IRIS Università degli Studi dell'Aquila
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Serum hepcidin evaluation as a promising biomarker in juvenile idiopathic arthritis
No full textObjectives: An important area of research in juvenile idiopathic arthritis (JIA) aims to identify sensitive and reliable biomarkers of disease activity. The key iron-regulatory hormone hepcidin-25 (HEP) has been advocated as a potential biomarker to assess anaemia of chronic disease and iron deficiency in adults with rheumatoid arthritis. Methods: We performed a cross-sectional study evaluating the utility of serum HEP in 79 non-systemic onset JIA patients (14 males, 65 females), with/without anaemia, determining its correlations with disease activity, assessed by the JIA Disease Activity Score (JADAS)-27, anaemia parameters, and iron status indices. Results: Significant positive correlations for serum HEP levels were found with the JADAS-27 score (r=0.8988, p<0.0001), and significant differences were found in HEP serum levels between active and inactive patients (8.6 IQR 10.0 ng/mL vs. 2.9 IQR 1.9 ng/mL; p<0.0001). Mean serum HEP concentrations were significantly greater in high disease activity group than in others (p<0.0001). At the ROC curve, an HEP level >4.35 ng/mL discriminated subjects with active disease with a sensitivity of 91.8% and a specificity of 80.0% (AUC: 0.93; 95% CI: 0.88-0.98). Moreover, HEP levels were significantly higher in anaemic, iron repleted and active disease patients. Conclusions: HEP is associated with JIA disease activity, and it could be useful in early detection and monitoring of disease exacerbations. These findings highlight that inflammation plays a major role in HEP induction and point out that HEP could be directly implicated in the JIA inflammatory cascade
Classification of “Ricotta” whey cheese from different milk and Designation of Origin-protected samples through infrared spectroscopy and chemometric analysis
Get PDFWhey cheeses are produced in various parts of the world, such as Portugal, Spain, and Turkey. In Italy, whey cheese goes under the name “ricotta”. This study investigates the classification of ricotta whey cheese derived from various milk sources (either protected designation of origin (PDO) or not) using an Attenuated Total Reflectance Fourier-transform infrared (ATR-FTIR) spectroscopy combined with chemometric analysis. Employing the SPORT-LDA method, which can incorporate Variable Importance in Projection (VIP) analysis, 287 samples of ricotta cheese produced using milk from four different animals (sheep, cow, goat, and water buffalo) were classified according to the animal origin. This led to the correct classification of 97 % of the test samples (3 misclassified samples over 97). VIP analysis revealed that the spectral ranges of 3300–3100 cm−1, 2900–2800 cm−1, and 1700–1300 cm−1 are consistently relevant across all milk sources, thanks to the key molecular vibrations associated with protein structures, lipid content, and water. Eventually, the analysis was circumscribed to sheep ricotta cheeses, because some of these present the PDO quality mark. SIMCA was used to classify PDO samples with respect to the Non-PDO sheep ricotta individuals. The application of SIMCA to model class PDO led to 82.1 % of sensitivity and 82.7 % of specificity (in external validation). The findings underscore the robustness of ATR-FTIR spectroscopy and chemometrics in maintaining the integrity of PDO products and ensuring quality control
Roadmap for the development of machine learning-based interatomic potentials
Get PDFAn interatomic potential, traditionally regarded as a mathematical function, serves to depict atomic interactions within molecules or solids by expressing potential energy concerning atom positions. These potentials are pivotal in materials science and engineering, facilitating atomic-scale simulations, predictive material behavior, accelerated discovery, and property optimization. Notably, the landscape is evolving with machine learning transcending conventional mathematical models. Various machine learning-based interatomic potentials, such as artificial neural networks, kernel-based methods, deep learning, and physics-informed models, have emerged, each wielding unique strengths and limitations. These methods decode the intricate connection between atomic configurations and potential energies, offering advantages like precision, adaptability, insights, and seamless integration. The transformative potential of machine learning-based interatomic potentials looms large in materials science and engineering. They promise tailor-made materials discovery and optimized properties for specific applications. Yet, formidable challenges persist, encompassing data quality, computational demands, transferability, interpretability, and robustness. Tackling these hurdles is imperative for nurturing accurate, efficient, and dependable machine learning-based interatomic potentials primed for widespread adoption in materials science and engineering. This roadmap offers an appraisal of the current machine learning-based interatomic potential landscape, delineates the associated challenges, and envisages how progress in this domain can empower atomic-scale modeling of the composition-processing-microstructure-property relationship, underscoring its significance in materials science and engineering
Hydrophobic gold nanoparticles coupled with fluorescent dyes: A smart tool for optoelectronic applications
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Is NAD+ a key factor in ovarian aging and dysfunction? Insights and uncertainties from current research
Get PDFRecent findings highlight NAD+ as a central regulator of various cellular processes, including energy metabolism, stress response, and aging. The growing evidence of the benefits associated with dietary NAD+ precursors has elevated NAD+ to a promising therapeutic target for addressing female infertility. This review aims to evaluate existing literature on the mechanisms governing the availability and utilization of NAD+ in the ovaries and its alterations in female reproductive disorders, with a particular focus on ovarian aging and dysfunction including polycystic ovary syndrome (PCOS) and premature ovarian insufficiency (POI). Alongside data from in vivo and in vitro studies on various NAD+ boosters, this review incorporates findings from research on genetic mutations, polymorphisms in human and animal populations, and insights from transgenic animal models. The present work emphasizes that NAD+ deficiency is largely driven by a combination of factors, including heightened consumption, impaired utilization efficiency, and diminished biosynthesis or transport. Analysing these aspects, we suggest that the ovary possesses its own unique NAD+ metabolism, but our understanding of the mechanisms governing it is still in its infancy. Key questions remain unanswered, such as how NAD+ and its precursors are transported into oocytes and ovarian cells, their specific preferences for different NAD+ precursors, as well as the specific changes associated with different ovarian dysfunctions. Finally, in this review methods for studying NAD+ metabolism are reported as essential tools to properly investigate the potential of NAD+ boosting therapies for counteracting ovarian aging and dysfunction
Selective activation of antioxidant resources and energy deficiency in Marinesco–Sjögren syndrome fibroblasts as an adaptive biological response to Sil1 loss
Get PDFMarinesco-Sjögren syndrome (MSS) is a neuromuscular disease which presents with ataxia, muscle weakness and cataracts. This syndrome is typically caused by mutations in SIL1 gene, an ER co-chaperone that disrupts protein folding. Although it is known that accumulation of misfolded proteins in the ER profoundly affect reduction-oxidation (redox) homeostasis and energy production, the possible role of these processes in MSS was not investigated to date. In patient-derived fibroblasts, both maximal mitochondrial respiration and mitochondrial ATP production rates were diminished, while the glycolytic fraction remained unaffected. Catalase and superoxide dismutase activities were increased, while glutathione peroxidase and glutathione reductase were decreased. Oxidative damage to lipids, proteins, and DNA was comparable or even lower to that observed in control cells. Similar alterations were observed in the muscle tissue of the woozy mouse model of MSS. In conclusion, we identified a mitochondrial energy deficit and an adaptive cellular mechanism that effectively manage oxidative stress in Sil1-deficient cells
Multidisciplinary Approaches to the Study of High-Altitude Biodiversity: A Case Study on Artemisia eriantha in the Central Apennines, Italy
No full textThe conservation of high-altitude biodiversity requires multidisciplinary approaches integrating botanical, genetic, ecological, and microbiological perspectives to understand
species’ resilience, evolutionary dynamics, and ecological interactions in extreme environments. These integrated methods are crucial for identifying factors influencing species’ survival in fragile, high-altitude ecosystems threatened by harsh conditions and climate change. Genetic studies reveal population structure and diversity, microbiological analyses explore plant-microbe interactions, and ecological assessments examine habitat conditions. Together, these approaches provide a comprehensive understanding of the factors shaping species adaptation and persistence. The present study investigates the genetic diversity and rhizosphere microbiota related to Artemisia eriantha, a glacial relict endemic to the Central Apennines. Plant and soil samples were collected from three sites in the Abruzzo region: Monte Corvo, Monte Portella (Gran Sasso massif), and Monte Focalone (Majella massif). Genetic analysis using Amplified Fragment Length Polymorphism (AFLP) markers revealed high within-population variability typical of outcrossing species and distinct population clustering. Rhizosphere microbiota diversity, analyzed via 16S rRNA metabarcoding, showed site-specific differences, with Monte Portella exhibiting lower diversity and the presence of unique genera, such as Streptomyces and Solirubrobacter, further underscore the localized adaptation of microbiota to site-specific conditions. The findings highlight how environmental factors shape plant genetic structure and associated microbiota, emphasizing the importance of multidisciplinary approaches. This integrated analysis provides a framework for targeted in-situ and ex-situ conservation strategies for endangered alpine species
Microbial Solutions in Agriculture: Enhancing Soil Health and Resilience Through Bio-Inoculants and Bioremediation
Get PDFHygrothermal degradation of modes I and II fracture toughness in flat carbon/epoxy composites: experimental and numerical insights
Get PDFFilament winding is a widely used technique for manufacturing axisymmetric fibre-reinforced composites, such as pressure vessels and pipes, designed for harsh environments. Understanding the effects of these conditions on mechanical performance is crucial. This study presents a combined experimental and numerical investigation of unidirectional carbon/epoxy composites manufactured via filament winding, subjected to tensile, compressive, shear, and interlaminar fracture toughness tests (Modes I and II). Samples were exposed to hygrothermal ageing at room and elevated temperatures to assess moisture absorption and its influence on fracture properties. Special attention is given to the variation in interlaminar fracture toughness due to hygrothermal exposure. Fractographic analysis reveals fibre bridging as a key mechanism behind enhanced Mode I toughness, while Mode II toughness deteriorates with ageing. The findings provide critical insights into the durability and failure mechanisms of filament-wound composites under service conditions