Algoa Progress
ALGOA PROGRESS is a “New Business from Research Ideas” (TUTLI) project funded by Business Finland and the European Regional Development Fund. The project aims to explore the commercial potential of an algorithm that can predict the progression of osteoarthritis. The project seeks to lay both technological and commercial foundations for a novel technology that allows individualized treatment planning for people with, e.g. osteoarthritis. The objective of this type of treatment planning would be to prevent osteoarthritis or to slow down its progression.
The project is based on long-term basic and applied research carried out by the Biophysics of Bone and Cartilage research group (http://luotain.uef.fi/) at the Department of Applied Physics, UEF, as well as on utilising these research findings in computational modelling.
Atte Eskelinen ([email protected])
I am currently a postdoctoral researcher in the fields of musculoskeletal diseases, osteoarthritis, biomechanics, and mechanobiology. My basic research focuses on experimental (explant culture/bioreactor) and computational modeling of cartilage degradation. As a translational research aspect, I am involved in the development of knee joint level mechanobiological models and preparation of clinical data collection from patients with painful osteoarthritis.
My research aims to build understanding of biomechanical and inflammatory mechanisms linked to osteoarthritis and chronic joint pain. The project is a part of an international consortium (MathKOA – The Center for Mathematical modeling of Knee OsteoArthritis, Aalborg University, Aalborg University Hospital, Lund University, UEF) with an overarching aim to develop personalized predictive models of osteoarthritis progression and pain to optimize treatment strategies for pain-free, musculoskeletal healthcare.
Biophysics of Bone and Cartilage (BBC)
Heta Orava ([email protected])
My research interests include contrast-enhanced computed tomography of articular cartilage, segmentation of bone and cartilage in computed tomography and computational modeling of osteochondral tissues.
Janne Mäkelä ([email protected])
Currently interested in contrast media and biolubricants in the early diagnosis and treatment of osteoarthritis. What is the potential of new contrast media in imaging of articular cartilage? How do you best use radiographic imaging to monitor the progression of osteoarthritis over time, and how does a synthetic biopolymer, that lubricates and reinforces the tissue, slow down the disease progression?
Group website
Jiri Jäntti ([email protected])
In my current research, I utilize nanoparticles as contrast media for computed tomography imaging of cartilage. Unique diffusion characteristics of nanoparticles offer a novel approach for cartilage injury diagnostics.
Joonas Kosonen ([email protected])
One of the hallmarks of osteoarthritis progression is cartilage degeneration, which is partly driven by cartilage cells. However, the mechanisms triggering the cell-driven cartilage degeneration and tissue adaptation are poorly understood. Thus, in my Phd work we investigate how different cell-level mechanisms contribute to the cartilage degradation and osteoarthritis progression in injured cartilage.
To provide insight to the cartilage degradation mechanisms, we implement computational models to assess cell-driven cartilage degeneration after biomechanical (excessive loading triggered degradation) and biochemical (pro-inflammatory cytokine, such as interleukin-1 (IL-1), triggered degradation) stimulus. As shown by previous experiments, these factors may cause cell death, oxidative stress, and cell damage, promoting cartilage proteoglycan (PG) degeneration. These degenerative factors will be simulated first with tissue-level models. With the new numerical model, we are also going to assess potential intervention strategies to mitigate cell death and cartilage degradation as well as potential tissue recovery. The model is going to be calibrated against new in vitro biological experiments.
Finally, the new cell-driven tissue-level degradation model will be augmented into the joint-level models of articular cartilage to estimate patients’ cartilage health. Improved joint-level models could supplement the current models by providing novel tools to better estimate cartilage adaptation as well as avail development of new intervention strategies.
Joose Peitola ([email protected])
Currently, my research is focused on studying knee osteoarthritis. The idea in my work is to use musculoskeletal and finite element models to study the forces in the knee joint, as well as the mechanical responses of the articular cartilage. My aim is to enhance the existing modeling workflow by implementing more accurate patient-specific parameters, and to reduce the time needed for the modeling.
Jukka Jurvelin ([email protected])
Biophysics of Bone and Cartilage research group, founder (1998); Research is focused on developement of biophysical methods for diagnostics, prediction and therapy of musculoskeletal diseases.