Advanced and Recurrent Endometrial Cancer; current concepts of treatment

Endometrial cancer is the most common gynecological malignancy in Western Countries. In the United States approximately 39,000 cases will be diagnosed in 2007 and 7,400 deaths will occur. Women have a 2.6% lifetime risk of developing endometrial cancer and it accounts for 6% of all cancers in women (1). The incidence of endometrial cancer rises from 2 per 100,000 women per year under the age of 40 years, to 40-50 per 100,000 women per year after the age of 60 (2). In the Netherlands, it is the fourth most common invasive tumor in women after breast, colorectal and lung cancer. Its incidence is still rising; 1,619 new cases of endometrial cancer were reported in the Netherlands in 2003, compared to 1,293 new cases in 1989 (www.ikcnet.nl). This increase is related not only to higher life expectancy but also to the exposure of the uterus to unopposed estrogens, either exogenous or endogenous as in obese patients

Difference in signalling between various hormone therapies in endometrium, myometrium and upper part of the vagina

BACKGROUND: Combined hormone treatments in post-menopausal women have different clinical responses on uterus and vagina; therefore, we investigated differences in steroid signalling between various hormone therapies in these tissues. METHODS: A total of 30 post-menopausal women scheduled for hysterectomy were distributed into four subgroups: control-group (n = 9), Tibolone-group (n = 8); estradiol (E(2))-group (n = 7); E(2) + medroxyprogesterone acetate (MPA)-group (n = 6). Medication was administered orally every day for 21 days prior to removal of uterus and upper part of the vagina. Tissue RNA was isolated, and gene expression profiles were generated using GeneChip technology and analysed by cluster analysis and significance analysis of microarrays. Apoptosis and cell proliferation assays, as well as immunohistochemistry for hormone receptors were performed. RESULTS: 21-days of treatment with E(2), E(2) + MPA or tibolone imposes clear differential gene expression profiles on endometrium and myometrium. Treatment with E(2) only results in the most pronounced effect on gene expression (up to 1493 genes differentially expressed), proliferation and apoptosis. Tibolone, potentially metabolized to both estrogenic and progestagenic metabolites, shows some resemblance to E(2) signalling in the endometrium and, in contrast, shows significant resemblance to E(2) + MPA signalling in the myometrium. In the vagina the situation is entirely different; all three hormonal treatments result in regulation of a small number (4-73) of genes, in comparison to signalling in endometrium and myometrium. CONCLUSION: Endometrium and myometrium differentially respond to the hormone therapies and use complet

Research issues in vector and tensor field visualization

Today, computational fluid dynamics (CFD) research is almost impossible without computer-generated visualizations of the very large amounts of data resulting from numerical simulations. Although good techniques now exist for analysis of scalar data, most existing techniques for the visualization of vector fields-the predominant data type in CFD-meet only part of what is required. Common techniques such as arrow plots, streamlines, and particles work well for 2D applications, but for 3D data sets they often lead to cluttered displays. For tensors, which are much more complex and abstract entities the problem is even more severe. There is a real need for visualization, but there are no simple solutions. Many researchers have recognized this challenge and developed new techniques. We restrict ourselves to open research issues. We proceed in three ways. First, we propose a classification of existing vector and tensor field visualization techniques based on work by Delmarcelle and Hesselink (1994) and point out research gaps in this classification scheme. Second, we discuss feature-based visualization, which shows higher level descriptions derived from elementary data. Third, we consider the role of visualization in the research process, again revealing gaps in our current know-how concerning visualization of vector and tensor fields

Three ways to show 3D fluid flow

Visualizing 3D fluid flow fields presents a challenge to scientific visualization, mainly because no natural visual representation of 3D vector fields exists. We can readily recognize geometric objects, color, and texture: unfortunately for computational fluid dynamics (CFD) researchers, vector fields are harder to grasp. Thus, we must construct simplified representations that human observers can understand. Simplification means focusing on relevant aspects of the flow. This offers many options, making a wide variety of flow visualization techniques both feasible and desirable. This article presents an overview of three different visualization techniques developed in the Netherlands. The three useful techniques for visualizing 3D flows are: implicit stream surfaces, turbulent particle animation, and a flow probe