998 resultados para Forssman, Berthold: Wörterbuch Estnisch-Deutsch
Resumo:
Locally advanced prostate cancer (LAPC) is a heterogeneous entity usually embracing T3-4 and/or pelvic lymph-node-positive disease in the absence of established metastases. Outcomes for LAPC with single therapies have traditionally been poor, leading to the investigation of adjuvant therapies. Prostate cancer is a hormonally sensitive tumour, which usually responds to pharmacological manipulation of the androgen receptor or its testosterone-related ligands. As such, androgen deprivation therapy (ADT) has become an important adjuvant strategy for the treatment of LAPC, particularly for patients managed primarily with radiotherapy. Such results have generally not been replicated in surgical patients. With increased use of ADT has come improved awareness of the numerous toxicities associated with long-term use of these agents, as well as the development of strategies for minimizing ADT exposure and actively managing adverse effects. Several trials are exploring agents to enhance radiation cell sensitivity as well as the application of adjuvant docetaxel, an agent with proven efficacy in the metastatic, castrate-resistant setting. The recent work showing activity of cabazitaxel, sipuleucel-T and abiraterone for castrate-resistant disease in the post-docetaxel setting will see these agents investigated in conjunction with definitive surgery and radiotherapy.
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With six targeted agents approved (sorafenib, sunitinib, temsirolimus, bevacizumab [+interferon], everolimus and pazopanib), many patients with metastatic renal cell carcinoma (mRCC) will receive multiple therapies. However, the optimum sequencing approach has not been defined. A group of European experts reviewed available data and shared their clinical experience to compile an expert agreement on the sequential use of targeted agents in mRCC. To date, there are few prospective studies of sequential therapy. The mammalian target of rapamycin (mTOR) inhibitor everolimus was approved for use in patients who failed treatment with inhibitors of vascular endothelial growth factor (VEGF) and VEGF receptors (VEGFR) based on the results from a Phase III placebo-controlled study; however, until then, the only licensed agents across the spectrum of mRCC were VEGF(R) inhibitors (sorafenib, sunitinib and bevacizumab + interferon), and as such, a large body of evidence has accumulated regarding their use in sequence. Data show that sequential use of VEGF(R) inhibitors may be an effective treatment strategy to achieve prolonged clinical benefit. The optimal place of each targeted agent in the treatment sequence is still unclear, and data from large prospective studies are needed. The Phase III AXIS study of second-line sorafenib vs. axitinib (including post-VEGF(R) inhibitors) has completed, but the data are not yet published; other ongoing studies include the Phase III SWITCH study of sorafenib-sunitinib vs. sunitinib-sorafenib (NCT00732914); the Phase III 404 study of temsirolimus vs. sorafenib post-sunitinib (NCT00474786) and the Phase II RECORD 3 study of sunitinib-everolimus vs. everolimus-sunitinib (NCT00903175). Until additional data are available, consideration of patient response and tolerability to treatment may facilitate current decision-making regarding when to switch and which treatment to switch to in real-life clinical practice.
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Spatial data analysis mapping and visualization is of great importance in various fields: environment, pollution, natural hazards and risks, epidemiology, spatial econometrics, etc. A basic task of spatial mapping is to make predictions based on some empirical data (measurements). A number of state-of-the-art methods can be used for the task: deterministic interpolations, methods of geostatistics: the family of kriging estimators (Deutsch and Journel, 1997), machine learning algorithms such as artificial neural networks (ANN) of different architectures, hybrid ANN-geostatistics models (Kanevski and Maignan, 2004; Kanevski et al., 1996), etc. All the methods mentioned above can be used for solving the problem of spatial data mapping. Environmental empirical data are always contaminated/corrupted by noise, and often with noise of unknown nature. That's one of the reasons why deterministic models can be inconsistent, since they treat the measurements as values of some unknown function that should be interpolated. Kriging estimators treat the measurements as the realization of some spatial randomn process. To obtain the estimation with kriging one has to model the spatial structure of the data: spatial correlation function or (semi-)variogram. This task can be complicated if there is not sufficient number of measurements and variogram is sensitive to outliers and extremes. ANN is a powerful tool, but it also suffers from the number of reasons. of a special type ? multiplayer perceptrons ? are often used as a detrending tool in hybrid (ANN+geostatistics) models (Kanevski and Maignank, 2004). Therefore, development and adaptation of the method that would be nonlinear and robust to noise in measurements, would deal with the small empirical datasets and which has solid mathematical background is of great importance. The present paper deals with such model, based on Statistical Learning Theory (SLT) - Support Vector Regression. SLT is a general mathematical framework devoted to the problem of estimation of the dependencies from empirical data (Hastie et al, 2004; Vapnik, 1998). SLT models for classification - Support Vector Machines - have shown good results on different machine learning tasks. The results of SVM classification of spatial data are also promising (Kanevski et al, 2002). The properties of SVM for regression - Support Vector Regression (SVR) are less studied. First results of the application of SVR for spatial mapping of physical quantities were obtained by the authorsin for mapping of medium porosity (Kanevski et al, 1999), and for mapping of radioactively contaminated territories (Kanevski and Canu, 2000). The present paper is devoted to further understanding of the properties of SVR model for spatial data analysis and mapping. Detailed description of the SVR theory can be found in (Cristianini and Shawe-Taylor, 2000; Smola, 1996) and basic equations for the nonlinear modeling are given in section 2. Section 3 discusses the application of SVR for spatial data mapping on the real case study - soil pollution by Cs137 radionuclide. Section 4 discusses the properties of the modelapplied to noised data or data with outliers.
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Leena Kolehmainen: Saksan ja suomen verbien morfologiaa, fraseologiaa, semantiikkaa ja valenssinmuutoksia ; Annekatrin Kaivapalu: Lähdekieli kielenoppimisen apuna ; Katja Huumo: Tieteen suomen suuntaviivat ; Paula Sjöblom: Nimellä on merkitystä ; Minna Sääskilahti: Vapise, kuningas alkoholi. Alkoholivalistuksen tekstilaji ja sen muuttuminen vuosien 1755 ja 2001 välisenä aikana
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Down syndrome (DS) is characterized by extensive phenotypic variability, with most traits occurring in only a fraction of affected individuals. Substantial gene-expression variation is present among unaffected individuals, and this variation has a strong genetic component. Since DS is caused by genomic-dosage imbalance, we hypothesize that gene-expression variation of human chromosome 21 (HSA21) genes in individuals with DS has an impact on the phenotypic variability among affected individuals. We studied gene-expression variation in 14 lymphoblastoid and 17 fibroblast cell lines from individuals with DS and an equal number of controls. Gene expression was assayed using quantitative real-time polymerase chain reaction on 100 and 106 HSA21 genes and 23 and 26 non-HSA21 genes in lymphoblastoid and fibroblast cell lines, respectively. Surprisingly, only 39% and 62% of HSA21 genes in lymphoblastoid and fibroblast cells, respectively, showed a statistically significant difference between DS and normal samples, although the average up-regulation of HSA21 genes was close to the expected 1.5-fold in both cell types. Gene-expression variation in DS and normal samples was evaluated using the Kolmogorov-Smirnov test. According to the degree of overlap in expression levels, we classified all genes into 3 groups: (A) nonoverlapping, (B) partially overlapping, and (C) extensively overlapping expression distributions between normal and DS samples. We hypothesize that, in each cell type, group A genes are the most dosage sensitive and are most likely involved in the constant DS traits, group B genes might be involved in variable DS traits, and group C genes are not dosage sensitive and are least likely to participate in DS pathological phenotypes. This study provides the first extensive data set on HSA21 gene-expression variation in DS and underscores its role in modulating the outcome of gene-dosage imbalance.
Resumo:
Congenital heart defect (CHD) occurs in 40% of Down syndrome (DS) cases. While carrying three copies of chromosome 21 increases the risk for CHD, trisomy 21 itself is not sufficient to cause CHD. Thus, additional genetic variation and/or environmental factors could contribute to the CHD risk. Here we report genomic variations that in concert with trisomy 21, determine the risk for CHD in DS. This case-control GWAS includes 187 DS with CHD (AVSD = 69, ASD = 53, VSD = 65) as cases, and 151 DS without CHD as controls. Chromosome 21-specific association studies revealed rs2832616 and rs1943950 as CHD risk alleles (adjusted genotypic P-values <0.05). These signals were confirmed in a replication cohort of 92 DS-CHD cases and 80 DS-without CHD (nominal P-value 0.0022). Furthermore, CNV analyses using a customized chromosome 21 aCGH of 135K probes in 55 DS-AVSD and 53 DS-without CHD revealed three CNV regions associated with AVSD risk (FDR ≤ 0.05). Two of these regions that are located within the previously identified CHD region on chromosome 21 were further confirmed in a replication study of 49 DS-AVSD and 45 DS- without CHD (FDR ≤ 0.05). One of these CNVs maps near the RIPK4 gene, and the second includes the ZBTB21 (previously ZNF295) gene, highlighting the potential role of these genes in the pathogenesis of CHD in DS. We propose that the genetic architecture of the CHD risk of DS is complex and includes trisomy 21, and SNP and CNV variations in chromosome 21. In addition, a yet-unidentified genetic variation in the rest of the genome may contribute to this complex genetic architecture.
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Variation in cellular gene expression levels has been shown to be inherited. Expression is controlled at transcriptional and post-transcriptional levels. Internal ribosome entry sites (IRES) are used by viruses to bypass inhibition of cap-dependent translation, and by eukaryotic cells to control translation under conditions when protein synthesis is inhibited. We aimed at identifying genomic determinants of variability in IRES-mediated translation of viral [Encephalomyocarditis virus (EMCV)] and cellular IRES [X-linked inhibitor-of-apoptosis (XIAP) and c-myc]. Bicistronic lentiviral constructs expressing two fluorescent reporters were used to transduce laboratory and B lymphoblastoid cell lines [15 CEPH pedigrees (n = 205) and 50 unrelated individuals]. IRES efficiency varied according to cell type and among individuals. Control of IRES activity has a significant genetic component (h(2) of 0.47 and 0.36 for EMCV and XIAP, respectively). Quantitative linkage analysis identified a suggestive locus (LOD 2.35) on chromosome 18q21.2, and genome-wide association analysis revealed of a cluster of SNPs on chromosome 3, intronic to the FHIT gene, marginally associated (P = 5.9E-7) with XIAP IRES function. This study illustrates the in vitro generation of intermediate phenotypes by using cell lines for the evaluation of genetic determinants of control of elements such as IRES.
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Stroma mediated wound healing signals may share similarities with the ones produced by tumor's microenvironment and their modulation may impact tumor response to the various anti-cancer treatments including radiation therapy. Therefore we conducted this study, to assess the crosstalk between stromal and carcinoma cells in response to radiotherapy by genetic modulation of the stroma and irradiation. We found that fibroblasts irrespective of their RhoB status do not modulate intrinsic radiosensitivity of TC-1 but produce diffusible factors able to modify tumor cell fate. Then we found that Wt and RhoB deficient fibroblasts stimulated TC-1 migration through distinct mechanisms which are TGF-β1 and MMP-mediated respectively. Lastly, we found that simultaneous irradiation of fibroblasts and TC-1 abrogated the pro-migratory phenotype by repression of TGF-β and MMP secretion. This last result is highly relevant to the clinical situation and suggests that conversely to, the current view; irradiated stroma would not enhance carcinoma migration and could be manipulated to promote anti-tumor immune response.
Resumo:
BACKGROUND: Gemcitabine plus cisplatin (GC) has been adopted as a neoadjuvant regimen for muscle-invasive bladder cancer despite the lack of Level I evidence in this setting. METHODS: Data were collected using an electronic data-capture platform from 28 international centers. Eligible patients had clinical T-classification 2 (cT2) through cT4aN0M0 urothelial cancer of the bladder and received neoadjuvant GC or methotrexate, vinblastine, doxorubicin, plus cisplatin (MVAC) before undergoing cystectomy. Logistic regression was used to compute propensity scores as the predicted probabilities of patients being assigned to MVAC versus GC given their baseline characteristics. These propensity scores were then included in a new logistic regression model to estimate an adjusted odds ratio comparing the odds of attaining a pathologic complete response (pCR) between patients who received MVAC and those who received GC. RESULTS: In total, 212 patients (146 patients in the GC cohort and 66 patients in the MVAC cohort) met criteria for inclusion in the analysis. The majority of patients in the MVAC cohort (77%) received dose-dense MVAC. The median age of patients was 63 years, they were predominantly men (74%), and they received a median of 3 cycles of neoadjuvant chemotherapy. The pCR rate was 29% in the MVAC cohort and 31% in the GC cohort. There was no significant difference in the pCR rate when adjusted for propensity scores between the 2 regimens (odds ratio, 0.91; 95% confidence interval, 0.48-1.72; P = .77). In an exploratory analysis evaluating survival, the hazard ratio comparing hazard rates for MVAC versus GC adjusted for propensity scores was not statistically significant (hazard ratio, 0.78; 95% confidence interval, 0.40-1.54; P = .48). CONCLUSIONS: Patients who received neoadjuvant GC and MVAC achieved comparable pCR rates in the current analysis, providing evidence to support what has become routine practice. Cancer 2015;121:2586-2593. © 2015 American Cancer Society.