Worldwide, a care gap has been recognized between presenting with a fracture and prevention of the next fracture. Fracture Liaison Service is the most cost-effective method to close this gap, but its implementation is sparse in the Nordic countries. To assess the need for a fracture prevention program, the primary aim of this study was to estimate the prevalence of osteoporosis in patients treated for fragility fractures at Aarhus University Hospital, Denmark. Secondary aims were to identify clinical risk factors associated with osteoporosis and the up-take of anti-osteoporosis treatment. The study was conducted as a cross-sectional study and patients aged 18+ years were consecutively identified over a 12 months period. Of 1164 identified patients, 832 were included and 794 (70% women, 66% aged ≥ 50 years) patients completed the study. Bone mineral density was measured by DXA and information about clinical risk factors were obtained. The overall prevalence of osteoporosis in this cohort was 14.9%, increasing to 20.3% in patients ≥ 50 years (22.9% in women, 9.6% in men). In addition to age above 50 years, female sex, low BMI, and early menopause were significantly associated with osteoporosis. At 3-years follow-up in patients diagnosed with osteoporosis, 95% of patients who initiated anti-osteoporosis treatment after their fracture were still adherent to treatment. Given that osteoporosis was demonstrated in one in five fragility fracture patients above 50 years, OFELIA stresses the need for implementation of a program aiming at securing appropriate investigation and treatment of osteoporosis in patients presenting a fragility fracture.

In Duchenne muscular dystrophy (DMD), the progressive skeletal and cardiac muscle dysfunction and degeneration is accompanied by low bone mineral density and bone fragility. Glucocorticoids, which remain the standard of care for patients with DMD, increase the risk of developing osteoporosis. The scope of this review emphasizes the mutual cohesion and common signaling pathways between bone and skeletal muscle in DMD.

Icariin (ICA) and icaritin (ICT) exhibit many pharmacological functions including anti-osteoporosis, anti-cardiovascular, and anti-cancer activities; however, there are few comprehensive studies that track the detailed effects on UVB-induced photoaging. The recovery effects of ICA and ICT were investigated in UVB-irradiated human keratinocytes (HaCaTs). The results indicated that ICT and ICA showed strong radical scavenging activity, and the reactive oxygen species (ROS) scavenging activity of ICT was superior. UVB-induced matrix metalloproteinase-1 (MMP-1) expression was blocked by ICA via the inhibition of mitogen-activated protein kinase/activator protein 1 (MAPK/AP-1), which directly reduced extracellular matrix (ECM) degradation. ICT activated nuclear factor erythroid 2 related factor 2 (Nrf2) to improve the anti-oxidative stress capacity and suppress nuclear factor-κB (NF-κB) activation, decreasing vascular endothelial growth factor (VEGF) protein, and inflammatory cytokines induced ECM degrading enzyme secretion. Moreover, ICT was more advantageous to improve transforming growth factor beta 1 (TGF-β1) and procollagen type I expression than ICA, promoting the synthesis of collagen. Therefore, ICA and ICT have potential to treat UVB-induced oxidative stress, inflammation and photoaging, and will be posited as a novel strategy to alleviate photodamage.

Osteoporosis, characterized by increased fracture risk and bone fragility, impacts millions of adults worldwide, but effective, non-invasive and easily accessible diagnostic tests of the disease remain elusive. We present a magnetic resonance (MR) technique that overcomes the motion limitations of traditional MR imaging to acquire high-resolution frequency-domain data to characterize the texture of biological tissues. This technique does not involve obtaining full two-dimensional or three-dimensional images, but can probe scales down to the order of 40 μm and in particular uncover structural information in trabecular bone. Using micro-computed tomography data of vertebral trabecular bone, we computationally validate this MR technique by simulating MR measurements of a 'ratio metric' determined from a few k-space values corresponding to trabecular thickness and spacing. We train a support vector machine classifier on ratio metric values determined from healthy and simulated osteoporotic bone data, which we use to accurately classify osteoporotic bone.