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Adherence to physical activity during the first trimester of pregnancy: a study from Southern Italy
No full textBackground: Although international recommendations strongly support regular physical activity during pregnancy due to the improved maternal and fetal outcomes, adherence to physical activity remains low, particularly in early gestation. Understanding activity patterns during the first trimester is crucial, as behaviors established in this phase often persist throughout pregnancy. Objectives: To describe physical activity levels and adherence to international recommendations among low-risk pregnant women in the first trimester, using the Italian version of the Pregnancy Physical Activity Questionnaire (PPAQ). Study design: This cross-sectional observational study includes 498 low-risk singleton pregnant women between 11+3 and 13+6 weeks' gestation, recruited at the University Hospital of Naples Federico II, Italy, between January 2022 and December 2023. Participants completed the Italian version of the PPAQ. Total energy expenditure was expressed in MET-h/week, and women were classified as exercisers (≥ 150 mines/week of moderate-intensity activity) or non-exercisers. Results: Participants reported a median of 11.5 (IQR 8.2-15.0) h/week of total activity, corresponding to 155.7 (102.6-241.7) METs-h/week. While 51% met the threshold of ≥ 150 min/week of moderate-intensity activity when considering all activity domains, only 7.8% reached this target through sport or structured exercise alone. Walking represented the most common exercise (64.1% slow, 46.2% brisk, 25.6% uphill). Employment status was significantly associated with higher adherence to recommendations, whereas other sociodemographic factors showed no significant differences. Conclusions: Structured exercise should be improved in the daily routine to optimize maternal and fetal health, although activity levels may appear adequate. Adherence to physical activity recommendations could be promoted by integrating validated tools such as the PPAQ into routine prenatal care and targeted interventions
Large-scale benchmarks for multimodal recommendation with Ducho
No full textWith the advent of deep learning and, more recently, large models, recommendation systems have greatly refined their capability of profiling users’ preferences and interests that, in most cases, are complex to disentangle. This is especially true for those recommendation algorithms that rely heavily on external side information, such as multimodal recommender systems. In specific domains like fashion, music, and movie recommendation, the multi-faceted features characterizing products and services may influence each customer on online platforms differently, paving the way to novel multimodal recommendation models that can learn from such multimodal content. According to the literature, the common multimodal recommendation pipeline involves (i) extracting multimodal features, (ii) refining their high-level representations to suit the recommendation task, (iii) optionally fusing all multimodal features, and (iv) predicting the user-item score. Although great effort has been put into designing optimal solutions for (ii-iv), to the best of our knowledge, very little attention has been devoted to exploring procedures for (i) in a rigorous way. In this respect, the existing literature outlines the large availability of multimodal datasets and the ever-growing number of large models accounting for multimodal-aware tasks, but (at the same time) an unjustified adoption of limited standardized solutions. As very recent works from the literature have begun to conduct empirical studies to assess the contribution of multimodality in recommendation, we decide to follow and complement this same research direction. To this end, this paper settles as the first attempt to offer a large-scale benchmarking for multimodal recommender systems, with a specific focus on multimodal extractors. Specifically, we take advantage of three popular and recent frameworks for multimodal feature extraction and reproducibility in recommendation, Ducho, and MMRec/Elliot, respectively, to offer a unified and ready-to-use experimental environment able to run extensive benchmarking analyses leveraging novel multimodal feature extractors. Results, largely validated under different extractors, hyper-parameters of the extractors, domains, and modalities, provide important insights on how to train and tune the next generation of multimodal recommendation algorithms
Ipotesi di rigenerazione fra permanenza e innovazione: il caso dell'ex Centro di smistamento postale di Via Monteverdi a Torino
No full textStarting from the analyses and project proposals developed during university workshops, the aim of this contribution is to explore hypotheses for the transformation of the former post office building in Via Monteverdi, Turin. This presents an opportunity for the regeneration of spaces and services within this part of the city. The building, decommissioned in 2009, is an example of an innovative industrial and service system from the 1970s. In its current material state, characterized by an impressive metal structure, it represents an important testimony to our recent past. It raises questions about the potential relationship between conservation and innovation, between the original purpose and opportunities for adaptive reuse, and also considers the interests and feelings of the residents. The prevalent experimental interventions have envisioned: - At the building level, particular attention to its historical and emotional value; - At the urban-territorial level, different degrees of openness and porosity. The strategic location of the area within a post-industrial context enables the enhancement of large green spaces, with an emphasis on a network of ecosystem services
Identification of prokineticin‐2 as potential pharmacodynamic biomarker for overcoming doxorubicin resistance in multicellular breast cancer spheroids
No full textBackground and purpose: Despite advances in immunotherapy, doxorubicin (Dox) chemotherapy is still the irreplaceable first-line therapy for solid tumours such as breast cancer. However, chemotherapy resistance is the major limiting factor, requiring the use of high doses of Dox to achieve the anti-tumour actions, often leading to severe side effects. Unravelling the mechanisms behind chemoresistance and identifying potential biomarkers for mitigating this resistance could enhance current treatment strategies and improve patient outcomes. Experimental approach: We developed human 3D breast cancer spheroids (HBCSs) as a model that closely mimics in vivo tumour structure and microenvironment. Given that hypoxia and elevated levels of the angiogenic cytokine, prokineticin-2 (PK2), are associated with chemoresistance to antiangiogenic therapy, we explored the effect of a hypoxia-inducible factor (HIF-1α) inhibitor on viability defect in HBCSs and the levels of PK2 in the conditioned medium following Dox treatment. We also assessed levels of HIF-1α, active caspase-3, TUNEL and reactive oxygen species (ROS), and CD73 enzymatic activity in HBCSs. Key results: Results showed that HIF-1α inhibitor increased viability defect in the Dox-resistant HBCSs. Interestingly, at higher Dox concentrations, chemoresistance was mitigated independently of HIF-1α and promoted apoptosis and ROS accumulation, which were correlated with PK2 release. Conclusions and implications: Our findings provide the first evidence that PK2 may serve as a predictive pharmacodynamic marker, offering a potential strategy to overcome drug resistance in targeted cancer therapy
Integrating AFM, raman, TERS, and complementary techniques for multiscale physical-chemical characterization in materials and life sciences
No full textTo understand the structural complexities in materials science and life sciences, such as structural, mechanical and chemical properties, it is essential to study their relationships on a nanometric scale to advance the applications of materials and the study of biological processes. This thesis presents a multi-analytical and multi-scale approach that integrates atomic force microscopy (AFM), Raman spectroscopy, tip-enhanced Raman spectroscopy (TERS) and related scanning electron microscopy (SEM) techniques, transmission electron microscopy (TEM) and X-ray diffraction (XRD) techniques in order to obtain a chemical-physical characterization of biological samples and materials. The first part of the work provides a detailed theoretical framework on how the techniques work, highlighting their operating principles, synergy and potential for integration. Subsequently, two representative case studies are discussed in two thematic sections. The first case addresses the chemical-physical characterization on a nanometric scale of extracellular vesicles derived from milk (mEVs), demonstrating how TERS allows, for the first time, the study of molecular heterogeneities present on a single vesicle, highlighting the different distributions of chemical bonds. The second case focuses on the multiscale characterization of laser-induced defects in the production of silicon heterojunction photovoltaic cells, showing how the integration of different techniques allows the morphological, mechanical and structural alterations caused by the laser itself to be highlighted. The results demonstrate that the use of a combined approach based on different techniques allows for a more in-depth understanding of the structure and optimization of its properties for future applications
Theranostic β-emitters production by thermal neutron spectrum reactors: the case of 161Tb at ENEA TRIGA RC-1, Italy
No full textIn recent years, the decommissioning of major nuclear facilities dedicated to medical radionuclide production has posed significant challenges to the fields of diagnostic imaging and radiotherapy. This situation has prompted extensive research and development efforts to identify new sources of supply and alternative production methods for these radionuclides. Such initiatives are essential for ensuring the continuity of medical applications, enhancing national self-sufficiency, and minimizing the risks of supply disruptions, ultimately contributing to a more effective and sustainable healthcare.
This thesis work fits within this framework, in collaboration with the ENEA Casaccia Research Center, which has been involved in SECURE, an EU-funded project (HORIZON-EURATOM-2021-NRT-01 call, Strengthening the European Chain of sUpply for next generation medical RadionuclidEs, October 2022 – September 2025). The project aimed to investigate the feasibility of local radionuclide production for
medical applications within Europe, considering both currently established practices and innovative approaches.
Specifically, it has been investigated the potential option to produce terbium-161 (161Tb), an isotope that shows to be promising for targeted radionuclide therapy and may offer advantages over lutetium-177 (177Lu), which is currently used in cancer treatment.
The production of 161Tb is carried out by neutron activation through the reaction channel 160Gd(n,γ)→161Gd(β−)→161Tb.
The use of a gadolinium target highly enriched (over 98%) in gadolinium-160 (160Gd) is necessary to overcome the limitations in chemical and radiochemical purity typically observed in the final product.
In addition, the need to irradiate large quantities of material arise from the low activity concentration generally achievable when the target is irradiated in a research reactor, i.e. in a lower neutron fluence rate magnitude condition with respect to production reactors established today. Enrichment also facilitate the chemical processing of the irradiated target, which involves the extraction and purification of both 161Tb -the radionuclide precursor used in radiopharmaceuticals preparation for cancer therapy- and 160Gd oxide, which can be recovered and reused in subsequent irradiation cycles.
Finally, an economic evaluation of the entire process was also carried out, and preliminary outcomes from the ENEA team developing the specialized chemical technique for processing the irradiated target are presented.
In conclusion, this work not only contributes to the scientific understanding of terbium-161 production through neutron activation in a medium-scale research reactor, but also highlights the strategic importance of developing autonomous and sustainable medical radionuclide supply chains within European countries. By combining technological innovation, economic assessment, and collaboration between research institutions, this study reinforces the vision of a resilient nuclear medicine ecosystem
Machine-detector interface optimization for a √s = 3 TeV Muon Collider
No full textThis thesis addresses the optimization of the Machine-Detector Interface (MDI) for a Muon Collider
operating at a center-of-mass energy of 3 TeV. The central focus is the design of the shielding
nozzle, a critical component for mitigating Beam-Induced Backgrounds (BIB). The BIB arises from
the interactions of secondary particles—mainly photons, neutrons, and electrons—produced by
electromagnetic showers initiated by electrons and positrons originating from muon decays along
the beamline. A detailed characterization of this background was carried out through high-statistics
FLUKA simulations, followed by an extensive study of how key geometrical parameters of the
shielding influence the background flux. Due to the significant computational cost of full simulations,
a Machine Learning–based strategy was developed to guide the design process. A surrogate model
was trained to reproduce the simulation output, enabling rapid evaluation of new configurations. A
custom metric was introduced to balance background suppression with geometric acceptance, and
a deep learning model was employed to identify the optimal nozzle design. The resulting geometry
preserves strong shielding performance while reducing material volume, offering a promising solution
for the MDI of future muon colliders
Exploring disparities in health and mortality in ageing societies
No full textDespite health being a universal human right, it remains unequally – and unfairly – distributed across nearly all populations. Understanding the fundamental causes of disparities in health and mortality is crucial, especially against the backdrop of population ageing. As life expectancy continues to rise, a growing share of the worldwide population is expected to reach older ages and experience health deterioration, posing unprecedented challenges to healthcare systems’ ability to ensure effective and equitable healthcare. Identifying the most vulnerable population subgroups can help target and tailor more effective policy interventions, as well as anticipate severe health complications through prevention. This thesis attempts a multidimensional exploration of disparities in health and mortality in ageing societies. Adopting a multidisciplinary approach, it examines how health in later life and mortality are shaped by multiple and intersecting social determinants, including education, gender, migration background, partnership status, and housing history. The thesis is a collection of three empirical studies, each shedding light on health disparities from a different angle. Study I adopts a life course approach to study how housing tenure trajectories over the life course (ages 16–65) predict disparities in later-life health among adults aged 65–75 in eleven European countries. Using SHARELIFE retrospective data (2017), sequence and cluster analysis are used for the identification of the main patterns of housing tenure trajectories, and logistic regression is employed to investigate their relationship with self-rated health, chronic morbidity, and activity limitations, net of other relevant social determinants. The study explores potential heterogeneity in the association by gender and country group (Continental, Northern, and Southern Europe). Six patterns are identified. The standard – i.e., the most common – trajectory (‘early-homeowners’) is characterized by early and sustained homeownership and comprises around 60% of the population under study. Overall, non-standard trajectories – ‘late-homeowners’, ‘never-leavers’, ‘private tenants’, ‘social tenants’, ‘rent-free and others’ – are associated with poorer health outcomes, compared to the standard pathway. Although evidence is mixed across health outcomes, some findings suggest that non-standard trajectories are more detrimental for women and individuals living in Southern Europe. Study II investigates educational disparities in dementia incidence and subsequent healthcare utilization in Lazio Region (Italy) during the years 2012–2022. Drawing on census-linked data from the Lazio Region Longitudinal Study, it pursues a two-fold aim: it first analyzes educational disparities in dementia incidence among 1.9 million dementia-free adults aged 50–90, and second, it analyzes disparities in subsequent healthcare utilization (all-cause and potentially preventable hospitalizations, and emergency visits) among around 70,000 incident dementia cases. Cox proportional hazards models are applied in both steps. Findings suggest that low-educated individuals are at a significantly higher risk of developing dementia, especially of early onset dementia (ages 50–64). Following disease onset, low-educated dementia patients also experience a higher risk of all-cause hospitalizations, potentially preventable hospitalizations, and emergency visits. Disparities in hospitalizations are mostly explained by pre-existing health conditions, but for emergency visits, other non-clinical factors may play a role. Study III investigates the extent to which the mortality advantage of being partnered (married and cohabitant) changes across migration generations (natives, first-generation, and second-generation). Partnered individuals generally experience lower mortality than their unpartnered peers, due to both selection and protection mechanisms. However, this advantage varies across population subgroups. The study uses Swedish register data (2012–2022) to examine heterogeneity in the mortality advantage of being partnered differs by migration generation and macro-area of origin. Using Gompertz proportional hazards regression models, it therefore explores differences in all-cause mortality between ages 18-79 mortality in Sweden, across combinations of partnership status and migration generation. Results confirm a mortality advantage for all partnered individuals; overall, the mortality advantage tends to be smaller among first-generation migrants than natives. Among second-generation migrants, instead, unpartnered men show a larger excess mortality, while women show similar patterns as native Swedes. Differential selection, protection, and compositional effects are likely responsible for heterogeneity in the mortality advantage
Multi-analytical study of shaping firing and painted inscriptions in a Roman Titulus Pictus amphora
No full textDuring the Roman period, amphorae were essential for storing and transporting goods, especially food. This study examines a fragment of a Roman amphora with a red titulus pictus, discovered at the Poggio Moscini archaeological site (Bolsena, Italy) and dated between 150 and 100 BC. A comprehensive archaeometric study has been conducted using the non-disruptive techniques of X-ray microscopy (XRM), X-ray powder diffraction (XRPD), energy-dispersive X-ray fluorescence (EDXRF) spectroscopy, fiber optics reflectance spectroscopy (FORS) and micro-Raman spectroscopy. XRM revealed a preferential pore orientation consistent with wheel-throwing manufacture. XRPD identified quartz, diopside, gehlenite, anorthite and sanidine, indicating the use of Ca-rich clays and firing temperatures between ~900 and 1000 °C. ED-XRF demonstrated a similar composition between the ceramic body and the pigment, confirming Fe-rich clay and Fe-oxide-based pigmentation. FORS shows absorption features typical of hematite, and micro-Raman spectroscopy identifies hematite as the red pigment and rules out gypsum in the ceramic body
Phase angle and vector analysis in the evaluation of body composition in sarcopenic obesity: A systematic review
No full textBackground Sarcopenic obesity (SO) is a condition characterized by low muscle mass and strength and high adiposity. Bioelectrical impedance analysis (BIA) derived phase angle (PhA) and bioelectrical impedance vector analysis (BIVA) are simple and inexpensive tools for the evaluation of body composition, with an emerging consensus in health research and application. Aim The aim of this systematic review was to analyze research on sarcopenic obesity using PhA or BIVA. Methods A bibliographic search was performed on 13 January 2025, using three databases: PubMed, Scopus and Web of Science. The search terms were: ("phase angle" OR BIVA) and (sarcopenic OR sarcopenia OR obesity). Studies addressing only obesity or sarcopenia were excluded. The quality of the studies was evaluated using the Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies, from the National Institute of Health. No meta-analysis was conducted. Results Nine studies were selected, mostly published in 2022 (89%) or later and focused on clinical applications (55.6%). The reviewed studies showed substantial methodological variability. Diagnostic criteria included the ESPEN–EASO algorithm as well as protocols based on different definitions of sarcopenia and obesity. Indices and cut-offs used to define body composition varied accordingly. Variability was also observed in population samples and in bioimpedance devices. All selected studies used PhA and two of them used BIVA. Although quantitative results are variable, with PhA values ranging from 3.9° to 7.1°, and mostly below 5.6°. The qualitative pattern of bioelectrical characteristics associated with body composition in SO is broadly consistent across studies: PhA is tendentially lower than in healthy subjects and patients with obesity and similar to those with sarcopenia; the specific vector is longer. Conclusions Research is still quite heterogeneous in terms of methods and diagnostic procedures, which limits the comparability of the results. However, the observed tendencies confirm the suitability of PhA for recognizing the reduced muscle mass associated with sarcopenia, while specific BIVA also appears capable of detecting excess fat mass related to obesity. Further research is needed to standardize procedures for characterizing sarcopenic obesity and monitoring its progression