23 research outputs found

    Molecular basis and therapeutic targets in prostate cancer: A comprehensive review

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    Prostate cancer is one of the most significant causes of morbidity and mortality in male patients. The incidence increases with age, and it is higher among African Americans. The occurrence of prostate cancer is associated with many risk factors, including genetic and hereditary predisposition. The most common genetic syndromes associated with prostate cancer risk are BRCA-associated hereditary breast and ovarian cancer (HBOC) and Lynch syndrome. Local-regional therapy, i.e., surgery is beneficial in early-stage prostate cancer management. Advanced and metastatic prostate cancers require systemic therapies, including hormonal inhibition, chemotherapy, and targeted agents. Most prostate cancers can be treated by targeting the androgen-receptor pathway and decreasing androgen production or binding to androgen receptors (AR). Castration-resistant prostate cancer (CRPC) usually involves the PI3K/AKT/mTOR pathway and requires targeted therapy. Specific molecular therapy can target mutated cell lines in which DNA defect repair is altered, caused by mutations of BRCA2, partner and localizer of BRCA2 (PALB2), and phosphatase and tensin homolog (PTEN) or the transmembrane protease serine 2-ERG (TMPRSS2-ERG) fusion. Most benefits were demonstrated in cyclin dependent-kinase 12 (CDK12) mutated cell lines when treated with anti-programmed cell death protein 1 (PD1) therapy. Therapies targeting p53 and AKT are the subject of ongoing clinical trials. Many genetic defects are listed as diagnostic, prognostic, and clinically actionable markers in prostate cancer. Androgen receptor splice variant 7 (AR-V7) is an important oncogenic driver and an early diagnostic and prognostic marker, as well as a therapeutic target in hormone-resistant CRPC. This review summarizes the pathophysiological mechanisms and available targeted therapies for prostate cancer

    The 42nd Symposium Chromatographic Methods of Investigating Organic Compounds : Book of abstracts

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    The 42nd Symposium Chromatographic Methods of Investigating Organic Compounds : Book of abstracts. June 4-7, 2019, Szczyrk, Polan

    A Lightweight Deep Learning Approach for Liver Segmentation

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    Liver segmentation is a prerequisite for various hepatic interventions and is a time-consuming manual task performed by radiology experts. Recently, various computationally expensive deep learning architectures tackled this aspect without considering the resource limitations of a real-life clinical setup. In this paper, we investigated the capabilities of a lightweight model, UNeXt, in comparison with the U-Net model. Moreover, we conduct a broad analysis at the micro and macro levels of these architectures by using two training loss functions: soft dice loss and unified focal loss, and by substituting the commonly used ReLU activation function, with the novel Funnel activation function. An automatic post-processing step that increases the overall performance of the models is also proposed. Model training and evaluation were performed on a public database—LiTS. The results show that the UNeXt model (Funnel activation, soft dice loss, post-processing step) achieved a 0.9902 dice similarity coefficient on the whole CT volumes in the test set, with 15× fewer parameters in nearly 4× less inference time, compared to its counterpart, U-Net. Thus, lightweight models can become the new standard in medical segmentation, and when implemented thoroughly can alleviate the computational burden while preserving the capabilities of a parameter-heavy architecture

    Minority protection and kin-state engagement: Karta Polaka in comparative perspective

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    In this article, the authors propose a new normative approach that recognises and responds more adequately to the quadratic political reality of kin-state—kin minorities relations. The authors’ point of departure is the dual contention that home-states have the primary duty to achieve full and effective equality between their citizens, while accommodating fairly their internal cultural and linguistic diversity; and that kin-states have a legitimate interest in their co-ethnics abroad. Building on this foundation, the authors argue that kin-state engagement should complement home-states’ domestic commitments to cultural justice, in order to foster more effective minority protection. The authors conclude by outlining a concept of shared responsibility for minority protection between kin-state and home-states

    A Lightweight Deep Learning Approach for Liver Segmentation

    No full text
    Liver segmentation is a prerequisite for various hepatic interventions and is a time-consuming manual task performed by radiology experts. Recently, various computationally expensive deep learning architectures tackled this aspect without considering the resource limitations of a real-life clinical setup. In this paper, we investigated the capabilities of a lightweight model, UNeXt, in comparison with the U-Net model. Moreover, we conduct a broad analysis at the micro and macro levels of these architectures by using two training loss functions: soft dice loss and unified focal loss, and by substituting the commonly used ReLU activation function, with the novel Funnel activation function. An automatic post-processing step that increases the overall performance of the models is also proposed. Model training and evaluation were performed on a public database—LiTS. The results show that the UNeXt model (Funnel activation, soft dice loss, post-processing step) achieved a 0.9902 dice similarity coefficient on the whole CT volumes in the test set, with 15× fewer parameters in nearly 4× less inference time, compared to its counterpart, U-Net. Thus, lightweight models can become the new standard in medical segmentation, and when implemented thoroughly can alleviate the computational burden while preserving the capabilities of a parameter-heavy architecture

    Senior Citizens and the European Union. A Romanian Perspective

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    The general goal of this paper is to study senior Romanian citizens’ EU attitudes after ten years of European membership, with a special focus on the unsolved tension between the instrumental and symbolic perspectives. By looking at the present context, the purpose of this research is to assess the challenges and transformations of the EU-related opinions and support of traditional euro-enthusiastic citizens in times of vulnerability and struggling economies. Equally, the paper favours a future-oriented view, and puts under scrutiny people’s expectations and evaluations of the future developments of the EU and their consequences at personal, national and supra-national level

    Karta Polaka, Poland and its co-ethnics abroad

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    The Role of Host-Universities in the Process of Erasmus Students’ Intercultural Adaptation

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    Within the general framework of the internationalization of higher education, this paper brings forward the role of host-universities in facilitating the intercultural adaptation of Erasmus students. In line with Kim’s (2001, 2005) theoretical approach, the general premise that we build our research on is that the more universities involve in organizing activities which encourage communication and social relationships for the visiting students, the easier the adaptive process to the new socio-cultural medium would be for them. Based on 20 in-depth interviews with Romanian students aged between 19 and 23, who went on an Erasmus programme of 4 to 8 months in different European countries, we discuss which were the main facilitators and barriers that they had to cope with during their mobility sojourn. Although the results show a low level of host-universities engagement in facilitating the adaptive process of visiting students, we lay stress on how universities can approach this process as a win-win relation and which are the short-term and long-term implications on both individual and organizational level
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