Die Therapeutischen eigenschaften der "Kamilla-med"-Losung

U ovom radu izneti su rezultati istraživanja rastvora » Kamilla-med « , koja su izvršena na 123 bolesnika, sa progresivnim parodontopatijama, ili nekim drugim oralnim oboljenjima. Za procenu terapijskih vrednosti, korišćena su objektivna merila (indeks inflamacije). » Kamilla-med « može da se koristi kao antiseptik. Može da se koristi za smirivanje inflamatornih stanja oralne sluzokože i za ublažavanje nekih subjektivnih simptoma u ustima. Nisu poznate kontraindikacije za njegovu upotrebu.The results of the analysis of the effect of » Kamilia-Med« solution carried out in 123 patients with progressive parodontal diseases and other oral diseases are presented in this paper. The therapeutic effects of this solution were estimated by objective methods (index of inflammation). It can be used as an antiseptic as well as for the alleviation of inflammatory conditions of oral mucous membrane or for the relief of some subjective symptoms in the oral cavity. Contraindications to its use are not known.In dieser Arbeit wird über Resultate der Untersuchungen von Kamilla-Med berichtet. Bei 123 Patienten mit progressiven Parodontopathien und anderen oralen Erkrankungen, wurde Kamilla-Med angewendet. Die therapeutischen Eigenschaften wurden am Index der Inflamation gewertet. Es konnte festgestellt werden, dass Kamilia-Med ein gutes Antisepticum ist. Es mildert den entzündlichen Zustand der oralen Schleimhaut und beeinflusst günstig subjektive Symptome. Kontraindikationen sind nicht bekannt

Bringing Video Communication to the Community: Opportunities and Challenges

The rise of online social networks, the wide availability of video communication technology and the deployment of high-speed broadband networks together provide the opportunity for video to become a medium for mass social communication among communities. However, current solutions provide poor support for ad hoc social interactions among multiple groups of participants. This position paper summarises the results of more than 5 years’ research to make communication and engagement easier between groups of people separated in space. It shows how communication can be effectively combined with different shared activities, and how the technical capabilities of Communication Orchestration and Dynamic Composition work together to improve the quality of human interactions. The paper also describes ongoing work to develop the Service-Aware Network as a means of optimising the quality of a user’s communication experience while making most efficient use of network resources. We believe these developments could enable video-mediated communication to become an effective and accepted enabler for social communication within community groups globall

Experiments with Distributed Theatre

The Tempest was probably the last play that Shakespeare wrote alone. It is unlikely that he would contemplate it being performed 400 years later, and

NETWORK INFERENCE DRIVEN DRUG DISCOVERY

The application of rational drug design principles in the era of network-pharmacology requires the investigation of drug-target and target-target interactions in order to design new drugs. The presented research was aimed at developing novel computational methods that enable the efficient analysis of complex biomedical data and to promote the hypothesis generation in the context of translational research. The three chapters of the Dissertation relate to various segments of drug discovery and development process. The first chapter introduces the integrated predictive drug discovery platform „SmartGraph”. The novel collaborative-filtering based algorithm „Target Based Recommender (TBR)” was developed in the framework of this project and was validated on a set of 28,270 experimentally determined bioactivity data points involving 1,882 compounds and 869 targets. The TBR is integrated into the SmartGraph platform. The graphical interface of SmartGraph enables data analysis and hypothesis generation even for investigators without substantial bioinformatics knowledge. The platform can be utilized in the context of target identification, drug-target prediction and drug repurposing. The second chapter of the Dissertation introduces an information theory inspired dynamic network model and the novel “Luminosity Diffusion (LD)” algorithm. The model can be utilized to prioritize protein targets for drug discovery purposes on the basis of available information and the importance of the targets. The importance of targets is accounted for in the information flow simulation process and is derived merely from network topology. The LD algorithm was validated on 8,010 relations of 794 proteins extracted from the Target Central Resource Database developed in the framework of the “Illuminating the Druggable Genome” project. The last chapter discusses a fundamental problem pertaining to the generation of similarity network of molecules and their clustering. The network generation process relies on the selection of a similarity threshold. The presented work introduces a network topology based systematic solution for selecting this threshold so that the likelihood of a reasonable clustering can be increased. Furthermore, the work proposes a solution for generating so-called “pseudo-reference clustering” for large molecular data sets for performance evaluation purposes. The results of this chapter are applicable in the lead identification and development processes