1. Imaging of human glioblastoma cells and their interactions with mesenchymal stem cells in the zebrafish (Danio rerio) embryonic brainMiloš Vittori, Barbara Breznik, Tajda Gredar, Katja Hrovat, Lilijana Bizjak-Mali, Tamara Lah Turnšek, 2016, original scientific article Abstract: Background
An attractive approach in the study of human cancers is the use of transparent zebrafish (Danio rerio) embryos, which enable the visualization of cancer progression in a living animal.
Materials and methods
We implanted mixtures of fluorescently labeled glioblastoma (GBM) cells and bonemarrow-derived mesenchymal stem cells (MSCs) into zebrafish embryos to study the cellular pathways of their invasion and the interactions between these cells in vivo.
Results
By developing and applying a carbocyanine-dye-compatible clearing protocol for observation of cells in deep tissues, we showed that U87 and U373 GBM cells rapidly aggregated into tumor masses in the ventricles and midbrain hemispheres of the zebrafish embryo brain, and invaded the central nervous system, often using the ventricular system and the central canal of the spinal cord. However, the GBM cells did not leave the central nervous system. With co-injection of differentially labeled cultured GBM cells and MSCs, the implanted cells formed mixed tumor masses in the brain. We observed tight associations between GBM cells and MSCs, and possible cell-fusion events. GBM cells and MSCs used similar invasion routes in the central nervous system.
Conclusions
This simple model can be used to study the molecular pathways of cellular processes in GBM cell invasion, and their interactions with various types of stromal cells in double or triple cell co-cultures, to design anti-GBM cell therapies that use MSCs as vectors.
Keywords: brain tumors, tumor microenvironment, animal models, xenotransplantation
Published in DiRROS: 25.07.2024; Views: 122; Downloads: 140
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2. A ǂFramework for applying data-driven AI/ML models in reliabilityRok Hribar, Margarita Antoniou, Gregor Papa, 2024, independent scientific component part or a chapter in a monograph Abstract: In this chapter, we present a framework for applying artificial intelligence (AI)/machine learning (ML) in reliability, in the context of the iRel40 project. Data-driven models are becoming an increasingly fruitful tool for detecting patterns in complex data and identifying the circumstances in which they occur. Using only data, gathered along the value chain, data-driven methods are now being used to detect indications of potential early failures, signs of wear out or degradation, and other unwanted events within the development, fabrication, or service phases of the electronic components and systems. We present general considerations that were found to be important during the iRel40 project, when designing pipelines that combine data processing with the AI/ML models for predicting or detecting reliability issues. This chapter serves as an introduction to the definitions and concepts used within the specific use cases that rely on the AI/ML methodology within the iRel40 project.
Keywords: machine learning, artificial intelligence, data-driven models
Published in DiRROS: 23.07.2024; Views: 86; Downloads: 38
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3. Reliability improvements for in-wheel motorGašper Petelin, Rok Hribar, Stane Ciglarič, Jernej Herman, Anton Biasizzo, Peter Korošec, Gregor Papa, 2024, independent scientific component part or a chapter in a monograph Abstract: Setting up a reliable electric propulsion system in the automotive sector requires an intelligent condition monitoring device capable of reliably assessing the state and the health of the electric motor. To allow for a massive integration of such monitoring devices, they must be inexpensive and small. These requirements limit their accuracy. However, we show in this chapter that these limitations can be significantly reduced by appropriate processing of the sensor data. We have used machine learning models (random forest and XGBoost) to transform very noisy motor winding insulation resistance measurements made by a low-cost device into a much more reliable value that can compete with measurements made by a high-priced state-of-the-art measurement system. The proposed method is an important building block for a future smart condition monitoring system and enables a cost-effective and accurate assessment of the condition of electric motor health in connection with the condition of their winding insulation.
Keywords: machine learning models, low-cost device, electric motor
Published in DiRROS: 23.07.2024; Views: 121; Downloads: 49
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4. Multi-platform, high-resolution study of a complex coastal system : the TOSCA experiment in the Gulf of TriesteStefano Querin, Simone Cosoli, Riccardo Gerin, Célia Laurent, Vlado Malačič, Neva Pristov, Pierre-Marie Poulain, 2021, original scientific article Abstract: Abstract
Although small in size, the Gulf of Trieste (GoT), a marginal coastal basin in the northern Adriatic Sea, is characterized by very complex dynamics and strong variability of its oceanographic conditions. In April–May 2012, a persistent, large-scale anticyclonic eddy was observed in the GoT. This event was captured by both High Frequency Radar (HFR) and Lagrangian drifter observations collected within the European MED TOSCA (Tracking Oil Spill and Coastal Awareness) project. The complexity of the system and the variety of forcing factors constitute major challenges from a numerical modeling perspective when it comes to simulating the observed features. In this study, we implemented a high-resolution hydrodynamic model in an attempt to reproduce and analyze the observed basin-wide eddy structure and determine its drivers. We adopted the Massachusetts Institute of Technology General Circulation Model (MITgcm), tailored for the GoT, nested into a large-scale simulation of the Adriatic Sea and driven by a tidal model, measured river freshwater discharge data and surface atmospheric forcing. Numerical results were qualitatively and quantitatively evaluated against HFR surface current maps, Lagrangian drifter trajectories and thermohaline data, showing good skills in reproducing the general circulation, but failing in accurately tracking the drifters. Model sensitivity to different forcing factors (wind, river and tides) was also assessed.
Keywords: Adriatic Sea, surface circulation, HF coastal radars, Lagrangian drifters, wind-driven currents, ocean circulation models
Published in DiRROS: 19.07.2024; Views: 103; Downloads: 93
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5. Breast cancer risk based on adapted IBIS prediction model in Slovenian women aged 40-49 years : coul it be better?Tjaša Oblak, Vesna Zadnik, Mateja Krajc, Katarina Lokar, Janez Žgajnar, 2020, original scientific article Keywords: breast surgery, IBIS, prediction models, risk factors
Published in DiRROS: 12.07.2024; Views: 123; Downloads: 58
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6. Imaging of human glioblastoma cells and their interactions with mesenchymal stem cells in the zebrafish (Danio rerio) embryonic brainMiloš Vittori, Barbara Breznik, Tajda Gredar, Katja Hrovat, Lilijana Bizjak-Mali, Tamara Lah Turnšek, 2016, original scientific article Keywords: brain tumors, tumor microenvironment, animal models, xenotransplantation
Published in DiRROS: 09.05.2024; Views: 237; Downloads: 482
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7. Qualitative analysis of the minimal Higgins model of glycolysisBrigita Ferčec, Matej Mencinger, Tatjana Petek, Orhan Ozgur Aybar, Ilknur Kusbeyzi Aybar, 2023, original scientific article Abstract: Glycolysis, one of the leading metabolic pathways, involves many
different periodic oscillations emerging at positive steady states of
the biochemical models describing this essential process. One of
the models employing the molecular diffusion of intermediates is
the Higgins biochemical model to explain sustained oscillations. In
this paper, we investigate the center-focus problem for the minimal
Higgins model for general values of the model parameters with the
help of computational algebra. We demonstrate that the model
always has a stable focus point by finding a general form of the first
Lyapunov number. Then, varying two of the model parameters, we
obtain the first three coefficients of the period function for the stable focus point of the model and prove that the singular point is actually a bi-weak monodromic equilibrium point of type $[1, 2]$. Additionally, we prove that there are two (small) intervals for a chosen parameter $a > 0$ for which one critical period bifurcates from this singular point after small perturbations.
Keywords: biological processes, biochemical models, glycolysis
Published in DiRROS: 18.03.2024; Views: 290; Downloads: 123
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8. Enhancing circular business model implementation in pulp and paper industry (PPI) : a phase-based implementation guide to waste valorisation strategiesaAmaia Sopelana, Asier Oleaga, Juan José Cepriá, Karmen Fifer Bizjak, Helena Paiva, Francisco-Javier Rios-Davila, Adriana H. Martinez, Antonio Cañas, 2023, original scientific article Abstract: Innovation in the circular economy (CE) and the deployment of effective circular business models (CBM) have attracted significant attention in times of growing natural resource scarcity. Despite this widespread interest, significant challenges remain between theoretical innovations and effective CBM implementation in any industrial sector where companies pursue cost-saving opportunities through waste valorisation strategies. Since current methods mislead in terms of the real limitations to designing feasible novel products and services under a circular economy, this study proposes exploring determinants underpinning the organisational resilience of CBMs under a resource efficiency strategy through three case studies. As a result of a co-creation process, the implementation of a CBM framework was built upon empirical data and, thence, a phase-based implementation guide was laid out to assist companies in designing and implementing innovative CBM dealing with the complexity of innovative waste valorisation strategies between the PPI and construction sectors. Relevant findings on managerial and policy recommendations encountered along the demo stage are provided in this paper favouring an effective implementation of CE strategies: the role of technological and non-technological aspects within the CBM, the perspective of the ecosystem and its value proposition, and specific guidelines for the different phases of CBM life cycle.
Keywords: circular business models (CBMs), resource recovery, waste valorisation, strategic management, pulp and paper industry (PPI), construction sector
Published in DiRROS: 13.12.2023; Views: 386; Downloads: 183
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9. Assessing the generalizability of a performance predictive modelAna Nikolikj, Gjorgjina Cenikj, Gordana Ispirova, Diederick Vermetten, Ryan Dieter Lang, Andries Petrus Engelbrecht, Carola Doerr, Peter Korošec, Tome Eftimov, 2023, published scientific conference contribution Keywords: algorithms, predictive models, machine learning
Published in DiRROS: 15.09.2023; Views: 513; Downloads: 338
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10. Makroekonomski učinki proizvodnje in predelave lesa listavcevDomen Arnič, Peter Prislan, Luka Juvančič, 2023, original scientific article Abstract: As far as the utilization of the value-added potential of hardwood assortments is concerned, we have considerable reserves in Slovenia. These could be exploited mainly by increasing the economic use of roundwood in Slovenia and by developing more technologically advanced processing methods for roundwood. The aim of this paper is to assess the untapped potential of the forest-wood chain in Slovenia using input-output models, focusing on the use of hardwood. For the whole forest-wood chain, we assessed the existing situation and tested five scenarios for the improvement of the forest-wood chain in Slovenia. We developed a national input-output model to evaluate possible scenarios for the future development of the wood-based bioeconomy. The results of scenario analysis of the input-output model show that the Slovenian wood-based bioeconomy can achieve up to 20% higher production value, a 24% increase in employment and 19% increase in household income in the future through restructuring of economic activities. In the paper, we discuss how upgrading the forestry and wood-processing industry (according to the defined scenarios) could be achieved by increasing the processing capacity of hardwoods and provide recommendations for decision makers.
Keywords: forest- and wood-based bioeconomy, hardwoods utilization, input-output models, wood processing industry, scenario analysis, mobilization of hardwoods
Published in DiRROS: 03.08.2023; Views: 530; Downloads: 287
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