Opin vísindi
Opin vísindi er varðveislusafn vísindaefnis og doktorsritgerða í opnum aðgangi á vegum íslenskra háskóla og Landsbókasafns Íslands - Háskólabókasafns.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Opinn aðgangur að rannsóknaniðurstöðum er í samræmi við 10. gr. laga nr. 3/2003 um opinberan stuðning við vísindarannsóknir sem og kröfur innlendra og erlendra rannsóknasjóða. Markmiðið með opnum aðgangi er að niðurstöður rannsókna séu aðgengilegar sem flestum óhindrað og án endurgjalds á rafrænu formi. Vistun í varðveislusafninu er varanleg og ætlað að tryggja aðgang að vísindaefni íslenskra háskóla í opnum aðgangi um ókomna tíð. Varðveislusafnið Opin vísindi er tengt við rannsóknagáttina IRIS og rannsóknaniðurstöður í opnum aðgangi sem eru skráðar í IRIS eru um leið vistaðar og gerðar aðgengilegar til framtíðar í varðveislusafninu. Með því að safna þessu efni saman í eitt safn verður aðgangur að því einfaldur og þægilegur fyrir alla sem vilja kynna sér það og geta þannig notið þess öfluga vísindastarfs sem fram fer í háskólum landsins.
Varðveislusafnið er OpenAIRE / OpenAIREplus samhæft og samrýmist kröfum sem gerðar eru um birtingu rannsóknaniðurstaðna úr verkefnum sem styrkt eru úr evrópsku rannsóknaáætlununum FP7 og H2020.
Varðveislusafnið notar opna hugbúnaðinn DSpace.
Nýlega bætt við
Innovative Diagnostic Approaches for Predicting Knee Cartilage Degeneration in Osteoarthritis Patients : A Radiomics-Based Study
(2025-02) Angelone, Francesca; Ciliberti, Federica Kiyomi; Tobia, Giovanni Paolo; Jónsson, Halldór; Ponsiglione, Alfonso Maria; Gislason, Magnus Kjartan; Tortorella, Francesco; Amato, Francesco; Gargiulo, Paolo; Department of Engineering
Osteoarthritis (OA) is a common joint disease affecting people worldwide, notably impacting quality of life due to joint pain and functional limitations. This study explores the potential of radiomics — quantitative image analysis combined with machine learning — to enhance knee OA diagnosis. Using a multimodal dataset of MRI and CT scans from 138 knees, radiomic features were extracted from cartilage segments. Machine learning algorithms were employed to classify degenerated and healthy knees based on radiomic features. Feature selection, guided by correlation and importance analyses, revealed texture and shape-related features as key predictors. Robustness analysis, assessing feature stability across segmentation variations, further refined feature selection. Results demonstrate high accuracy in knee OA classification using radiomics, showcasing its potential for early disease detection and personalized treatment approaches. This work contributes to advancing OA assessment and is part of the European SINPAIN project aimed at developing new OA therapies.
HeartMAP : A multi-chamber spatial framework for cardiac cell-cell communication
(2025-01) Kgabeng, Tumo; Wang, Lulu; Ngwangwa, Harry; Pandelani, Thanyani; Department of Engineering
Understanding cell-cell communication within and between the four distinct cardiac chambers is fundamental to elucidating cardiac function and disease mechanisms. Each chamber exhibits unique cellular and molecular characteristics that reflect specialised physiological roles, yet existing frameworks for mapping chamber-specific intercellular networks have remained limited. Here, we present HeartMAP (Heart Multi-chamber Analysis Platform), a computational framework that infers cardiac cell-cell communication networks at chamber resolution through integration of single-cell RNA-seq co-expression patterns and ligand-receptor interaction databases. Using a dataset of 287,269 cells from seven healthy human heart donors (Single Cell Portal SCP498), we identified chamber-specific cell populations, communication networks, and therapeutic targets. HeartMAP employs a progressive three-tier analytical approach comprising basic pipeline analysis, advanced communication modelling and multi-chamber atlas construction to reveal both conserved and chamber-specific signalling pathways; cross-chamber correlation analysis demonstrated the highest similarity between ventricles (r = 0.985) and the lowest between left atrium and left ventricle (r = 0.870), reflecting functional specialisation. Communication hub analysis identified atrial cardiomyocytes and adipocytes as key signalling centres with hub scores of 0.037–0.047, while differential expression analysis revealed over 150 significantly different genes per chamber pair. These findings establish a molecular foundation for precision cardiology approaches, enabling chamber-specific therapeutic strategies that could improve treatment outcomes for cardiovascular diseases. HeartMAP is freely available as a Python package than can be installed using “pip install heartmap”, the package's documentation can be found on https://pypi.org/project/heartmap/, it can also be accessed via a user-friendly web interface freely available at https://huggingface.co/spaces/Tumo505/heartmap-cell-analysis.
VALID Care Pathways : A Framework for Meaningful Digital Platform Design
(2025) Schmitz, Lisa; Richert, Elena; Jóhannsdóttir, Kamilla Rún; Arnardottir, Erna Sif; Islind, Anna Sigridur; Department of Engineering; Department of Psychology; Department of Computer Science
Despite the advancement in design, development, and use of digital platforms in general, data-driven platforms and novel use of emerging technologies in healthcare, in particular, have been lagging behind. Sleep is one of the fundamental pillars of health and the cognitive functioning connected to sleep deprivation has, to date, not been researched to a large extent. Moreover, cognitive functioning is usually measured in an in-laboratory setting, although digital measuring at-home would be beneficial. Thus, digitally measuring cognitive functioning over an extended period of time can provide valuable insights into sleep health. Based on findings from a two-year action design research project, dimensions of the design and development of a digital platform to deliver at-home measuring of cognitive functioning were explored. The digital platform was designed with the primary objective of achieving high usability while preserving the validity of relevant clinical measurements. The main contribution of this paper consists of conceptualizing and theorizing care pathways through digital platforms based on our novel findings from co-designing and evaluating the platform with professionals and 55 participants, leading to the formulation of VALID framework to inform the ongoing design and development process of digital platforms of the future.
Synthetic 3D printed tibial plateau with gradient material properties for biomechanical accuracy
(2025) Coato, Damiano; Dolino, Gianmarco; Berardo, Alice; Belluzzi, Elisa; Pozzuoli, Assunta; Ruggieri, Pietro; Carniel, Emanuele Luigi; Gargiulo, Paolo; Department of Engineering
Introduction: This study presents the design and fabrication of a synthetic 3D printed tibial plateau, complete with tibial cartilages, developed to replicate the mechanical behavior of its natural counterpart. Methods: Patient-specific anatomical data were used to design the model, which was fabricated using advanced PolyJet™ multi-material printing. Gradient material properties were integrated within the construct to reproduce the stiffness variations observed in native cartilage. Three different material mixes were developed and tested under indentation loading, and the optimal configuration (Mix 3) was selected based on its mechanical fidelity to biological tissue. Results: Mix 3 successfully reproduced the regional stiffness variations of native tibial cartilage. The instantaneous modulus (IM) of the synthetic cartilage closely matched that of the biological sample, with values of 3.19 (Formula presented.) 1.95 (Formula presented.) vs. 3.31 (Formula presented.) 2.33 (Formula presented.) in the lateral compartment and 3.71 (Formula presented.) 1.38 (Formula presented.) vs. 3.72 (Formula presented.) 2.56 (Formula presented.) in the medial compartment. Statistical analysis confirmed that most regional comparisons showed no significant differences (p (Formula presented.) 0.05), supporting the strong mechanical agreement between synthetic and native cartilage. Conclusion: This study demonstrates the potential of Digital Anatomy materials produced with PolyJet™ technology as a viable method for 3D printing anatomically and mechanically accurate models of the human tibial plateau. Overall, this approach provides a reproducible and ethically sustainable alternative to biological specimens, with implications for preclinical testing, implant design optimization, and the advancement of high-fidelity surgical training models.
Novelle approach to simulating spinal cord stimulation during tSCS using CT images and FEM
(2024-12-01) Árnason, Jón Andri; Gumundsdóttir-Korchai, Ragnhildur; Afework Tesfahunegn, Yonatan; Helgason, Pórur; Department of Engineering
Transcutaneous spinal cord stimulation (tSCS) offers non-invasive relief for chronic pain and improves motor function in spinal cord injured (SCI) patients. However, its mechanisms are not currently fully understood, and patientspecific factors, such as Body mass index (BMI) and age, complicate treatments. This paper aims to understand tSCS better by developing a novel Finite Element Model (FEM) of the human body using CT scans. Three subjects (sex, male, female, male. Age: 26, 27, 64. BMI: 38.9, 24.1, 28.4) underwent a CT scan, performed on a Cannon Aquilion Prime (Slice thickness [mm]: 0.8, Voxel size [mm3]: 0.564, 0.328, 0.527), which imaged the trunk of the body, from top of the abdomen to the bottom of the pelvis. The images were then used in Materialize Mimics Research 21.0 to create 3D images of individual organs, skin, fat, muscles, skeleton, and spinal cord. After pre-processing in Autodesk Meshmixer, the models were converted into solid CAD objects in Ansys SpaceClaim R2021 and combined into a single abdominal model. Ansys Maxwell R2021 was then used for simulations. Five different two-electrode configurations were tested in the prototype phase with a simplified model setup. The positive electrodes were placed over the (Thoracic) T10, T12, (Lumbar) L2 and L4 vertebrae sequentially, with the negative electrode over (Sacral) S2. The simulations took on average 47.4 hours. A marked decline in electrical current penetration depth was observed as the electrodes were placed closer together which was consistent with known current distribution patterns. A preliminary validation test was also performed using a lamb's thigh. Two electrodes were placed a known distance apart and a stimulation was given, needle electrodes were then inserted in a grid-like pattern to obtain voltage values. The setup was recreated and simulated in Ansys Maxwell. The resulting average percent difference was 44.93 ± 33.3 % (5Vpp Square wave) and 35.02 ± 23.38 % (5V DC). In both instances, the highest difference was at the edges of the electrodes and the lowest difference in the midpoint between electrodes. Later versions of FEM models incorporated more organs and had improved on previous mesh generation flaws, but encountered new mesh generation errors which could not be rectified before the conclusion of the master's project. Despite complications, this project has provided a pipeline for creating similar models and shown their usability. Future work will involve overcoming the current mesh generation errors, reducing calculation time, and performing a thorough validation test.
Flokkar í Opnum vísindum
Veldu flokk til að skoða.
- University of Iceland
- University of Akureyri
- Bifröst University
- Hólar University College
- IRIS
- Agricultural University of Iceland
- National and University Library of Iceland
- Iceland University of the Arts