Motivation beim Fremdsprachenerwerb. Eine qualitative Pilotstudie zur Motivation schwedischer Deutschlerner

Beim Erlernen einer Sprache spielen eine Vielzahl an internen und externen Variablen eine Rolle, die zudem in Wechselwirkung zueinander stehen und somit den Lernprozess hochgradig individualisieren. Einen ganz wesentlichen Faktor stellt in diesem Zusammenhang die Motivation eines Lerners dar. Sie liefert nicht nur den Anreiz zum Lernen einer Sprache, sondern ist das Rädchen, das das Lernen vorantreibt, das den Lerner zum Durchhalten bewegt. Für die hier vorgestellte Pilotstudie wurden schwedische DaF-Lerner hinsichtlich ihrer Motivation beim Deutschlernen befragt. Die Vorgehensweise war qualitativ, es wurden Interviews mit vier Studierenden der Universität Uppsala durchgeführt und anschließend für jeden Untersuchungsteilnehmer ein Motivationsprofil erstellt. Neben internen Persönlichkeitsfaktoren wie Erfolgs-/Misserfolgsattribuierung, Selbstbewusstsein, Selbstbestimmungsgrad u.a wurde auch das spezielle schwedische Umfeld der Lerner berücksichtigt, so dass auch eine Reihe externer Faktoren in die Untersuchung mit eingingen (z. B. Schulsystem, Kontakt, andere Fremdsprachen). Die explorative Vorgehensweise der Studie knüpfte dabei an die bestehenden Theorien und Annahmen der Motivationsforschung an und ermöglichte es darüber hinaus, der Individualität der Untersuchungsteilnehmer und dem speziellen schwedischen Kontext gerecht zu werden. Ziel der Untersuchung war es, neben dem Erstellen individueller Motivationsprofile, durch Vergleich der Profile untereinander, eine Antwort auf die Frage zu finden, in wie weit sich der soziale Kontext (Gesellschaft, Bildungssystem, Medien in Schweden) auf die Motivation der Lerner auswirkt und ob diesbezüglich allgemeine Aussagen möglich sind

Investigation of a standardized qualitative behaviour assessment and exploration of potential influencing factors on the emotional state of dairy calves

open4siopenMarta Brscic , Nina Dam Otten , Barbara Contiero , Marlene Katharina KirchnerBrscic, Marta; Dam Otten, Nina; Contiero, Barbara; Katharina Kirchner, Marlen

Prognostic value of indoleamine 2,3 dioxygenase in patients with higher‐risk myelodysplastic syndromes treated with azacytidine

Hypomethylating agents (HMAs) are widely used in patients with higher‐risk myelodysplastic syndromes (MDS) not eligible for stem cell transplantation; however, the response rate is <50%. Reliable predictors of response are still missing, and it is a major challenge to develop new treatment strategies. One current approach is the combination of azacytidine (AZA) with checkpoint inhibitors; however, the potential benefit of targeting the immunomodulator indoleamine‐2,3‐dioxygenase (IDO‐1) has not yet been evaluated. We observed moderate to strong IDO‐1 expression in 37% of patients with high‐risk MDS. IDO‐1 positivity was predictive of treatment failure and shorter overall survival. Moreover, IDO‐1 positivity correlated inversely with the number of infiltrating CD8+ T cells, and IDO‐1+ patients failed to show an increase in CD8+ T cells under AZA treatment. In vitro experiments confirmed tryptophan catabolism and depletion of CD8+ T cells in IDO‐1+ MDS, suggesting that IDO‐1 expression induces an immunosuppressive microenvironment in MDS, thereby leading to treatment failure under AZA treatment. In conclusion, IDO‐1 is expressed in more than one‐third of patients with higher‐risk MDS, and is predictive of treatment failure and shorter overall survival. Therefore, IDO‐1 is emerging as a promising predictor and therapeutic target, especially for combination therapies with HMAs or checkpoint inhibitors

Systematic Analysis of Double-Ionization Dynamics Based on Four-Body Dalitz Plots

We report on an experimental and theoretical systematic study of double ionization of helium by ion impact in terms of four-particle Dalitz plots. Several collision systems covering abroad range of perturbation parameters η (projectile charge to speed ratio) were investigated. With increasing η we observe a systematic trend from features, characteristic to correlated double-ionization mechanisms, to signatures of higher-order processes not requiring electron-electron correlations [the mechanism called two-step-two projectile-electron interaction (TS-2)]. The data for the largest η can qualitatively be amazingly well described by a simple model only including the TS-2 mechanism

Can Radiomics Provide Additional Information in [F-18]FET-Negative Gliomas?

Simple Summary Amino acid positron emission tomography (PET) complements standard magnetic resonance imaging (MRI) since it directly visualizes the increased amino acid transport into tumor cells. Amino acid PET using O-(2-[F-18]fluoroethyl)-L-tyrosine ([F-18]FET) has proven to be relevant, for example, for glioma classification, identification of tumor progression or recurrence, or for the delineation of tumor extent. Nevertheless, a relevant proportion of low-grade gliomas (30%) and few high-grade gliomas (5%) were found to show no or even decreased amino acid uptake by conventional visual analysis of PET images. Advanced image analysis with the extraction of radiomic features is known to provide more detailed information on tumor characteristics than conventional analyses. Hence, this study aimed to investigate whether radiomic features derived from dynamic [F-18]FET PET data differ between [F-18]FET-negative glioma and healthy background and thus provide information that cannot be extracted by visual read. The purpose of this study was to evaluate the possibility of extracting relevant information from radiomic features even in apparently [F-18]FET-negative gliomas. A total of 46 patients with a newly diagnosed, histologically verified glioma that was visually classified as [F-18]FET-negative were included. Tumor volumes were defined using routine T2/FLAIR MRI data and applied to extract information from dynamic [F-18]FET PET data, i.e., early and late tumor-to-background (TBR5-15, TBR20-40) and time-to-peak (TTP) images. Radiomic features of healthy background were calculated from the tumor volume of interest mirrored in the contralateral hemisphere. The ability to distinguish tumors from healthy tissue was assessed using the Wilcoxon test and logistic regression. A total of 5, 15, and 69% of features derived from TBR20-40, TBR5-15, and TTP images, respectively, were significantly different. A high number of significantly different TTP features was even found in isometabolic gliomas (after exclusion of photopenic gliomas) with visually normal [F-18]FET uptake in static images. However, the differences did not reach satisfactory predictability for machine-learning-based identification of tumor tissue. In conclusion, radiomic features derived from dynamic [F-18]FET PET data may extract additional information even in [F-18]FET-negative gliomas, which should be investigated in larger cohorts and correlated with histological and outcome features in future studies