Archivio Istituzionale della Ricerca- Università del Piemonte Orientale
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Politica e sentimento a sinistra. Una storia da ricostruire
No full textRecensione al volume di Stefano Pivato, Alla riscossa! Emozioni e politica nell’Italia contemporanea (Il Mulino 2024). Una narrazione scorrevole tra «colori che fanno rumore», simboli, canti e liturgie laiche; il termine a quo è il 1789: è infatti durante la Rivoluzione francese, che si mettono a punto «miti, simboli e atti liturgici» volti a «far leva sulle emozioni» spingendo così «la gente comune» a «partecipare attivamente alle religioni laiche che si affermano nel corso dell’Ottocento» e proseguono lungo tutto il Novecento
Discovery of a new selective ERAP1 inhibitor for Hedgehog-dependent cancer treatment
Full text linkInappropriate activation of the Hedgehog (HH) signaling pathway drives the pathogenesis of several cancers, including medulloblastoma (MB), the most common malignant brain tumor in children. HH group MB (HH-MB) is highly heterogeneous and resistant to current treatments. Understanding the molecular events underlying the control of the HH pathway is critical for the development of more effective and tailored interventions. Endoplasmic reticulum aminopeptidase 1 (ERAP1), a key regulator of the immune response, has emerged as a promising therapeutic target for HH-MB, but the lack of clinically viable ERAP1 inhibitors has hindered progress in this area. Here, we identify canthin-6-one (N1) as a selective ERAP1 inhibitor. N1 binds directly to ERAP1 and disrupts its function in the HH pathway, resulting in reduced signaling. Specifically, N1 impairs the association of ERAP1 with the deubiquitinase USP47, promoting βTrCP protein stability and Gli1 degradation. Notably, HH-dependent cells genetically depleted for ERAP1 are insensitive to N1, confirming its specificity. Remarkably, N1 inhibits HH-MB growth in vitro and in vivo , crosses the blood-brain barrier, and improves survival in an HH-MB mouse model. These findings highlight N1 as a breakthrough ERAP1 inhibitor and provide a promising therapeutic option for the treatment of HH-dependent cancers
Temporal relational algebras supporting preferences in temporal relational databases: Definition, properties and evaluation
Full text linkDespite numerous approaches address the treatment of time within relational contexts, temporal preferences remain unexplored. Many tasks and applications, such as planning, scheduling, workflows, and guidelines, involve scenarios where the exact timing of events is not known — referred to as indeterminate time. In such cases, preferences can be assigned to different possible temporal outcomes. In a recent study, we established the theoretical foundation for handling preferential indeterminate time in temporal relational databases. This includes proposing a temporal relational representation and a corresponding temporal relational algebra, along with an analysis of their theoretical properties, such as correctness and reducibility. The contributions of this paper are twofold. First, we extend the above theoretical framework to deal with a more expressive representation of temporal preferences. Second, we assess both theoretical frameworks in terms of performance evaluation along different dimensions, and study the overhead added to cope with preferences with respect to relational approaches without time, with exact time, and with indeterminate time but no preferences
A deep learning approach to predicting hospitalized patients’ SEIRD states using multimodal spatiotemporal data
No full textBackground and Objective: The increasing prevalence of hospital-acquired infections (HAIs) due to antimicrobial resistance presents a formidable challenge to patient outcomes and resource allocation. Existing prediction models often operate at a population level, failing to provide the granular, individual patient-specific risk assessments crucial for targeted interventions. Our study addresses this gap by developing and evaluating multimodal deep learning models designed to leverage rich spatial and temporal hospital data for precise, individual-level HAI risk prediction.
Methods: We engineered three distinct deep learning architectures, each employing a different strategy for spatiotemporal data integration. These included: 1) an integrated approach using Heterogeneous Graph Convolution Long Short-Term Memory for unified learning; 2) a decoupled model combining separate Long Short-Term Memory and Diffusion Convolutional Recurrent Neural Network components; and crucially, 3) a novel hybrid model. This hybrid architecture is designed to first allow specialized components to learn distinct representations from spatial and temporal data independently, followed by a joint fine-tuning phase that intelligently fuses these pre-trained representations. All models were rigorously evaluated using a peer-reviewed synthetic hospital simulation dataset that meticulously captures real-world patient movement and infection dynamics. We employed stratified 10-fold cross-validation with accuracy and F1 score metrics.
Results: The hybrid model consistently surpassed both the integrated and decoupled paradigms across all experimental conditions. Over a 7-day prediction window, it achieved peak accuracy (78.96 %) and F1 score (0.75), substantially outperforming the decoupled (71.46 % accuracy, 0.72 F1) and integrated (57.73 % accuracy, 0.42 F1) models. Furthermore, the hybrid model demonstrated enhanced generalization and robustness, maintaining strong performance across varying hospital scales and prediction horizons.
Conclusions: Our findings underscore the efficacy of a hybrid deep learning strategy that skillfully combines specialized learning of spatial and temporal hospital data with a subsequent joint fine-tuning process. This innovative approach yields superior predictive capabilities for individual patient HAI risk, even when evaluated on a complex, real-world representative synthetic dataset. The demonstrated performance and methodological insights suggest significant potential for real-time clinical decision support and optimization of infection control measures. Its inherent adaptability makes it a promising foundation for deployment in diverse healthcare settings, with future work focused on validation with real-world clinical data
Dialogues on the future of social work: exploring post-anthropocentric approaches through practitioner imagination
No full textThis study explores the integration of a post-anthropocentric approach in social work, addressing the discipline's anthropocentric limitations within a six-month exploratory project, the first Italian inquiry into such perspectives. Drawing on feminist posthumanism and neo-materialist theories, this exploratory small-scale study examines how Italian social workers make sense of post-anthropocentric ideas, the ethical questions these raise, and the perceived implications for everyday practice.
The research, conducted through a workshop using the future dialogue technique, involved Italian social workers who envisioned social work in 2034 and pathways toward adopting this approach. The analysis reveals enthusiasm and concern: participants recognise the need for ethical change but identify institutional and organisational barriers to implementation.
The findings suggest that social workers see the urgency of expanding ethics to include more-than-human subjectivities, but emphasise the need for gradual integration through interdisciplinary training and policy adaptation. The study contributes by mapping receptivity and resistance areas and highlighting organisational and educational prerequisites for gradual integration, proposing “purposeful slowness” as an ethical stance for pacing change. It concludes that imagination and ethical commitment are central to shaping post-anthropocentric professional futures
Patient safety incidents in the psychiatric inpatient setting: determinants, consequences, and strategies. A systematic review
Full text linkIntroduction: Patient safety in psychiatric inpatient settings remains an underexplored area despite the heightened vulnerability of this population to preventable harm. This review aimed to provide an updated and comprehensive overview of Patient Safety Incidents (PSIs) in psychiatric inpatient settings, identifying their types, contributing factors, preventive strategies, consequences, and mitigating actions.
Methods: A systematic search was conducted in PubMed, Embase and Scopus for primary studies published from 2000 onward. A total of 92 studies were included. Data were synthesized using the World Health Organization’s International Classification for Patient Safety as the guiding framework.
Results: The most frequently reported PSIs included behavior-related incidents (self-harm, suicide attempts, and patient aggression), medication-related events, and patient falls. Contributing factors were predominantly linked to patient characteristics (e.g., psychiatric symptoms), staff performance and communication issues, organizational shortcomings (e.g., inadequate protocols), and environmental hazards (e.g., unsafe physical infrastructure). Preventive actions primarily focused on improving safety culture, staff training, and environmental modifications. However, only a minority of studies described intervention outcomes or reported quantitative data.
Conclusion: This review highlights significant gaps in evidence-based interventions tailored to psychiatric care, as well as a lack of research from long-term care settings and low- and middle-income countries. To enhance patient safety in psychiatry, future efforts should prioritize the development and implementation of targeted strategies, multidisciplinary collaboration, integration with general patient safety initiatives, and robust quantitative evaluation. Strengthening safety culture across psychiatric facilities is essential to reduce harm and improve care quality for this high-risk population
Circulating fatty acid binding protein 4 ( FABP ‐4) concentrations and mortality in individuals with colorectal cancer in the European Prospective Investigation into Cancer and Nutrition study
No full textHuman fatty acid binding protein-4 (FABP-4), a protein elevated in obesity that promotes colon cancer cell invasiveness and metastasis, may be associated with higher mortality in individuals with colorectal cancer (CRC) and may serve as a mediator of the obesity–mortality association in these individuals. We used a causal diagram to inform covariate selection and applied Cox proportional hazards models to estimate hazard ratios (HRs) for CRC-specific, non-CRC-specific, and all-cause mortality by FABP-4 levels measured in baseline blood samples from 1371 incident CRC cases from the European Prospective Investigation into Cancer and Nutrition cohort. Competing risk analyses were adapted for CRC and non-CRC deaths. Mediation analyses were conducted to estimate total effects (TEs), direct effects (DEs), and mediation proportions (MPs) by FABP-4 of pre-diagnostic body mass index (BMI) on mortality. In the fully adjusted model including BMI, higher circulating FABP-4 concentrations were associated with higher CRC mortality (HRQ4vsQ1 = 1.49; 95% CI: 1.11–2.00) and all-cause mortality (HRQ4vsQ1 = 1.49; 95% CI: 1.15–1.93), but not statistically associated with non-CRC mortality (HRQ4vsQ1 = 1.51; 95% CI: 0.82–2.76). The TE and DE per 5 kg/m2 of BMI on all-cause mortality were 1.21; 95% CI: 1.10–1.34, and 1.13; 95% CI: 1.02–1.26, respectively, with a MP of 34.5% (p =.002) by FABP-4. For CRC-specific and non-CRC-specific mortality, MPs by FABP-4 were 33.7% (p =.03) and 36.1% (p =.02), respectively. In conclusion, higher concentrations of FABP-4 were associated with higher CRC-specific and all-cause mortality in individuals with CRC. FABP-4 was a significant partial mediator of the adiposity-mortality relationship in individuals with CRC
The Interplay Between Ca2+ Homeostasis, Endoplasmic Reticulum Stress, and the Unfolded Protein Response in Human Diseases
Full text linkThe maintenance of endoplasmic reticulum (ER) Ca2+ homeostasis is intrinsically linked to the fidelity of protein folding, forming a functional tether that, when disrupted, triggers the Unfolded Protein Response (UPR). This bidirectional axis serves as a critical rheostat for cellular viability, yet its chronic dysregulation underpins the molecular etiology of numerous pathologies, including neurodegeneration, heart failure, and malignant transformation. This review provides a comprehensive interrogation of the Ca2+-ER Stress–UPR network, delineating how primary stress sensors—PERK, IRE1alpha, and ATF6—engage in complex feedback loops that either reinstate equilibrium or commit the cell to apoptosis. We specifically examine the PERK-CHOP-SERCA2b inhibitory circuit as a central driver of persistent Ca2+ depletion and discuss the role of Mitochondria-Associated Membranes (MAMs) in governing lethal Ca2+ transfer. Notably, we move beyond the classical paradigm of CHOP as a terminal apoptotic executioner, incorporating emerging evidence of its context-dependent adaptive functions. By synthesizing mechanistic insights across diverse disease models, this work highlights the transition from adaptive to maladaptive UPR as a universal pathological checkpoint. Ultimately, we evaluate the therapeutic potential of ‘axis-targeted’ interventions, such as SERCA activators and selective UPR modulators, aimed at resolving the underlying Ca2+ signaling defects in ER stress-related disorders
