Background/Objectives: The increasing incidence of cancer during pregnancy is a growing public health concern, driven by delayed parenthood and rising maternal age. Pregnancy-associated cancer (PAC) presents complex clinical challenges, necessitating a balance between maternal cancer treatment and fetal safety. Historically considered incompatible with favorable pregnancy outcomes, evidence now suggests that pregnancy can often proceed without affecting cancer prognosis. A 2022 study in Italy provided the first population-based PAC estimates by linking cancer registries (CRs) and hospital discharge records (HDRs). This study aimed to update PAC estimates to 2019, covering 30% of the Italian population and addressing prior data limitations. Methods: A retrospective longitudinal analysis was conducted on women aged 15-49 diagnosed with malignant cancers between 2003 and 2019. Data from 21 Italian CRs were linked with HDRs to identify PAC cases, defined as obstetric hospitalizations occurring for women diagnosed with cancer in our study cohort in the period spanning from one year before to two years after a cancer diagnosis. All malignant cancers, excluding non-melanoma skin cancers, were analyzed. PAC rates were calculated per 1000 pregnancies, and trends were assessed using log-linear and JoinPoint regression models. Results: Among 131,774 women diagnosed with cancer, 6329 PAC cases were identified, with a PAC rate of 1.43 per 1000 pregnancies, consistent with global estimates. Thyroid (24.4%) and breast cancer (23.2%) were the most common. Analyzing the PAC rate by pregnancy outcome, in the period 2015-2019, this increased for both childbirths and miscarriages but decreased for voluntary terminations. Most hospitalizations (54%) occurred pre-diagnosis, peaking at diagnosis, especially for breast cancer (69%). Conclusions: PAC incidence is rising, particularly for live births and miscarriages, underscoring the need for multidisciplinary care and robust epidemiological insights to guide clinical management.

Background: The number and projections of cancer survivors are necessary to meet the healthcare needs of patients, while data on cure prevalence, that is, the percentage of patients who will not die of cancer by time since diagnosis, are lacking. Materials and methods: Data from Italian cancer registries (duration of registration ranged from 9 to 40 years, with a median of 22 years) covering 47% of the population were used to calculate the limited-duration prevalence, the complete prevalence in 2018, projections to 2030, and cure prevalence, by cancer type, sex, age, and time since diagnosis. Results: A total of 3 347 809 people were alive in Italy in 2018 after a cancer diagnosis, corresponding to 5.6% of the resident population. They will increase by 1.5% per year to 4 012 376 in 2030, corresponding to 6.9% of the resident population, 7.6% of women and similar to 22% after age 75 years. In 2030, more than one-half of all prevalent cases (2 million) will have been diagnosed by >= 10 years. Those with breast (1.05 million), prostate (0.56 million), or colorectal cancers (0.47 million) will be 52% of all prevalent patients. Cure prevalence was 86% for all patients alive in 2018 (87% for patients with breast cancer and 99% for patients with thyroid or testicular cancer), increasing with time since diagnosis to 93% for patients alive after 5 years and 96% after 10 years. Among patients who survived at least 5 years, the excess risk of death (1 - cure prevalence) was <5% for patients with most cancer types except for those with cancers of the breast (8.3%), lung (11.1%), kidney (13.2%), and bladder (15.5%). Conclusions: Study findings encourage the implementation of evidence-based policies aimed at improving long-term clinical follow-up and rehabilitation of people living after cancer diagnosis throughout the course of the disease. Updated estimates of complete prevalence are important to enhance data-driven cancer control planning.

OBJECTIVES:Concurrence of pregnancy and cancer diagnosis is increasingly frequent in Italy. The study aimed to compare women with pregnancy-associated cancers (PACs) to those of childbearing age, focusing on fertility, induced abortion, and miscarriage. METHODS:The population-based study included women aged 15-49 years, both with and without PAC, who were residents in the area covered by the 19 participating Cancer Registries between 2003 and 2015 and identified by individual deterministic linkage with the Hospital Discharge Database. RESULTS:Overall, 2,218,139 obstetrics hospitalizations occurred, covering delivery (75%), induced abortion (14%), and miscarriage (11%). Among 2409 women with PAC, 69% gave birth, 16% had an induced abortion and 15% a miscarriage. Compared with the reference population, the fertility rate in women with PACs was steadily lower (mean values 25.7/1000 vs 37.7/1000), while induced abortion (from 359/1000 - SRR 1.99, 95%CI 1.32-3.00 - in 2003 to 147/1000 - SRR 1.11, 95%CI 0.59-2.09 - in 2015) and miscarriage ratios exhibited a decreasing trend. CONCLUSION:These results are consistent with international literature and are probably due to advancements in diagnostic and therapeutic opportunities. This is the first Italian population-based study analysing fertility and pregnancy outcomes among women with PAC based on a reliable information on cancer diagnosis.

The field of territorial representation has undergone significant transformations in response to the proliferation of the internet, leading to the emergence of platforms dedicated to global exploration. Notably, Google Earth has assumed a pivotal role and stands as one of the most widely utilized tools for making territorial information universally accessible. Google recently introduced direct access to photorealistic 3DTiles via dedicated APIs, ushering in a new era of possibilities. This integration forms a robust foundation for crafting customized applications and interactive experiences within a geospatial three-dimensional environment. The primary objective of this research is the assessment of the accuracy and potential of the resources provided by Google within a workflow focused on digital twin processing and geospatial data visualization. To achieve this goal, a comparative analysis of distinct models was conducted, with each model representing a unique approach to three-dimensional reconstruction. The research introduces a methodology designed for easy replication in other case studies, demonstrating intrinsic scalability suitable for more complex or diverse scenarios. Furthermore, the study offers a comprehensive assessment of the differences and characteristics of the three methods analyzed, providing insights into their potential and limitations.

This paper represents an attempt to illustrate HBIM (Historic Building Information Modelling) to support the management of historic buildings, with particular attention to the methods of organising and sharing information from a public administration perspective. Within the framework of a research agreement between the Faculty of Civil and Environmental Engineering of the University of Perugia and the Municipality of Città di Castello (PG), it was decided to carry out a case study on Palazzo Vitelli in San Giacomo, a sixteenth century building. The aim is to provide the Municipality with a BIM model of the building and to support them in the digitization processes, completely from an information technology point of view and embedded in a valid data exchange and management system. The BIM modelling of historical architecture is an opportunity to reflect on the potential of this logic and to address the numerous problems related to the complexity of the historical-architectural heritage. Moreover, the comparison with a context of modest possibilities presents the challenge of adapting structures for sharing information created for different purposes to the BIM, revealing that in many cases the transition to new forms of data management must be made in the spirit of continuity and intelligent use of resources.

The aim of this study is to describe the frequency and trend of pregnancy-associated cancer (PAC) in Italy, an increasingly relevant phenomenon due to postponing age at childbirth. To this purpose, a population-based retrospective longitudinal study design based on cohorts of women aged 15–49 diagnosed with cancer and concomitant pregnancy is proposed. The study uses 19 population-based Cancer Registries, covering about 22% of Italy, and linked at an individual level with Hospital Discharge Records. A total of 2,861,437 pregnancies and 3559 PAC are identified from 74,165 women of the cohort with a rate of 1.24 PAC per 1000 pregnancies. The most frequent cancer site is breast (24.3%), followed by thyroid (23.9%) and melanoma (14.3%). The most frequent outcome is delivery (53.1%), followed by voluntary termination of pregnancy and spontaneous abortion (both 12.0%). The trend of PAC increased from 2003 to 2015, especially when the outcome is delivery, thus confirming a new attitude of clinicians to manage cancer throughout pregnancy. This represents the first attempt in Italy to describe PAC from Cancer Registries data; the methodology is applicable to other areas with the same data availability. Evidence from this study is addressed to clinicians for improving clinical management of women with PAC.

This research aims to improve wayfinding in the Fontivegge district of Perugia, a chaotic and disorienting area due to the numerous redevelopment projects. The goal is the development of an Augmented Reality application to improve the urban orientation experience. The app will provide users with indications on how to reach pre-selected places of interest, through the visualisation of directional arrows placed horizontally along the route and vertically at major turning points. In addition, it will provide a number of thematically categorised infopoints, which will accompany the user along the route, enriching it with information. The aim is, therefore, to create a more positive and engaging orientation experience for users and to promote a sense of belonging and social cohesion in the place.

The research aims to preserve and support the historical memory of Perugia's Fontivegge district through an analysis and valorisation of the existing cultural heritage. The selected case study is represented by the original design of the station, ideated by architect Antonio Cipolla. In order to enhance this project, which was never realised, it was decided to exploit the three-dimensional reconstruction of the building, which had already been elaborated previously, to create a virtual reality experience, through users can visualize, explore and walk inside the build. The purpose is to consolidate the relationship between the historical memory of the city and its users, allowing them a new interaction with the space and bringing them to a deeper level of knowledge and understanding of the place they live. To increase the user base of this virtual experience, it was decided to create an application for mobile devices. The Unreal Engine software was selected for development, given the ease of exporting projects for the main mobile platforms (Android, iOS) and the specific functions for reading GPS data. In fact, the application only allows the exploration of the virtual scenario to real users of the place, so they physically visit it and thus can understand the differences and similarities between the real scenario and the virtual historical reconstruction. Once the geolocation is verified, the app provides the 3D model for a panoramic view of the build under examination and, subsequently, an immersive experience in which it is possible to freely navigate within the virtual reconstruction.

The study aims at enhancing and requalifying the area of Fontivegge in Perugia. It seeks to instil in the population a sense of identity and belonging to the place through the digital reconstruction of the first design hypothesis of the station itself, transmitting the cultural heritage of the place with new participatory methods, such as serious games and virtual reality. Starting from the project drawings preserved at the academy of San Luca in Rome, conceived by the architect Antonio Cipolla, the project is reconstructed philologically following historical and archival studies, by interpreting the data collected. Following the reconstruction of the 3D model, evocative mook up images and a virtual reality are created, making the intangible tangible and explorable. Through the virtual simulation of the place and its visualisation, new forms of participation are sought, mending the relationship between territory and population, laying the foundations for a different reading of the area and a cultural heritage accessible and open to all.

The research presents a new digital approach to wayfinding analysis in immersive reality, integrated with biosensors for the interpretation of data surveyed. The three-dimensional model of the actual state of the Hall of Perugia Railway Station was realized, considering and detecting the present signage, and it was developed a specific algorithm for a multi-platform graphics engine, able to register an interaction mediated by HMD devices. Wayfinding experiences in immersive reality are developed guaranteeing to the user to move freely to complete the missions assigned. The algorithm in this phase runs in the background and records the movements of users and their pupil, saving them in a special file. In the second phase, instead, the real data processing and the subsequent representation of the collected information take place. Starting from its current state, the Station hall is transformed inserting different elements, derived by the aim of developing four scenarios, to analyse different users’ response in wayfinding. A three-dimensional heat map of visual attentions is created and the different scenarios can be valued for their impact in the user wayfinding, the results are then confronted with the neuro-analysis obtained by EEG instruments and biosensors. In this way, it is possible to value the impact of the environment and spatial orientation cues, by quantifying and qualifying the impact of the project choices.

The research aims to interpret the image of the city, according to the conventions defined by Kevin Lynch, obtained from the analysis of the impact of environmental stimuli on the person. The study relates the digital reconstruction of the spaces analysed with the detection of the trend of valence obtained on a statistical sample using an EEG helmet. The monitoring of the degree of attraction or aversion to the stimuli of the surrounding environment is processed through algorithmic procedures to identify along a path the perceptual poles. This path, reported in GIS environment, allows to reconstruct georeferenced maps that interpret the brain data, synchronized with GNSS. The spatial poles thus identified are further investigated using eye-tracker to understand the reasons for the impact of the environment on humans.

Landscape refers to the qualities of a place, the result of a structural, territorial and environmental component, and the attribution of meanings, which is certainly the fundamental issue of the interpretative process. Percepire etymologically derives from "per", which means "by means of, through", and "capere", which translates as "to take", "to collect" (information, sensory data), "to learn". Since images are derived from the territory, it is of first interest to propose a comparison between representations derived from automated processes on photographs and the synthetic data interpreting the territory inherent in the plans developed with GIS in order to obtain a more precise perceptual analysis. The emergence of new tools for the processing and reproduction of data offers new opportunities for the knowledge and representation of the landscape, in architectural and urban contexts, and the integrative support that these processes can bring to the representation of the qualities of a place have to be reinterpreted in a Spatial Information Dataset in order to make synthetic and intelligible information. Identifying specific themes by questioning these data through criteria and placing at the centre the capacity of the digital environment in its mathematisation to compare data, transforming them into information, in an automated process is aimed at the exploitation of Big Data and the full replicability of the procedure. In this way, it is possible to enter into the analysis of the quality of space, of that notion of landscape concieved as "that part of the territory perceived by the population that lives it".

Background Survival is a key metric of the effectiveness of a health system in managing cancer. We set out to provide a comprehensive examination of worldwide variation and trends in survival from brain tumors in adults, by histology. Methods We analyzed individual data for adults (15-99 years) diagnosed with a brain tumor (ICD-O-3 topography code C71) during 2000-2014, regardless of tumor behavior. Data underwent a 3-phase quality control as part of CONCORD-3. We estimated net survival for 11 histology groups, using the unbiased nonparametric Pohar Perme estimator. Results The study included 556,237 adults. In 2010-2014, the global range in age-standardized 5-year net survival for the most common sub-types was broad: in the range 20%-38% for diffuse and anaplastic astrocytoma, from 4% to 17% for glioblastoma, and between 32% and 69% for oligodendroglioma. For patients with glioblastoma, the largest gains in survival occurred between 2000-2004 and 2005-2009. These improvements were more noticeable among adults diagnosed aged 40-70 years than among younger adults. Conclusions To the best of our knowledge, this study provides the largest account to date of global trends in population-based survival for brain tumors by histology in adults. We have highlighted remarkable gains in 5-year survival from glioblastoma since 2005, providing large-scale empirical evidence on the uptake of chemoradiation at population level. Worldwide, survival improvements have been extensive, but some countries still lag behind. Our findings may help clinicians involved in national and international tumor pathway boards to promote initiatives aimed at more extensive implementation of clinical guidelines.

Background Early diagnosis of breast, colon, rectum and prostate cancers improves health outcomes. Low socioeconomic status (SES) is related to advanced stages at diagnosis; inequalities could explain differences in outcomes by age. The influence of SES, age and residence area on staging was explored in the Umbrian population. Methods 2001-2010 cases were geo-coded by census tract of residence. Stage distribution or Gleason score were analyzed by multilevel multinomial logistic regression with age and SES as the fixed effects and census tract as the random-effect. Results For breast and colorectal cancers, the screening age class was advantaged. For breast, age effect was modulated by deprivation and census tract. In the elderly, the richest were advantaged, the poorest disadvantaged; issues emerged for the young. For colon, age effect is modulated by census tract in early stages and deprivation in late stages. The elderly were disadvantaged; the young and the deprived had more stages IV. About rectum, age effect was modulated by deprivation in the late stages. The elderly were disadvantaged; the young and the deprived presented more stages IV. For prostate, age effect was modulated by deprivation and census tract. The intermediate age class was advantaged, the elderly disadvantaged. Conclusion Age was not always the determinant of a delayed staging when SES was considered. For breast and colorectal cancers, issues of delayed diagnosis emerged in the young. If the care center was near the residence, the census tract modified the stage at diagnosis. These results are useful to reduce SES barriers by specific programs adapted to the age of the patient and area of residence.

Background In Italy, the beginning of 2021 was characterized by the emergence of new variants of SARS-CoV-2 and by the availability of effective vaccines that contributed to the mitigation of non-pharmaceutical interventions and to the avoidance of hospital collapse. Methods We analyzed the COVID-19 propagation in Italy starting from September 2021 with a Susceptible-Exposed-Infected-Recovered (SEIR) model that takes into account SARS-CoV-2 lineages, intervention measures and efficacious vaccines. The model was calibrated with the Bayesian method Conditional Robust Calibration (CRC) using COVID-19 data from September 2020 to May 2021. Here, we apply the Conditional Robustness Analysis (CRA) algorithm to the calibrated model in order to identify model parameters that most affect the epidemic diffusion in the long-term scenario. We focus our attention on vaccination and intervention parameters, which are the key parameters for long-term solutions for epidemic control. Results Our model successfully describes the presence of new variants and the impact of vaccinations and non-pharmaceutical interventions in the Italian scenario. The CRA analysis reveals that vaccine efficacy and waning immunity play a crucial role for pandemic control, together with asymptomatic transmission. Moreover, even though the presence of variants may impair vaccine effectiveness, virus transmission can be kept low with a constant vaccination rate and low restriction levels. Conclusions In the long term, a policy of booster vaccinations together with contact tracing and testing will be key strategies for the containment of SARS-CoV-2 spread.

Programmed death ligand 1 (PD-L1) expression is a predictive biomarker of the success of PD-1/PD-L1 inhibitor therapy for patients with advanced non-small cell lung cancer (NSCLC) but its role as a prognostic marker for early-stage resectable NSCLC remains unclear. We studied gene expression levels of immune-related genes PD-1, PD-L1, PD-L2, IDO-1, IDO-2 and INFγ in tumor tissue of surgically resected NSCLC and correlated the finding with clinicopathological features and patient outcomes. A total of 191 consecutive early-stage NSCLC patients who underwent curative pulmonary resection were studied. The mRNA expression levels of immune-related genes were evaluated by quantitative reverse transcription polymerase chain reaction (qRT-PCR) using RT2 Profiler PCR Arrays (Qiagen). PD-1, PD-L2 and IDO-2 gene expression levels were significantly higher in patients with squamous histology (p = 0.001, p = 0.021 and p < 0.001; respectively). PD-1, PD-L1 and IDO-2 gene expression levels were significantly higher in patients with higher stage (p = 0.005, p = 0.048 and p = 0.002, respectively). The univariate analysis for recurrence-free survival (RFS) and overall survival (OS) showed that patients with higher levels of three-genes (PD-L1/PD-L2/INFγ) (hazard ratio (HR)) 1.90 (95% confidence interval (CI), 1.13–3.21), p = 0.015) were associated with a worse RFS, while patients with higher levels of both genes (PD-L1/IDO-2) or (PD-L2/IDO-1) were associated with a worse OS (HR 1.63 95% CI, 1.06–2.51, p = 0.024; HR 1.54 95% CI, 1.02–2.33, p = 0.04; respectively). The multivariate interaction model adjusted for histology and stage confirmed that higher levels of three genes (PD-L1/PD-L2/INFγ) were significantly associated with worse RFS (HR 1.98, p = 0.031) and higher levels of both genes (PD-L1/IDO-2) and (PD-L2/IDO-1) with worse OS (HR 1.98, p = 0.042, HR 1.92, p = 0.022). PD-L1/IDO-2 and PD-L2/IDO-1 co-expression high levels are independent negative prognostic factors for survival in early NSCLC. These features may have important implications for future immune-checkpoint therapeutic approaches.

The Italian school building heritage built between the seventies and eighties is every year increasingly abandoned and it remains in a state of neglect. It is increasingly necessary a recovery and enhancement methodology that preserves the memory of the place and at the same time, it makes it capable of adapting to the new needs of the city. The proposed research project originates from the study of the interactions between man and the environment applied to an architectural context with the identification of emotions. This methodology applied to citizenship, aims to make the population participate in the improvement from the point of view of well-being. This process was possible thanks to the combined use of immersive reality (VR) and the use of the GEW model, the data of which are the foundation and verification of the choices of architectural design, analyzed through the impacts on humans.

Background Acute or chronic irreversible respiratory failure may occur in patients undergoing pneumonectomy. Aim of this study was to determine transcriptome expression changes after experimental pneumonectomy in swine model. Experimental left pneumonectomy was performed in five pigs under general anaesthesia. Both the resected and the remaining lung, after 60 post-operative completely uneventful days, underwent genome-wide bulk RNA-Sequencing (RNA-Seq). Results Histological analysis showed dilation of air spaces and rupture of interalveolar septa. In addition, mild inflammation, no fibrosis, radial stretch of the bronchus, strong enlargement of airspaces and thinning of the blood supply were observed. Bioinformatic analyses of bulk RNA-Seq data identified 553 Differentially Expressed Genes (DEGs) at adjusted P -value below 0.001, between pre- and post-pneumonectomy. The top 10 up-regulated DEGs were Edn1, Areg, Havcr2, Gadd45g, Depp1, Cldn4, Atf3, Myc, Gadd45b, Socs3 ; the top 10 down-regulated DEGs were Obscn, Cdkn2b, ENSSSCG00000015738, Prrt2, Amer1, Flrt3, Efnb2, Tox3, Znf793, Znf365. Leveraging digital cytometry tools, no difference in cellular abundance was found between the two experimental groups, while the analysis of cell type-specific gene expression patterns highlighted a striking predominance of macrophage-specific genes among the DEGs. DAVID-based gene ontology analysis showed a significant enrichment of “Extrinsic apoptotic signaling pathway” (FDR q = 7.60 × 10 − 3 ) and “Response to insulin” (FDR q = 7.60 × 10 − 3 ) genes, along with an enrichment of genes involved as “Negative regulators of DDX58/IFIH1 signaling” (FDR q = 7.50 × 10 − 4 ) found by querying the REACTOME pathway database. Gene network analyses indicated a general dysregulation of gene inter-connections. Conclusion This translational genomics study highlighted the existence both of individual genes, mostly dysregulated in certain cellular populations (e.g., macrophages), and gene-networks involved in pulmonary reaction after left pneumonectomy. Their involvement in lung homeostasis is largely supported by previous studies, carried out both in humans and in other animal models (under homeostatic or disease-related conditions), that adopted candidate-gene approaches. Overall, the present findings represent a preliminary assessment for future, more focused, studies on compensatory lung adaptation, pulmonary regeneration and functional reload.

Immune checkpoint inhibitors (ICIs) have revolutionized the treatment of lung cancer. However, their clinical benefit is limited to a minority of patients. To unravel immune-related factors that are predictive of sensitivity or resistance to immunotherapy, we performed a gene expression analysis by RNA-Seq using the Oncomine Immuno Response Assay (OIRRA) on a total of 33 advanced NSCLC patients treated with ICI evaluating the expression levels of 365 immune-related genes. We found four genes (CD1C, HLA-DPA1, MMP2, and TLR7) downregulated (p < 0.05) and two genes (IFNB1 and MKI67) upregulated (p < 0.05) in ICI-Responders compared to ICI-Non-Responders. The Bayesian enrichment computational analysis showed a more complex interaction network that involved 10 other genes (IFNA1, TLR4, CD40, TLR2, IL12A, IL12B, TLR9, CD1E, IFNG, and HLA-DPB1) correlated with different functional groups. Five main pathways were identified (FDR < 0.0001). High TLR7 expression levels were significantly associated with a lack of response to immunotherapy (p < 0.0001) and worse outcome in terms of both PFS (p < 0.001) and OS (p = 0.03). The multivariate analysis confirmed TLR7 RNA expression as an independent predictor for both poor PFS (HR = 2.97, 95% CI, 1.16–7.6, p = 0.023) and OS (HR = 2.2, 95% CI, 1–5.08, p = 0.049). In conclusion, a high TLR7 gene expression level was identified as an independent predictor for poor clinical benefits from ICI. These data could have important implications for the development of novel single/combinatorial strategies TLR-mediated for an efficient selection of “individualized” treatments for NSCLC in the era of immunotherapy.

From the end of 2020, different vaccines against COVID-19 have been approved, offering a glimmer of hope and relief worldwide. However, in late 2020, new cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) started to re-surge, worsened by the emergence of highly infectious variants. To study this scenario, we extend the Susceptible-Exposed-Infectious-Removed model with lockdown measures used in our previous work with the inclusion of new lineages and mass vaccination campaign. We estimate model parameters using the Bayesian method Conditional Robust Calibration in two case studies: Italy and the Umbria region, the Italian region being worse affected by the emergence of variants. We then use the model to explore the dynamics of COVID-19, given different vaccination paces and a policy of gradual reopening. Our findings confirm the higher reproduction number of Umbria and the increase of transmission parameters due to the presence of new variants. The results illustrate the importance of preserving population-wide interventions, especially during the beginning of vaccination. Finally, under the hypothesis of waning immunity, the predictions show that a seasonal vaccination with a constant rate would probably be necessary to control the epidemic.