@article{SolgerKunzFinketal.2020,
  author    = {Solger, Franziska and Kunz, Tobias C. and Fink, Julian and Paprotka, Kerstin and Pfister, Pauline and Hagen, Franziska and Schumacher, Fabian and Kleuser, Burkhard and Seibel, J{\"u}rgen and Rudel, Thomas},
  title     = {A Role of Sphingosine in the Intracellular Survival of Neisseria gonorrhoeae},
  series = {Frontiers in Cellular and Infection Microbiology},
  volume    = {10},
  journal   = {Frontiers in Cellular and Infection Microbiology},
  issn      = {2235-2988},
  doi       = {10.3389/fcimb.2020.00215},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-204111},
  year      = {2020},
  abstract  = {Obligate human pathogenic Neisseria gonorrhoeae are the second most frequent bacterial cause of sexually transmitted diseases. These bacteria invade different mucosal tissues and occasionally disseminate into the bloodstream. Invasion into epithelial cells requires the activation of host cell receptors by the formation of ceramide-rich platforms. Here, we investigated the role of sphingosine in the invasion and intracellular survival of gonococci. Sphingosine exhibited an anti-gonococcal activity in vitro. We used specific sphingosine analogs and click chemistry to visualize sphingosine in infected cells. Sphingosine localized to the membrane of intracellular gonococci. Inhibitor studies and the application of a sphingosine derivative indicated that increased sphingosine levels reduced the intracellular survival of gonococci. We demonstrate here, that sphingosine can target intracellular bacteria and may therefore exert a direct bactericidal effect inside cells.},
  language  = {en}
}
@article{LichthardtKerscherDietzetal.2016,
  author    = {Lichthardt, Sven and Kerscher, Alexander and Dietz, Ulrich A. and Jurowich, Christian and Kunzmann, Volker and von Rahden, Burkhard H. A. and Germer, Christoph-Thomas and Wiegering, Armin},
  title     = {Original article: role of adjuvant chemotherapy in a perioperative chemotherapy regimen for gastric cancer},
  series = {BMC Cancer},
  volume    = {16},
  journal   = {BMC Cancer},
  number    = {650},
  doi       = {10.1186/s12885-016-2708-0},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-147743},
  year      = {2016},
  abstract  = {Background Multimodal treatment strategies - perioperative chemotherapy (CTx) and radical surgery - are currently accepted as treatment standard for locally advanced gastric cancer. However, the role of adjuvant postoperative CTx (postCTx) in addition to neoadjuvant preoperative CTx (preCTx) in this setting remains controversial. Methods Between 4/2006 and 12/2013, 116 patients with locally advanced gastric cancer were treated with preCTx. 72 patients (62 \%), in whom complete tumor resection (R0, subtotal/total gastrectomy with D2-lymphadenectomy) was achieved, were divided into two groups, one of which receiving adjuvant therapy (n = 52) and one without (n = 20). These groups were analyzed with regard to survival and exclusion criteria for adjuvant therapy. Results Postoperative complications, as well as their severity grade, did not correlate with fewer postCTx cycles administered (p = n.s.). Long-term survival was shorter in patients receiving postCTx in comparison to patients without postCTx, but did not show statistical significance. In per protocol analysis by excluding two patients with perioperative death, a shorter 3-year survival rate was observed in patients receiving postCTx compared to patients without postCTx (3-year survival: 71.2 \% postCTx group vs. 90.0 \% non-postCTx group; p = 0.038). Conclusion These results appear contradicting to the anticipated outcome. While speculative, they question the value of post-CTx. Prospectively randomized studies are needed to elucidate the role of postCTx.},
  language  = {en}
}
@article{StaigerCadotKooteretal.2012,
  author    = {Staiger, Christine and Cadot, Sidney and Kooter, Raul and Dittrich, Marcus and M{\"u}ller, Tobias and Klau, Gunnar W. and Wessels, Lodewyk F. A.},
  title     = {A Critical Evaluation of Network and Pathway-Based Classifiers for Outcome Prediction in Breast Cancer},
  series = {PLoS One},
  volume    = {7},
  journal   = {PLoS One},
  number    = {4},
  doi       = {10.1371/journal.pone.0034796},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-131323},
  pages     = {e34796},
  year      = {2012},
  abstract  = {Recently, several classifiers that combine primary tumor data, like gene expression data, and secondary data sources, such as protein-protein interaction networks, have been proposed for predicting outcome in breast cancer. In these approaches, new composite features are typically constructed by aggregating the expression levels of several genes. The secondary data sources are employed to guide this aggregation. Although many studies claim that these approaches improve classification performance over single genes classifiers, the gain in performance is difficult to assess. This stems mainly from the fact that different breast cancer data sets and validation procedures are employed to assess the performance. Here we address these issues by employing a large cohort of six breast cancer data sets as benchmark set and by performing an unbiased evaluation of the classification accuracies of the different approaches. Contrary to previous claims, we find that composite feature classifiers do not outperform simple single genes classifiers. We investigate the effect of (1) the number of selected features; (2) the specific gene set from which features are selected; (3) the size of the training set and (4) the heterogeneity of the data set on the performance of composite feature and single genes classifiers. Strikingly, we find that randomization of secondary data sources, which destroys all biological information in these sources, does not result in a deterioration in performance of composite feature classifiers. Finally, we show that when a proper correction for gene set size is performed, the stability of single genes sets is similar to the stability of composite feature sets. Based on these results there is currently no reason to prefer prognostic classifiers based on composite features over single genes classifiers for predicting outcome in breast cancer.},
  language  = {en}
}