Teledermoscopy has shown high diagnostic accuracy (sensitivity 90.48% and specificity 92.57%) for early detection of skin cancer in Estonia. However, not all its potential for early detection has been utilized, contributing to high melanoma mortality rates.
Objective:
This project aims to assess the impact of an integrated approach to patient pathways initiated by teledermoscopy on melanoma management effectiveness, focusing on faster diagnosis confirmation and treatment.
Methodology:
The study will evaluate the smoothness and effectiveness of the patient pathway initiated by teledermoscopy, integrating improvements based on existing requirements and study findings. The primary outcome measure will be the speed of histologically confirmed diagnosis and subsequent treatment.
Result-Hypothesis:
It's hypothesized that the integrated pathway will lead to better melanoma patient outcomes compared to previous studies, ensuring timely diagnosis confirmation and treatment."
In the wake of the COVID-19 pandemic and the ensuing effects on society and the economy, there has been a significant increase in concerns about the possibility that malicious actors could return to using hazardous agents in future plots. These concerns are legitimate in Europe, where there are still technological gaps in several aspects of the CBRN Security Cycle and specifically in the devices for rapid detection, identification and monitoring of low-volatile chemical warfare agents (CWAs) and non-volatile biological warfare agents (BWAs), mainly in complex natural environments. Benchmark technologies, including IMS, GC-IMS, and Py-GC-IMS, can sample and identify the most volatile CWAs within seconds (IMS) or BWAs within minutes (Py-GC-IMS), even at low ppbV concentration levels, but cannot detect extremely low doses of low-volatile toxic fourth generation CWAs (e.g. Novichoks), nor can they differentiate biological fragments from harmless substances. To overcome these gaps, it is necessary to develop new highly selective and sensitive detectors with detection limits in the pptV range, operated at elevated temperatures (> 200 °C) to prevent condensation of low volatile constituents, high 2D resolving power and robust analytical methods. TeChBioT aims for the development of a universal detection technology based on high-temperature (HT) ion mobility spectrometry (IMS) with optional gas chromotographic pre-separation (GC) and pyrolysis (Py) for enabling fast detection and identification of nonvolatile biological and low-volatile chemical agents. The innovative technology is combined with Artificial Intelligence (AI) and Deep Learning (DL) models to reduce the dimensionality of the 2D spectral data and enable distinguishing of bacteria, fungi, viruses, low volatile chemical warfare agents, and toxic industrial compounds at pptV concentration levels based on their unique fingerprint within a complex environment.
Estonia's significant mineral resource, peat, is currently mainly extracted and exported as growth substrates for European agriculture. We offer technological solutions to produce high-value materials from by-products/residue of peat production. We are exploring two different experimental chemical valorization directions for peat. Firstly, the production of carbon nanomaterials (carbon nanoparticles, carbon quantum dots CQD), which have a wide range of applications from biomedicine to optics and electronic components. Examples: bioimaging applications, portable sensors, solar panel components etc. The application of CQDs is rapidly developing and new start-up ideas appear often. Secondly, the production of chemically modified biopolymers as high-performance alternatives to petroleum-derived products such as construction panels, packaging containers or conventional adsorbent materials. The resulting products contribute to long-term carbon sequestration, helping to balance the carbon footprint of the peat industry.
New or reoccurring bacterial threats are a major challenge of this century, and a delayed response due to the lack of field-testing options risks human lives and causing an epidemic. Classical microbiology techniques are relatively slow, while cytometric methods allow the measurement of cell count, morphology etc. in an easy, reliable, and fast way. State of the art flow cytometers are high-throughput benchtop instruments that are neither portable nor cheap enough for field testing, causing logistic delays in bacterial testing in remote areas and conflict zones or where infrastructure is limited. The goal of this R&D activity is to create the proof of concept of and develop the methodology for low-cost, fully portable flow cytometers based on droplet microfluidics, which will not only allow field analysis of bacteria, but will have a single-cell resolution. Furthermore, through cognitive electronics, the system will be easy to use and fully automated from sample input to result output.
Formation of new synapses, and alteration of the strength and stability of existing synapses are regarded as the main cellular basis for memory and long-term behavioral adaptations. Neuronal activity-regulated gene expression plays a crucial role in synaptic development and function, and its deregulation gives rise to various nervous system disorders. Knowledge about the regulatory mechanisms of activity-dependent gene expression is important both for understanding of nervous system function and for finding new drug targets. The aim of this project is to study the molecular mechanisms of neuronal activity-regulated gene expression, including transcription, translation and posttranslational modifications, in the nervous system health and disease. The studies are focused on two genes, the neurotrophin BDNF and the basic helix-loop-helix transcription factor TCF4.
Autonomous driving is no longer just an idea of technology vision, instead a real technical trend all over the world. The continuing development to a further level of autonomy requires more from energy optimization. The optimization of electric propulsion drive systems of self-driving electric vehicles by using autonomous and monitoring sensors are not often discussed. The goal of the proposal is to develop a specialized unsupervised prognosis and control platform for such energy system performance estimation. This goal requires the development of several test platforms and digital twins. A digital twin is composed of three components – the physical entities in the real world, their virtual models, and the connected data/view that ties the two worlds together.
Smart Industry Centre (SmartIC) was created at Tallinn University of Technology (TalTech) and Estonian University of Life Sciences (Institute of Technology) in 2017 to improve collaboration in research and development and use of distributed infrastructure in the field of Industry 4.0 - robotics, mechatronics, additive manufacturing, product quality control and related fields of IT (especially artificial intelligence). In 2018, Institute of Technology of University of Tartu joined in collaboration (mainly in the field of robotics). In 2017-2020 several new labs were opened (FMS and Robotics Lab, Industrial Virtual and Augmented Reality Lab, Additive Manufacturing Lab/ ProtoLab, Computer Tomography Lab for quality control, etc). Several new ERF and H2020 funded projects were initiated and launched in 2017-2020.