University of Modena and Reggio Emilia
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Intelligenza Artificiale e Disturbi Specifici dell'Apprendimento Artificial Intelligence and Specific Learning Disorders
No full textCapric acid–based therapeutic deep eutectic systems: A focused review within the framework of deep eutectic solvents
No full textBackground/Objectives: Capric acid (CA)–therapeutic deep eutectic systems (THEDES) are emerging as a distinct class of biofunctional matrices capable of reshaping drug solubilization, permeability, and bioactivity. Methods: Relevant studies on CA–THEDES were identified through targeted database searches and screened for evidence on their design, mechanisms, and pharmaceutical performance. Results: This review synthesizes current evidence on their structural design, mechanistic behavior, and pharmaceutical performance, revealing several unifying principles. Across multiple drug classes, CA consistently drives strong, directional hydrogen bonding and drug amorphization, resulting in marked solubility enhancement and stabilization of non-crystalline or supersaturated states relative to crystalline drugs or conventional solvent systems. Its amphiphilic C10 chain further contributes to membrane fluidization, which explains the improved transdermal and transmucosal permeation repeatedly observed in CA-THEDES. Additionally, synergistic antimicrobial and anticancer effects reported in several systems confirm that CA acts not only as a solvent component but as a bioactive co-therapeutic. Collectively, the reviewed data show that CA serves as a structurally determinant element whose dual hydrogen-bonding and membrane-interacting roles underpin the high pharmaceutical performance of these systems. However, gaps remain in long-term stability, toxicological profiling, and regulatory classification. Emerging Artificial Intelligence (AI) and Machine Learning (ML)-guided predictive approaches offer promising solutions by enabling rational selection of eutectic partners, optimal ratios, and property optimization through computational screening. Conclusions: Overall, CA-THEDES represent a rationally designable platform for next-generation drug delivery, where solvent functionality and therapeutic activity converge within a single, green formulation system
Learning environments and inclusion: a case study of transposition of the Reggio Emilia approach in Swedish schools
No full textThe Reggio Emilia Approach is a child-centered educational approach,
originally from the city of Reggio Emilia, Italy. This study explores the introduction of
Reggio Emilia Approach in Sweden in the 1960s and its current application in the
Stockholm region. Based on interviews and observations with staff members from the
Reggio Emilia Institutet and professionals in preschools, schools and Reuse Creative
Centers inspired by this approach, supported by photos and thematic analysis, the research
highlights three main conclusions: (1) the historical and cultural factors that facilitated
the adoption of Reggio Emilia Approach in Sweden; (2) the Swedish interpretation of
learning environments aligned with Reggio Emilia Approach principles, emphasizing
consistency, attention, and support for learning; and (3) inclusive practices shaped by
both continuity with Reggio Emilia Approach ideals and local adaptations. The study
shows how elements of Reggio Emilia Approach are reinterpreted and integrated into
Swedish educational culture through a dynamic and reflective process
Impatto dell’analisi radiomica della TC preoperatoria nella predizione degli esiti oncologici post-resezione per colangiocarcinoma intraepatico: studio multicentirco retrospettivo
No full textBackground
Il colangiocarcinoma intraepatico (iCCA) presenta uno dei più alti tassi di recidiva tra i tumori primitivi del fegato, anche dopo resezione a intento curativo. L’integrazione delle caratteristiche radiomiche estratte dalle immagini TC con mezzo di contrasto preoperatorie nei modelli clinici di prognosi può offrire uno strumento non invasivo per affinare la stratificazione del rischio di recidiva.
Metodi
Sono stati analizzati retrospettivamente 124 pazienti consecutivi provenienti da quattro centri di chirurgia epato-bilio-pancreatica (HPB), sottoposti a resezione epatica a intento curativo per iCCA tra il 2005 e il 2022. Sono stati raccolti dati clinici, patologici e di imaging al fine di identificare i determinanti della sopravvivenza libera da recidiva (RFS). Le caratteristiche radiomiche sono state estratte mediante PyRadiomics dalle fasi arteriosa e venosa delle TC preoperatorie e normalizzate nell’intervallo (0,1). Dopo le fasi di pre-elaborazione e standardizzazione, è stato applicato un filtro bootstrap-based minimum redundancy–maximum relevance (mRMR) per selezionare le variabili più stabili e non ridondanti, maggiormente predittive della RFS. Sono stati quindi costruiti modelli di regressione di Cox basati su: (A) variabili clinico-patologiche, (B) caratteristiche radiomiche e (C) loro combinazione. La capacità discriminante dei modelli è stata valutata mediante la statistica di concordanza di Uno.
Risultati
L’età mediana dei pazienti è stata di 69 anni (IQR 61–74). La sopravvivenza globale mediana e la RFS sono state rispettivamente di 36,0 mesi (IC 95% 25,9–44,4) e 12,6 mesi (IC 95% 10,6–14,8). All’analisi multivariata, il numero di linfonodi positivi (HR = 2,58, p < 0,001), la dimensione massima del tumore (per cm HR = 1,12, p = 0,009) e il pattern necrotico (HR = 3,28 per necrosi ben delimitata vs assente, p = 0,004) sono risultati predittori indipendenti di recidiva.
L’inclusione delle variabili radiomiche ha determinato un marcato miglioramento delle prestazioni del modello. Tre caratteristiche wavelet-based sono risultate le più stabili e predittive: Imc1_glcm_wavelet.LHH (fase arteriosa), indicativa di microeterogeneità e fine correlazione tessutale; SmallAreaLowGrayLevelEmphasis_glszm_wavelet.HLL (fase arteriosa), correlata alla presenza di piccole aree ipodense; e ClusterShade_glcm_wavelet.LHL (fase venosa), espressiva dell’asimmetria e complessità strutturale della trama tumorale. Il modello basato esclusivamente su dati radiomici ha raggiunto un indice di concordanza pari a 0,66 (IC 95% 0,59–0,74). La combinazione di tali caratteristiche con le variabili tumorali (modello C) ha incrementato la capacità discriminante a 0,75 (IC 95% 0,67–0,82), rispetto a 0,71 (IC 95% 0,64–0,78) del modello clinico-patologico (p = 0,05 per la differenza).
Conclusioni
La profilazione radiomica delle TC preoperatorie ha migliorato in modo significativo la predizione della RFS dopo resezione per iCCA. L’inclusione di biomarcatori d’imaging basati sulla texture ha consentito di cogliere l’eterogeneità tumorale e le irregolarità microstrutturali non rilevabili con la diagnostica convenzionale o con l’esame istologico. Questo approccio integrato può permettere una più accurata stratificazione del rischio, orientando le decisioni chirurgiche, l’intensità del follow-up e la potenziale indicazione a terapie neoadiuvanti o adiuvanti.Background
Intrahepatic cholangiocarcinoma (iCCA) carries one of the highest recurrence rates among primary liver cancers, even after curative-intent resection. The integration of radiomic features extracted from preoperative contrast-enhanced CT imaging into clinical prognostication models may offer a noninvasive means to refine recurrence risk stratification.
Methods
We retrospectively analyzed 124 consecutive patients from four HPB centers who underwent curative-intent liver resection for iCCA between 2005 and 2022. Clinical, pathological, and imaging data were collected to identify determinants of recurrence-free survival (RFS). Radiomic features were extracted using PyRadiomics from the arterial and venous phases of preoperative CT scans and normalized to the (0,1) interval. After preprocessing and standardization, a bootstrap-based minimum redundancy–maximum relevance (mRMR) filter was applied to select stable and nonredundant variables most predictive of RFS. Cox regression models were built using (A) clinicopathologic variables alone, (B) radiomic features alone, and (C) their combination. Model discrimination was assessed using Uno’s concordance statistic.
Results
Median age was 69 years (IQR 61–74). Median overall survival and RFS were 36.0 months (95% CI 25.9–44.4) and 12.6 months (95% CI 10.6–14.8), respectively. On multivariable analysis, number of positive lymph nodes (HR = 2.58, p < 0.001), maximum tumor size (per cm HR = 1.12, p = 0.009), and tumor necrosis pattern (HR = 3.28 for well-circumscribed vs. absent, p = 0.004) were independent predictors of recurrence.
Incorporation of radiomic data markedly enhanced model performance. Three wavelet-based features were selected as the most stable predictors: Imc1_glcm_wavelet.LHH (arterial), reflecting fine-texture correlation and micro-heterogeneity; SmallAreaLowGrayLevelEmphasis_glszm_wavelet.HLL (arterial), quantifying small hypodense foci; and ClusterShade_glcm_wavelet.LHL (venous), expressing asymmetry and structural complexity of tumor texture. The radiomic-only model achieved a concordance index of 0.66 (95% CI 0.59–0.74). When combined with tumor variables (Model C), discrimination improved to 0.75 (95% CI 0.67–0.82), compared with 0.71 (95% CI 0.64–0.78) for clinico-pathologic factors alone (p = 0.05 for difference).
Conclusions
Radiomic profiling of preoperative CT images significantly improved RFS prediction after resection of iCCA. The inclusion of texture-based imaging biomarkers captured tumor heterogeneity and microstructural irregularity, which are not discernible by standard imaging or pathology. This integrative approach may enable more accurate risk stratification, guiding surgical decision-making, follow-up intensity, and potential use of neoadjuvant or adjuvant therapies
Nuovo attacco per applicazione di un sistema di antenna nella protesica navigata e robotica
No full textCFD modelling of cathode conditions and membrane crossover flux in PEM water electrolysis
No full textProton Exchange Membrane water electrolysis is a high-relevance technology to accomplish the industrial upscale of green hydrogen generation, addressing the urgency of the ecological transition thanks to its well-known principle and high conversion efficiency. In this study a comprehensive three-dimensional, two-phase Proton Exchange Membrane Electrolysis Cell (PEMEC) model is proposed, with the aim to investigate how different operating conditions influence the cell behaviour. Particular attention is posed on cathode pressure and humidification levels. The model was validated against experimental data showing excellent agreement between simulation results and experimental polarization curves for two working temperatures (333.15 K, 353.15 K), confirming that for an applied electric potential of 2.0 V the current density drops approximately 20 % for the lower temperature. Dry cathode conditions do not affect electrolysis efficiency due to the water electro-osmotic drag flux, which remains largely dominant on the water back-diffusion transport, keeping the polymeric membrane fully hydrated. Pressure increase at the negative electrode leads to slightly higher overpotentials for medium-low current densities (ΔEOCV≅+0.05156V for pc=30bar) while ohmic losses are reduced allowing similar electrolysis performance for i>2.0A/cm2. This means that PEMECs can operate at high efficiencies at optimal conditions for the direct hydrogen storage in specific metal hydrides (MH). Hydrogen cross-flow is highly dependent on the pressure differential and on the flow field, with an increase as the pressure raises and an accumulation in the corner of the serpentine. Even in the most critical condition (pc=30bar) the maximum hydrogen molar concentration (2.4936×10−4kmol/m3), remains below the 4 %mol limit of potentially explosive conditions, thus providing a virtual safety indication
A novel slip-friction connector for seismic applications in timber structures: analytical and experimental investigation
No full text
Pedagogia interculturale e inclusione sociale
No full textIn un tempo in cui l’intercultura e l’inclusione rischiano di svuotarsi in slogan rassicuranti o in una sterile retorica delle «buone intenzioni», questo volume propone una visione nuova e radicale. L’educazione non è mai un atto neutro, ma un campo di battaglia teorico e politico in cui si costruiscono gerarchie, visioni del mondo e reali possibilità di convivenza. Muovendo da una prospettiva pedagogica critica, il manuale invita a superare la tentazione di un’inclusione puramente simbolica — quella forma di visibilità che rassicura le istituzioni senza intaccare realmente il potere che discrimina — per riscoprire l’agire educativo come autentica pratica di emancipazione e giustizia sociale. Attraverso una scrittura corale e rigorosa, il testo interroga le condizioni materiali e simboliche che rendono possibile l’incontro con l’altro, decostruendo il paradigma eurocentrico che ancora abita i nostri sistemi formativi e smascherando le asimmetrie nascoste dietro il lessico umanitario di facciata. Dalla sfida delle frontiere postdigitali all’analisi dei pregiudizi algoritmici nella condizione onlife, queste pagine offrono strumenti teorici e operativi per professionisti e ricercatori che intendano trasformare l’aula in uno spazio di formazione e trasformazione
Altered abundance in cancer patients gut of diadenylate cyclase-encoding bacteria
No full textc-di-AMP is a bacterial second messenger recognized by host immune sensors such as the STING pathway, linking gut microbiota activity to tumor immunity. This interaction holds significant therapeutic potential particularly for oncologic patients, given the increasingly recognized relationship between gut microbiota and tumor immunity. Recent evidence shows that microbial c-di-AMP can enhance anti-tumor responses and improve the efficacy of PD-1/PD-L1 blockade and radiotherapy. This study identified gut microbial species capable of synthesizing c-di-AMP by mining the Unified Human Gastrointestinal Protein catalogue for diadenylate cyclases (DACs), generating a database of 4,228 DACs across 3,901 species out of 4,744 presents in the Unified Human Gastrointestinal Genome catalogue. Analysis of metagenomic data from 190 healthy subjects and 569 cancer patients (melanoma, NSCLC, renal carcinoma) revealed a significantly higher abundance of DAC-encoding species in healthy microbiota, with no differences between responders and non-responders to immunotherapy. These findings indicate that c-di-AMP-producing bacteria are depleted in cancer-associated microbiota, supporting further studies on their role in modulating anti-tumor immunity