1. Circular RNAs and their emerging roles in muscular immune-related diseasesFelicita Urzi, Anja Srpčič, Katja Lakota, 2025, review article Abstract: Circular RNAs (circRNAs) have recently emerged as a highly stable and versatile class of non-coding RNAs that play critical roles in gene regulation, yet their involvement in immune-mediated muscle disorders remains largely underexplored. This review synthesizes how circRNAs influence key processes in both skeletal muscle and immune cells, from myogenesis, regeneration, and muscle stem cell function to inflammatory signaling and muscle wasting. Our aim was to identify circRNA insights across muscle immune-mediated diseases. However, we found no idiopathic inflammatory myopathy-focused circRNA studies, only a limited body of work in Duchenne muscular dystrophy, and predominantly peripheral blood mononuclear cell-based evidence in myasthenia gravis. These gaps highlight clear priorities: subtype-resolved circRNA atlases for idiopathic inflammatory myopathy; paired muscle–biofluid and cell-type–resolved profiling (including infiltrating immune populations); rigorous in vivo functional validation beyond correlative expression; fuller mechanistic delineation beyond miRNA competition (e.g., RNA binding protein interactions, translation, epigenetic regulation); and longitudinal cohorts linking circRNA dynamics to disease activity and treatment response. We particularly noted lack of in-depth studies addressing the interplay between muscle and immune cells in these conditions. Furthermore, we examine pioneering efforts to engineer circRNAs as therapeutic agents, capable of either neutralizing pathogenic pathways that drive muscle atrophy or restoring dystrophin expression in genetic disease models. Finally, we outline future directions for circRNA profiling in patient tissues and biofluids, rigorous functional validation in vivo, and the development of circRNA-based diagnostics. This positions circRNAs at the forefront of next-generation strategies for understanding and combating immune-related muscular disorders.
Keywords: circular RNA, skeletal muscle, immune cells, idiopathic inflammatory myopathies, Duchenne muscular dystrophy, myasthenia gravis
Published in RUP: 18.11.2025; Views: 334; Downloads: 2
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4. Identifying risk factors for sarcopenia using machine learning : insights from multimodal dataFelicita Urzi, Domen Šoberl, Ornella Caputo, Marco Vincenzo Narici, 2025, original scientific article Abstract: Purpose This study aims to identify key risk factors for sarcopenia using machine learning models, leveraging anthropomet- ric, biochemical, functional, nutritional, and genetic data. By developing predictive models, the research seeks to improve early detection, enhance diagnostic accuracy, and facilitate personalized interventions for individuals at risk of sarcopenia. Methods We analysed multimodal data from 484 older adults. Two scenarios: Set-a (including SARC–CalF, excluding SARC-F) and Set-b (including SARC-F, excluding SARC–CalF) were applied in a three-stage modeling process with progressively reduced features and optimized predictive performance using machine learning models. Key predictors were ranked using SHAP values, and model performance was evaluated using AUC, accuracy, sensitivity, and specificity. Internal validation and DeLong’s test were applied to assess robustness and statistical differences. Results The most predictive risk factors included functional measures (chair stand, gait speed), nutritional indicators (pro- tein, folate, copper, vitamin B7), clinical conditions (diabetes, comorbidities, low-density lipoprotein (LDL)), and anthro- pometric markers (body mass index (BMI), calf circumference). Genetic features also contributed to risk stratification. The best-performing model Set-b (with screening test SARC-F) achieved an AUC of 0.951 and an accuracy of 93.62%. While SARC–CalF showed higher individual feature importance, the model achieved an AUC of 0.945 and accuracy of 92.2%. Conclusions This study highlights that traditional sarcopenia screening can be enhanced by capturing complex interplay of functional, nutritional, clinical, and genetic factors, offering clinicians a more accurate and tailored tool for early detec- tion and risk stratification. Future research should focus on validating these models in larger, independent, and longitudinal cohorts to assess their predictive utility across diverse populations and over time.
Keywords: genetics, nutrition, risk factors, sarcopenia
Published in RUP: 23.07.2025; Views: 605; Downloads: 12
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10. Population genetic structure of European wildcats inhabiting the area between the Dinaric Alps and the Scardo-Pindic mountainsFelicita Urzi, Nikica Šprem, Hubert Potočnik, Magda Sindičić, Dean Konjević, Duško Ćirović, Andrea Rezić, Luka Duniš, Dime Melovski, Elena Bužan, 2021, original scientific article Keywords: genetic variation, microsatellite markers, hybridisation, wildcat
Published in RUP: 18.10.2021; Views: 3517; Downloads: 56
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