Gangliosides from histopathologically-defined human cerebrum-resembling remnant and cerebellum from 37 and 30 gestational week-old anencephaluses were identified using mass spectrometry and high performance thin layer chromatography combined with immunochemical analysis in comparison to respective normal newborn/fetal and adult brain regions. A novel strategy of nano-electrospray ionization quadrupole time-of-flight tandem MS has been developed for identification of ganglioside components in complex mixtures. By morphoanatomical and histological investigation the anencephalic cerebral remnant was found to be aberrant, while the anencephalic cerebellum was defined as normal. Total ganglioside concentrations in the anencephalic cerebral remnant and the cerebellum were 34% and 13% lower in relation to the age-matched controls. In the cerebral remnant, GD3, GM2 and GT1b were elevated, while GD1a was decreased in the anencephalic cerebral remnant, but enriched in anencephalic cerebellum. GQ1b was reduced in both anencephalic regions. Gg4Cer, GM1b and GD1alpha, members of the alpha-series biosynthetic pathway, and neolacto-series gangliosides were found to be present in anencephalic, as well as in normal, fetal and adult brain tissues, indicating the occurrence of these biosynthetic pathways in human brain. In both cerebral and cerebellar anencephalic tissues, GM1b, GD1alpha, nLM1 and nLD1 were expressed at a higher rate in relation to normal tissue. It can be demonstrated that the anencephalic cerebral remnant, as a primitive brain structure, represents a naturally-occurring model to study the ganglioside involvement in induction of aberrant brain development.

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NANOG is an important stem cell transcription factor involved in human development and cancerogenesis. Its expression is complex and regulated on different levels. Moreover, NANOG protein might regulate hundreds of target genes at the same time. NANOG is crucial for preimplantation development phase and progressively decreases during embryonic stem cells differentiation, thus regulating embryonic and fetal development. Postnatally, NANOG is undetectable or expressed in very low amounts in the majority of human tissues. NANOG re-expression can be detected during cancerogenesis, already in precancerous lesions, with increasing levels of NANOG in high grade dysplasia. NANOG is believed to enable cancer cells to obtain stem-cell like properties, which are believed to be the source of expanding growth, tumor maintenance, metastasis formation, and tumor relapse. High NANOG expression in cancer is frequently associated with advanced stage, poor differentiation, worse overall survival, and resistance to treatment, and is therefore a promising prognostic and predictive marker. We summarize the current knowledge on the role of NANOG in cancerogenesis and development, including our own experience. We provide a critical overview of NANOG as a prognostic and diagnostic factor, including problems regarding its regulation and detection. Impact statement NANOG has emerged as a key stem cell transcription factor in normal development and cancerogenesis. It is generally regarded as a good prognostic and predictive factor in various human cancers. It is less known that it is expressed already at precancerous stages in various organs, suggesting that finally an ideal candidate diagnostic marker has been discovered, enabling to distinguish between true dysplasia and reactive atypia. NANOG regulation is complex, and new insights into our understanding of its regulation might provide important information for future development in a broad field of two entirely different processes, i.e. normal development and cancerogenesis, showing how a physiologic mechanism can be used and abused, transforming itself into a key mechanism of disease development and progression.

The increasing development of real-time multimedia network applications, many of which require multiple participants, has created the need for efficient multicast routing algorithms. Examples of such applications include video and tele-conferencing, video-on-demand, tele-medicine, distance education, etc. Several of them require multicasting with a certain Quality of Service (QoS) with respect to elements such as delay or bandwidth. This paper deals with Delay-Constrained Multicast Routing (DCMR) where the maximum end-to-end delay in a multicast session is bounded. The DCMR problem can be reduced to the Constrained Minimum Steiner Tree Problem in Graphs (CMStTG) which has been proven to be NP-complete. As a result, several heuristics have been developed to help solve it. In this paper, we developed a GRASP heuristic for the DCMR problem. Computational experiments on medium sized problems (50-100 nodes) from literature and comparison with existing algorithms have shown that the suggested GRASP heuristic is superior in quality for this set of problems.

Ahstrncl-With today's development of information technologycomes the increased development of numerous real-time multimedia network applications. Some examples include video and tele-confereneing, tele-medicine. video-on-demand, distance education, applications in finance, etc. Several of these applications require multicasting with a certain Quality of Service (QoS). One of the most important QoS parametcrs is the maximum end-to-end delay from the source to any destination in a multicast session. This paper deals with the problem of DelayConstrained Multicast Routing (DCMR). The DCMR problem cm be reduced to the constrained Minimum Steiner Tree Problem in Graphs (CMStTG). Since the Minimum Steiner Tree Problem in Graphs (MStTG) has been proven to be NP-complete, several heuristics have been developed for solving hlStTG and CMStTG. I n this paper, we suggest a tabu search heuristic for the DChlR problem. This heuristic was developed on the basis of a tabu search heuristic designed for solving unconstrained minimum Steiner tree problems. Preliminary testing on drta from B publicly available library, StcinLib, has shown that this heuristic gives near optimal solutions in moderate time and a moderate number o f iterations for medium sized problems (SO-100 nodes). Comparing with B well known algorithm for solving the ChlStTG problem, tests have shown that our tabu search heuristic is superior in quality for medium sized problems.