Automated Classification of Written Proficiency Levels on the CEFR-Scale through Complexity Contours and RNNs

Automatically predicting the level of second language (L2) learner proficiency is an emerging topic of interest and research based on machine learning approaches to language learning and development. The key to the present paper is the combined use of what we refer to as ‘complexity contours’, a series of measurements of indices of L2 proficiency obtained by a computational tool that implements a sliding window technique, and recurrent neural network (RNN) classifiers that adequately capture the sequential information in those contours. We used the EF-Cambridge Open Language Database (Geertzen et al. 2013) with its labelled Common European Framework of Reference (CEFR) levels (Council of Europe 2018) to predict six classes of L2 proficiency levels (A1, A2, B1, B2, C1, C2) in the assessment of writing skills. Our experiments demonstrate that an RNN classifier trained on complexity contours achieves higher classification accuracy than one trained on text-average complexity scores. In a secondary experiment, we determined the relative importance of features from four distinct categories through a sensitivity-based pruning technique. Our approach makes an important contribution to the field of automated identification of language proficiency levels, more specifically, to the increasing efforts towards the empirical validation of CEFR levels

C-IPS: Specifying decision interdependencies in negotiations

Abstract. Negotiation is an important mechanism of coordination in multiagent systems. Contrary to early conceptualizations of negotiating agents, we believe that decisions regarding the negotiation issue and the negotiation partner are equally important as the selection of negotiation steps. Our C-IPS approach considers these three aspects as separate decision processes. It requires an explicit specification of interdependencies between them. In this article we address the task of specifying the dynamic interdependencies by means of IPS dynamics. Thereby we introduce a new level of modeling negotiating agents that is above negotiation mechanism and protocol design. IPS dynamics are presented using state charts. We define some generally required states, predicates and actions. We illustrate the dynamics by a simple example. The example is first specified for an idealized scenario and is then extended to a more realistic model that captures some features of open multiagent systems. The well-structured reasoning process for negotiating agents enables more comprehensive and hence more flexible architectures. The explicit modeling of all involved decisions and dependencies eases the understanding, evaluation, and comparison of different approaches to negotiating agents.

Evidence for Distinct Mechanisms in the Shaping of the CD4 T Cell Repertoire in Histologically Distinct Myasthenia Gravis – Associated Thymomas

The major histocompatibility complex (MHC) class II is involved both in thymocyte maturation and peptide presentation and might thus play a key role in the pathogenesis of paraneoplastic myasthenia gravis (MG) in thymomas. To further investigate this issue, we analyzed and scored the expression of epithelial class II expression in 35 thymomas (medullary, MDT; mixed, MXT; cortical and well differentiated thymic carcinoma, CT / WDTC) and correlated it with the histological tumor subtype, prevalence of MG and thymocyte maturation, which was analyzed by flow cytometry and RT-PCR. Our results show that both MHC class II expression and thymocyte maturation are highly dependent on the histological tumor subtype. CT / WDTC retain features of the normal outer thymic cortex, namely substantial MHC class II expression together with normal early thymocyte maturation until late phases of positive selection, but disturbed terminal thymopoiesis. By contrast, MDT and MXT retain features of the normal inner cortex and the medulla with low to absent class II expression and highly abnormal early thymocyte maturation including impaired positive selection, while terminal T cell maturation in MXT appeared undisturbed. There was no correlation between MHC class II expression and MG status for a given tumor subtype. In conclusion, our results provide evidence for a different histogenesis of cortical thymomas and well differentiated carcinomas on the one hand and mixed and medullary thymomas on the other

Activation of CD44/PAK1/AKT signaling promotes resistance to FGFR1 inhibition in squamous-cell lung cancer

Lung cancer is the leading cause of cancer-related deaths worldwide. Fibroblast growth factor receptor 1 (FGFR1) gene amplification is one of the most prominent and potentially targetable genetic alterations in squamous-cell lung cancer (SQCLC). Highly selective tyrosine kinase inhibitors have been developed to target FGFR1; however, resistance mechanisms originally existing in patients or acquired during treatment have so far led to limited treatment efficiency in clinical trials. In this study we performed a wide-scale phosphoproteomic mass-spectrometry analysis to explore signaling pathways that lead to resistance toward FGFR1 inhibition in lung cancer cells that display (i) intrinsic, (ii) pharmacologically induced and (iii) mutationally induced resistance. Additionally, we correlated AKT activation to CD44 expression in 175 lung cancer patient samples. We identified a CD44/PAK1/AKT signaling axis as a commonly occurring resistance mechanism to FGFR1 inhibition in lung cancer. Co-inhibition of AKT/FGFR1, CD44/FGFR1 or PAK1/FGFR1 sensitized ‘intrinsically resistant’ and ‘induced-resistant’ lung-cancer cells synergetically to FGFR1 inhibition. Furthermore, strong CD44 expression was significantly correlated with AKT activation in SQCLC patients. Collectively, our phosphoproteomic analysis of lung-cancer cells resistant to FGFR1 inhibitor provides a large data library of resistance-associated phosphorylation patterns and leads to the proposal of a common resistance pathway comprising CD44, PAK1 and AKT activation. Examination of CD44/PAK1/AKT activation could help to predict response to FGFR1 inhibition. Moreover, combination between AKT and FGFR1 inhibitors may pave the way for an effective therapy of patients with treatment-resistant FGFR1-dependent lung cancer

Elucidation of tonic and activated B-cell receptor signaling in Burkitt's lymphoma provides insights into regulation of cell survival.

Burkitt's lymphoma (BL) is a highly proliferative B-cell neoplasm and is treated with intensive chemotherapy that, because of its toxicity, is often not suitable for the elderly or for patients with endemic BL in developing countries. BL cell survival relies on signals transduced by B-cell antigen receptors (BCRs). However, tonic as well as activated BCR signaling networks and their relevance for targeted therapies in BL remain elusive. We have systematically characterized and compared tonic and activated BCR signaling in BL by quantitative phosphoproteomics to identify novel BCR effectors and potential drug targets. We identified and quantified ∼16,000 phospho-sites in BL cells. Among these sites, 909 were related to tonic BCR signaling, whereas 984 phospho-sites were regulated upon BCR engagement. The majority of the identified BCR signaling effectors have not been described in the context of B cells or lymphomas yet. Most of these newly identified BCR effectors are predicted to be involved in the regulation of kinases, transcription, and cytoskeleton dynamics. Although tonic and activated BCR signaling shared a considerable number of effector proteins, we identified distinct phosphorylation events in tonic BCR signaling. We investigated the functional relevance of some newly identified BCR effectors and show that ACTN4 and ARFGEF2, which have been described as regulators of membrane-trafficking and cytoskeleton-related processes, respectively, are crucial for BL cell survival. Thus, this study provides a comprehensive dataset for tonic and activated BCR signaling and identifies effector proteins that may be relevant for BL cell survival and thus may help to develop new BL treatments