Humanities for the Future: a new European Agenda

FGW – Publications not associated with a particular research are

Lack of CD151/integrin alpha 3 beta 1 complex is predictive of poor outcome in node-negative lobular breast carcinoma: opposing roles of CD151 in invasive lobular and ductal breast cancers

background: The proposed involvement of CD151 in breast cancer (BCa) progression is based on findings from studies in invasive ductal carcinoma (IDC). The IDC and invasive lobular carcinoma (ILC) represent distinct disease entities. Here we evaluated clinical significance of CD151 alone and in association with integrin α3β1 in patients with ILC in context of the data of our recent IDC study. methods: Expression of CD151 and/or integrin α3β1 was evaluated in ILC samples (N=117) using immunohistochemistry. The findings were analysed in relation to our results from an IDC cohort (N=182) demonstrating a prognostic value of an expression of CD151/integrin α3β1 complex in patients with HER2-negative tumours. results: Unlike in the IDCs, neither CD151 nor CD151/α3β1 complex showed any correlation with any of the ILC characteristics. Lack of both CD151 and α3β1 was significantly correlated with poor survival (P=0.034) in lymph node-negative ILC N(−) cases. The CD151−/α3β1− patients had 3.12-fold higher risk of death from BCa in comparison with the rest of the ILC N(−) patients. conclusions: Biological role of CD151/α3β1 varies between ILC and IDC. Assessment of CD151/α3β1 might help to identify ILC N(−) patients with increased risk of distant metastases

Multi-method approach to velocity determination from acoustic well logging

Three different methods of building detailed velocity models for seismic interpretation are explained and discussed in terms of their advantages and limitations. All of the proposed methods are based on the analysis of acoustic well logs. An application of acoustic full waveform measurements, as well as the FalaFWS and Estymacja software, is presented as a tool for determining P-wave and S-wave slowness (transit time interval, velocity reciprocal). Well log data from several wells, located near the special research seismic transect in the Polish Lowland, were processed using the methods proposed. The results of data analysis are presented for a depth section of up to 3623 m for the lithostratigraphic units, recorded from the Środa Wielkopolska 5 (SW5) well. The results of P-wave and S-wave slowness filtering, used to upscale well log data to a seismic scale of resolution, are shown for the entire geological profile of the SW5 well

Wyznaczenie norm dla testu Kinga-Devicka u dzieci w wieku od 7 do 15 lat

Test Kinga-Devicka (K-D) stanowi przesiewowe narzędzie do subiektywnej oceny sakadowych ruchów oczu występujących podczas czytania. Celem niniejszych badań było rozpoczęcie procesu standaryzacji tego testu w Polsce u dzieci w wieku od 7 do 15 lat. Przebadano łącznie 358 uczniów szkoły podstawowej oraz gimnazjum z miasta Kłobuck (woj. śląskie) i jego okolic. Otrzymane czasy odczytywania kart testu K-D zostały zestawione z czasami osiąganymi przez duńskie i amerykańskie dzieci. Ponadto w badanej grupie dzieci i nastolatków dokonano analizy porównawczej pomiędzy wynikami dla kolejnych grup wiekowych oraz pomiędzy wynikami osiąganymi przez chłopców i dziewczęta z każdej grupy wiekowej. Wykazano, że pomiędzy dziećmi polskimi i amerykańskimi nie występują znaczne różnice w wynikach testu K-D. Najbardziej dynamiczne zmiany w wynikach testu K-D u dzieci polskich były zauważalne w okresie od 9. do 11. roku życia. W grupach wiekowych 12- oraz 13-latków nie odnotowano znaczących różnic dla wyników testu K-D. Również zbliżone wyniki osiągała grupa 14- i 15-latków. Nie odnotowano istotnych różnic w wynikach testu K-D dla dziewcząt i chłopców. Uzyskane lokalne normy dla K-D należałoby rozszerzyć w kolejnych badaniach w celu stworzenia ogólnopolskiej normy dla testu Kinga-Devicka.King-Devick (K-D) test is a screening tool for indirect evaluation of saccadic eye movements that occur during reading. The aim of the present paper was to start research that will, resultingly, create the standardized norms for the King-Devick test in Poland for children aged 7 to 15 years. Using the K-D test, 358 students from primary and secondary school from Kłobuck (Silesian) and their surroundings were examined. The obtained results were compared with the results received in the USA and Denmark. Moreover, the comparison analysis was made for two groups: 1. subsequent age groups, and 2. age-matched boys and girls. Based on the comparison between the obtained results and those from Danish and American population, it can be observed that are no significant differences in the K-D test results between the Polish and the US children. The most dynamic changes between age groups were observed in the age range 9–11 yr. 12- and 13 year-olds achieved close results, similar situation took place for 14- and 15-year-olds. There are no reported significant differences in K-D test results between boys and girls. The obtained local standards for K-D should be extended in further studies to create nation-wide standards for the King-Devick test

The Monte Carlo validation framework for the discriminant partial least squares model extended with variable selection methods applied to authenticity studies of Viagra (R) based on chromatographic impurity profiles

&lt;p&gt;The aim of this work was to develop a general framework for the validation of discriminant models based on the Monte Carlo approach that is used in the context of authenticity studies based on chromatographic impurity profiles. The performance of the validation approach was applied to evaluate the usefulness of the diagnostic logic rule obtained from the partial least squares discriminant model (PLS-DA) that was built to discriminate authentic Viagra® samples from counterfeits (a two-class problem). The major advantage of the proposed validation framework stems from the possibility of obtaining distributions for different figures of merit that describe the PLS-DA model such as, e.g., sensitivity, specificity, correct classification rate and area under the curve in a function of model complexity. Therefore, one can quickly evaluate their uncertainty estimates. Moreover, the Monte Carlo model validation allows balanced sets of training samples to be designed, which is required at the stage of the construction of PLS-DA and is recommended in order to obtain fair estimates that are based on an independent set of samples. In this study, as an illustrative example, 46 authentic Viagra® samples and 97 counterfeit samples were analyzed and described by their impurity profiles that were determined using high performance liquid chromatography with photodiode array detection and further discriminated using the PLS-DA approach. In addition, we demonstrated how to extend the Monte Carlo validation framework with four different variable selection schemes: the elimination of uninformative variables, the importance of a variable in projections, selectivity ratio and significance multivariate correlation. The best PLS-DA model was based on a subset of variables that were selected using the variable importance in the projection approach. For an independent test set, average estimates with the corresponding standard deviation (based on 1000 Monte Carlo runs) of the correct classification rate, sensitivity, specificity and area under the curve were equal to 96.42% ± 2.04, 98.69% ± 1.38, 94.16% ± 3.52 and 0.982 ± 0.017, respectively.&lt;/p&gt;</p

The Monte Carlo validation framework for the discriminant partial least squares model extended with variable selection methods applied to authenticity studies of Viagra® based on chromatographic impurity profiles.

&lt;p&gt;The aim of this work was to develop a general framework for the validation of discriminant models based on the Monte Carlo approach that is used in the context of authenticity studies based on chromatographic impurity profiles. The performance of the validation approach was applied to evaluate the usefulness of the diagnostic logic rule obtained from the partial least squares discriminant model (PLS-DA) that was built to discriminate authentic Viagra® samples from counterfeits (a two-class problem). The major advantage of the proposed validation framework stems from the possibility of obtaining distributions for different figures of merit that describe the PLS-DA model such as, e.g., sensitivity, specificity, correct classification rate and area under the curve in a function of model complexity. Therefore, one can quickly evaluate their uncertainty estimates. Moreover, the Monte Carlo model validation allows balanced sets of training samples to be designed, which is required at the stage of the construction of PLS-DA and is recommended in order to obtain fair estimates that are based on an independent set of samples. In this study, as an illustrative example, 46 authentic Viagra® samples and 97 counterfeit samples were analyzed and described by their impurity profiles that were determined using high performance liquid chromatography with photodiode array detection and further discriminated using the PLS-DA approach. In addition, we demonstrated how to extend the Monte Carlo validation framework with four different variable selection schemes: the elimination of uninformative variables, the importance of a variable in projections, selectivity ratio and significance multivariate correlation. The best PLS-DA model was based on a subset of variables that were selected using the variable importance in the projection approach. For an independent test set, average estimates with the corresponding standard deviation (based on 1000 Monte Carlo runs) of the correct classification rate, sensitivity, specificity and area under the curve were equal to 96.42% ± 2.04, 98.69% ± 1.38, 94.16% ± 3.52 and 0.982 ± 0.017, respectively.&lt;/p&gt;</p