University of Eastern Finland

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    Metabolic disruption by mycotoxins: focus on metabolic endpoints steatosis, adipogenesis and glucose metabolism in vivo and in vitro

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    Metabolic disruption encompasses the processes leading to adverse effects to major metabolic organs, such as liver and pancreas after exposure to e.g., environmental chemicals. As some mycotoxins act as endocrine disruptors, their structural similarity may lead to effects in lipid and glucose metabolism as well. Via systematic literature search, we mapped the potential of mycotoxins to cause metabolic disruption. Our systematic data search involved mycotoxin keywords combined with metabolic disruption keywords. The retrieved 31 studies revealed 24 in vivo studies, and 18 in vitro studies in total of 13 different mycotoxins. Most studied parameters were triglycerides from blood or liver, followed by total cholesterol and glucose or insulin levels. In vitro studies most often aimed to reveal mechanisms of metabolic disruption, but common metabolic parameters (lipid or cholesterol accumulation). In general, mycotoxin exposure showed a trend towards positive metabolic effects, such as reduction of blood triglycerides levels. Emodin was the most studied mycotoxin. Other mycotoxins were studied in one to three studies. Positive effects were also identified for equisetin, fumonisin B1, fumigaclavine C and ergostatrien-3-B-ol. Adverse effects (e.g. increased lipid deposition to liver) were identified for aflatoxin B1, ochratoxin A, deoxynivalenol, citreoviridin, T-2 toxin and paxilline. As demonstrated by the evaluated in vivo and in vitro studies, mycotoxins seem to have more positive than negative effects on metabolism. However, based on the available data, a general conclusion on the role of mycotoxins as a group cannot be made

    Neuroepätyypillisen vanhemman toimijuus sosiaalityön kontekstissa

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    Postoperative Opioid Use and Associated Treatment Costs in Finnish Hospitals

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    Time-dependent computational model of post-traumatic osteoarthritis to estimate how mechanoinflammatory mechanisms impact cartilage aggrecan content

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    These data encompass computational models (Abaqus, COMSOL Multiphysics), codes, and experimentally observed aggrecan content in immature bovine cartilage plugs subjected to both injurious and physiological cyclic loading. They support the findings presented in the main article and its supplementary material. ABSTRACT: Degenerative musculoskeletal diseases like osteoarthritis can be initiated by joint injury. Injurious overloading-induced mechanical straining of articular cartilage and subsequent biological responses may trigger cartilage degradation. One early sign of degradation is loss of aggrecan content which is potentially accelerated near chondral lesions under physiological loading. Yet, the mechanoinflammatory mechanisms explaining time-dependent degradation in regions with disparate mechanical loading are unclear and challenging to assess with experiments alone. Here, we developed computational models unraveling potential mechanisms behind aggrecan content adaptation in fibril-reinforced porohyperelastic cartilage after single injurious overloading (50% compressive strain magnitude, 100%/s strain rate) followed by physiological cyclic loading (15% strain, 1 Hz, haversine waveform). The simulated adaptation of aggrecan content was compared spatially and at several time points to tissue composition found in Safranin-O-stained sections of young bovine articular cartilage subjected to the same loading protocols. Incorporating mechanical strain-driven cell damage and downstream proteolytic enzyme release, fluid flow-driven aggrecan depletion, and fluid pressure-stimulated regulation of aggrecan biosynthesis, the models agreed with experiments and exhibited 14%-points greater near-lesion aggrecan loss after 12 days of physiological loading compared to without loading. The near-lesion aggrecan loss was driven by fluid flow and proteolytic aggrecanase activity, while chondroprotective pro-anabolic responses (increased aggrecan biosynthesis) were prominent in the deeper tissue despite damaged superficial layer. This significant advancement in mechanistic understanding incorporated into cartilage adaptation model can help in development and guidance of personalized therapies, such as rehabilitation protocols and tissue-engineered constructs

    Refractive index sensors using hybrid waveguides: design, fabrication, and characterization

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    Periodontal health, tooth loss, and risk for cognitive decline and dementia: oral health and cognition

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    Adaptation of Gamification Elements in a Multicultural Company

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