A Carbon-Cycle Based Stochastic Cellular Automata Climate Model

In this article a stochastic cellular automata model is examined, which has been developed to study a "small" world, where local changes may noticeably alter global characteristics. This is applied to a climate model, where global temperature is determined by an interplay between atmospheric carbon dioxide and carbon stored by plant life. The latter can be relased by forest fires, giving rise to significant changes of global conditions within short time.Comment: 17 pages, 8 figure

Phase Transition in a Stochastic Forest Fire Model and Effects of the Definition of Neighbourhood

We present results on a stochastic forest fire model, where the influence of the neighbour trees is treated in a more realistic way than usual and the definition of neighbourhood can be tuned by an additional parameter. This model exhibits a surprisingly sharp phase transition which can be shifted by redefinition of neighbourhood. The results can also be interpreted in terms of disease-spreading and are quite unsettling from the epidemologist's point of view, since variation of one crucial parameter only by a few percent can result in the change from endemic to epidemic behaviour.Comment: 23 pages, 13 figure

Nonperturbative contributions to the QCD pressure

We summarize the most important arguments why a perturbative description of finite-temperature QCD is unlikely to be possible and review various well-established approaches to deal with this problem. Then, using a recently proposed method, we investigate nonperturbative contributions to the QCD pressure and other observables (like energy, anomaly and bulk viscosity) obtained by imposing a functional cutoff at the Gribov horizon. Finally, we discuss how such contributions fit into the picture of consecutive effective theories, as proposed by Braaten and Nieto, and give an outline of the next steps necessary to improve this type of calculation.Comment: 15 pages, 13 figures, uses xcolor.sty; in v2 quality of some figures has been improved, discussion of other approaches has been extende

Detection of circulating tumor cells using manually performed immunocytochemistry (MICC) does not correlate with outcome in patients with early breast cancer – Results of the German SUCCESS-A- trial

Background: Recently, the prognostic significance of circulating tumor cells (CTCs) in primary breast cancer as assessed using the Food-and-Drug-Administration-approved CellSearch® system has been demonstrated. Here, we evaluated the prognostic relevance of CTCs, as determined using manually performed immunocytochemistry (MICC) in peripheral blood at primary diagnosis, in patients from the prospectively randomized multicenter SUCCESS-A trial (EudraCT2005000490-21). Methods: We analyzed 23 ml of blood from 1221 patients with node-positive or high risk node-negative breast cancer before adjuvant taxane-based chemotherapy. Cells were separated using a density gradient followed by epithelial cell labeling with the anti-cytokeratin-antibody A45-B/B3, immunohistochemical staining with new fuchsin, and cytospin preparation. All cytospins were screened for CTCs, and the cutoff for positivity was at least one CTC. The prognostic value of CTCs with regard to disease-free survival (DFS), distant disease-free survival (DDFS), breast-cancer-specific survival (BCSS), and overall survival (OS) was assessed using both univariate analyses applying the Kaplan–Meier method and log-rank tests, and using multivariate Cox regressions adjusted for other predictive factors. Results: In 20.6% of all patients (n = 251) a median of 1 (range, 1–256) CTC was detected, while 79.4% of the patients (n = 970) were negative for CTCs before adjuvant chemotherapy. A pT1 tumor was present in 40.% of patients, 4.8% had G1 grading and 34.6% were node-negative. There was no association between CTC positivity and tumor stage, nodal status, grading, histological type, hormone receptor status, Her2 status, menopausal status or treatment. Univariate survival analyses based on a median follow-up of 64 months revealed no significant differences between CTC-positive and CTC-negative patients with regard to DFS, DDFS, BCSS, or OS. This was confirmed by fully adjusted multivariate Cox regressions, showing that the presence of CTCs (yes/no) as assessed by MICC did not predict DFS, DDFS, BCSS or OS. Conclusions: We could not demonstrate prognostic relevance regarding CTCs that were quantified using the MICC method at the time of primary diagnosis in our cohort of early breast cancer patients. Further studies are necessary to evaluate if the presence of CTCs assessed using MICC has prognostic relevance, or can be used for risk stratification and treatment monitoring in adjuvant breast cancer. Trial registration The ClinicalTrial.gov registration ID of this prospectively randomized trial is NCT02181101; the (retrospective) registration date was June 2014 (study start date September 2005)