Self-tuning Personalized Information Retrieval in an Ontology-Based Framework

Reliability is a well-known concern in the field of personalization technologies. We propose the extension of an ontology-based retrieval system with semantic-based personalization techniques, upon which automatic mechanisms are devised that dynamically gauge the degree of personalization, so as to benefit from adaptivity but yet reduce the risk of obtrusiveness and loss of user control. On the basis of a common domain ontology KB, the personalization framework represents, captures and exploits user preferences to bias search results towards personal user interests. Upon this, the intensity of personalization is automatically increased or decreased according to an assessment of the imprecision contained in user requests and system responses before personalization is applied

Question Answering on Scholarly Knowledge Graphs

Answering questions on scholarly knowledge comprising text and other artifacts is a vital part of any research life cycle. Querying scholarly knowledge and retrieving suitable answers is currently hardly possible due to the following primary reason: machine inactionable, ambiguous and unstructured content in publications. We present JarvisQA, a BERT based system to answer questions on tabular views of scholarly knowledge graphs. Such tables can be found in a variety of shapes in the scholarly literature (e.g., surveys, comparisons or results). Our system can retrieve direct answers to a variety of different questions asked on tabular data in articles. Furthermore, we present a preliminary dataset of related tables and a corresponding set of natural language questions. This dataset is used as a benchmark for our system and can be reused by others. Additionally, JarvisQA is evaluated on two datasets against other baselines and shows an improvement of two to three folds in performance compared to related methods.Comment: Pre-print for TPDL2020 accepted full paper, 14 page

Using graph-kernels to represent semantic information in text classification

Most text classification systems use bag-of-words represen- tation of documents to find the classification target function. Linguistic structures such as morphology, syntax and semantic are completely ne- glected in the learning process. This paper proposes a new document representation that, while includ- ing its context independent sentence meaning, is able to be used by a structured kernel function, namely the direct product kernel. The proposal is evaluated using a dataset of articles from a Portuguese daily newspaper and classifiers are built using the SVM algorithm. The results show that this structured representation, while only partially de- scribing document’s significance has the same discriminative power over classes as the traditional bag-of-words approach

Viral transduction of primary human lymphoma B cells reveals mechanisms of NOTCH-mediated immune escape

Hotspot mutations in the PEST-domain of NOTCH1 and NOTCH2 are recurrently identified in B cell malignancies. To address how NOTCH-mutations contribute to a dismal prognosis, we have generated isogenic primary human tumor cells from patients with Chronic Lymphocytic Leukemia (CLL) and Mantle Cell Lymphoma (MCL), differing only in their expression of the intracellular domain (ICD) of NOTCH1 or NOTCH2. Our data demonstrate that both NOTCH-paralogs facilitate immune-escape of malignant B cells by up-regulating PD-L1, partly dependent on autocrine interferon-? signaling. In addition, NOTCH-activation causes silencing of the entire HLA-class II locus via epigenetic regulation of the transcriptional co-activator CIITA. Notably, while NOTCH1 and NOTCH2 govern similar transcriptional programs, disease-specific differences in their expression levels can favor paralog-specific selection. Importantly, NOTCH-ICD also strongly down-regulates the expression of CD19, possibly limiting the effectiveness of immune-therapies. These NOTCH-mediated immune escape mechanisms are associated with the expansion of exhausted CD8+ T cells in vivo.© 2022. The Author(s)

Stromal cell protein kinase C-β inhibition enhances chemosensitivity in B cell malignancies and overcomes drug resistance.

Overcoming drug resistance remains a key challenge to cure patients with acute and chronic B cell malignancies. Here, we describe a stromal cell-autonomous signaling pathway, which contributes to drug resistance of malignant B cells. We show that protein kinase C (PKC)-β-dependent signals from bone marrow-derived stromal cells markedly decrease the efficacy of cytotoxic therapies. Conversely, small-molecule PKC-β inhibitors antagonize prosurvival signals from stromal cells and sensitize tumor cells to targeted and nontargeted chemotherapy, resulting in enhanced cytotoxicity and prolonged survival in vivo. Mechanistically, stromal PKC-β controls the expression of adhesion and matrix proteins, required for activation of phosphoinositide 3-kinases (PI3Ks) and the extracellular signal-regulated kinase (ERK)-mediated stabilization of B cell lymphoma-extra large (BCL-XL) in tumor cells. Central to the stroma-mediated drug resistance is the PKC-β-dependent activation of transcription factor EB, regulating lysosome biogenesis and plasma membrane integrity. Stroma-directed therapies, enabled by direct inhibition of PKC-β, enhance the effectiveness of many antileukemic therapies.This work was funded by Cancer Research UK (CRUK; C49940/A17480). I.R. is a senior CRUK fellow. M.S.S is supported by the DFG through SCHM2440/7-1 and CRC1243 (A12). L.G. & O.W. received funding from CWCUK (grant 14-169) and GOSHCC (grant V2617). A.E. receives research grants from the Austrian Science Fund (FWF; Transcan I2795-B28 to A.E. (FIRE-CLL), DACH grants I3282-B26 and I1299-B21 (FOR2036) and a grant from the Paracelsus Medical University (PMU Grant E-13/18/091-EGF). S.S. receives funding from the DFG (SFB1074 , project B1), relevant to this work

Viral transduction of primary human lymphoma B cells reveals mechanisms of NOTCH-mediated immune escape

Hotspot mutations in the PEST-domain of NOTCH1 and NOTCH2 are recurrently identified in B cell malignancies. To address how NOTCH-mutations contribute to a dismal prognosis, we have generated isogenic primary human tumor cells from patients with Chronic Lymphocytic Leukemia (CLL) and Mantle Cell Lymphoma (MCL), differing only in their expression of the intracellular domain (ICD) of NOTCH1 or NOTCH2. Our data demonstrate that both NOTCH-paralogs facilitate immune-escape of malignant B cells by up-regulating PD-L1, partly dependent on autocrine interferon-γ signaling. In addition, NOTCH-activation causes silencing of the entire HLA-class II locus via epigenetic regulation of the transcriptional co-activator CIITA. Notably, while NOTCH1 and NOTCH2 govern similar transcriptional programs, disease-specific differences in their expression levels can favor paralog-specific selection. Importantly, NOTCH-ICD also strongly down-regulates the expression of CD19, possibly limiting the effectiveness of immune-therapies. These NOTCH-mediated immune escape mechanisms are associated with the expansion of exhausted CD8+ T cells in vivo