MRI-based vessel function maps for high-resolution differentiation between tumor and nontumoral tissues in brain tumor patients.

2078 Background: Changes in enhancement seen in post treatment brain MRIs in primary and secondary brain malignancies often mimic tumor progression (pseudoprogression, radiation necrosis). Conventional MRI cannot differentiate tumor progression from treatment related effects resulting in suboptimal patient management. Methods: The application of delayed contrast extravasation MRI for depicting unique vessels characteristics with high resolution and high sensitivity to subtle BBB disruption is demonstrated in 17 GBM and 15 brain metastases patients undergoing standard chemoradiation and radiosurgery respectively. Results: 2 primary vessel function populations were defined: a slow population where contrast clearance from the tissue was slower than accumulation, and a fast population where clearance was faster than accumulation. Ten stereotactic biopsies acquired from GBM patients showed complete correlation with the maps, confirming the discrimination between fast population regions, reflecting morphological active tumor and slow regions reflecting necrosis/treatment-induced changes. Typical fast population vessel morphology consisted of proliferating endothelial cells, dilated lumen, peri vascular fibrosis and glumeroloid vessels, while slow regions consisted of necrotic vessels, in agreement with the observed MRI vessel function. The fast component volume 3 weeks post treatment was significantly correlated with the fast volume 4 (r2=0.84, p<0.0005) and 6 months (r2=0.84, p<0.01) later, suggesting early prediction of response. Brain metastases histology showed similar results: 5 brain metastases with a fast population component were confirmed histologically to contain morphologically active tumor. One metastasis consisting of the slow population only significantly decreased in volume in the following MRIs. Conclusions: These results demonstrate the feasibility of applying our delayed contrast extravasation high resolution function vessel maps for improving patient management by clearly depicting tumor and non-tumoral tissues in patients with primary and secondary brain malignancies undergoing standard chemoradiation or radiosurgery.

Morphological variability of leaves of Sorbus torminalis (L.) Crantz in Poland

This paper presents the results of the study on morphological variability of leaves of a scattered tree species <em>Sorbus torminalis</em> (L.) Crantz) in Poland. The leaves from short- and long shoots were collected from 17 localities widespread within the range of the species in Poland. Leaves were measured according to 15 morphological traits. The biometric data were subjected to multivariate statistical analysis in attempt to define variability between local populations. Most of the leaf traits are significantly correlated and are characterised by moderate level of variation. The average among population component of variation was 32.82% and 27.46% for leaves on short- and long shoots, respectively. The differences between sampled populations are significant, but only a weak geographical pattern of this differentiation was detected. Clinal type of variation was ascertained in two traits. Leaf traits which discriminate best the studied populations are also indicated. It was proved that leaves on short shoots differ markedly in shape and size from those of long shoots. Leaves on long shoots are steadier, but morphological trait values are less correlated. The study also confirmed the occurrence of individuals with leaves characteristic for <em>S. torminalis</em> var. perincisa Borbas et Feck and <em>S. torminalis</em> f. <em>mollis</em> Beck in a few Polish populations.

CAEP: AN EVOLUTION-BASED TOOL FOR REAL-VALUED FUNCTION OPTIMIZATION USING CULTURAL ALGORITHMS

Cultural Algorithms are computational self-adaptive models which consist of a population and a belief space. The problem-solving experience of individuals selected from the population space by the acceptance function is generalized and stored in the belief space. This knowledge can then control the evolution of the population component by means of the influence function. Here, we examine the role that different forms of knowledge can play in the self-adaptation process within cultural systems. In particular, we compare various approaches that use normative and situational knowledge in different ways to guide the function optimization process. The results in this study demonstrate that Cultural Algorithms are a naturally useful framework for self-adaptation and that the use of a cultural framework to support self-adaptation in Evolutionary Programming can produce substantial performance improvements over population-only systems as expressed in terms of (1) systems success ratio, (2) execution CPU time, and (3) convergence (mean best solution) for a given set of 34 function minimization problems. The nature of these improvements and the type of knowledge that is most effective in producing them depend on the problem's functional landscape. In addition, it was found that the same held true for the population-only self-adaptive EP systems. Each level of self-adaptation (component, individual, and population) outperformed the others for problems with particular landscape features.

Patterns of seed polymorphism and allozyme variation in the bladder campions, Silene vulgaris and Silene uniflora (Caryophyllaceae)

Seed morphology (testa ornamentation and seed shape) and allozyme variation were investigated in three closely related and partially sympatric taxa of Silene in the Nordic region. Within this region, Silene vulgaris is a widespread weed of anthropogenic habitats. The two subspecies of Silene uniflora are restricted to naturally open habitats; ssp. uniflora has a coastal distribution, whereas the Swedish endemic, ssp. petraea, is restricted to limestone habitats on the islands of Öland and Gotland. All three taxa show a seed ornamentation polymorphism, with individuals producing either tubercled or smooth ("armadillo") seeds. Both seed morphology and allozymes show a separation between the two species Silene vulgaris and Silene uniflora and support the present taxonomic treatment of the endemic "petraea" as a subspecies of Silene uniflora. Tubercled seeds predominate in Silene vulgaris and armadillo seeds predominate in Silene uniflora. However, there is considerable between-population variation in seed morph frequencies within taxa. In contrast to the other two taxa, populations of Silene uniflora ssp. petraea consistently show intermediate frequencies of both seed morphs. Silene uniflora ssp. petraea has the lowest between-population component of diversity in both seed shape (18–46%) and allozymes (0.8%) and shows no significant geographic structure in any of the character sets. Both Silene uniflora ssp. uniflora and Silene vulgaris show significant geographic differentiation in allozymes and seed morphology. The highest between-population component of diversity was found in Silene uniflora ssp. uniflora, where 17% of the total allozyme diversity and 39–82% of the seed shape diversity are accounted for by differences between populations. Key words: allozymes, geographic differentiation, diversity, seed shape, elliptic Fourier coefficients, Landmark characters.