку об’єму запасів корисних копалин в приконтурній та глибинній зоні. Встановлено характер впливу параметрів доробки глибоких крутоспадних родовищ відкритим способом на доцільне положення поточних та проектних контурів кар’єру. Встановлено, що найменший середній коефіцієнт розкриву досягається при мінімальному значенні суми обсягів корисної копалини приконтурної зони лежачого і висячого боків покладу в проектному положенні. Найменший поточний коефіцієнт розкриву досягається при мінімальному значенні суми обсягів корисної копалини приконтурної зони лежачого і висячого боків покладу, а також робочого борту кар'єру в поточному положенні

PESCADOR, a web-based tool to assist text-mining of biointeractions extracted from PubMed queries

BACKGROUND: Biological function is greatly dependent on the interactions of proteins with other proteins and genes. Abstracts from the biomedical literature stored in the NCBI's PubMed database can be used for the derivation of interactions between genes and proteins by identifying the co-occurrences of their terms. Often, the amount of interactions obtained through such an approach is large and may mix processes occurring in different contexts. Current tools do not allow studying these data with a focus on concepts of relevance to a user, for example, interactions related to a disease or to a biological mechanism such as protein aggregation. RESULTS: To help the concept-oriented exploration of such data we developed PESCADOR, a web tool that extracts a network of interactions from a set of PubMed abstracts given by a user, and allows filtering the interaction network according to user-defined concepts. We illustrate its use in exploring protein aggregation in neurodegenerative disease and in the expansion of pathways associated to colon cancer. CONCLUSIONS: PESCADOR is a platform independent web resource available at: http://cbdm.mdc-berlin.de/tools/pescador