Osteoporosis and associated low energy fractures are a significant clinical problem, especially in the elderly population. The occurrence of a hip fracture is associated with significant mortality and a high risk of disability. For this, apart from the treatment of osteoporosis, effective prevention of both the development of the disease and related fractures is extremely important. One aspect of osteoporosis prevention is proper dietary calcium intake and normal vitamin D3 levels. However, there is some evidence for a potential role of vitamin C in osteoporosis and fracture prevention, too. This review aims to summarize the current knowledge about the role of vitamin C in osteoporosis development, prevention and treatment. The PubMed/Medline search on the role of vitamin C in bone metabolism database was performed for articles between 2000 and May 2020. Reports from in vitro and animal studies seem promising. Epidemiological studies also indicate the positive effect of high vitamin C content in the daily diet on bone mineral density. Despite promising observations, there are still few observational and intervention studies and their results do not allow for unequivocal determination of the benefits of high daily intake of vitamin C or its long-term supplementation.

Gout, known as “the disease of the kings”, is the most frequent type of arthritis. It results from sustained hyperuricemia that leads to monosodium urate crystal deposition in joint structures and soft tissue. Environmental factors such as diet affect the incidence of gout; there is a known relationship between the occurrence of an acute attack of gout and the consumption of alcohol and meat; and a low purine diet is a widely recognized nonpharmacological method of supplementing the treatment and preventing recurrence of arthritis. This review aims to summarize the current knowledge about the role of vitamin C in prevention and treatment of gout. A PubMed/Medline database search on the role of vitamin C in purine metabolism was done. Reports from in vitro and animal studies seem to be promising and to allow explanation of the physiological relationship between vitamin C and uric acid. Most epidemiological studies indicate a significant correlation between high vitamin C intake and lower serum uric acid levels. Despite promising observations, there are few observational and interventional studies, and their results do not clearly define the benefits of a high daily intake of vitamin C in preventing the development and recurrence of gout.

This review provides a detailed examination of original research and previously published reviews regarding cardiovascular involvement in systemic sclerosis (SSc). Our study aims to evaluate the current understanding of SSc-associated heart involvement (SHI), focusing on its most prevalent forms, diagnostic methods and treatment options. A comprehensive search of PUBMED, Medline, Web of science, Scopus and DOAJ databases was conducted, involving articles published between January 2019 and August 2024, available in English, both original research and reviews. Additionally, the authors examined the references cited in the selected articles, reviewed relevant literature, and included key publications dating back to 2010. Systemic Sclerosis (SSc) is an autoimmune connective tissue disease characterized by skin and internal organs fibrosis with accompanying vasculopathy. SHI encompasses both primary and secondary cardiac disease with a prevalence rate of up to 39%. It constitutes one of the leading causes of death among affected individuals. Systemic sclerosis- primary heart involvement comprises a wide range of conditions including arrhythmias, heart failure, pericardial disease, valvular abnormalities, and myocardial inflammation. However, its subclinical course, often misinterpreted as other forms of cardiomyopathy, poses true diagnostic challenges, requiring diagnostic tools like transthoracic echocardiography with tissue Doppler echocardiography and cardiac magnetic resonance imaging. The review underscores the importance of SHI and a holistic approach to managing patients with systemic sclerosis. Furthermore, it emphasizes the need for further investigation into potential pathogenetic mechanisms and biomarkers crucial for targeted treatment to fully optimize recommendations for this patient subgroup.

Aim As part of its strategic objectives for 2023, EULAR aims to improve the work participation of people with rheumatic and musculoskeletal diseases (RMDs). One strategic initiative focused on the development of overarching points to consider (PtC) to support people with RMDs in healthy and sustainable paid work participation. Methods EULAR’s standardised operating procedures were followed. A steering group identified six research areas on paid work participation. Three systematic literature reviews, several non-systematic reviews and two surveys were conducted. A multidisciplinary taskforce of 25 experts from 10 European countries and Canada formulated overarching principles and PtC after discussion of the results of literature reviews and surveys. Consensus was obtained through voting, with levels of agreement obtained anonymously. Results Three overarching principles and 11 PtC were formulated. The PtC recognise various stakeholders are important to improving work participation. Five PtC emphasise shared responsibilities (eg, obligation to provide active support) (PtC 1, 2, 3, 5, 6). One encourages people with RMDs to discuss work limitations when necessary at each phase of their working life (PtC 4) and two focus on the role of interventions by healthcare providers or employers (PtC 7, 8). Employers are encouraged to create inclusive and flexible workplaces (PtC 10) and policymakers to make necessary changes in social and labour policies (PtC 9, 11). A research agenda highlights the necessity for stronger evidence aimed at personalising work-related support to the diverse needs of people with RMDs. Conclusion Implementation of these EULAR PtC will improve healthy and sustainable work participation of people with RMDs.

Idiopathic inflammatory myopathies (IIM) are progressive, debilitating diseases that can lead to severe impairment. The aim of the study was to evaluate the level of disability and compare it between different subtypes of IIM as well as to estimate clinical symptoms associated with greater risk of disability and distinguish the most troublesome activities in this group of patients. A online form concerning clinical symptoms, comorbidities and limitations in daily living was created and distributed to online support groups for patients with IIM. Health Assessment Questionnaire was used to estimate disability and physical limitations while visual analogue scales enabled to assess the intensity of clinical symptoms. 361 out of 377 responders were included for further evaluation. High prevalence of disability was observed in each subtype yet predominantly in patients with inclusion body myositis (IBM) as 51.43% of them fulfilled the criteria of severe to very severe disability. Level of disability correlated with muscle weakness, tolerance of physical activity and level of fatigue. 45.62% of responders in general required walking devices and 43.50% of participants declared using facilitating devices for maintaining hygiene. Patients with IIM encounter multitude physical limitations that can be partially compensated by usage of facilitating devices or aid of the caregivers. IBM seems to be the most disabling subtype.

Machine learning (ML) algorithms can handle complex genomic data and identify predictive patterns that may not be apparent through traditional statistical methods. They become popular tools for medical applications including prediction, diagnosis or treatment of complex diseases like rheumatoid arthritis (RA). RA is an autoimmune disease in which genetic factors play a major role. Among the most important genetic factors predisposing to the development of this disease and serving as genetic markers are HLA-DRB and non-HLA genes single nucleotide polymorphisms (SNPs). Another marker of RA is the presence of anticitrullinated peptide antibodies (ACPA) which is correlated with severity of RA. We use genetic data of SNPs in four non-HLA genes (PTPN22, STAT4, TRAF1, CD40 and PADI4) to predict the occurrence of ACPA positive RA in the Polish population. This work is a comprehensive comparative analysis, wherein we assess and juxtapose various ML classifiers. Our evaluation encompasses a range of models, including logistic regression, k-nearest neighbors, naïve Bayes, decision tree, boosted trees, multilayer perceptron, and support vector machines. The top-performing models demonstrated closely matched levels of accuracy, each distinguished by its particular strengths. Among these, we highly recommend the use of a decision tree as the foremost choice, given its exceptional performance and interpretability. The sensitivity and specificity of the ML models is about 70% that are satisfying. In addition, we introduce a novel feature importance estimation method characterized by its transparent interpretability and global optimality. This method allows us to thoroughly explore all conceivable combinations of polymorphisms, enabling us to pinpoint those possessing the highest predictive power. Taken together, these findings suggest that non-HLA SNPs allow to determine the group of individuals more prone to develop RA rheumatoid arthritis and further implement more precise preventive approach.