Integrative functional genomics analysis of sustained polyploidy phenotypes in breast cancer cells identifies an oncogenic profile for GINS2

Aneuploidy is among the most obvious differences between normal and cancer cells. However, mechanisms contributing to development and maintenance of aneuploid cell growth are diverse and incompletely understood. Functional genomics analyses have shown that aneuploidy in cancer cells is correlated with diffuse gene expression signatures and that aneuploidy can arise by a variety of mechanisms, including cytokinesis failures, DNA endoreplication and possibly through polyploid intermediate states. Here, we used a novel cell spot microarray technique to identify genes with a loss-of-function effect inducing polyploidy and/or allowing maintenance of polyploid cell growth of breast cancer cells. Integrative genomics profiling of candidate genes highlighted GINS2 as a potential oncogene frequently overexpressed in clinical breast cancers as well as in several other cancer types. Multivariate analysis indicated GINS2 to be an independent prognostic factor for breast cancer outcome (p = 0.001). Suppression of GINS2 expression effectively inhibited breast cancer cell growth and induced polyploidy. In addition, protein level detection of nuclear GINS2 accurately distinguished actively proliferating cancer cells suggesting potential use as an operational biomarker.

Sanailua, kynäilyä, intoilua ja epäilyä : Oppilaiden kirjoitustaito ja sen arvioiminen alkuopetuksessa

Objectives. In primary education the pupils form a basis for their writing skills. By assessing pupils writing skills the teacher gathers information about the development of their skills and notices possible learning disabilities. The assessment of writing skills requires both knowledge of different evaluation methods and the phonological system in Finnish language. The purpose of this study is to analyze the pupils writing skills and different assessment methods that help the teacher in writing evaluation. The pupils writing skills are viewed from spelling, composing and writing motivation s point of view. Methods. The research material consists of dictation exercises, written stories and writing motivation self-assessments of 19 pupils. Dictation exercises measured the spelling skills of pupils and they were written in the spring of the first grade and the autumn of the second grade. Dictation exercises were analyzed with two different methods: mistake analysis and word-structure analysis. Information of pupils spelling skills development was gathered by comparing their performance in autumn s dictation exercise to spring s dictation. Composing skills were measured with stories that the pupils wrote. Both the stories and the writing motivation s self-assessment were made in the autumn of the second grade. Composing skills were analyzed according to assessment criteria formed for this study. Results. The spelling skill of most of the pupils had developed from the first grade s spring to the second grade s autumn. The spelling skills of half of the pupils (N=9) had improved significantly. The composing skills of the pupils varied largely. Strongest part of the pupils composing skill was following instructions and the weakest part was the use of versatile vocabulary and clause structures. The girls outdid the boys in all segments of their composing skills. For most pupils their spelling skill reflected their composing skill: good spellers were also good story writers. The relation between writing motivation and general writing skill was not this simple: some pupils (N=5) writing motivation was much higher than what would have been expected based on their writing skills.

Categorical Meteorological Products: Evaluation and Analysis

In meteorology, observations and forecasts of a wide range of phenomena for example, snow, clouds, hail, fog, and tornados can be categorical, that is, they can only have discrete values (e.g., "snow" and "no snow"). Concentrating on satellite-based snow and cloud analyses, this thesis explores methods that have been developed for evaluation of categorical products and analyses. Different algorithms for satellite products generate different results; sometimes the differences are subtle, sometimes all too visible. In addition to differences between algorithms, the satellite products are influenced by physical processes and conditions, such as diurnal and seasonal variation in solar radiation, topography, and land use. The analysis of satellite-based snow cover analyses from NOAA, NASA, and EUMETSAT, and snow analyses for numerical weather prediction models from FMI and ECMWF was complicated by the fact that we did not have the true knowledge of snow extent, and we were forced simply to measure the agreement between different products. The Sammon mapping, a multidimensional scaling method, was then used to visualize the differences between different products. The trustworthiness of the results for cloud analyses [EUMETSAT Meteorological Products Extraction Facility cloud mask (MPEF), together with the Nowcasting Satellite Application Facility (SAFNWC) cloud masks provided by Météo-France (SAFNWC/MSG) and the Swedish Meteorological and Hydrological Institute (SAFNWC/PPS)] compared with ceilometers of the Helsinki Testbed was estimated by constructing confidence intervals (CIs). Bootstrapping, a statistical resampling method, was used to construct CIs, especially in the presence of spatial and temporal correlation. The reference data for validation are constantly in short supply. In general, the needs of a particular project drive the requirements for evaluation, for example, for the accuracy and the timeliness of the particular data and methods. In this vein, we discuss tentatively how data provided by general public, e.g., photos shared on the Internet photo-sharing service Flickr, can be used as a new source for validation. Results show that they are of reasonable quality and their use for case studies can be warmly recommended. Last, the use of cluster analysis on meteorological in-situ measurements was explored. The Autoclass algorithm was used to construct compact representations of synoptic conditions of fog at Finnish airports.