Delineation of molecular events that occur in a PKCα-KR-mediated murine model of CLL

Chronic lymphocytic leukaemia (CLL) is the most prevalent leukaemia of the Western world, and despite the recent evolution in clinical treatment of the disease, it remains incurable. Although current therapies such as allogeneic hematopoietic stem cell (HSC) transplantation have been successfully used to treat CLL, this is an option for only a minority, as most CLL patients are diagnosed over the age of sixty and cannot withstand the harsh transplantation procedures. Combination chemotherapy, such as fludarabine and cyclophosphamide, has been shown to significantly improve response rate and prolonged remission in CLL patients, however, no improvement in overall survival has been observed. Patients eventually relapse due to re-emergence of minimal residual disease (MRD). Therefore it is critical that further clinical therapies are investigated in order to eliminate MRD, and offer hope to patients that are unresponsive to current treatments. CLL is marked by the presence of the accumulation of long-lived mature monoclonal B cells in peripheral lymphoid organs, bone marrow and peripheral blood with the specific phenotype of CD19hi, CD5+, CD23+ and IgMlo that resist apoptosis. The in vivo accumulation of leukaemic lymphocytes is highly facilitated by interactions of CLL cells with other cells present in their microenvironment, including stromal cells and soluble factors such as IL4. Studies have established a variety of mechanisms potentially responsible for disease progression in CLL, including chromosomal abnormalities and intrinsic defects in the apoptotic machinery due to higher levels of the anti-apoptotic protein Bcl-2 family member proteins Bcl-2 and Mcl-1, thus making this disease extremely heterogeneous. Although the apoptotic machinery is certainly dysregulated in CLL, it is not simply a disease of a clonal accumulation of B cells, rather, proliferation is occurring as well as apoptosis, accounting for up to 2% of the clone size per day. CLL B cell proliferation centres exist within lymph nodes (LN) and bone marrow (BM) where B cells receive signals from their B cell antigen receptor (BCR) to proliferate, generating a very aggressive form of the disease. In addition, evidence suggests that stimulation through the BCR plays a pivotal role in pathogenesis of CLL since CLL B cells have a phenotypic profile of B cells activated by antigen interaction and a genetic expression profile of antigen experienced B cells. During the course of our studies assessing the impact of modulating protein kinase C (PKC) signaling in B cell development in vitro or in vivo, we developed a unique model system to investigate the mechanisms underlying the induction of CLL. Introduction of full length, catalytically inactive PKCα (PKCα-KR) into HSCs derived from wild type mouse fetal liver (FL), and subsequent culture of the cells either in vitro or in vivo resulted in the generation of a population of B lymphocytes that are phenotypically similar to human CLL cells (CD19hi, CD5+, CD23+, IgMlo). PKCα-KR-expressing FL cells also expressed enhanced proliferative capacity over untransduced cells and were refractory to apoptosis. These results indicate that the subversion of PKCα signaling acts as an oncogenic trigger for developing B lymphocytes. The aim of this project was to identify similarities between our murine CLL (mCLL) model and human CLL and investigate putative translational therapeutic targets. The main findings of this study implicate PKCβII as an important survival and proliferation signal within mCLL. Cyclin D1 is also upregulated within mCLL, linked to an increase in the proliferative capacity of mCLL cells, and is regulated through transcriptional repressor 4EBP1, which appears inactive in both mCLL and human CLL. In addition, PKCα-KR transduced cells harbour the potential for lineage plasticity in a microenvironment-dependent manner, whereby PKCα-KR B cells lineage switch to T cells upon Notch ligation. The reprogramming occurs via a reduction in B cell specific genes and an upregulation of T cell specific genes, implicating the deregulation of PKCα activity/expression as a potential mechanism for lineage trans-differentiation during malignancies. Importantly, in human CLL, PKCα is downregulated at the transcript and protein levels implicating it a tumour suppressor, highlighting the translational capacity of our CLL mouse model

Contrastive Study of Lexical Profiles of International and U.S. Lectures Delivered in English

International academic contexts where English is used as a lingua franca (ELF) have become ubiquitous. ELF lectures have been studied from a number of perspectives, but they have not been lexically profiled. We depart from the assumption that the lexical profile of academic lectures delivered in international settings may differ from that of lectures delivered in Anglophone contexts, and that these differences have pedagogical implications for the teaching and learning of academic English from an ELF-perspective. We lexically profile a corpus of fifty university lectures delivered in English in five European countries and compare them against sixty-two lectures delivered in English in the U.S. We find that 3,000 words are needed for good listening comprehension in both sets of lectures, while ideal comprehension is reached at 11,000 words for international and 7,000 words for U.S. lectures, which suggests differences between the two in terms of variation in low-frequency vocabulary. Some function words are much more frequent in international than in U.S. lectures. International lectures also feature less high-frequency and more mid-frequency academic vocabulary than U.S. lectures. These differences mostly reflect the use of ELF-specific communicative strategies in international lectures. Focusing on them and potentially making academic ELF-specific word lists may ensure the more efficient teaching of academic English from an ELF-perspective

Generation of a poor prognostic chronic lymphocytic leukemia-like disease model: PKC subversion induces up-regulation of PKC II expression in B lymphocytes

Overwhelming evidence identifies the microenvironment as a critical factor in the development and progression of chronic lymphocytic leukemia, underlining the importance of developing suitable translational models to study the pathogenesis of the disease. We previously established that stable expression of kinase dead protein kinase C alpha in hematopoietic progenitor cells resulted in the development of a chronic lymphocytic leukemia-like disease in mice. Here we demonstrate that this chronic lymphocytic leukemia model resembles the more aggressive subset of chronic lymphocytic leukemia, expressing predominantly unmutated immunoglobulin heavy chain genes, with upregulated tyrosine kinase ZAP-70 expression and elevated ERK-MAPK-mTor signaling, resulting in enhanced proliferation and increased tumor load in lymphoid organs. Reduced function of PKCα leads to an up-regulation of PKCβII expression, which is also associated with a poor prognostic subset of human chronic lymphocytic leukemia samples. Treatment of chronic lymphocytic leukemia-like cells with the selective PKCβ inhibitor enzastaurin caused cell cycle arrest and apoptosis both in vitro and in vivo, and a reduction in the leukemic burden in vivo. These results demonstrate the importance of PKCβII in chronic lymphocytic leukemia-like disease progression and suggest a role for PKCα subversion in creating permissive conditions for leukemogenesis

From Chatter to Matter: Addressing Critical Steps of Emotion Recognition Learning in Task-oriented Dialogue

Emotion recognition in conversations (ERC) is a crucial task for building human-like conversational agents. While substantial efforts have been devoted to ERC for chit-chat dialogues, the task-oriented counterpart is largely left unattended. Directly applying chit-chat ERC models to task-oriented dialogues (ToDs) results in suboptimal performance as these models overlook key features such as the correlation between emotions and task completion in ToDs. In this paper, we propose a framework that turns a chit-chat ERC model into a task-oriented one, addressing three critical aspects: data, features and objective. First, we devise two ways of augmenting rare emotions to improve ERC performance. Second, we use dialogue states as auxiliary features to incorporate key information from the goal of the user. Lastly, we leverage a multi-aspect emotion definition in ToDs to devise a multi-task learning objective and a novel emotion-distance weighted loss function. Our framework yields significant improvements for a range of chit-chat ERC models on EmoWOZ, a large-scale dataset for user emotion in ToDs. We further investigate the generalisability of the best resulting model to predict user satisfaction in different ToD datasets. A comparison with supervised baselines shows a strong zero-shot capability, highlighting the potential usage of our framework in wider scenarios.Comment: Accepted by SIGDIAL 202

EmoUS: Simulating User Emotions in Task-Oriented Dialogues

Existing user simulators (USs) for task-oriented dialogue systems only model user behaviour on semantic and natural language levels without considering the user persona and emotions. Optimising dialogue systems with generic user policies, which cannot model diverse user behaviour driven by different emotional states, may result in a high drop-off rate when deployed in the real world. Thus, we present EmoUS, a user simulator that learns to simulate user emotions alongside user behaviour. EmoUS generates user emotions, semantic actions, and natural language responses based on the user goal, the dialogue history, and the user persona. By analysing what kind of system behaviour elicits what kind of user emotions, we show that EmoUS can be used as a probe to evaluate a variety of dialogue systems and in particular their effect on the user's emotional state. Developing such methods is important in the age of large language model chat-bots and rising ethical concerns.Comment: accepted by SIGIR202

CAMELL: Confidence-based Acquisition Model for Efficient Self-supervised Active Learning with Label Validation

Supervised neural approaches are hindered by their dependence on large, meticulously annotated datasets, a requirement that is particularly cumbersome for sequential tasks. The quality of annotations tends to deteriorate with the transition from expert-based to crowd-sourced labelling. To address these challenges, we present \textbf{CAMELL} (Confidence-based Acquisition Model for Efficient self-supervised active Learning with Label validation), a pool-based active learning framework tailored for sequential multi-output problems. CAMELL possesses three core features: (1) it requires expert annotators to label only a fraction of a chosen sequence, (2) it facilitates self-supervision for the remainder of the sequence, and (3) it employs a label validation mechanism to prevent erroneous labels from contaminating the dataset and harming model performance. We evaluate CAMELL on sequential tasks, with a special emphasis on dialogue belief tracking, a task plagued by the constraints of limited and noisy datasets. Our experiments demonstrate that CAMELL outperforms the baselines in terms of efficiency. Furthermore, the data corrections suggested by our method contribute to an overall improvement in the quality of the resulting datasets

ChatGPT for Zero-shot Dialogue State Tracking: A Solution or an Opportunity?

Recent research on dialogue state tracking (DST) focuses on methods that allow few- and zero-shot transfer to new domains or schemas. However, performance gains heavily depend on aggressive data augmentation and fine-tuning of ever larger language model based architectures. In contrast, general purpose language models, trained on large amounts of diverse data, hold the promise of solving any kind of task without task-specific training. We present preliminary experimental results on the ChatGPT research preview, showing that ChatGPT achieves state-of-the-art performance in zero-shot DST. Despite our findings, we argue that properties inherent to general purpose models limit their ability to replace specialized systems. We further theorize that the in-context learning capabilities of such models will likely become powerful tools to support the development of dedicated and dynamic dialogue state trackers.Comment: 13 pages, 3 figures, accepted at ACL 202

Smartphone addiction, sleep quality, depression, anxiety, and stress among medical students

IntroductionStudies consistently link excessive smartphone use to poor sleep quality, depression, anxiety, and stress. This study specifically aimed to investigate these associations among medical students in Belgrade and Nis (Central Serbia).Materials and methodsThe cross-sectional study included a sample of 761 students, who were selected from both the Faculties of Medicine at the University of Belgrade and the University of Nis. Questionnaires, including the International Physical Activity Questionnaire – Short Form (IPAQ-SF), Smartphone Addiction Scale – Short Version (SAS-SV), the Pittsburgh Sleep Quality Index (PSQI), and the Depression, Anxiety, and Stress Scale – 21 items (DASS-21), were completed by the participants. Statistical analysis techniques, such as the Chi-square test, student’s t-test, and logistic regression, were employed to examine the relationship between smartphone addiction, physical activity, sleep quality, depression, anxiety, and stress.ResultsThe findings indicated a prevalence of smartphone addiction among medical students at 21.7%, with rates of 22.9% among males and 21.1% among females. Females exhibited significantly higher scores on the SAS-SV scale compared to males (p = 0.032). Univariate logistic regression analysis revealed significant associations between smartphone addiction and spending over 4 h daily on smartphones (OR = 2.39; p < 0.001), poor sleep quality (OR = 1.65; p = 0,005), as well as elevated levels of stress (OR = 1.75; p = 0.003), anxiety (OR = 2.04; p < 0.001), and depression (OR = 2.29; p < 0.001). Multivariate regression analysis identified spending more than 4 h daily on smartphones (OR = 2.39; p < 0.001) and increased levels of depression (OR = 2.51; p < 0.001) as independent significant factors associated with smartphone addiction.ConclusionThis study sheds light on the prevalence of smartphone addiction among medical students, with spending excessive time on smartphones and higher levels of depression standing out as significant factors. Future research should delve into the underlying mechanisms and causal relationships between smartphone addiction and these psychosocial factors. Understanding these connections will aid in developing effective interventions and strategies to tackle this growing public health concern

Adult haematopoietic stem cells lacking Hif-1α self-renew normally

The haematopoietic stem cell (HSC) pool is maintained under hypoxic conditions within the bone marrow (BM) microenvironment. Cellular responses to hypoxia are largely mediated by hypoxia-inducible factors, Hif-1 and Hif-2. The oxygen-regulated alpha subunits of Hif-1 and Hif-2 (namely, Hif-1α and Hif-2α) form dimers with their stably expressed beta subunits, and control the transcription of downstream hypoxia-responsive genes to facilitate adaptation to low oxygen tension. An initial study concluded that Hif-1α is essential for HSC maintenance, whereby Hif-1α-deficient HSCs lost their ability to self-renew in serial transplantation assays. In another study, we demonstrated that Hif-2α is dispensable for cell-autonomous HSC maintenance, both under steady-state conditions and following transplantation. Given these unexpected findings, we set out to revisit the role of Hif-1α in cell-autonomous HSC functions. Here we demonstrate that inducible acute deletion of Hif-1α has no impact on HSC survival. Notably, unstressed HSCs lacking Hif-1α efficiently self-renew and sustain long-term multilineage haematopoiesis upon serial transplantation. Finally, Hif-1α-deficient HSCs recover normally after hematopoietic injury induced by serial administration of 5-fluorouracil. We therefore conclude that despite the hypoxic nature of the BM microenvironment, Hif-1α is dispensable for cell-autonomous HSC maintenance