University of Rome Tor Vergata

The landscape of modern computing systems is shifting towards architectures built by combining available services under the “everything as a service” paradigm. These architectures are deployed on distributed cloud-edge infrastructures, aiming to provide innovative services to a wide range of users. However, it is crucial for these systems to address environmental sustainability concerns. This poses challenges in operating such systems in open, dynamic, and uncertain environments while minimizing their energy consumption. To tackle these challenges, we propose a decentralized service assembly approach that ensures the assembly is energetically self-sustainable by relying on locally harvested and stored energy. In our contribution, we introduce a general service selection template that enables the derivation of different selection policies. These policies guide the construction and maintenance of the service assembly. To evaluate their effectiveness in meeting the sustainability requirements, we conduct a comprehensive set of simulation experiments, providing valuable insights.

Transmural healing (TH) has emerged as a therapeutic target in Crohn's disease (CD), providing a more comprehensive indicator of deep remission than mucosal healing alone. Intestinal ultrasound (IUS) is a noninvasive method for assessing TH, but its prognostic value remains insufficiently defined. The aim of this prospective study was to evaluate whether early improvement in IUS parameters during biological therapy could predict TH at 12 months. This is a prospective multicenter study enrolling CD patients initiating biological therapies. IUS and Doppler parameters were assessed at baseline, 3 months, and 12 months. Delta (Δ) represented the variation in ultrasound measurements between baseline and 3 months. TH was defined as normalization of bowel wall features and absence of hypervascularization. A total of 142 CD patients were included. At 12 months, the TH rate was 19%, the IUS response rate was 44%. Patients achieving TH showed a significantly greater ΔBWT than nonresponders (P = .0004). On ROC analysis, a ΔBWT reduction of 1.25 mm predicted TH with 73% sensitivity and 61% specificity. IUS responders had a significantly greater ΔBWT than nonresponders (P < .0001), with the same threshold predicting response with 83% sensitivity and 57% specificity. Notably, the combination of ΔBWT and Limberg score improvement was strongly associated with both TH (OR 13.26; P < .0001) and IUS response (OR 20.9; P < .0001) at 12 months. Early reduction in BWT, especially when combined with Limberg score, is a strong predictor of TH and IUS response at 12 months, supporting the use of early IUS monitoring in clinical practice.

The 2026 report from the Global Initiative for Chronic Obstructive Lung Disease (GOLD) introduces substantial conceptual and practical updates to the management of chronic obstructive pulmonary disease. While maintaining the established spirometric definition, the report emphasizes early diagnosis, multi-dimensional assessment, and personalized treatment strategies that move beyond a spirometry-centric approach. Key innovations include formally recognizing disease activity as a therapeutic target, refining the ABE classification with a lower threshold for patients prone to exacerbations (Group E), and integrating blood eosinophil counts to guide inhaled corticosteroid therapy. Nonpharmacologic interventions, such as pulmonary rehabilitation, vaccination, smoking cessation, structured self-management, and post-exacerbation care, are elevated to core disease-modifying strategies. Pharmacological escalation is structured around dual bronchodilation as the preferred initial step, with further intensification to biomarker-guided triple therapy, including inhaled corticosteroids or other anti-inflammatory agents, reserved for selected patients who remain symptomatic or experience exacerbations despite optimized dual therapy. GOLD 2026 also introduces biologics, dupilumab and mepolizumab, as an add-on therapy for exacerbation-prone eosinophilic chronic obstructive pulmonary disease. However, it also highlights ongoing limitations in efficacy, cost effectiveness, and generalizability. Artificial intelligence and emerging digital technologies are recognized as promising adjuncts in the management of chronic obstructive pulmonary disease, though their clinical implementation remains preliminary. Overall, GOLD 2026 advances precision medicine in chronic obstructive pulmonary disease by combining structured individualized assessments with early targeted interventions. However, significant uncertainties remain, including biological variability of biomarkers, limited evidence for emerging therapies, and barriers to equitable access to nonpharmacologic and advanced interventions. Careful context-sensitive application and continued validation are essential.

Multiple sclerosis (MS) is characterized by large-scale brain network dysfunctions. EEG microstate analysis may track these dynamics. We investigated whether microstates could distinguish patients with MS from healthy volunteers, and cognitively impaired from cognitively preserved (CP) patients. For this cross-sectional observational study, we recruited participants from the Policlinico Umberto I Multiple Sclerosis Center (Rome). We compared microstates of patients with relapsing-remitting MS (Expanded Disability Status Scale [EDSS] score <3, no relapses within 30 days) with those of age-matched and sex-matched healthy volunteers. We also compared cognitively impaired and preserved patients. Group comparisons were performed on microstate temporal parameters and topographies (topographic analysis of variance). Classification used stepwise linear discriminant analysis (LDA). We enrolled 88 patients with MS (60 women, mean age 42.75 years) and 46 healthy volunteers (23 women, mean age 33.7 years). Compared with healthy volunteers (n = 45, 23 women, mean age 33.7 years), patients with MS (n = 46, 25 women, mean age 34.6 years) showed greater explained variance (p < 0.001), occurrence (p < 0.001), and coverage (p < 0.001) of class B (visual network) and reduced mean duration (MD) of classes F (salience network, p = 0.014) and G (sensorimotor network, p = 0.009). Topographic differences were found between cognitively impaired (n = 57, 20 women, mean age 35.5 years) and preserved (n = 31, 40 women, mean age 46.7 years) patients for classes C, F, and G (p < 0.05). Patients with cognitive impairment exhibited significantly reduced explained variance of class F (p = 0.003). Class A was associated with longer disease duration (explained variance, p = 0.006; MD, p = 0.042; coverage, p = 0.007), higher EDSS scores (MD, p = 0.013), and poorer ambulation (explained variance, p = 0.049). Class D inversely correlated with EDSS scores (occurrence, p = 0.011; coverage, p = 0.036), whereas class B inversely correlated with information processing speed (explained variance, p = 0.025; occurrence, p = 0.018; coverage, p = 0.028). Stepwise LDA identified classes B and D as discriminators between patients with MS and healthy volunteers (77% accuracy, p < 0.001), and class F as a discriminator between CP and impaired participants (64.8% accuracy, p = 0.007). EEG microstates reveal behaviorally relevant alterations in patients with MS, supporting their utility as sensitive markers of large-scale functional network reorganization associated with clinical disability.