Epstein-Barr-Virus - Ein klinisch relevanter Marker für das Nasopharynxkarzinom? = Epstein-Barr virus - a clinically relevant feature of nasopharyngeal carcinoma? (author's transl.)

Nasopharyngeal carcinoma (NPC) has been linked to Epstein-Barr Virus (EBV) by seroepidemiological evidence and by the regular proof of EBV-DNA in the epithelial tumor cells. We have been able to study the serological parameters of 62 NPC patients of the local ENT-Clinic. All patients were kaukasians in contrast to a previous study by Henle et al. Our results emphasize the remarkable predominance of EBV-IgA antibodies to viral capsid antigen (VCA) and early antigen (EA) in NPC patients and prove the value of the test for the initial diagnosis of the disease. Follow-up studies with subsequent serological tests strongly suggest that this test is related to the stage of the disease. We have also found NPC-typical serological EBV-IgA titers in 3 lymphoepithelial carcinomas of the tonsil and the soft palate. Similar titers have been found in two cases of poorly differentiated carcinomas of the base of the tongue. All these tumors arise in the lymphoepithelial tissue of Waldeyer's ring. We conclude that possibly some carcinomas of Waldeyer's ring are similarly related to EBV as nasopharyngeal carcinomas are

Alpha-decay branching ratios of near-threshold states in 19Ne and the astrophysical rate of 15O(alpha,gamma)19Ne

The 15O(alpha,gamma)19Ne reaction is one of two routes for breakout from the hot CNO cycles into the rp process in accreting neutron stars. Its astrophysical rate depends critically on the decay properties of excited states in 19Ne lying just above the 15O + alpha threshold. We have measured the alpha-decay branching ratios for these states using the p(21Ne,t)19Ne reaction at 43 MeV/u. Combining our measurements with previous determinations of the radiative widths of these states, we conclude that no significant breakout from the hot CNO cycle into the rp process in novae is possible via 15O(alpha,gamma)19Ne, assuming current models accurately represent their temperature and density conditions

Ligand-induced type II interleukin-4 receptor dimers are sustained by rapid re-association within plasma membrane microcompartments

Biological and Soft Matter Physic

Ecological distribution and population physiology defined by proteomics in a natural microbial community

Community proteomics applied to natural microbial biofilms resolves how the physiology of different populations from a model ecosystem change with measured environmental factors in situ.The initial colonists, Leptospirillum Group II bacteria, persist throughout ecological succession and dominate all communities, a pattern that resembles community assembly patterns in some macroecological systems.Interspecies interactions, and not abiotic environmental factors, demonstrate the strongest correlation to physiological changes of Leptospirillum Group II.Environmental niches of subdominant populations seem to be determined by combinations of specific sets of abiotic environmental factors

Exploratory analysis of protein translation regulatory networks using hierarchical random graphs

Abstract Background Protein translation is a vital cellular process for any living organism. The availability of interaction databases provides an opportunity for researchers to exploit the immense amount of data in silico such as studying biological networks. There has been an extensive effort using computational methods in deciphering the transcriptional regulatory networks. However, research on translation regulatory networks has caught little attention in the bioinformatics and computational biology community. Results In this paper, we present an exploratory analysis of yeast protein translation regulatory networks using hierarchical random graphs. We derive a protein translation regulatory network from a protein-protein interaction dataset. Using a hierarchical random graph model, we show that the network exhibits well organized hierarchical structure. In addition, we apply this technique to predict missing links in the network. Conclusions The hierarchical random graph mode can be a potentially useful technique for inferring hierarchical structure from network data and predicting missing links in partly known networks. The results from the reconstructed protein translation regulatory networks have potential implications for better understanding mechanisms of translational control from a system’s perspective