Projects

Europe still sees a quarter of the world's cancer cases each year, making cancer the second leading cause of death and illness in the region after cardiovascular diseases. Unless we take decisive action, lives lost to cancer in the EU are set to increase by more than 24% by 2035, making it the leading cause of death in the EU. Cross-border collaboration can address this challenge by combining data from various modalities and sources, extracting meaningful insights to deepen our understanding of cancer. However, ethical, legal, and national regulations, along with data access processes, including differing interpretations of the EU GDPR create significant hurdles. Technical interoperability issues across European cancer RIs, and patients' and citizens' rights to control who uses their personal information and for what purposes further complicate data sharing. The project will provide European researchers, SMEs, and innovators with a decentralized collaborative network, “UNCAN-CONNECT,” for cancer research. It consists of both technical components, a governance, compliance, and operational framework based on the UNCAN blueprint, with the goal of operationalizing it. The objective is to facilitate access to cancer data, promote open science, and revolutionize cancer research and treatment by co-creating an open-source federation of federations platform. It will be developed using specific use cases focused on six major cancer types: Paediatric, Lymphoid malignancies, Pancreatic cancer, Ovarian, Lung, and Prostate cancers and active collaboration with a diverse range of stakeholders,including researchers, SMEs, industrial end users, and citizens. It will build on existing European RIs such as BBMRI as well as initiatives like EOSC4CANCER, CanSERV, EUCAIM, to enable seamless storage, access, sharing, and processing of data across Member States and associated countries. This approach will foster interoperability and collaboration, accelerating progress in cancer research. This action is part of the Cancer Mission clusters of projects 'Understanding' established in 2022.

Brain diseases commonly include neurological, neurosurgical and neuropsychiatric diseases. These are costly to the society accounting for almost a third of all health losses. Despite the science advances, no treatments have been found to restore the often irreversible damaged nervous system, thus calling for improving early diagnosis. Brain diseases as diverse as schizophrenia, Parkinson's disease and now the long-term effects of COVID-19 on the brain show clear involvement of the immune system. However, our characterization of systemic immunity in brain disease is severely lacking. We have recently developed mimotope variation analysis (MVA), a multiplex assay to measure antibody-mediated immune response at a high resolution. Here, we seek by using this approach to uncover immunological mechanisms that contribute to the neuropathologies. Findings from these studies would greatly increase our knowledge on brain disease and provide new avenues for diagnosis and therapy.

DNA replication is one of the major targets of cancer therapies, as cancer cells tend to proliferate faster than normal cells and are generally more prone to replication stress. Most of our current knowledge about DNA replication initiation, or origin firing, currently comes from model organisms, such as yeast, but their applicability to the human system is limited. It is important to study replication initiation in human cells in order to be able to exploit the findings in cancer therapies. The main objectives of this project are to identify novel players in various stages of human replication initiation and characterize the non-catalytic roles of DNA polymerase epsilon and protein Timeless in replisome assembly.

A collaborative and creative atmosphere in the learning process, professional feedback/feed forward, beliefs based on the university's values and systematic self-reflection contribute to achievement of the development goals of the teaching staff and students of Tallinn University of Technology. The aim of this study is to find out: How the lecturer introduces the subject; How the lecturer refers to the learning outcomes and evaluation criteria; Which teaching methods are mostly used by teachers of STEM subjects: What is the average percentage of active learning methods used per lesson; What do students think about the active learning techniques used in the learning process; What is the standard teaching material distributed to students, what teaching material do students prefer; What is the experience of students regarding the involvement in the learning process; What kind of a didactic support does the lecturer need and want the most; What kind of support or help do students need (and want) the most in the learning process; What is the practice of giving feed forward/feedback for teachers, what for students; What examples of good learning and teaching practice can be pointed out in comparison with the top 10 technical universities in the world